Tests for a future article.
Cpuminer-Opt Cpuminer-Opt is a fork of cpuminer-multi that carries a wide range of CPU performance optimizations for measuring the potential cryptocurrency mining performance of the CPU/processor with a wide variety of cryptocurrencies. The benchmark reports the hash speed for the CPU mining performance for the selected cryptocurrency. Learn more via the OpenBenchmarking.org test page.
Result
OpenBenchmarking.org kH/s, More Is Better Cpuminer-Opt 3.15.5 Algorithm: Skeincoin EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 140K 280K 420K 560K 700K SE +/- 611.43, N = 6 SE +/- 728.58, N = 3 SE +/- 1328.09, N = 3 SE +/- 981.65, N = 3 SE +/- 3944.26, N = 15 SE +/- 4313.15, N = 3 SE +/- 2127.92, N = 3 SE +/- 2411.69, N = 3 SE +/- 6158.44, N = 12 SE +/- 9107.04, N = 12 SE +/- 5351.86, N = 13 SE +/- 12582.41, N = 12 SE +/- 654.80, N = 15 SE +/- 335.77, N = 3 63648 105140 150287 151030 210539 316350 317250 324420 468227 470502 631038 605852 79365 182403 1. (CXX) g++ options: -O2 -lcurl -lz -lpthread -lssl -lcrypto -lgmp
kH/s Per Watt
OpenBenchmarking.org kH/s Per Watt, More Is Better Cpuminer-Opt 3.15.5 Algorithm: Skeincoin EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 2K 4K 6K 8K 10K 1483.87 2410.51 3270.93 2891.08 3879.07 5770.73 4208.20 5932.59 7328.52 6520.94 8559.50 8011.78 1374.22 2197.63
Result Confidence
OpenBenchmarking.org kH/s, More Is Better Cpuminer-Opt 3.15.5 Algorithm: Skeincoin EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 110K 220K 330K 440K 550K Min: 61790 / Avg: 63648.33 / Max: 66140 Min: 103990 / Avg: 105140 / Max: 106490 Min: 148430 / Avg: 150286.67 / Max: 152860 Min: 149150 / Avg: 151030 / Max: 152460 Min: 187570 / Avg: 210538.67 / Max: 242310 Min: 310740 / Avg: 316350 / Max: 324830 Min: 313810 / Avg: 317250 / Max: 321140 Min: 319750 / Avg: 324420 / Max: 327800 Min: 404270 / Avg: 468226.67 / Max: 483970 Min: 373060 / Avg: 470501.67 / Max: 494480 Min: 570830 / Avg: 631038.46 / Max: 649140 Min: 470320 / Avg: 605851.67 / Max: 630960 Min: 75330 / Avg: 79365.33 / Max: 84270 Min: 181900 / Avg: 182403.33 / Max: 183040 1. (CXX) g++ options: -O2 -lcurl -lz -lpthread -lssl -lcrypto -lgmp
Sysbench This is a benchmark of Sysbench with CPU and memory sub-tests. Learn more via the OpenBenchmarking.org test page.
Result
OpenBenchmarking.org Events Per Second, More Is Better Sysbench 2018-07-28 Test: CPU EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 20K 40K 60K 80K 100K SE +/- 1.09, N = 5 SE +/- 5.53, N = 5 SE +/- 10.65, N = 5 SE +/- 9.93, N = 5 SE +/- 12.89, N = 5 SE +/- 9.32, N = 5 SE +/- 7.32, N = 5 SE +/- 20.39, N = 5 SE +/- 23.00, N = 5 SE +/- 52.65, N = 5 SE +/- 97.15, N = 5 SE +/- 2.64, N = 5 SE +/- 7.33, N = 5 13398.10 20091.96 26778.62 27632.19 42008.11 56038.72 55254.66 56066.79 80743.89 108892.22 106421.95 16323.92 32649.36 1. (CC) gcc options: -pthread -O3 -funroll-loops -ggdb3 -march=amdfam10 -rdynamic -ldl -laio -lm
Events Per Second Per Watt
OpenBenchmarking.org Events Per Second Per Watt, More Is Better Sysbench 2018-07-28 Test: CPU EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 200 400 600 800 1000 297.08 391.60 474.66 432.15 539.88 638.23 521.63 667.05 733.57 783.68 754.73 261.75 313.31
Result Confidence
OpenBenchmarking.org Events Per Second, More Is Better Sysbench 2018-07-28 Test: CPU EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 20K 40K 60K 80K 100K Min: 13395.23 / Avg: 13398.1 / Max: 13400.85 Min: 20074.61 / Avg: 20091.96 / Max: 20104.41 Min: 26746.06 / Avg: 26778.62 / Max: 26804.47 Min: 27594.22 / Avg: 27632.19 / Max: 27651.61 Min: 41974.26 / Avg: 42008.11 / Max: 42044 Min: 56017.18 / Avg: 56038.72 / Max: 56065.58 Min: 55238.42 / Avg: 55254.66 / Max: 55276.83 Min: 55989.07 / Avg: 56066.79 / Max: 56109.25 Min: 80668.55 / Avg: 80743.89 / Max: 80805.58 Min: 108721.1 / Avg: 108892.22 / Max: 109052.86 Min: 106076.46 / Avg: 106421.95 / Max: 106643.26 Min: 16316.25 / Avg: 16323.92 / Max: 16331.8 Min: 32621.61 / Avg: 32649.36 / Max: 32663.3 1. (CC) gcc options: -pthread -O3 -funroll-loops -ggdb3 -march=amdfam10 -rdynamic -ldl -laio -lm
Stress-NG Stress-NG is a Linux stress tool developed by Colin King of Canonical. Learn more via the OpenBenchmarking.org test page.
Result
OpenBenchmarking.org Bogo Ops/s, More Is Better Stress-NG 0.11.07 Test: CPU Stress EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 4K 8K 12K 16K 20K SE +/- 8.87, N = 3 SE +/- 5.85, N = 3 SE +/- 4.51, N = 3 SE +/- 1.11, N = 3 SE +/- 3.25, N = 3 SE +/- 8.85, N = 3 SE +/- 14.79, N = 3 SE +/- 39.53, N = 3 SE +/- 23.53, N = 3 SE +/- 45.79, N = 3 SE +/- 24.42, N = 3 SE +/- 4.39, N = 3 SE +/- 1.01, N = 3 2708.90 4078.21 5463.45 5622.82 8541.12 11121.59 10901.47 11234.60 15958.16 20174.76 19926.61 3306.39 6629.06 1. (CC) gcc options: -O2 -std=gnu99 -lm -laio -lbsd -lcrypt -lrt -lz -ldl -lpthread -lc
Bogo Ops/s Per Watt
OpenBenchmarking.org Bogo Ops/s Per Watt, More Is Better Stress-NG 0.11.07 Test: CPU Stress EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 30 60 90 120 150 48.74 61.95 75.08 68.61 79.28 96.72 82.69 94.22 108.92 125.49 119.94 41.61 47.44
Result Confidence
OpenBenchmarking.org Bogo Ops/s, More Is Better Stress-NG 0.11.07 Test: CPU Stress EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 3K 6K 9K 12K 15K Min: 2691.46 / Avg: 2708.9 / Max: 2720.48 Min: 4067.37 / Avg: 4078.21 / Max: 4087.43 Min: 5456.78 / Avg: 5463.45 / Max: 5472.04 Min: 5620.68 / Avg: 5622.82 / Max: 5624.41 Min: 8535.73 / Avg: 8541.12 / Max: 8546.95 Min: 11109.84 / Avg: 11121.59 / Max: 11138.93 Min: 10874.37 / Avg: 10901.47 / Max: 10925.3 Min: 11159.1 / Avg: 11234.6 / Max: 11292.66 Min: 15919.41 / Avg: 15958.16 / Max: 16000.66 Min: 20083.31 / Avg: 20174.76 / Max: 20224.79 Min: 19890.13 / Avg: 19926.61 / Max: 19972.98 Min: 3301.92 / Avg: 3306.39 / Max: 3315.16 Min: 6628.02 / Avg: 6629.06 / Max: 6631.08 1. (CC) gcc options: -O2 -std=gnu99 -lm -laio -lbsd -lcrypt -lrt -lz -ldl -lpthread -lc
OpenVINO This is a test of the Intel OpenVINO, a toolkit around neural networks, using its built-in benchmarking support and analyzing the throughput and latency for various models. Learn more via the OpenBenchmarking.org test page.
Result
OpenBenchmarking.org FPS, More Is Better OpenVINO 2021.1 Model: Age Gender Recognition Retail 0013 FP16 - Device: CPU EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 6K 12K 18K 24K 30K SE +/- 41.71, N = 15 SE +/- 89.67, N = 3 SE +/- 50.79, N = 3 SE +/- 21.57, N = 3 SE +/- 95.61, N = 3 SE +/- 42.04, N = 3 SE +/- 22.86, N = 3 SE +/- 85.72, N = 3 SE +/- 55.79, N = 3 SE +/- 31.70, N = 3 SE +/- 46.32, N = 3 SE +/- 28.57, N = 3 SE +/- 52.69, N = 3 SE +/- 43.76, N = 3 4012.40 6689.95 10017.98 9316.80 12800.59 18612.54 16446.88 19922.01 23441.91 22986.05 28284.87 25067.04 4953.65 9663.43
Result Confidence
OpenBenchmarking.org FPS, More Is Better OpenVINO 2021.1 Model: Age Gender Recognition Retail 0013 FP16 - Device: CPU EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 5K 10K 15K 20K 25K Min: 3827.5 / Avg: 4012.4 / Max: 4339.41 Min: 6524.74 / Avg: 6689.95 / Max: 6832.97 Min: 9917.01 / Avg: 10017.98 / Max: 10078.03 Min: 9293.16 / Avg: 9316.8 / Max: 9359.87 Min: 12615.39 / Avg: 12800.59 / Max: 12934.43 Min: 18567.53 / Avg: 18612.54 / Max: 18696.54 Min: 16403.4 / Avg: 16446.88 / Max: 16480.83 Min: 19751.03 / Avg: 19922.01 / Max: 20018.47 Min: 23347.44 / Avg: 23441.91 / Max: 23540.57 Min: 22927.38 / Avg: 22986.05 / Max: 23036.21 Min: 28192.24 / Avg: 28284.87 / Max: 28331.27 Min: 25025.67 / Avg: 25067.04 / Max: 25121.85 Min: 4855.38 / Avg: 4953.65 / Max: 5035.74 Min: 9575.98 / Avg: 9663.43 / Max: 9710.01
NAS Parallel Benchmarks NPB, NAS Parallel Benchmarks, is a benchmark developed by NASA for high-end computer systems. This test profile currently uses the MPI version of NPB. This test profile offers selecting the different NPB tests/problems and varying problem sizes. Learn more via the OpenBenchmarking.org test page.
Result
OpenBenchmarking.org Total Mop/s, More Is Better NAS Parallel Benchmarks 3.4 Test / Class: EP.D EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 900 1800 2700 3600 4500 SE +/- 0.03, N = 3 SE +/- 7.84, N = 3 SE +/- 1.25, N = 3 SE +/- 3.28, N = 3 SE +/- 1.11, N = 3 SE +/- 4.32, N = 3 SE +/- 1.11, N = 3 SE +/- 5.63, N = 3 SE +/- 6.05, N = 3 SE +/- 8.46, N = 3 SE +/- 9.36, N = 3 SE +/- 9.06, N = 3 SE +/- 0.03, N = 3 SE +/- 0.05, N = 3 579.18 860.01 1156.26 1190.48 1813.29 2380.27 2333.54 2389.76 3292.84 3322.99 4019.09 3989.79 705.21 1410.59 1. (F9X) gfortran options: -O3 -march=native -pthread -lmpi_usempif08 -lmpi_mpifh -lmpi 2. Open MPI 4.0.3
Total Mop/s Per Watt
OpenBenchmarking.org Total Mop/s Per Watt, More Is Better NAS Parallel Benchmarks 3.4 Test / Class: EP.D EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 6 12 18 24 30 9.24 11.07 13.47 12.24 14.01 16.63 14.32 17.20 20.64 18.05 24.18 23.49 7.56 8.30
Result Confidence
OpenBenchmarking.org Total Mop/s, More Is Better NAS Parallel Benchmarks 3.4 Test / Class: EP.D EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 700 1400 2100 2800 3500 Min: 579.13 / Avg: 579.18 / Max: 579.23 Min: 844.33 / Avg: 860.01 / Max: 868.26 Min: 1153.76 / Avg: 1156.26 / Max: 1157.7 Min: 1183.95 / Avg: 1190.48 / Max: 1194.25 Min: 1811.43 / Avg: 1813.29 / Max: 1815.27 Min: 2371.63 / Avg: 2380.27 / Max: 2384.67 Min: 2331.32 / Avg: 2333.54 / Max: 2334.74 Min: 2378.57 / Avg: 2389.76 / Max: 2396.35 Min: 3282.03 / Avg: 3292.84 / Max: 3302.95 Min: 3306.1 / Avg: 3322.99 / Max: 3332.1 Min: 4001.46 / Avg: 4019.09 / Max: 4033.33 Min: 3972.06 / Avg: 3989.79 / Max: 4001.86 Min: 705.16 / Avg: 705.21 / Max: 705.27 Min: 1410.49 / Avg: 1410.59 / Max: 1410.66 1. (F9X) gfortran options: -O3 -march=native -pthread -lmpi_usempif08 -lmpi_mpifh -lmpi 2. Open MPI 4.0.3
OpenVINO This is a test of the Intel OpenVINO, a toolkit around neural networks, using its built-in benchmarking support and analyzing the throughput and latency for various models. Learn more via the OpenBenchmarking.org test page.
Result
OpenBenchmarking.org FPS, More Is Better OpenVINO 2021.1 Model: Age Gender Recognition Retail 0013 FP32 - Device: CPU EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 6K 12K 18K 24K 30K SE +/- 46.05, N = 4 SE +/- 21.76, N = 3 SE +/- 103.67, N = 4 SE +/- 6.65, N = 3 SE +/- 157.24, N = 3 SE +/- 60.57, N = 3 SE +/- 24.60, N = 3 SE +/- 75.75, N = 3 SE +/- 49.13, N = 3 SE +/- 4.60, N = 3 SE +/- 30.27, N = 3 SE +/- 48.27, N = 3 SE +/- 6.26, N = 3 SE +/- 47.83, N = 3 4115.44 6803.09 9884.62 9314.82 13220.95 18514.60 16443.73 19958.41 23559.17 22996.93 28316.50 25012.98 4984.35 9866.08
Result Confidence
OpenBenchmarking.org FPS, More Is Better OpenVINO 2021.1 Model: Age Gender Recognition Retail 0013 FP32 - Device: CPU EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 5K 10K 15K 20K 25K Min: 4003.8 / Avg: 4115.44 / Max: 4226.83 Min: 6767.48 / Avg: 6803.09 / Max: 6842.56 Min: 9618.02 / Avg: 9884.62 / Max: 10112.13 Min: 9307.85 / Avg: 9314.82 / Max: 9328.12 Min: 12906.62 / Avg: 13220.95 / Max: 13386.45 Min: 18416.86 / Avg: 18514.6 / Max: 18625.46 Min: 16395.26 / Avg: 16443.73 / Max: 16475.33 Min: 19820.95 / Avg: 19958.41 / Max: 20082.32 Min: 23467.34 / Avg: 23559.17 / Max: 23635.37 Min: 22990.44 / Avg: 22996.93 / Max: 23005.82 Min: 28279.61 / Avg: 28316.5 / Max: 28376.51 Min: 24963.18 / Avg: 25012.98 / Max: 25109.5 Min: 4971.91 / Avg: 4984.35 / Max: 4991.8 Min: 9816.8 / Avg: 9866.08 / Max: 9961.72
NAS Parallel Benchmarks NPB, NAS Parallel Benchmarks, is a benchmark developed by NASA for high-end computer systems. This test profile currently uses the MPI version of NPB. This test profile offers selecting the different NPB tests/problems and varying problem sizes. Learn more via the OpenBenchmarking.org test page.
Result
OpenBenchmarking.org Total Mop/s, More Is Better NAS Parallel Benchmarks 3.4 Test / Class: EP.C EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 900 1800 2700 3600 4500 SE +/- 0.60, N = 4 SE +/- 0.17, N = 5 SE +/- 0.78, N = 6 SE +/- 0.45, N = 6 SE +/- 1.48, N = 7 SE +/- 3.24, N = 8 SE +/- 5.08, N = 8 SE +/- 4.60, N = 8 SE +/- 9.01, N = 9 SE +/- 6.29, N = 9 SE +/- 10.02, N = 10 SE +/- 13.78, N = 10 SE +/- 0.27, N = 4 SE +/- 0.69, N = 6 578.12 867.81 1155.88 1191.90 1806.54 2368.69 2318.44 2375.48 3252.13 3310.34 3967.28 3908.23 704.69 1407.62 1. (F9X) gfortran options: -O3 -march=native -pthread -lmpi_usempif08 -lmpi_mpifh -lmpi 2. Open MPI 4.0.3
Total Mop/s Per Watt
OpenBenchmarking.org Total Mop/s Per Watt, More Is Better NAS Parallel Benchmarks 3.4 Test / Class: EP.C EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 10 20 30 40 50 10.52 13.77 17.46 16.06 21.02 27.29 22.61 28.10 36.28 32.45 42.58 41.11 9.02 11.81
Result Confidence
OpenBenchmarking.org Total Mop/s, More Is Better NAS Parallel Benchmarks 3.4 Test / Class: EP.C EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 700 1400 2100 2800 3500 Min: 576.33 / Avg: 578.12 / Max: 578.84 Min: 867.17 / Avg: 867.81 / Max: 868.12 Min: 1152.71 / Avg: 1155.88 / Max: 1157.48 Min: 1190.44 / Avg: 1191.9 / Max: 1193.16 Min: 1799.65 / Avg: 1806.54 / Max: 1812.17 Min: 2349.79 / Avg: 2368.69 / Max: 2379.63 Min: 2296.55 / Avg: 2318.44 / Max: 2338.82 Min: 2361.46 / Avg: 2375.48 / Max: 2394.12 Min: 3210.93 / Avg: 3252.13 / Max: 3290.8 Min: 3286.05 / Avg: 3310.34 / Max: 3336.05 Min: 3922.41 / Avg: 3967.28 / Max: 4021.83 Min: 3840.34 / Avg: 3908.23 / Max: 3966.84 Min: 703.93 / Avg: 704.69 / Max: 705.19 Min: 1404.92 / Avg: 1407.62 / Max: 1409.44 1. (F9X) gfortran options: -O3 -march=native -pthread -lmpi_usempif08 -lmpi_mpifh -lmpi 2. Open MPI 4.0.3
Stress-NG Stress-NG is a Linux stress tool developed by Colin King of Canonical. Learn more via the OpenBenchmarking.org test page.
Result
OpenBenchmarking.org Bogo Ops/s, More Is Better Stress-NG 0.11.07 Test: Vector Math EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 90K 180K 270K 360K 450K SE +/- 4.97, N = 3 SE +/- 1.61, N = 3 SE +/- 4.86, N = 3 SE +/- 3.30, N = 3 SE +/- 100.32, N = 3 SE +/- 66.32, N = 3 SE +/- 47.74, N = 3 SE +/- 32.95, N = 3 SE +/- 189.45, N = 3 SE +/- 137.59, N = 3 SE +/- 205.94, N = 3 SE +/- 4.12, N = 3 SE +/- 3.54, N = 3 58583.38 87851.58 117080.86 120826.81 182716.39 237596.66 232455.68 241722.09 328019.70 400773.38 397326.45 71366.17 142756.35 1. (CC) gcc options: -O2 -std=gnu99 -lm -laio -lbsd -lcrypt -lrt -lz -ldl -lpthread -lc
Bogo Ops/s Per Watt
OpenBenchmarking.org Bogo Ops/s Per Watt, More Is Better Stress-NG 0.11.07 Test: Vector Math EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 500 1000 1500 2000 2500 961.66 1163.29 1400.36 1278.65 1407.24 1705.78 1476.94 1741.29 2071.71 2387.46 2315.41 783.29 850.73
Result Confidence
OpenBenchmarking.org Bogo Ops/s, More Is Better Stress-NG 0.11.07 Test: Vector Math EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 70K 140K 210K 280K 350K Min: 58573.44 / Avg: 58583.38 / Max: 58588.42 Min: 87849.93 / Avg: 87851.58 / Max: 87854.8 Min: 117074.78 / Avg: 117080.86 / Max: 117090.47 Min: 120822.19 / Avg: 120826.81 / Max: 120833.2 Min: 182574.85 / Avg: 182716.39 / Max: 182910.32 Min: 237474.07 / Avg: 237596.66 / Max: 237701.83 Min: 232394.78 / Avg: 232455.68 / Max: 232549.81 Min: 241657.95 / Avg: 241722.09 / Max: 241767.28 Min: 327828.63 / Avg: 328019.7 / Max: 328398.59 Min: 400607.54 / Avg: 400773.38 / Max: 401046.47 Min: 397034.87 / Avg: 397326.45 / Max: 397724.18 Min: 71360.29 / Avg: 71366.17 / Max: 71374.11 Min: 142752.27 / Avg: 142756.35 / Max: 142763.4 1. (CC) gcc options: -O2 -std=gnu99 -lm -laio -lbsd -lcrypt -lrt -lz -ldl -lpthread -lc
John The Ripper This is a benchmark of John The Ripper, which is a password cracker. Learn more via the OpenBenchmarking.org test page.
Result
OpenBenchmarking.org Real C/S, More Is Better John The Ripper 1.9.0-jumbo-1 Test: Blowfish EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 16K 32K 48K 64K 80K SE +/- 2.31, N = 3 SE +/- 4.10, N = 3 SE +/- 12.17, N = 3 SE +/- 3.06, N = 3 SE +/- 1.00, N = 3 SE +/- 8.37, N = 3 SE +/- 9.84, N = 3 SE +/- 17.06, N = 3 SE +/- 72.25, N = 3 SE +/- 3.00, N = 3 SE +/- 4.67, N = 3 SE +/- 15.77, N = 3 SE +/- 1.67, N = 3 SE +/- 3.33, N = 3 10825 16224 21454 22314 33755 43703 42800 44596 59963 61119 73579 70033 13183 26345 1. (CC) gcc options: -m64 -lssl -lcrypto -fopenmp -lgmp -pthread -lm -lz -ldl -lcrypt -lbz2
Real C/S Per Watt
OpenBenchmarking.org Real C/S Per Watt, More Is Better John The Ripper 1.9.0-jumbo-1 Test: Blowfish EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 100 200 300 400 500 177.43 213.21 255.06 235.34 260.68 316.71 273.00 317.83 379.39 337.12 439.24 420.61 144.00 156.27
Result Confidence
OpenBenchmarking.org Real C/S, More Is Better John The Ripper 1.9.0-jumbo-1 Test: Blowfish EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 13K 26K 39K 52K 65K Min: 10821 / Avg: 10825 / Max: 10829 Min: 16216 / Avg: 16223.67 / Max: 16230 Min: 21436 / Avg: 21453.67 / Max: 21477 Min: 22310 / Avg: 22314 / Max: 22320 Min: 33753 / Avg: 33755 / Max: 33756 Min: 43689 / Avg: 43703.33 / Max: 43718 Min: 42782 / Avg: 42799.67 / Max: 42816 Min: 44563 / Avg: 44596 / Max: 44620 Min: 59835 / Avg: 59963.33 / Max: 60085 Min: 61113 / Avg: 61119 / Max: 61122 Min: 73574 / Avg: 73578.67 / Max: 73588 Min: 70003 / Avg: 70033.33 / Max: 70056 Min: 13181 / Avg: 13182.67 / Max: 13186 Min: 26342 / Avg: 26345.33 / Max: 26352 1. (CC) gcc options: -m64 -lssl -lcrypto -fopenmp -lgmp -pthread -lm -lz -ldl -lcrypt -lbz2
OSPray Intel OSPray is a portable ray-tracing engine for high-performance, high-fidenlity scientific visualizations. OSPray builds off Intel's Embree and Intel SPMD Program Compiler (ISPC) components as part of the oneAPI rendering toolkit. Learn more via the OpenBenchmarking.org test page.
Result
OpenBenchmarking.org FPS, More Is Better OSPray 1.8.5 Demo: San Miguel - Renderer: Path Tracer EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 1.1228 2.2456 3.3684 4.4912 5.614 SE +/- 0.00, N = 3 SE +/- 0.00, N = 3 SE +/- 0.00, N = 3 SE +/- 0.00, N = 3 SE +/- 0.00, N = 3 SE +/- 0.00, N = 3 SE +/- 0.00, N = 3 SE +/- 0.00, N = 3 SE +/- 0.00, N = 3 SE +/- 0.01, N = 3 SE +/- 0.01, N = 3 SE +/- 0.01, N = 3 SE +/- 0.00, N = 3 SE +/- 0.00, N = 3 0.76 1.22 1.59 1.65 2.45 3.03 2.97 3.23 4.17 4.21 4.99 4.92 0.95 1.48 MAX: 0.77 MIN: 1.21 MIN: 1.58 / MAX: 1.6 MIN: 1.63 MIN: 2.43 / MAX: 2.46 MIN: 2.99 / MAX: 3.04 MIN: 2.93 / MAX: 2.99 MIN: 3.19 / MAX: 3.24 MIN: 4.12 / MAX: 4.18 MIN: 4.1 / MAX: 4.24 MIN: 4.95 / MAX: 5.03 MIN: 4.88 / MAX: 4.95 MIN: 1.47 / MAX: 1.49
FPS Per Watt
OpenBenchmarking.org FPS Per Watt, More Is Better OSPray 1.8.5 Demo: San Miguel - Renderer: Path Tracer EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 0.009 0.018 0.027 0.036 0.045 0.01 0.01 0.02 0.02 0.02 0.02 0.02 0.02 0.03 0.03 0.04 0.03 0.01 0.01
Result Confidence
OpenBenchmarking.org FPS, More Is Better OSPray 1.8.5 Demo: San Miguel - Renderer: Path Tracer EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 2 4 6 8 10 Min: 0.76 / Avg: 0.76 / Max: 0.76 Min: 1.22 / Avg: 1.22 / Max: 1.22 Min: 1.59 / Avg: 1.59 / Max: 1.59 Min: 1.65 / Avg: 1.65 / Max: 1.65 Min: 2.44 / Avg: 2.45 / Max: 2.45 Min: 3.03 / Avg: 3.03 / Max: 3.03 Min: 2.97 / Avg: 2.97 / Max: 2.97 Min: 3.23 / Avg: 3.23 / Max: 3.23 Min: 4.17 / Avg: 4.17 / Max: 4.17 Min: 4.2 / Avg: 4.21 / Max: 4.22 Min: 4.98 / Avg: 4.99 / Max: 5 Min: 4.9 / Avg: 4.92 / Max: 4.93 Min: 0.95 / Avg: 0.95 / Max: 0.95 Min: 1.48 / Avg: 1.48 / Max: 1.48
Pennant Pennant is an application focused on hydrodynamics on general unstructured meshes in 2D. Learn more via the OpenBenchmarking.org test page.
Result
OpenBenchmarking.org Hydro Cycle Time - Seconds, Fewer Is Better Pennant 1.0.1 Test: leblancbig EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 10 20 30 40 50 SE +/- 0.039126, N = 3 SE +/- 0.292336, N = 3 SE +/- 0.019691, N = 3 SE +/- 0.036573, N = 3 SE +/- 0.019214, N = 3 SE +/- 0.026648, N = 4 SE +/- 0.014397, N = 5 SE +/- 0.043495, N = 4 SE +/- 0.095577, N = 5 SE +/- 0.054901, N = 6 SE +/- 0.058701, N = 6 SE +/- 0.037928, N = 3 SE +/- 0.007758, N = 4 45.154600 33.808520 28.993920 21.951880 16.653750 14.781570 10.885760 14.164820 8.988538 6.995321 7.033982 34.580030 16.139290 1. (CXX) g++ options: -fopenmp -pthread -lmpi_cxx -lmpi
Result Confidence
OpenBenchmarking.org Hydro Cycle Time - Seconds, Fewer Is Better Pennant 1.0.1 Test: leblancbig EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 9 18 27 36 45 Min: 45.1 / Avg: 45.15 / Max: 45.23 Min: 33.47 / Avg: 33.81 / Max: 34.39 Min: 28.96 / Avg: 28.99 / Max: 29.03 Min: 21.9 / Avg: 21.95 / Max: 22.02 Min: 16.63 / Avg: 16.65 / Max: 16.69 Min: 14.73 / Avg: 14.78 / Max: 14.84 Min: 10.85 / Avg: 10.89 / Max: 10.92 Min: 14.12 / Avg: 14.16 / Max: 14.3 Min: 8.8 / Avg: 8.99 / Max: 9.33 Min: 6.85 / Avg: 7 / Max: 7.2 Min: 6.86 / Avg: 7.03 / Max: 7.24 Min: 34.52 / Avg: 34.58 / Max: 34.65 Min: 16.12 / Avg: 16.14 / Max: 16.16 1. (CXX) g++ options: -fopenmp -pthread -lmpi_cxx -lmpi
Stress-NG Stress-NG is a Linux stress tool developed by Colin King of Canonical. Learn more via the OpenBenchmarking.org test page.
Result
OpenBenchmarking.org Bogo Ops/s, More Is Better Stress-NG 0.11.07 Test: Crypto EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 3K 6K 9K 12K 15K SE +/- 0.98, N = 3 SE +/- 0.42, N = 3 SE +/- 0.60, N = 3 SE +/- 5.77, N = 3 SE +/- 0.38, N = 3 SE +/- 6.32, N = 3 SE +/- 2.43, N = 3 SE +/- 2.98, N = 3 SE +/- 6.05, N = 3 SE +/- 2.16, N = 3 SE +/- 5.99, N = 3 SE +/- 2.21, N = 3 SE +/- 2.53, N = 3 1878.74 2821.19 3760.66 3871.57 5847.70 7273.71 7105.73 7720.58 9992.15 12091.56 11996.59 2288.33 4580.08 1. (CC) gcc options: -O2 -std=gnu99 -lm -laio -lbsd -lcrypt -lrt -lz -ldl -lpthread -lc
Bogo Ops/s Per Watt
OpenBenchmarking.org Bogo Ops/s Per Watt, More Is Better Stress-NG 0.11.07 Test: Crypto EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 16 32 48 64 80 28.52 33.86 40.39 37.06 40.81 52.91 45.60 49.49 61.88 70.11 68.08 23.03 24.38
Result Confidence
OpenBenchmarking.org Bogo Ops/s, More Is Better Stress-NG 0.11.07 Test: Crypto EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 2K 4K 6K 8K 10K Min: 1877.16 / Avg: 1878.74 / Max: 1880.55 Min: 2820.54 / Avg: 2821.19 / Max: 2821.99 Min: 3759.79 / Avg: 3760.66 / Max: 3761.8 Min: 3864.76 / Avg: 3871.57 / Max: 3883.04 Min: 5846.99 / Avg: 5847.7 / Max: 5848.3 Min: 7261.15 / Avg: 7273.71 / Max: 7281.24 Min: 7100.89 / Avg: 7105.73 / Max: 7108.61 Min: 7715.51 / Avg: 7720.58 / Max: 7725.83 Min: 9980.12 / Avg: 9992.15 / Max: 9999.28 Min: 12087.35 / Avg: 12091.56 / Max: 12094.48 Min: 11984.94 / Avg: 11996.59 / Max: 12004.82 Min: 2285.96 / Avg: 2288.33 / Max: 2292.74 Min: 4577.39 / Avg: 4580.08 / Max: 4585.14 1. (CC) gcc options: -O2 -std=gnu99 -lm -laio -lbsd -lcrypt -lrt -lz -ldl -lpthread -lc
oneDNN This is a test of the Intel oneDNN as an Intel-optimized library for Deep Neural Networks and making use of its built-in benchdnn functionality. The result is the total perf time reported. Intel oneDNN was formerly known as DNNL (Deep Neural Network Library) and MKL-DNN before being rebranded as part of the Intel oneAPI initiative. Learn more via the OpenBenchmarking.org test page.
Result
OpenBenchmarking.org ms, Fewer Is Better oneDNN 2.0 Harness: Convolution Batch Shapes Auto - Data Type: f32 - Engine: CPU EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 2 4 6 8 10 SE +/- 0.004801, N = 7 SE +/- 0.005350, N = 7 SE +/- 0.008434, N = 7 SE +/- 0.006442, N = 7 SE +/- 0.005689, N = 7 SE +/- 0.008223, N = 7 SE +/- 0.001701, N = 7 SE +/- 0.011195, N = 7 SE +/- 0.003838, N = 7 SE +/- 0.002747, N = 7 SE +/- 0.002146, N = 7 SE +/- 0.002719, N = 7 SE +/- 0.007190, N = 7 SE +/- 0.002179, N = 7 6.376680 5.953480 5.864580 3.706400 3.543470 3.462360 1.483740 3.461740 1.719670 1.108050 0.993732 1.078440 4.301300 2.001830 MIN: 6.27 MIN: 5.82 MIN: 5.63 MIN: 3.6 MIN: 3.47 MIN: 3.38 MIN: 1.28 MIN: 3.38 MIN: 1.63 MIN: 4.22 MIN: 1.91 1. (CXX) g++ options: -O3 -std=c++11 -fopenmp -msse4.1 -fPIC -pie -lpthread
Result Confidence
OpenBenchmarking.org ms, Fewer Is Better oneDNN 2.0 Harness: Convolution Batch Shapes Auto - Data Type: f32 - Engine: CPU EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 3 6 9 12 15 Min: 6.36 / Avg: 6.38 / Max: 6.4 Min: 5.94 / Avg: 5.95 / Max: 5.98 Min: 5.83 / Avg: 5.86 / Max: 5.9 Min: 3.67 / Avg: 3.71 / Max: 3.73 Min: 3.52 / Avg: 3.54 / Max: 3.56 Min: 3.43 / Avg: 3.46 / Max: 3.5 Min: 1.47 / Avg: 1.48 / Max: 1.49 Min: 3.44 / Avg: 3.46 / Max: 3.53 Min: 1.7 / Avg: 1.72 / Max: 1.73 Min: 1.1 / Avg: 1.11 / Max: 1.12 Min: 0.99 / Avg: 0.99 / Max: 1 Min: 1.07 / Avg: 1.08 / Max: 1.09 Min: 4.26 / Avg: 4.3 / Max: 4.32 Min: 1.99 / Avg: 2 / Max: 2.01 1. (CXX) g++ options: -O3 -std=c++11 -fopenmp -msse4.1 -fPIC -pie -lpthread
ASKAP ASKAP is a set of benchmarks from the Australian SKA Pathfinder. The principal ASKAP benchmarks are the Hogbom Clean Benchmark (tHogbomClean) and Convolutional Resamping Benchmark (tConvolve) as well as some previous ASKAP benchmarks being included as well for OpenCL and CUDA execution of tConvolve. Learn more via the OpenBenchmarking.org test page.
Result
OpenBenchmarking.org Mpix/sec, More Is Better ASKAP 1.0 Test: tConvolve MPI - Degridding EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 5K 10K 15K 20K 25K SE +/- 28.76, N = 3 SE +/- 48.79, N = 9 SE +/- 27.68, N = 3 SE +/- 68.60, N = 3 SE +/- 63.07, N = 3 SE +/- 137.10, N = 3 SE +/- 215.40, N = 3 SE +/- 162.55, N = 3 SE +/- 61.33, N = 3 SE +/- 197.00, N = 3 SE +/- 121.22, N = 3 SE +/- 112.07, N = 3 SE +/- 74.25, N = 4 SE +/- 118.03, N = 3 3350.22 6100.18 6587.57 10427.20 12173.70 12067.30 18311.70 11976.90 16990.10 21472.30 20993.10 20185.50 6907.54 13692.30 1. (CXX) g++ options: -O3 -fstrict-aliasing -fopenmp
Result Confidence
OpenBenchmarking.org Mpix/sec, More Is Better ASKAP 1.0 Test: tConvolve MPI - Degridding EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 4K 8K 12K 16K 20K Min: 3321.46 / Avg: 3350.22 / Max: 3407.74 Min: 5788.14 / Avg: 6100.18 / Max: 6247.52 Min: 6559.89 / Avg: 6587.57 / Max: 6642.93 Min: 10290 / Avg: 10427.2 / Max: 10495.8 Min: 12110.6 / Avg: 12173.67 / Max: 12299.8 Min: 11793.1 / Avg: 12067.3 / Max: 12204.4 Min: 18096.3 / Avg: 18311.7 / Max: 18742.5 Min: 11662 / Avg: 11976.87 / Max: 12204.4 Min: 16928.8 / Avg: 16990.13 / Max: 17112.8 Min: 21275.3 / Avg: 21472.3 / Max: 21866.3 Min: 20783.8 / Avg: 20993.07 / Max: 21203.7 Min: 19992 / Avg: 20185.5 / Max: 20380.2 Min: 6728.09 / Avg: 6907.54 / Max: 7091.77 Min: 13456.2 / Avg: 13692.27 / Max: 13810.3 1. (CXX) g++ options: -O3 -fstrict-aliasing -fopenmp
Coremark This is a test of EEMBC CoreMark processor benchmark. Learn more via the OpenBenchmarking.org test page.
Result
OpenBenchmarking.org Iterations/Sec, More Is Better Coremark 1.0 CoreMark Size 666 - Iterations Per Second EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 400K 800K 1200K 1600K 2000K SE +/- 102.44, N = 3 SE +/- 270.65, N = 3 SE +/- 538.09, N = 3 SE +/- 1815.81, N = 3 SE +/- 1542.09, N = 3 SE +/- 609.31, N = 3 SE +/- 707.15, N = 3 SE +/- 1150.50, N = 3 SE +/- 10873.39, N = 3 SE +/- 473.83, N = 3 SE +/- 1046.01, N = 3 SE +/- 818.34, N = 3 SE +/- 1470.27, N = 3 293387.40 440879.64 586659.10 603381.33 902070.15 1147733.95 1123555.30 1203386.72 1530338.79 1867023.46 1845888.80 356570.41 716393.88 1. (CC) gcc options: -O2 -lrt" -lrt
Iterations/Sec Per Watt
OpenBenchmarking.org Iterations/Sec Per Watt, More Is Better Coremark 1.0 CoreMark Size 666 - Iterations Per Second EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 3K 6K 9K 12K 15K 4345.65 5295.21 6395.91 5810.65 6564.90 8528.23 7324.67 8324.83 10306.40 11942.55 11585.51 3489.81 3863.56
Result Confidence
OpenBenchmarking.org Iterations/Sec, More Is Better Coremark 1.0 CoreMark Size 666 - Iterations Per Second EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 300K 600K 900K 1200K 1500K Min: 293258.49 / Avg: 293387.4 / Max: 293589.77 Min: 440356.87 / Avg: 440879.64 / Max: 441262.65 Min: 585752.04 / Avg: 586659.1 / Max: 587614.19 Min: 599995.31 / Avg: 603381.33 / Max: 606211.3 Min: 899666.14 / Avg: 902070.15 / Max: 904945.39 Min: 1146516.78 / Avg: 1147733.95 / Max: 1148394.04 Min: 1122462.4 / Avg: 1123555.3 / Max: 1124879.16 Min: 1201201.2 / Avg: 1203386.72 / Max: 1205102.86 Min: 1517351.75 / Avg: 1530338.79 / Max: 1551938.41 Min: 1866161.25 / Avg: 1867023.46 / Max: 1867795.13 Min: 1844712.66 / Avg: 1845888.8 / Max: 1847975.17 Min: 355244.72 / Avg: 356570.41 / Max: 358064.49 Min: 713469.52 / Avg: 716393.88 / Max: 718122.78 1. (CC) gcc options: -O2 -lrt" -lrt
oneDNN This is a test of the Intel oneDNN as an Intel-optimized library for Deep Neural Networks and making use of its built-in benchdnn functionality. The result is the total perf time reported. Intel oneDNN was formerly known as DNNL (Deep Neural Network Library) and MKL-DNN before being rebranded as part of the Intel oneAPI initiative. Learn more via the OpenBenchmarking.org test page.
Result
OpenBenchmarking.org ms, Fewer Is Better oneDNN 2.0 Harness: IP Shapes 3D - Data Type: f32 - Engine: CPU EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 2 4 6 8 10 SE +/- 0.01715, N = 5 SE +/- 0.00853, N = 5 SE +/- 0.00189, N = 5 SE +/- 0.00471, N = 5 SE +/- 0.01609, N = 5 SE +/- 0.00256, N = 5 SE +/- 0.00475, N = 5 SE +/- 0.00208, N = 5 SE +/- 0.00795, N = 5 SE +/- 0.01041, N = 5 SE +/- 0.01221, N = 5 SE +/- 0.00630, N = 5 SE +/- 0.00869, N = 5 SE +/- 0.01324, N = 5 7.15030 4.97512 4.47287 3.76395 4.13382 2.96283 1.25154 2.95830 2.28611 1.22011 1.12502 1.15943 6.68209 2.77826 MIN: 6.45 MIN: 4.75 MIN: 4.3 MIN: 3.68 MIN: 3.91 MIN: 2.89 MIN: 1.2 MIN: 2.88 MIN: 2.2 MIN: 6.52 MIN: 2.68 1. (CXX) g++ options: -O3 -std=c++11 -fopenmp -msse4.1 -fPIC -pie -lpthread
Result Confidence
OpenBenchmarking.org ms, Fewer Is Better oneDNN 2.0 Harness: IP Shapes 3D - Data Type: f32 - Engine: CPU EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 3 6 9 12 15 Min: 7.11 / Avg: 7.15 / Max: 7.19 Min: 4.94 / Avg: 4.98 / Max: 4.99 Min: 4.47 / Avg: 4.47 / Max: 4.48 Min: 3.75 / Avg: 3.76 / Max: 3.78 Min: 4.08 / Avg: 4.13 / Max: 4.18 Min: 2.96 / Avg: 2.96 / Max: 2.97 Min: 1.24 / Avg: 1.25 / Max: 1.26 Min: 2.95 / Avg: 2.96 / Max: 2.97 Min: 2.26 / Avg: 2.29 / Max: 2.3 Min: 1.19 / Avg: 1.22 / Max: 1.25 Min: 1.1 / Avg: 1.13 / Max: 1.17 Min: 1.14 / Avg: 1.16 / Max: 1.17 Min: 6.66 / Avg: 6.68 / Max: 6.71 Min: 2.75 / Avg: 2.78 / Max: 2.83 1. (CXX) g++ options: -O3 -std=c++11 -fopenmp -msse4.1 -fPIC -pie -lpthread
m-queens A solver for the N-queens problem with multi-threading support via the OpenMP library. Learn more via the OpenBenchmarking.org test page.
Result
OpenBenchmarking.org Seconds, Fewer Is Better m-queens 1.2 Time To Solve EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 20 40 60 80 100 SE +/- 0.01, N = 3 SE +/- 0.02, N = 3 SE +/- 0.04, N = 3 SE +/- 0.02, N = 3 SE +/- 0.08, N = 3 SE +/- 0.05, N = 3 SE +/- 0.03, N = 3 SE +/- 0.05, N = 3 SE +/- 0.06, N = 4 SE +/- 0.03, N = 4 SE +/- 0.03, N = 4 SE +/- 0.01, N = 3 SE +/- 0.01, N = 3 87.19 58.22 43.74 42.38 28.19 22.63 23.05 21.37 16.61 13.75 13.84 71.58 35.92 1. (CXX) g++ options: -fopenmp -O2 -march=native
Result Confidence
OpenBenchmarking.org Seconds, Fewer Is Better m-queens 1.2 Time To Solve EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 20 40 60 80 100 Min: 87.19 / Avg: 87.19 / Max: 87.2 Min: 58.19 / Avg: 58.22 / Max: 58.26 Min: 43.69 / Avg: 43.74 / Max: 43.81 Min: 42.35 / Avg: 42.38 / Max: 42.41 Min: 28.07 / Avg: 28.19 / Max: 28.33 Min: 22.57 / Avg: 22.63 / Max: 22.73 Min: 23.01 / Avg: 23.05 / Max: 23.09 Min: 21.31 / Avg: 21.37 / Max: 21.46 Min: 16.48 / Avg: 16.61 / Max: 16.78 Min: 13.72 / Avg: 13.75 / Max: 13.84 Min: 13.77 / Avg: 13.84 / Max: 13.89 Min: 71.55 / Avg: 71.58 / Max: 71.6 Min: 35.9 / Avg: 35.92 / Max: 35.93 1. (CXX) g++ options: -fopenmp -O2 -march=native
Stockfish This is a test of Stockfish, an advanced C++11 chess benchmark that can scale up to 128 CPU cores. Learn more via the OpenBenchmarking.org test page.
Result
OpenBenchmarking.org Nodes Per Second, More Is Better Stockfish 12 Total Time EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 20M 40M 60M 80M 100M SE +/- 150250.14, N = 3 SE +/- 71263.56, N = 3 SE +/- 236966.05, N = 10 SE +/- 332801.18, N = 6 SE +/- 304616.08, N = 3 SE +/- 436034.06, N = 15 SE +/- 708563.50, N = 4 SE +/- 88880.09, N = 3 SE +/- 82765.80, N = 3 SE +/- 1212155.43, N = 4 SE +/- 597478.91, N = 3 SE +/- 79798.13, N = 3 SE +/- 416432.88, N = 3 16034994 24314443 31246137 32973749 48804732 60864616 58384026 64152929 82397132 98847469 100908453 19191199 39043410 1. (CXX) g++ options: -m64 -lpthread -fno-exceptions -std=c++17 -pedantic -O3 -msse -msse3 -mpopcnt -msse4.1 -mssse3 -msse2 -flto -flto=jobserver
Nodes Per Second Per Watt
OpenBenchmarking.org Nodes Per Second Per Watt, More Is Better Stockfish 12 Total Time EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 120K 240K 360K 480K 600K 205655.17 246303.77 311552.67 271259.26 325661.01 419124.02 369416.83 391203.16 491891.78 560733.59 552076.25 162559.29 179617.03
Result Confidence
OpenBenchmarking.org Nodes Per Second, More Is Better Stockfish 12 Total Time EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 20M 40M 60M 80M 100M Min: 15735361 / Avg: 16034994 / Max: 16204568 Min: 24195092 / Avg: 24314443.33 / Max: 24441587 Min: 30342075 / Avg: 31246136.8 / Max: 32525396 Min: 32141990 / Avg: 32973748.83 / Max: 34537511 Min: 48420286 / Avg: 48804732.33 / Max: 49406252 Min: 57227030 / Avg: 60864616.13 / Max: 63501145 Min: 56735799 / Avg: 58384025.75 / Max: 60090226 Min: 63992140 / Avg: 64152928.67 / Max: 64298968 Min: 82260216 / Avg: 82397132 / Max: 82546157 Min: 95322228 / Avg: 98847468.5 / Max: 100858323 Min: 99825755 / Avg: 100908453 / Max: 101887714 Min: 19064701 / Avg: 19191199.33 / Max: 19338721 Min: 38530677 / Avg: 39043410.33 / Max: 39868176 1. (CXX) g++ options: -m64 -lpthread -fno-exceptions -std=c++17 -pedantic -O3 -msse -msse3 -mpopcnt -msse4.1 -mssse3 -msse2 -flto -flto=jobserver
N-Queens This is a test of the OpenMP version of a test that solves the N-queens problem. The board problem size is 18. Learn more via the OpenBenchmarking.org test page.
Result
OpenBenchmarking.org Seconds, Fewer Is Better N-Queens 1.0 Elapsed Time EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 4 8 12 16 20 SE +/- 0.001, N = 3 SE +/- 0.000, N = 4 SE +/- 0.004, N = 5 SE +/- 0.000, N = 5 SE +/- 0.001, N = 7 SE +/- 0.001, N = 8 SE +/- 0.001, N = 8 SE +/- 0.000, N = 8 SE +/- 0.001, N = 9 SE +/- 0.001, N = 10 SE +/- 0.001, N = 10 SE +/- 0.000, N = 4 SE +/- 0.000, N = 6 17.421 11.618 8.785 8.449 5.645 4.599 4.710 4.273 3.352 2.787 2.802 14.298 7.152 1. (CC) gcc options: -static -fopenmp -O3 -march=native
Result Confidence
OpenBenchmarking.org Seconds, Fewer Is Better N-Queens 1.0 Elapsed Time EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 4 8 12 16 20 Min: 17.42 / Avg: 17.42 / Max: 17.42 Min: 11.62 / Avg: 11.62 / Max: 11.62 Min: 8.78 / Avg: 8.79 / Max: 8.8 Min: 8.45 / Avg: 8.45 / Max: 8.45 Min: 5.64 / Avg: 5.65 / Max: 5.65 Min: 4.6 / Avg: 4.6 / Max: 4.6 Min: 4.71 / Avg: 4.71 / Max: 4.71 Min: 4.27 / Avg: 4.27 / Max: 4.27 Min: 3.35 / Avg: 3.35 / Max: 3.36 Min: 2.78 / Avg: 2.79 / Max: 2.79 Min: 2.8 / Avg: 2.8 / Max: 2.81 Min: 14.3 / Avg: 14.3 / Max: 14.3 Min: 7.15 / Avg: 7.15 / Max: 7.15 1. (CC) gcc options: -static -fopenmp -O3 -march=native
C-Ray This is a test of C-Ray, a simple raytracer designed to test the floating-point CPU performance. This test is multi-threaded (16 threads per core), will shoot 8 rays per pixel for anti-aliasing, and will generate a 1600 x 1200 image. Learn more via the OpenBenchmarking.org test page.
Result
OpenBenchmarking.org Seconds, Fewer Is Better C-Ray 1.1 Total Time - 4K, 16 Rays Per Pixel EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 20 40 60 80 100 SE +/- 0.03, N = 3 SE +/- 0.01, N = 3 SE +/- 0.03, N = 3 SE +/- 0.01, N = 3 SE +/- 0.01, N = 3 SE +/- 0.02, N = 3 SE +/- 0.01, N = 3 SE +/- 0.03, N = 3 SE +/- 0.02, N = 4 SE +/- 0.01, N = 4 SE +/- 0.02, N = 4 SE +/- 0.01, N = 4 SE +/- 0.02, N = 3 SE +/- 0.02, N = 3 79.17 52.81 39.66 38.49 25.68 20.91 21.43 19.55 15.21 15.04 12.82 12.85 64.97 32.58 1. (CC) gcc options: -lm -lpthread -O3
Result Confidence
OpenBenchmarking.org Seconds, Fewer Is Better C-Ray 1.1 Total Time - 4K, 16 Rays Per Pixel EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 15 30 45 60 75 Min: 79.13 / Avg: 79.17 / Max: 79.22 Min: 52.8 / Avg: 52.81 / Max: 52.82 Min: 39.61 / Avg: 39.66 / Max: 39.7 Min: 38.48 / Avg: 38.49 / Max: 38.51 Min: 25.67 / Avg: 25.68 / Max: 25.7 Min: 20.89 / Avg: 20.91 / Max: 20.94 Min: 21.4 / Avg: 21.43 / Max: 21.45 Min: 19.49 / Avg: 19.55 / Max: 19.6 Min: 15.17 / Avg: 15.21 / Max: 15.24 Min: 15.01 / Avg: 15.04 / Max: 15.06 Min: 12.79 / Avg: 12.81 / Max: 12.87 Min: 12.83 / Avg: 12.85 / Max: 12.87 Min: 64.93 / Avg: 64.97 / Max: 64.99 Min: 32.55 / Avg: 32.58 / Max: 32.61 1. (CC) gcc options: -lm -lpthread -O3
IndigoBench This is a test of Indigo Renderer's IndigoBench benchmark. Learn more via the OpenBenchmarking.org test page.
Result
OpenBenchmarking.org M samples/s, More Is Better IndigoBench 4.4 Acceleration: CPU - Scene: Supercar EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 5 10 15 20 25 SE +/- 0.002, N = 3 SE +/- 0.010, N = 3 SE +/- 0.005, N = 3 SE +/- 0.006, N = 3 SE +/- 0.014, N = 3 SE +/- 0.031, N = 3 SE +/- 0.016, N = 3 SE +/- 0.008, N = 3 SE +/- 0.038, N = 3 SE +/- 0.035, N = 3 SE +/- 0.063, N = 3 SE +/- 0.043, N = 3 SE +/- 0.002, N = 3 SE +/- 0.013, N = 3 3.117 4.855 6.214 6.575 9.630 11.854 11.531 12.738 15.984 16.230 19.062 19.095 3.883 7.684
M samples/s Per Watt
OpenBenchmarking.org M samples/s Per Watt, More Is Better IndigoBench 4.4 Acceleration: CPU - Scene: Supercar EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 0.0225 0.045 0.0675 0.09 0.1125 0.04 0.05 0.06 0.05 0.06 0.08 0.07 0.08 0.09 0.09 0.10 0.10 0.03 0.03
Result Confidence
OpenBenchmarking.org M samples/s, More Is Better IndigoBench 4.4 Acceleration: CPU - Scene: Supercar EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 5 10 15 20 25 Min: 3.11 / Avg: 3.12 / Max: 3.12 Min: 4.84 / Avg: 4.85 / Max: 4.87 Min: 6.21 / Avg: 6.21 / Max: 6.22 Min: 6.57 / Avg: 6.58 / Max: 6.59 Min: 9.6 / Avg: 9.63 / Max: 9.65 Min: 11.8 / Avg: 11.85 / Max: 11.9 Min: 11.52 / Avg: 11.53 / Max: 11.56 Min: 12.72 / Avg: 12.74 / Max: 12.75 Min: 15.93 / Avg: 15.98 / Max: 16.06 Min: 16.18 / Avg: 16.23 / Max: 16.3 Min: 18.94 / Avg: 19.06 / Max: 19.14 Min: 19.02 / Avg: 19.1 / Max: 19.16 Min: 3.88 / Avg: 3.88 / Max: 3.89 Min: 7.67 / Avg: 7.68 / Max: 7.71
Aircrack-ng Aircrack-ng is a tool for assessing WiFi/WLAN network security. Learn more via the OpenBenchmarking.org test page.
Result
OpenBenchmarking.org k/s, More Is Better Aircrack-ng 1.5.2 EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 30K 60K 90K 120K 150K SE +/- 6.91, N = 3 SE +/- 28.65, N = 3 SE +/- 30.64, N = 3 SE +/- 34.38, N = 3 SE +/- 16.32, N = 3 SE +/- 15.49, N = 3 SE +/- 7.45, N = 3 SE +/- 28.55, N = 3 SE +/- 87.07, N = 3 SE +/- 45.55, N = 3 SE +/- 32.87, N = 3 SE +/- 31.81, N = 3 SE +/- 28.30, N = 3 SE +/- 28.27, N = 3 23406.40 35086.95 46017.20 48284.83 71372.79 87391.79 85303.35 94237.65 119683.65 120520.68 143292.79 143169.12 28528.34 56973.85 1. (CXX) g++ options: -O3 -fvisibility=hidden -masm=intel -fcommon -rdynamic -lpthread -lz -lcrypto -lhwloc -ldl -lm -pthread
k/s Per Watt
OpenBenchmarking.org k/s Per Watt, More Is Better Aircrack-ng 1.5.2 EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 200 400 600 800 1000 334.92 387.56 473.01 426.14 481.81 628.13 551.30 584.98 725.65 669.52 819.37 798.57 262.96 275.97
Result Confidence
OpenBenchmarking.org k/s, More Is Better Aircrack-ng 1.5.2 EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 20K 40K 60K 80K 100K Min: 23398.23 / Avg: 23406.4 / Max: 23420.13 Min: 35057.87 / Avg: 35086.95 / Max: 35144.26 Min: 45958.39 / Avg: 46017.2 / Max: 46061.5 Min: 48218.5 / Avg: 48284.83 / Max: 48333.69 Min: 71350.26 / Avg: 71372.79 / Max: 71404.51 Min: 87370.61 / Avg: 87391.79 / Max: 87421.95 Min: 85294.1 / Avg: 85303.35 / Max: 85318.1 Min: 94189.9 / Avg: 94237.65 / Max: 94288.64 Min: 119543.75 / Avg: 119683.65 / Max: 119843.41 Min: 120433.36 / Avg: 120520.68 / Max: 120586.84 Min: 143233.45 / Avg: 143292.79 / Max: 143346.95 Min: 143136.28 / Avg: 143169.12 / Max: 143232.73 Min: 28484.88 / Avg: 28528.34 / Max: 28581.47 Min: 56938.61 / Avg: 56973.85 / Max: 57029.76 1. (CXX) g++ options: -O3 -fvisibility=hidden -masm=intel -fcommon -rdynamic -lpthread -lz -lcrypto -lhwloc -ldl -lm -pthread
IndigoBench This is a test of Indigo Renderer's IndigoBench benchmark. Learn more via the OpenBenchmarking.org test page.
Result
OpenBenchmarking.org M samples/s, More Is Better IndigoBench 4.4 Acceleration: CPU - Scene: Bedroom EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 2 4 6 8 10 SE +/- 0.002, N = 3 SE +/- 0.001, N = 3 SE +/- 0.001, N = 3 SE +/- 0.006, N = 3 SE +/- 0.009, N = 3 SE +/- 0.006, N = 3 SE +/- 0.008, N = 3 SE +/- 0.002, N = 3 SE +/- 0.007, N = 3 SE +/- 0.020, N = 3 SE +/- 0.013, N = 3 SE +/- 0.006, N = 3 SE +/- 0.002, N = 3 SE +/- 0.004, N = 3 1.456 2.289 2.932 3.129 4.494 5.477 5.415 5.950 7.555 7.596 8.898 8.811 1.808 3.461
M samples/s Per Watt
OpenBenchmarking.org M samples/s Per Watt, More Is Better IndigoBench 4.4 Acceleration: CPU - Scene: Bedroom EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 0.0113 0.0226 0.0339 0.0452 0.0565 0.02 0.02 0.03 0.03 0.03 0.04 0.03 0.03 0.04 0.04 0.05 0.05 0.02 0.02
Result Confidence
OpenBenchmarking.org M samples/s, More Is Better IndigoBench 4.4 Acceleration: CPU - Scene: Bedroom EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 3 6 9 12 15 Min: 1.45 / Avg: 1.46 / Max: 1.46 Min: 2.29 / Avg: 2.29 / Max: 2.29 Min: 2.93 / Avg: 2.93 / Max: 2.93 Min: 3.12 / Avg: 3.13 / Max: 3.14 Min: 4.48 / Avg: 4.49 / Max: 4.51 Min: 5.47 / Avg: 5.48 / Max: 5.49 Min: 5.4 / Avg: 5.42 / Max: 5.43 Min: 5.95 / Avg: 5.95 / Max: 5.96 Min: 7.54 / Avg: 7.56 / Max: 7.57 Min: 7.57 / Avg: 7.6 / Max: 7.64 Min: 8.88 / Avg: 8.9 / Max: 8.93 Min: 8.8 / Avg: 8.81 / Max: 8.82 Min: 1.8 / Avg: 1.81 / Max: 1.81 Min: 3.46 / Avg: 3.46 / Max: 3.47
Stress-NG Stress-NG is a Linux stress tool developed by Colin King of Canonical. Learn more via the OpenBenchmarking.org test page.
Result
OpenBenchmarking.org Bogo Ops/s, More Is Better Stress-NG 0.11.07 Test: Context Switching EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 4M 8M 12M 16M 20M SE +/- 9437.39, N = 3 SE +/- 15626.15, N = 3 SE +/- 32954.83, N = 3 SE +/- 35625.01, N = 3 SE +/- 28222.94, N = 3 SE +/- 19374.10, N = 3 SE +/- 55451.20, N = 3 SE +/- 65922.96, N = 3 SE +/- 29075.41, N = 3 SE +/- 163606.09, N = 3 SE +/- 235328.27, N = 3 SE +/- 6120.44, N = 3 SE +/- 30731.73, N = 3 3438510.35 5095560.16 6612368.67 7003110.18 10443329.12 12896969.64 12627261.93 13858394.61 17727598.84 20981193.88 20917619.76 4265815.03 8225794.40 1. (CC) gcc options: -O2 -std=gnu99 -lm -laio -lbsd -lcrypt -lrt -lz -ldl -lpthread -lc
Bogo Ops/s Per Watt
OpenBenchmarking.org Bogo Ops/s Per Watt, More Is Better Stress-NG 0.11.07 Test: Context Switching EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 30K 60K 90K 120K 150K 50370.93 58318.22 68963.86 63978.31 70344.07 93564.11 80883.70 86092.82 107976.93 120719.38 117242.06 40925.63 41954.82
Result Confidence
OpenBenchmarking.org Bogo Ops/s, More Is Better Stress-NG 0.11.07 Test: Context Switching EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 4M 8M 12M 16M 20M Min: 3425266.43 / Avg: 3438510.35 / Max: 3456778.84 Min: 5064455.01 / Avg: 5095560.16 / Max: 5113736.06 Min: 6549932.25 / Avg: 6612368.67 / Max: 6661871.66 Min: 6942183.09 / Avg: 7003110.18 / Max: 7065563.44 Min: 10405966.38 / Avg: 10443329.12 / Max: 10498652.3 Min: 12861868.91 / Avg: 12896969.64 / Max: 12928733.42 Min: 12516504.31 / Avg: 12627261.93 / Max: 12687546.78 Min: 13729117.41 / Avg: 13858394.61 / Max: 13945462.29 Min: 17694612.55 / Avg: 17727598.84 / Max: 17785565.68 Min: 20708784.06 / Avg: 20981193.88 / Max: 21274387.73 Min: 20467620.04 / Avg: 20917619.76 / Max: 21262048.98 Min: 4253702.33 / Avg: 4265815.03 / Max: 4273401.47 Min: 8193174.36 / Avg: 8225794.4 / Max: 8287218.36 1. (CC) gcc options: -O2 -std=gnu99 -lm -laio -lbsd -lcrypt -lrt -lz -ldl -lpthread -lc
OSPray Intel OSPray is a portable ray-tracing engine for high-performance, high-fidenlity scientific visualizations. OSPray builds off Intel's Embree and Intel SPMD Program Compiler (ISPC) components as part of the oneAPI rendering toolkit. Learn more via the OpenBenchmarking.org test page.
Result
OpenBenchmarking.org FPS, More Is Better OSPray 1.8.5 Demo: XFrog Forest - Renderer: Path Tracer EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 2 4 6 8 10 SE +/- 0.00, N = 3 SE +/- 0.00, N = 3 SE +/- 0.00, N = 3 SE +/- 0.00, N = 3 SE +/- 0.01, N = 3 SE +/- 0.00, N = 3 SE +/- 0.00, N = 3 SE +/- 0.01, N = 3 SE +/- 0.00, N = 3 SE +/- 0.01, N = 3 SE +/- 0.01, N = 3 SE +/- 0.00, N = 3 SE +/- 0.00, N = 3 SE +/- 0.00, N = 3 0.99 1.55 1.98 2.15 3.07 3.75 3.70 4.04 5.10 5.15 6.00 5.92 1.27 2.34 MAX: 1 MIN: 1.54 / MAX: 1.57 MIN: 1.96 / MAX: 1.99 MIN: 2.13 / MAX: 2.16 MIN: 3.02 / MAX: 3.11 MIN: 3.72 / MAX: 3.77 MIN: 3.64 / MAX: 3.73 MIN: 3.98 / MAX: 4.07 MIN: 5.05 / MAX: 5.15 MIN: 5.08 / MAX: 5.21 MIN: 5.92 / MAX: 6.06 MIN: 5.85 / MAX: 5.99 MIN: 1.26 / MAX: 1.28 MIN: 2.29 / MAX: 2.38
FPS Per Watt
OpenBenchmarking.org FPS Per Watt, More Is Better OSPray 1.8.5 Demo: XFrog Forest - Renderer: Path Tracer EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 0.009 0.018 0.027 0.036 0.045 0.01 0.02 0.02 0.02 0.02 0.03 0.02 0.02 0.03 0.03 0.04 0.03 0.01 0.01
Result Confidence
OpenBenchmarking.org FPS, More Is Better OSPray 1.8.5 Demo: XFrog Forest - Renderer: Path Tracer EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 2 4 6 8 10 Min: 0.99 / Avg: 0.99 / Max: 0.99 Min: 1.55 / Avg: 1.55 / Max: 1.55 Min: 1.98 / Avg: 1.98 / Max: 1.98 Min: 2.15 / Avg: 2.15 / Max: 2.15 Min: 3.06 / Avg: 3.07 / Max: 3.08 Min: 3.75 / Avg: 3.75 / Max: 3.75 Min: 3.7 / Avg: 3.7 / Max: 3.7 Min: 4.03 / Avg: 4.04 / Max: 4.05 Min: 5.1 / Avg: 5.1 / Max: 5.1 Min: 5.13 / Avg: 5.15 / Max: 5.15 Min: 5.99 / Avg: 6 / Max: 6.02 Min: 5.92 / Avg: 5.92 / Max: 5.92 Min: 1.27 / Avg: 1.27 / Max: 1.27 Min: 2.33 / Avg: 2.34 / Max: 2.35
Result
OpenBenchmarking.org FPS, More Is Better OSPray 1.8.5 Demo: NASA Streamlines - Renderer: Path Tracer EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 4 8 12 16 20 SE +/- 0.00, N = 3 SE +/- 0.00, N = 3 SE +/- 0.00, N = 3 SE +/- 0.01, N = 3 SE +/- 0.00, N = 3 SE +/- 0.04, N = 3 SE +/- 0.00, N = 3 SE +/- 0.00, N = 3 SE +/- 0.00, N = 3 SE +/- 0.00, N = 3 SE +/- 0.00, N = 4 SE +/- 0.00, N = 4 SE +/- 0.00, N = 3 SE +/- 0.02, N = 3 2.82 4.39 5.65 6.07 8.77 10.60 10.42 11.36 14.29 14.49 16.95 16.67 3.65 6.83 MIN: 2.79 / MAX: 2.86 MIN: 4.33 / MAX: 4.44 MIN: 5.59 / MAX: 5.75 MIN: 5.99 / MAX: 6.13 MIN: 8.62 / MAX: 8.85 MIN: 10.42 / MAX: 10.75 MIN: 10.2 / MAX: 10.53 MIN: 11.11 / MAX: 11.49 MIN: 13.89 / MAX: 14.49 MIN: 14.08 / MAX: 14.71 MIN: 16.39 / MAX: 17.24 MIN: 16.39 / MAX: 16.95 MIN: 3.58 / MAX: 3.69 MIN: 6.67 / MAX: 6.94
FPS Per Watt
OpenBenchmarking.org FPS Per Watt, More Is Better OSPray 1.8.5 Demo: NASA Streamlines - Renderer: Path Tracer EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 0.027 0.054 0.081 0.108 0.135 0.04 0.05 0.06 0.05 0.06 0.08 0.07 0.08 0.10 0.09 0.12 0.11 0.03 0.03
Result Confidence
OpenBenchmarking.org FPS, More Is Better OSPray 1.8.5 Demo: NASA Streamlines - Renderer: Path Tracer EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 4 8 12 16 20 Min: 2.82 / Avg: 2.82 / Max: 2.83 Min: 4.39 / Avg: 4.39 / Max: 4.39 Min: 5.65 / Avg: 5.65 / Max: 5.65 Min: 6.06 / Avg: 6.07 / Max: 6.1 Min: 8.77 / Avg: 8.77 / Max: 8.77 Min: 10.53 / Avg: 10.6 / Max: 10.64 Min: 10.42 / Avg: 10.42 / Max: 10.42 Min: 11.36 / Avg: 11.36 / Max: 11.36 Min: 14.29 / Avg: 14.29 / Max: 14.29 Min: 14.49 / Avg: 14.49 / Max: 14.49 Min: 16.95 / Avg: 16.95 / Max: 16.95 Min: 16.67 / Avg: 16.67 / Max: 16.67 Min: 3.64 / Avg: 3.65 / Max: 3.65 Min: 6.8 / Avg: 6.83 / Max: 6.85
asmFish This is a test of asmFish, an advanced chess benchmark written in Assembly. Learn more via the OpenBenchmarking.org test page.
Result
OpenBenchmarking.org Nodes/second, More Is Better asmFish 2018-07-23 1024 Hash Memory, 26 Depth EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 30M 60M 90M 120M 150M SE +/- 57670.67, N = 3 SE +/- 91373.33, N = 3 SE +/- 215295.19, N = 3 SE +/- 230890.74, N = 3 SE +/- 395352.82, N = 3 SE +/- 375595.74, N = 3 SE +/- 939330.26, N = 3 SE +/- 394553.31, N = 3 SE +/- 373542.05, N = 3 SE +/- 1202983.30, N = 3 SE +/- 688813.01, N = 3 SE +/- 83002.90, N = 3 SE +/- 491333.28, N = 3 21027795 31791813 41583844 42112219 62581775 78084684 74422699 82716262 105304578 126290077 122849461 24675753 46342665
Nodes/second Per Watt
OpenBenchmarking.org Nodes/second Per Watt, More Is Better asmFish 2018-07-23 1024 Hash Memory, 26 Depth EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 140K 280K 420K 560K 700K 282725.36 333068.50 394905.45 359777.90 390336.76 513107.47 437974.87 473583.96 586425.64 665647.19 630429.66 228242.13 231626.04
Result Confidence
OpenBenchmarking.org Nodes/second, More Is Better asmFish 2018-07-23 1024 Hash Memory, 26 Depth EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 20M 40M 60M 80M 100M Min: 20912491 / Avg: 21027794.67 / Max: 21087999 Min: 31610049 / Avg: 31791813.33 / Max: 31899083 Min: 41298645 / Avg: 41583844.33 / Max: 42005822 Min: 41683109 / Avg: 42112219 / Max: 42474524 Min: 61945670 / Avg: 62581775.33 / Max: 63306570 Min: 77335639 / Avg: 78084684 / Max: 78508351 Min: 72577275 / Avg: 74422699 / Max: 75650094 Min: 82311763 / Avg: 82716261.67 / Max: 83505284 Min: 104841596 / Avg: 105304577.67 / Max: 106043845 Min: 124900585 / Avg: 126290076.67 / Max: 128685849 Min: 122057435 / Avg: 122849461.33 / Max: 124221646 Min: 24510321 / Avg: 24675752.67 / Max: 24770415 Min: 45648904 / Avg: 46342664.67 / Max: 47292245
OSPray Intel OSPray is a portable ray-tracing engine for high-performance, high-fidenlity scientific visualizations. OSPray builds off Intel's Embree and Intel SPMD Program Compiler (ISPC) components as part of the oneAPI rendering toolkit. Learn more via the OpenBenchmarking.org test page.
Result
OpenBenchmarking.org FPS, More Is Better OSPray 1.8.5 Demo: XFrog Forest - Renderer: SciVis EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 3 6 9 12 15 SE +/- 0.00, N = 3 SE +/- 0.00, N = 3 SE +/- 0.00, N = 3 SE +/- 0.00, N = 3 SE +/- 0.01, N = 3 SE +/- 0.02, N = 3 SE +/- 0.00, N = 3 SE +/- 0.00, N = 3 SE +/- 0.00, N = 3 SE +/- 0.03, N = 3 SE +/- 0.00, N = 3 SE +/- 0.04, N = 3 SE +/- 0.00, N = 3 SE +/- 0.01, N = 3 1.89 2.93 3.72 4.02 5.76 7.01 6.90 7.58 9.52 9.58 11.24 11.07 2.39 4.45 MIN: 1.84 / MAX: 1.91 MIN: 2.9 / MAX: 2.97 MIN: 3.69 / MAX: 3.76 MIN: 3.98 / MAX: 4.05 MIN: 5.68 / MAX: 5.81 MIN: 6.94 / MAX: 7.09 MIN: 6.8 / MAX: 6.99 MIN: 7.46 / MAX: 7.63 MIN: 9.35 / MAX: 9.62 MIN: 9.17 / MAX: 9.71 MIN: 10.99 / MAX: 11.36 MIN: 10.75 / MAX: 11.24 MIN: 2.37 / MAX: 2.42 MIN: 4.31 / MAX: 4.52
FPS Per Watt
OpenBenchmarking.org FPS Per Watt, More Is Better OSPray 1.8.5 Demo: XFrog Forest - Renderer: SciVis EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 0.0158 0.0316 0.0474 0.0632 0.079 0.02 0.03 0.04 0.03 0.04 0.05 0.05 0.05 0.06 0.06 0.07 0.07 0.02 0.02
Result Confidence
OpenBenchmarking.org FPS, More Is Better OSPray 1.8.5 Demo: XFrog Forest - Renderer: SciVis EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 3 6 9 12 15 Min: 1.89 / Avg: 1.89 / Max: 1.89 Min: 2.93 / Avg: 2.93 / Max: 2.93 Min: 3.72 / Avg: 3.72 / Max: 3.72 Min: 4.02 / Avg: 4.02 / Max: 4.02 Min: 5.75 / Avg: 5.76 / Max: 5.78 Min: 6.99 / Avg: 7.01 / Max: 7.04 Min: 6.9 / Avg: 6.9 / Max: 6.9 Min: 7.58 / Avg: 7.58 / Max: 7.58 Min: 9.52 / Avg: 9.52 / Max: 9.52 Min: 9.52 / Avg: 9.58 / Max: 9.62 Min: 11.24 / Avg: 11.24 / Max: 11.24 Min: 10.99 / Avg: 11.07 / Max: 11.11 Min: 2.39 / Avg: 2.39 / Max: 2.39 Min: 4.44 / Avg: 4.45 / Max: 4.46
ASKAP ASKAP is a set of benchmarks from the Australian SKA Pathfinder. The principal ASKAP benchmarks are the Hogbom Clean Benchmark (tHogbomClean) and Convolutional Resamping Benchmark (tConvolve) as well as some previous ASKAP benchmarks being included as well for OpenCL and CUDA execution of tConvolve. Learn more via the OpenBenchmarking.org test page.
Result
OpenBenchmarking.org Mpix/sec, More Is Better ASKAP 1.0 Test: tConvolve MPI - Gridding EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 5K 10K 15K 20K 25K SE +/- 50.92, N = 3 SE +/- 54.85, N = 9 SE +/- 69.42, N = 3 SE +/- 0.00, N = 3 SE +/- 82.20, N = 3 SE +/- 101.60, N = 3 SE +/- 233.09, N = 3 SE +/- 136.29, N = 3 SE +/- 0.00, N = 3 SE +/- 111.87, N = 3 SE +/- 197.85, N = 2 SE +/- 66.13, N = 4 SE +/- 0.00, N = 3 3879.10 7130.89 7358.19 12204.40 13892.50 12698.20 20585.30 12699.50 17300.80 23040.70 20991.70 20382.20 8265.99 16399.70 1. (CXX) g++ options: -O3 -fstrict-aliasing -fopenmp
Mpix/sec Per Watt
OpenBenchmarking.org Mpix/sec Per Watt, More Is Better ASKAP 1.0 Test: tConvolve MPI - Gridding EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 30 60 90 120 150 62.30 97.15 92.77 132.05 123.63 104.15 137.34 105.62 117.11 139.29 123.10 116.25 93.74 117.06
Result Confidence
OpenBenchmarking.org Mpix/sec, More Is Better ASKAP 1.0 Test: tConvolve MPI - Gridding EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 4K 8K 12K 16K 20K Min: 3802.84 / Avg: 3879.1 / Max: 3975.69 Min: 6786.09 / Avg: 7130.89 / Max: 7288.77 Min: 7288.77 / Avg: 7358.19 / Max: 7497.02 Min: 12204.4 / Avg: 12204.4 / Max: 12204.4 Min: 13810.3 / Avg: 13892.5 / Max: 14056.9 Min: 12495 / Avg: 12698.2 / Max: 12799.8 Min: 20184.3 / Avg: 20585.33 / Max: 20991.7 Min: 12495 / Avg: 12699.47 / Max: 12957.8 Min: 17300.8 / Avg: 17300.8 / Max: 17300.8 Min: 22817 / Avg: 23040.73 / Max: 23152.6 Min: 20184.3 / Avg: 20382.15 / Max: 20580 Min: 8199.86 / Avg: 8265.99 / Max: 8464.38 Min: 16399.7 / Avg: 16399.7 / Max: 16399.7 1. (CXX) g++ options: -O3 -fstrict-aliasing -fopenmp
Tachyon This is a test of the threaded Tachyon, a parallel ray-tracing system, measuring the time to ray-trace a sample scene. Learn more via the OpenBenchmarking.org test page.
Result
OpenBenchmarking.org Seconds, Fewer Is Better Tachyon 0.99b6 Total Time EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 30 60 90 120 150 SE +/- 0.26, N = 3 SE +/- 0.04, N = 3 SE +/- 0.27, N = 3 SE +/- 0.03, N = 3 SE +/- 0.07, N = 3 SE +/- 0.02, N = 3 SE +/- 0.02, N = 3 SE +/- 0.05, N = 3 SE +/- 0.03, N = 3 SE +/- 0.03, N = 3 SE +/- 0.02, N = 3 SE +/- 0.01, N = 3 SE +/- 0.14, N = 3 SE +/- 0.05, N = 3 112.39 75.04 58.47 54.84 37.73 30.90 31.57 28.59 22.81 22.56 19.08 19.12 92.16 46.59 1. (CC) gcc options: -m64 -O3 -fomit-frame-pointer -ffast-math -ltachyon -lm -lpthread
Result Confidence
OpenBenchmarking.org Seconds, Fewer Is Better Tachyon 0.99b6 Total Time EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 20 40 60 80 100 Min: 112.07 / Avg: 112.39 / Max: 112.9 Min: 74.96 / Avg: 75.04 / Max: 75.08 Min: 58.2 / Avg: 58.47 / Max: 59 Min: 54.8 / Avg: 54.84 / Max: 54.9 Min: 37.62 / Avg: 37.73 / Max: 37.87 Min: 30.86 / Avg: 30.9 / Max: 30.92 Min: 31.53 / Avg: 31.57 / Max: 31.59 Min: 28.5 / Avg: 28.59 / Max: 28.69 Min: 22.76 / Avg: 22.81 / Max: 22.84 Min: 22.52 / Avg: 22.56 / Max: 22.63 Min: 19.06 / Avg: 19.08 / Max: 19.12 Min: 19.11 / Avg: 19.12 / Max: 19.14 Min: 91.95 / Avg: 92.16 / Max: 92.42 Min: 46.49 / Avg: 46.59 / Max: 46.65 1. (CC) gcc options: -m64 -O3 -fomit-frame-pointer -ffast-math -ltachyon -lm -lpthread
7-Zip Compression This is a test of 7-Zip using p7zip with its integrated benchmark feature or upstream 7-Zip for the Windows x64 build. Learn more via the OpenBenchmarking.org test page.
Result
OpenBenchmarking.org MIPS, More Is Better 7-Zip Compression 16.02 Compress Speed Test EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 60K 120K 180K 240K 300K SE +/- 84.48, N = 3 SE +/- 108.98, N = 3 SE +/- 313.91, N = 3 SE +/- 192.03, N = 3 SE +/- 315.33, N = 3 SE +/- 249.88, N = 3 SE +/- 894.75, N = 3 SE +/- 190.42, N = 3 SE +/- 453.51, N = 3 SE +/- 419.38, N = 3 SE +/- 226.28, N = 3 SE +/- 288.04, N = 3 SE +/- 558.99, N = 3 45941 69655 90588 95137 138575 171362 171242 176148 229747 270140 264908 56955 109069 1. (CXX) g++ options: -pipe -lpthread
MIPS Per Watt
OpenBenchmarking.org MIPS Per Watt, More Is Better 7-Zip Compression 16.02 Compress Speed Test EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 400 800 1200 1600 2000 710.08 872.02 1034.12 969.68 1091.49 1397.09 1207.72 1318.89 1667.35 1860.21 1772.21 601.78 654.08
Result Confidence
OpenBenchmarking.org MIPS, More Is Better 7-Zip Compression 16.02 Compress Speed Test EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 50K 100K 150K 200K 250K Min: 45801 / Avg: 45941.33 / Max: 46093 Min: 69500 / Avg: 69654.67 / Max: 69865 Min: 90180 / Avg: 90587.67 / Max: 91205 Min: 94939 / Avg: 95137 / Max: 95521 Min: 138164 / Avg: 138575.33 / Max: 139195 Min: 170978 / Avg: 171362 / Max: 171831 Min: 169527 / Avg: 171242 / Max: 172542 Min: 175784 / Avg: 176148 / Max: 176427 Min: 229189 / Avg: 229746.67 / Max: 230645 Min: 269353 / Avg: 270139.67 / Max: 270785 Min: 264563 / Avg: 264907.67 / Max: 265334 Min: 56532 / Avg: 56954.67 / Max: 57505 Min: 108136 / Avg: 109069.33 / Max: 110069 1. (CXX) g++ options: -pipe -lpthread
John The Ripper This is a benchmark of John The Ripper, which is a password cracker. Learn more via the OpenBenchmarking.org test page.
Result
OpenBenchmarking.org Real C/S, More Is Better John The Ripper 1.9.0-jumbo-1 Test: MD5 EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 900K 1800K 2700K 3600K 4500K SE +/- 798.79, N = 3 SE +/- 881.92, N = 3 SE +/- 2000.00, N = 3 SE +/- 2603.42, N = 3 SE +/- 1452.97, N = 3 SE +/- 2185.81, N = 3 SE +/- 1527.53, N = 3 SE +/- 2905.93, N = 3 SE +/- 881.92, N = 3 SE +/- 881.92, N = 3 SE +/- 3282.95, N = 3 SE +/- 525.27, N = 3 SE +/- 1763.83, N = 3 717175 1072333 1354000 1460333 2127333 2596333 2534000 2798667 3528667 3557667 4195333 4183000 874700 1731667 1. (CC) gcc options: -m64 -lssl -lcrypto -fopenmp -lgmp -pthread -lm -lz -ldl -lcrypt -lbz2
Real C/S Per Watt
OpenBenchmarking.org Real C/S Per Watt, More Is Better John The Ripper 1.9.0-jumbo-1 Test: MD5 EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 5K 10K 15K 20K 25K 9459.27 10769.05 13466.23 11851.02 13762.68 17709.04 15619.65 16435.49 20367.12 18839.03 22927.63 22232.88 7334.16 7625.61
Result Confidence
OpenBenchmarking.org Real C/S, More Is Better John The Ripper 1.9.0-jumbo-1 Test: MD5 EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 700K 1400K 2100K 2800K 3500K Min: 716134 / Avg: 717175 / Max: 718745 Min: 1071000 / Avg: 1072333.33 / Max: 1074000 Min: 1352000 / Avg: 1354000 / Max: 1358000 Min: 1456000 / Avg: 1460333.33 / Max: 1465000 Min: 2125000 / Avg: 2127333.33 / Max: 2130000 Min: 2592000 / Avg: 2596333.33 / Max: 2599000 Min: 2531000 / Avg: 2534000 / Max: 2536000 Min: 2794000 / Avg: 2798666.67 / Max: 2804000 Min: 3527000 / Avg: 3528666.67 / Max: 3530000 Min: 3556000 / Avg: 3557666.67 / Max: 3559000 Min: 4189000 / Avg: 4195333.33 / Max: 4200000 Min: 873984 / Avg: 874700.33 / Max: 875724 Min: 1729000 / Avg: 1731666.67 / Max: 1735000 1. (CC) gcc options: -m64 -lssl -lcrypto -fopenmp -lgmp -pthread -lm -lz -ldl -lcrypt -lbz2
Chaos Group V-RAY This is a test of Chaos Group's V-RAY benchmark. V-RAY is a commercial renderer that can integrate with various creator software products like SketchUp and 3ds Max. The V-RAY benchmark is standalone and supports CPU and NVIDIA CUDA/RTX based rendering. Learn more via the OpenBenchmarking.org test page.
Result
OpenBenchmarking.org vsamples, More Is Better Chaos Group V-RAY 5 Mode: CPU EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 10K 20K 30K 40K 50K SE +/- 50.21, N = 3 SE +/- 140.41, N = 4 SE +/- 120.35, N = 3 SE +/- 298.29, N = 3 SE +/- 144.16, N = 3 SE +/- 305.20, N = 6 SE +/- 284.86, N = 11 SE +/- 392.90, N = 8 SE +/- 469.86, N = 3 SE +/- 117.08, N = 4 SE +/- 165.84, N = 3 7864 12198 15246 28448 28401 30632 37843 44658 45292 10044 19521
vsamples Per Watt
OpenBenchmarking.org vsamples Per Watt, More Is Better Chaos Group V-RAY 5 Mode: CPU EPYC 7272 EPYC 7282 EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7662 EPYC 7F32 EPYC 7F52 60 120 180 240 300 135.50 168.70 212.71 193.49 202.52 244.21 272.08 84.74 94.82
Result Confidence
OpenBenchmarking.org vsamples, More Is Better Chaos Group V-RAY 5 Mode: CPU EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 8K 16K 24K 32K 40K Min: 7769 / Avg: 7863.67 / Max: 7940 Min: 11788 / Avg: 12198.25 / Max: 12425 Min: 15016 / Avg: 15246.33 / Max: 15422 Min: 28095 / Avg: 28448 / Max: 29041 Min: 28141 / Avg: 28400.67 / Max: 28639 Min: 29652 / Avg: 30632 / Max: 31469 Min: 36221 / Avg: 37842.73 / Max: 38879 Min: 43124 / Avg: 44658.38 / Max: 46027 Min: 44695 / Avg: 45292 / Max: 46219 Min: 9719 / Avg: 10044.25 / Max: 10235 Min: 19190 / Avg: 19521 / Max: 19705
ASTC Encoder ASTC Encoder (astcenc) is for the Adaptive Scalable Texture Compression (ASTC) format commonly used with OpenGL, OpenGL ES, and Vulkan graphics APIs. This test profile does a coding test of both compression/decompression. Learn more via the OpenBenchmarking.org test page.
Result
OpenBenchmarking.org Seconds, Fewer Is Better ASTC Encoder 2.0 Preset: Exhaustive EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 60 120 180 240 300 SE +/- 0.12, N = 3 SE +/- 0.01, N = 3 SE +/- 0.02, N = 3 SE +/- 0.05, N = 3 SE +/- 0.01, N = 3 SE +/- 0.01, N = 3 SE +/- 0.00, N = 3 SE +/- 0.01, N = 3 SE +/- 0.01, N = 3 SE +/- 0.01, N = 3 SE +/- 0.01, N = 3 SE +/- 0.02, N = 3 SE +/- 0.16, N = 3 262.14 176.04 137.78 129.26 89.07 73.38 75.27 67.95 54.34 45.84 45.80 214.44 109.17 1. (CXX) g++ options: -std=c++14 -fvisibility=hidden -O3 -flto -mfpmath=sse -mavx2 -mpopcnt -lpthread
Result Confidence
OpenBenchmarking.org Seconds, Fewer Is Better ASTC Encoder 2.0 Preset: Exhaustive EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 50 100 150 200 250 Min: 262.01 / Avg: 262.14 / Max: 262.39 Min: 176.03 / Avg: 176.04 / Max: 176.05 Min: 137.74 / Avg: 137.78 / Max: 137.82 Min: 129.21 / Avg: 129.26 / Max: 129.36 Min: 89.06 / Avg: 89.07 / Max: 89.08 Min: 73.37 / Avg: 73.38 / Max: 73.4 Min: 75.26 / Avg: 75.27 / Max: 75.27 Min: 67.93 / Avg: 67.95 / Max: 67.96 Min: 54.32 / Avg: 54.34 / Max: 54.35 Min: 45.83 / Avg: 45.84 / Max: 45.85 Min: 45.79 / Avg: 45.8 / Max: 45.82 Min: 214.41 / Avg: 214.44 / Max: 214.47 Min: 108.86 / Avg: 109.17 / Max: 109.35 1. (CXX) g++ options: -std=c++14 -fvisibility=hidden -O3 -flto -mfpmath=sse -mavx2 -mpopcnt -lpthread
OSPray Intel OSPray is a portable ray-tracing engine for high-performance, high-fidenlity scientific visualizations. OSPray builds off Intel's Embree and Intel SPMD Program Compiler (ISPC) components as part of the oneAPI rendering toolkit. Learn more via the OpenBenchmarking.org test page.
Result
OpenBenchmarking.org FPS, More Is Better OSPray 1.8.5 Demo: Magnetic Reconnection - Renderer: SciVis EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 9 18 27 36 45 SE +/- 0.00, N = 3 SE +/- 0.00, N = 3 SE +/- 0.00, N = 4 SE +/- 0.00, N = 4 SE +/- 0.00, N = 5 SE +/- 0.17, N = 5 SE +/- 0.00, N = 5 SE +/- 0.00, N = 6 SE +/- 0.00, N = 6 SE +/- 0.08, N = 6 SE +/- 0.06, N = 3 6.99 10.42 13.89 14.08 20.83 26.05 25.00 27.78 34.48 34.48 40.00 40.00 8.16 13.45 MIN: 5.95 / MAX: 7.04 MIN: 10.1 / MAX: 10.64 MIN: 13.33 / MAX: 14.08 MIN: 12.99 / MAX: 14.29 MIN: 20.41 / MAX: 21.28 MIN: 25.64 / MAX: 26.32 MIN: 23.81 / MAX: 25.64 MIN: 27.03 MIN: 33.33 / MAX: 35.71 MIN: 33.33 / MAX: 35.71 MIN: 38.46 / MAX: 41.67 MIN: 34.48 / MAX: 41.67 MIN: 6.85 / MAX: 8.4 MIN: 12.82 / MAX: 13.89
FPS Per Watt
OpenBenchmarking.org FPS Per Watt, More Is Better OSPray 1.8.5 Demo: Magnetic Reconnection - Renderer: SciVis EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 0.0698 0.1396 0.2094 0.2792 0.349 0.11 0.13 0.16 0.15 0.17 0.23 0.19 0.22 0.28 0.25 0.31 0.30 0.08 0.09
Result Confidence
OpenBenchmarking.org FPS, More Is Better OSPray 1.8.5 Demo: Magnetic Reconnection - Renderer: SciVis EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 8 16 24 32 40 Min: 6.99 / Avg: 6.99 / Max: 6.99 Min: 10.42 / Avg: 10.42 / Max: 10.42 Min: 13.89 / Avg: 13.89 / Max: 13.89 Min: 14.08 / Avg: 14.08 / Max: 14.08 Min: 20.83 / Avg: 20.83 / Max: 20.83 Min: 25.64 / Avg: 26.05 / Max: 26.32 Min: 27.78 / Avg: 27.78 / Max: 27.78 Min: 34.48 / Avg: 34.48 / Max: 34.48 Min: 34.48 / Avg: 34.48 / Max: 34.48 Min: 7.75 / Avg: 8.16 / Max: 8.26 Min: 13.33 / Avg: 13.45 / Max: 13.51
Result
OpenBenchmarking.org FPS, More Is Better OSPray 1.8.5 Demo: San Miguel - Renderer: SciVis EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 13 26 39 52 65 SE +/- 0.00, N = 3 SE +/- 0.00, N = 3 SE +/- 0.00, N = 3 SE +/- 0.00, N = 3 SE +/- 0.00, N = 3 SE +/- 0.00, N = 3 SE +/- 0.00, N = 3 SE +/- 0.00, N = 3 SE +/- 0.00, N = 3 SE +/- 0.00, N = 3 SE +/- 0.17, N = 3 10.31 15.63 19.61 20.83 30.30 37.04 35.71 40.00 50.00 50.00 58.82 55.56 12.50 22.56 MIN: 10.1 / MAX: 10.99 MIN: 15.15 / MAX: 16.67 MIN: 19.23 / MAX: 21.28 MIN: 20.41 / MAX: 22.73 MIN: 29.41 / MAX: 32.26 MIN: 34.48 / MAX: 40 MIN: 33.33 / MAX: 38.46 MIN: 37.04 / MAX: 41.67 MIN: 47.62 / MAX: 52.63 MIN: 47.62 / MAX: 52.63 MIN: 52.63 / MAX: 62.5 MIN: 50 / MAX: 62.5 MIN: 12.2 / MAX: 13.33 MIN: 21.28 / MAX: 24.39
FPS Per Watt
OpenBenchmarking.org FPS Per Watt, More Is Better OSPray 1.8.5 Demo: San Miguel - Renderer: SciVis EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 0.162 0.324 0.486 0.648 0.81 0.19 0.26 0.34 0.31 0.44 0.57 0.43 0.59 0.69 0.62 0.72 0.67 0.16 0.21
Result Confidence
OpenBenchmarking.org FPS, More Is Better OSPray 1.8.5 Demo: San Miguel - Renderer: SciVis EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 12 24 36 48 60 Min: 10.31 / Avg: 10.31 / Max: 10.31 Min: 15.63 / Avg: 15.63 / Max: 15.63 Min: 19.61 / Avg: 19.61 / Max: 19.61 Min: 20.83 / Avg: 20.83 / Max: 20.83 Min: 30.3 / Avg: 30.3 / Max: 30.3 Min: 37.04 / Avg: 37.04 / Max: 37.04 Min: 35.71 / Avg: 35.71 / Max: 35.71 Min: 58.82 / Avg: 58.82 / Max: 58.82 Min: 55.56 / Avg: 55.56 / Max: 55.56 Min: 12.5 / Avg: 12.5 / Max: 12.5 Min: 22.22 / Avg: 22.56 / Max: 22.73
Stress-NG Stress-NG is a Linux stress tool developed by Colin King of Canonical. Learn more via the OpenBenchmarking.org test page.
Result
OpenBenchmarking.org Bogo Ops/s, More Is Better Stress-NG 0.11.07 Test: Matrix Math EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 40K 80K 120K 160K 200K SE +/- 186.09, N = 3 SE +/- 183.06, N = 3 SE +/- 294.16, N = 3 SE +/- 123.36, N = 3 SE +/- 377.08, N = 3 SE +/- 1288.21, N = 3 SE +/- 270.71, N = 3 SE +/- 157.32, N = 3 SE +/- 457.19, N = 3 SE +/- 1795.92, N = 3 SE +/- 558.83, N = 3 SE +/- 382.53, N = 3 SE +/- 417.25, N = 3 31690.60 46780.94 59431.03 63930.72 92207.07 112205.01 110766.79 122762.96 152001.95 179496.78 179226.24 38378.08 76923.39 1. (CC) gcc options: -O2 -std=gnu99 -lm -laio -lbsd -lcrypt -lrt -lz -ldl -lpthread -lc
Bogo Ops/s Per Watt
OpenBenchmarking.org Bogo Ops/s Per Watt, More Is Better Stress-NG 0.11.07 Test: Matrix Math EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 200 400 600 800 1000 412.61 484.49 617.90 545.34 638.73 791.90 717.75 751.29 911.37 1022.61 987.36 324.00 348.06
Result Confidence
OpenBenchmarking.org Bogo Ops/s, More Is Better Stress-NG 0.11.07 Test: Matrix Math EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 30K 60K 90K 120K 150K Min: 31367.04 / Avg: 31690.6 / Max: 32011.65 Min: 46417.91 / Avg: 46780.94 / Max: 47003.53 Min: 59024.95 / Avg: 59431.03 / Max: 60002.73 Min: 63684.02 / Avg: 63930.72 / Max: 64057.16 Min: 91633.53 / Avg: 92207.07 / Max: 92917.94 Min: 109640.44 / Avg: 112205.01 / Max: 113701 Min: 110323.78 / Avg: 110766.79 / Max: 111257.86 Min: 122497.64 / Avg: 122762.96 / Max: 123042.09 Min: 151506.09 / Avg: 152001.95 / Max: 152915.2 Min: 175929.7 / Avg: 179496.78 / Max: 181644.9 Min: 178344.47 / Avg: 179226.24 / Max: 180261.88 Min: 37633.18 / Avg: 38378.08 / Max: 38901.65 Min: 76194.59 / Avg: 76923.39 / Max: 77639.82 1. (CC) gcc options: -O2 -std=gnu99 -lm -laio -lbsd -lcrypt -lrt -lz -ldl -lpthread -lc
Chaos Group V-RAY This is a test of Chaos Group's V-RAY benchmark. Learn more via the OpenBenchmarking.org test page.
Result
OpenBenchmarking.org Ksamples, More Is Better Chaos Group V-RAY 4.10.07 Mode: CPU EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 13K 26K 39K 52K 65K SE +/- 44.44, N = 3 SE +/- 80.88, N = 3 SE +/- 122.98, N = 3 SE +/- 114.11, N = 3 SE +/- 87.62, N = 3 SE +/- 264.62, N = 15 SE +/- 397.54, N = 5 SE +/- 391.02, N = 6 SE +/- 328.54, N = 3 SE +/- 179.29, N = 3 SE +/- 467.21, N = 3 SE +/- 487.40, N = 3 SE +/- 31.21, N = 3 SE +/- 71.92, N = 3 11136 17550 22022 23486 33184 37085 36223 38904 53570 54445 62295 62754 14204 27132
Ksamples Per Watt
OpenBenchmarking.org Ksamples Per Watt, More Is Better Chaos Group V-RAY 4.10.07 Mode: CPU EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 80 160 240 320 400 152.41 185.79 233.63 202.24 235.77 275.92 243.18 257.36 328.86 306.53 364.02 353.18 124.47 127.66
Result Confidence
OpenBenchmarking.org Ksamples, More Is Better Chaos Group V-RAY 4.10.07 Mode: CPU EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 11K 22K 33K 44K 55K Min: 11048 / Avg: 11136.33 / Max: 11189 Min: 17397 / Avg: 17550 / Max: 17672 Min: 21875 / Avg: 22021.67 / Max: 22266 Min: 23305 / Avg: 23486.33 / Max: 23697 Min: 33018 / Avg: 33183.67 / Max: 33316 Min: 35376 / Avg: 37084.67 / Max: 38925 Min: 35373 / Avg: 36223.2 / Max: 37595 Min: 37112 / Avg: 38903.83 / Max: 39603 Min: 53078 / Avg: 53569.67 / Max: 54193 Min: 54235 / Avg: 54445.33 / Max: 54802 Min: 61378 / Avg: 62294.67 / Max: 62910 Min: 62183 / Avg: 62754.33 / Max: 63724 Min: 14151 / Avg: 14203.67 / Max: 14259 Min: 27010 / Avg: 27132 / Max: 27259
Pennant Pennant is an application focused on hydrodynamics on general unstructured meshes in 2D. Learn more via the OpenBenchmarking.org test page.
Result
OpenBenchmarking.org Hydro Cycle Time - Seconds, Fewer Is Better Pennant 1.0.1 Test: sedovbig EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 15 30 45 60 75 SE +/- 0.14, N = 3 SE +/- 0.11, N = 3 SE +/- 0.06, N = 3 SE +/- 0.07, N = 3 SE +/- 0.05, N = 3 SE +/- 0.10, N = 3 SE +/- 0.02, N = 3 SE +/- 0.08, N = 3 SE +/- 0.02, N = 4 SE +/- 0.03, N = 4 SE +/- 0.03, N = 4 SE +/- 0.02, N = 3 SE +/- 0.02, N = 3 66.42 49.11 41.69 34.03 25.89 23.03 18.06 22.23 15.35 11.80 11.94 52.79 25.88 1. (CXX) g++ options: -fopenmp -pthread -lmpi_cxx -lmpi
Result Confidence
OpenBenchmarking.org Hydro Cycle Time - Seconds, Fewer Is Better Pennant 1.0.1 Test: sedovbig EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 13 26 39 52 65 Min: 66.13 / Avg: 66.42 / Max: 66.58 Min: 48.99 / Avg: 49.11 / Max: 49.32 Min: 41.58 / Avg: 41.69 / Max: 41.79 Min: 33.93 / Avg: 34.03 / Max: 34.16 Min: 25.8 / Avg: 25.89 / Max: 25.96 Min: 22.87 / Avg: 23.03 / Max: 23.23 Min: 18.03 / Avg: 18.06 / Max: 18.09 Min: 22.07 / Avg: 22.23 / Max: 22.32 Min: 15.3 / Avg: 15.35 / Max: 15.39 Min: 11.75 / Avg: 11.8 / Max: 11.87 Min: 11.88 / Avg: 11.94 / Max: 12 Min: 52.75 / Avg: 52.79 / Max: 52.81 Min: 25.85 / Avg: 25.88 / Max: 25.92 1. (CXX) g++ options: -fopenmp -pthread -lmpi_cxx -lmpi
Blender Blender is an open-source 3D creation software project. This test is of Blender's Cycles benchmark with various sample files. GPU computing via OpenCL or CUDA is supported. Learn more via the OpenBenchmarking.org test page.
Result
OpenBenchmarking.org Seconds, Fewer Is Better Blender 2.90 Blend File: Barbershop - Compute: CPU-Only EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 200 400 600 800 1000 SE +/- 0.62, N = 3 SE +/- 1.20, N = 3 SE +/- 0.65, N = 3 SE +/- 0.25, N = 3 SE +/- 0.35, N = 3 SE +/- 0.46, N = 3 SE +/- 0.14, N = 3 SE +/- 0.07, N = 3 SE +/- 0.31, N = 3 SE +/- 0.23, N = 3 SE +/- 0.20, N = 3 SE +/- 0.04, N = 3 SE +/- 0.11, N = 3 SE +/- 0.69, N = 3 866.85 554.64 432.92 411.56 291.52 237.65 243.58 223.08 180.94 179.18 154.23 154.42 683.81 356.90
Result Confidence
OpenBenchmarking.org Seconds, Fewer Is Better Blender 2.90 Blend File: Barbershop - Compute: CPU-Only EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 150 300 450 600 750 Min: 865.62 / Avg: 866.85 / Max: 867.52 Min: 552.98 / Avg: 554.64 / Max: 556.98 Min: 432.21 / Avg: 432.92 / Max: 434.21 Min: 411.08 / Avg: 411.56 / Max: 411.94 Min: 291.13 / Avg: 291.52 / Max: 292.22 Min: 237.18 / Avg: 237.65 / Max: 238.58 Min: 243.32 / Avg: 243.58 / Max: 243.79 Min: 222.95 / Avg: 223.08 / Max: 223.18 Min: 180.32 / Avg: 180.94 / Max: 181.27 Min: 178.74 / Avg: 179.18 / Max: 179.54 Min: 153.83 / Avg: 154.23 / Max: 154.49 Min: 154.37 / Avg: 154.42 / Max: 154.49 Min: 683.61 / Avg: 683.81 / Max: 683.97 Min: 356.09 / Avg: 356.9 / Max: 358.27
Result
OpenBenchmarking.org Seconds, Fewer Is Better Blender 2.90 Blend File: Pabellon Barcelona - Compute: CPU-Only EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 140 280 420 560 700 SE +/- 0.72, N = 3 SE +/- 0.64, N = 3 SE +/- 1.19, N = 3 SE +/- 0.50, N = 3 SE +/- 1.69, N = 3 SE +/- 0.14, N = 3 SE +/- 0.33, N = 3 SE +/- 0.07, N = 3 SE +/- 0.92, N = 3 SE +/- 0.14, N = 3 SE +/- 0.39, N = 3 SE +/- 0.15, N = 3 SE +/- 0.51, N = 3 SE +/- 0.98, N = 3 664.29 426.59 338.52 317.27 219.75 182.76 189.09 167.99 139.21 137.83 118.26 119.17 508.26 265.13
Result Confidence
OpenBenchmarking.org Seconds, Fewer Is Better Blender 2.90 Blend File: Pabellon Barcelona - Compute: CPU-Only EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 120 240 360 480 600 Min: 662.88 / Avg: 664.29 / Max: 665.27 Min: 425.64 / Avg: 426.59 / Max: 427.81 Min: 336.65 / Avg: 338.52 / Max: 340.74 Min: 316.57 / Avg: 317.27 / Max: 318.25 Min: 217.98 / Avg: 219.75 / Max: 223.14 Min: 182.48 / Avg: 182.76 / Max: 182.95 Min: 188.42 / Avg: 189.09 / Max: 189.45 Min: 167.9 / Avg: 167.99 / Max: 168.12 Min: 138.06 / Avg: 139.21 / Max: 141.03 Min: 137.55 / Avg: 137.83 / Max: 138.03 Min: 117.87 / Avg: 118.26 / Max: 119.05 Min: 118.86 / Avg: 119.17 / Max: 119.35 Min: 507.47 / Avg: 508.26 / Max: 509.22 Min: 263.71 / Avg: 265.13 / Max: 267.02
Facebook RocksDB This is a benchmark of Facebook's RocksDB as an embeddable persistent key-value store for fast storage based on Google's LevelDB. Learn more via the OpenBenchmarking.org test page.
Result
OpenBenchmarking.org Op/s, More Is Better Facebook RocksDB 6.3.6 Test: Read While Writing EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 2M 4M 6M 8M 10M SE +/- 1710.84, N = 3 SE +/- 24217.23, N = 3 SE +/- 26792.49, N = 3 SE +/- 25144.15, N = 3 SE +/- 43537.48, N = 3 SE +/- 24292.51, N = 3 SE +/- 32730.71, N = 3 SE +/- 55384.00, N = 3 SE +/- 44027.23, N = 3 SE +/- 69440.76, N = 6 SE +/- 27617.12, N = 3 SE +/- 47749.78, N = 3 SE +/- 10805.74, N = 13 SE +/- 8186.58, N = 3 1470621 2357928 3023239 3086237 4397695 5486066 5214302 5564433 7183579 7131600 8175383 8232474 1603673 3012387 1. (CXX) g++ options: -O3 -march=native -std=c++11 -fno-builtin-memcmp -fno-rtti -rdynamic -lpthread
Op/s Per Watt
OpenBenchmarking.org Op/s Per Watt, More Is Better Facebook RocksDB 6.3.6 Test: Read While Writing EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 9K 18K 27K 36K 45K 18803.69 23416.29 29403.11 24738.50 28233.69 36657.22 31284.41 32038.20 40538.44 37151.16 44350.10 43072.97 14725.01 14841.44
Result Confidence
OpenBenchmarking.org Op/s, More Is Better Facebook RocksDB 6.3.6 Test: Read While Writing EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 1.4M 2.8M 4.2M 5.6M 7M Min: 1467509 / Avg: 1470620.67 / Max: 1473409 Min: 2309505 / Avg: 2357928 / Max: 2383052 Min: 2989438 / Avg: 3023238.67 / Max: 3076148 Min: 3036500 / Avg: 3086236.67 / Max: 3117538 Min: 4337144 / Avg: 4397695 / Max: 4482162 Min: 5439082 / Avg: 5486065.67 / Max: 5520271 Min: 5150993 / Avg: 5214301.67 / Max: 5260375 Min: 5463565 / Avg: 5564432.67 / Max: 5654508 Min: 7101279 / Avg: 7183579 / Max: 7251844 Min: 7048399 / Avg: 7131599.5 / Max: 7477000 Min: 8142180 / Avg: 8175382.67 / Max: 8230211 Min: 8181136 / Avg: 8232473.67 / Max: 8327881 Min: 1550246 / Avg: 1603672.85 / Max: 1683898 Min: 3002918 / Avg: 3012386.67 / Max: 3028689 1. (CXX) g++ options: -O3 -march=native -std=c++11 -fno-builtin-memcmp -fno-rtti -rdynamic -lpthread
NAMD NAMD is a parallel molecular dynamics code designed for high-performance simulation of large biomolecular systems. NAMD was developed by the Theoretical and Computational Biophysics Group in the Beckman Institute for Advanced Science and Technology at the University of Illinois at Urbana-Champaign. Learn more via the OpenBenchmarking.org test page.
Result
OpenBenchmarking.org days/ns, Fewer Is Better NAMD 2.14 ATPase Simulation - 327,506 Atoms EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 0.6132 1.2264 1.8396 2.4528 3.066 SE +/- 0.00080, N = 3 SE +/- 0.00045, N = 3 SE +/- 0.00125, N = 3 SE +/- 0.00048, N = 3 SE +/- 0.00125, N = 3 SE +/- 0.00041, N = 3 SE +/- 0.00074, N = 3 SE +/- 0.00071, N = 3 SE +/- 0.00037, N = 3 SE +/- 0.00034, N = 3 SE +/- 0.00014, N = 3 SE +/- 0.00053, N = 3 SE +/- 0.00063, N = 3 SE +/- 0.00173, N = 3 2.72553 1.83895 1.45145 1.35058 0.93705 0.77439 0.79079 0.71549 0.57484 0.57048 0.48908 0.49264 2.22949 1.14375
Result Confidence
OpenBenchmarking.org days/ns, Fewer Is Better NAMD 2.14 ATPase Simulation - 327,506 Atoms EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 2 4 6 8 10 Min: 2.72 / Avg: 2.73 / Max: 2.73 Min: 1.84 / Avg: 1.84 / Max: 1.84 Min: 1.45 / Avg: 1.45 / Max: 1.45 Min: 1.35 / Avg: 1.35 / Max: 1.35 Min: 0.94 / Avg: 0.94 / Max: 0.94 Min: 0.77 / Avg: 0.77 / Max: 0.78 Min: 0.79 / Avg: 0.79 / Max: 0.79 Min: 0.71 / Avg: 0.72 / Max: 0.72 Min: 0.57 / Avg: 0.57 / Max: 0.58 Min: 0.57 / Avg: 0.57 / Max: 0.57 Min: 0.49 / Avg: 0.49 / Max: 0.49 Min: 0.49 / Avg: 0.49 / Max: 0.49 Min: 2.23 / Avg: 2.23 / Max: 2.23 Min: 1.14 / Avg: 1.14 / Max: 1.15
Facebook RocksDB This is a benchmark of Facebook's RocksDB as an embeddable persistent key-value store for fast storage based on Google's LevelDB. Learn more via the OpenBenchmarking.org test page.
Result
OpenBenchmarking.org Op/s, More Is Better Facebook RocksDB 6.3.6 Test: Random Read EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 50M 100M 150M 200M 250M SE +/- 468827.18, N = 3 SE +/- 532212.35, N = 3 SE +/- 860580.20, N = 3 SE +/- 731623.27, N = 6 SE +/- 701112.41, N = 3 SE +/- 298644.62, N = 3 SE +/- 577476.24, N = 3 SE +/- 979987.31, N = 3 SE +/- 1503518.94, N = 3 SE +/- 1627088.40, N = 3 SE +/- 1573991.80, N = 3 SE +/- 2628540.04, N = 3 SE +/- 173513.15, N = 3 SE +/- 33050.19, N = 3 39206156 56928967 74816560 76972090 114391434 139338056 133038550 147488280 185095008 185712982 214717760 218469824 48331735 93883130 1. (CXX) g++ options: -O3 -march=native -std=c++11 -fno-builtin-memcmp -fno-rtti -rdynamic -lpthread
Op/s Per Watt
OpenBenchmarking.org Op/s Per Watt, More Is Better Facebook RocksDB 6.3.6 Test: Random Read EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 200K 400K 600K 800K 1000K 482400.32 561814.90 744401.17 623360.93 752967.14 931173.20 820332.86 861998.88 1055932.79 966385.49 1165531.87 1144599.80 383902.17 405107.75
Result Confidence
OpenBenchmarking.org Op/s, More Is Better Facebook RocksDB 6.3.6 Test: Random Read EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 40M 80M 120M 160M 200M Min: 38308495 / Avg: 39206155.67 / Max: 39889615 Min: 55956147 / Avg: 56928967.33 / Max: 57789497 Min: 73275140 / Avg: 74816560.33 / Max: 76250454 Min: 75222240 / Avg: 76972090.17 / Max: 79656987 Min: 112997116 / Avg: 114391434.33 / Max: 115217369 Min: 138995330 / Avg: 139338056 / Max: 139933058 Min: 131941123 / Avg: 133038549.67 / Max: 133898996 Min: 146389489 / Avg: 147488280.33 / Max: 149443243 Min: 182409655 / Avg: 185095007.67 / Max: 187609592 Min: 182486843 / Avg: 185712982.33 / Max: 187695198 Min: 211571907 / Avg: 214717760.33 / Max: 216390965 Min: 213921113 / Avg: 218469824.33 / Max: 223026632 Min: 48063107 / Avg: 48331734.67 / Max: 48656311 Min: 93839853 / Avg: 93883129.67 / Max: 93948038 1. (CXX) g++ options: -O3 -march=native -std=c++11 -fno-builtin-memcmp -fno-rtti -rdynamic -lpthread
PostgreSQL pgbench This is a benchmark of PostgreSQL using pgbench for facilitating the database benchmarks. Learn more via the OpenBenchmarking.org test page.
Result
OpenBenchmarking.org TPS, More Is Better PostgreSQL pgbench 13.0 Scaling Factor: 100 - Clients: 250 - Mode: Read Only EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 200K 400K 600K 800K 1000K SE +/- 518.37, N = 3 SE +/- 696.35, N = 3 SE +/- 804.68, N = 3 SE +/- 891.46, N = 3 SE +/- 1318.12, N = 3 SE +/- 1108.32, N = 3 SE +/- 853.89, N = 3 SE +/- 1178.79, N = 3 SE +/- 3710.21, N = 3 SE +/- 1360.28, N = 3 SE +/- 6923.68, N = 3 SE +/- 5067.03, N = 3 SE +/- 681.51, N = 3 SE +/- 248.26, N = 3 169832 275677 343229 368449 521653 614183 587548 655774 791456 775687 939750 899992 213345 397038 1. (CC) gcc options: -fno-strict-aliasing -fwrapv -O2 -lpgcommon -lpgport -lpq -lpthread -lrt -ldl -lm
Result Confidence
OpenBenchmarking.org TPS, More Is Better PostgreSQL pgbench 13.0 Scaling Factor: 100 - Clients: 250 - Mode: Read Only EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 160K 320K 480K 640K 800K Min: 168803.67 / Avg: 169832.3 / Max: 170458.78 Min: 274390.74 / Avg: 275676.66 / Max: 276782.78 Min: 341698.14 / Avg: 343228.63 / Max: 344424.83 Min: 367104.95 / Avg: 368449.41 / Max: 370135.74 Min: 519362.06 / Avg: 521653.42 / Max: 523928.08 Min: 613074.34 / Avg: 614182.67 / Max: 616399.31 Min: 585986.61 / Avg: 587547.73 / Max: 588927.93 Min: 654021.41 / Avg: 655774.08 / Max: 658015.96 Min: 784040.65 / Avg: 791455.71 / Max: 795407.24 Min: 773949.79 / Avg: 775687.15 / Max: 778368.93 Min: 926183.25 / Avg: 939750.48 / Max: 948934.04 Min: 889916.01 / Avg: 899992.3 / Max: 905966.24 Min: 212208.72 / Avg: 213344.58 / Max: 214564.99 Min: 396660.01 / Avg: 397038.18 / Max: 397505.91 1. (CC) gcc options: -fno-strict-aliasing -fwrapv -O2 -lpgcommon -lpgport -lpq -lpthread -lrt -ldl -lm
Result
OpenBenchmarking.org ms, Fewer Is Better PostgreSQL pgbench 13.0 Scaling Factor: 100 - Clients: 250 - Mode: Read Only - Average Latency EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 0.3314 0.6628 0.9942 1.3256 1.657 SE +/- 0.005, N = 3 SE +/- 0.002, N = 3 SE +/- 0.002, N = 3 SE +/- 0.002, N = 3 SE +/- 0.001, N = 3 SE +/- 0.001, N = 3 SE +/- 0.001, N = 3 SE +/- 0.001, N = 3 SE +/- 0.001, N = 3 SE +/- 0.001, N = 3 SE +/- 0.002, N = 3 SE +/- 0.002, N = 3 SE +/- 0.004, N = 3 SE +/- 0.001, N = 3 1.473 0.908 0.729 0.679 0.480 0.407 0.426 0.382 0.316 0.323 0.267 0.279 1.173 0.630 1. (CC) gcc options: -fno-strict-aliasing -fwrapv -O2 -lpgcommon -lpgport -lpq -lpthread -lrt -ldl -lm
Result Confidence
OpenBenchmarking.org ms, Fewer Is Better PostgreSQL pgbench 13.0 Scaling Factor: 100 - Clients: 250 - Mode: Read Only - Average Latency EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 2 4 6 8 10 Min: 1.47 / Avg: 1.47 / Max: 1.48 Min: 0.9 / Avg: 0.91 / Max: 0.91 Min: 0.73 / Avg: 0.73 / Max: 0.73 Min: 0.68 / Avg: 0.68 / Max: 0.68 Min: 0.48 / Avg: 0.48 / Max: 0.48 Min: 0.41 / Avg: 0.41 / Max: 0.41 Min: 0.43 / Avg: 0.43 / Max: 0.43 Min: 0.38 / Avg: 0.38 / Max: 0.38 Min: 0.32 / Avg: 0.32 / Max: 0.32 Min: 0.32 / Avg: 0.32 / Max: 0.32 Min: 0.26 / Avg: 0.27 / Max: 0.27 Min: 0.28 / Avg: 0.28 / Max: 0.28 Min: 1.17 / Avg: 1.17 / Max: 1.18 Min: 0.63 / Avg: 0.63 / Max: 0.63 1. (CC) gcc options: -fno-strict-aliasing -fwrapv -O2 -lpgcommon -lpgport -lpq -lpthread -lrt -ldl -lm
Blender Blender is an open-source 3D creation software project. This test is of Blender's Cycles benchmark with various sample files. GPU computing via OpenCL or CUDA is supported. Learn more via the OpenBenchmarking.org test page.
Result
OpenBenchmarking.org Seconds, Fewer Is Better Blender 2.90 Blend File: Classroom - Compute: CPU-Only EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 120 240 360 480 600 SE +/- 0.21, N = 3 SE +/- 0.31, N = 3 SE +/- 0.83, N = 3 SE +/- 0.64, N = 3 SE +/- 0.04, N = 3 SE +/- 0.20, N = 3 SE +/- 1.09, N = 3 SE +/- 0.41, N = 3 SE +/- 0.69, N = 3 SE +/- 0.77, N = 3 SE +/- 0.25, N = 3 SE +/- 0.41, N = 3 SE +/- 0.25, N = 3 SE +/- 0.74, N = 3 558.87 387.23 304.34 287.81 196.70 162.29 168.40 148.50 122.03 121.21 101.68 103.55 454.49 237.79
Result Confidence
OpenBenchmarking.org Seconds, Fewer Is Better Blender 2.90 Blend File: Classroom - Compute: CPU-Only EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 100 200 300 400 500 Min: 558.51 / Avg: 558.87 / Max: 559.22 Min: 386.68 / Avg: 387.23 / Max: 387.74 Min: 303.05 / Avg: 304.34 / Max: 305.88 Min: 286.64 / Avg: 287.81 / Max: 288.83 Min: 196.63 / Avg: 196.7 / Max: 196.77 Min: 161.98 / Avg: 162.29 / Max: 162.65 Min: 167.27 / Avg: 168.4 / Max: 170.57 Min: 147.97 / Avg: 148.5 / Max: 149.3 Min: 120.66 / Avg: 122.03 / Max: 122.86 Min: 120.06 / Avg: 121.21 / Max: 122.68 Min: 101.18 / Avg: 101.68 / Max: 101.94 Min: 103.02 / Avg: 103.55 / Max: 104.35 Min: 454.13 / Avg: 454.49 / Max: 454.97 Min: 236.43 / Avg: 237.79 / Max: 238.96
Rodinia Rodinia is a suite focused upon accelerating compute-intensive applications with accelerators. CUDA, OpenMP, and OpenCL parallel models are supported by the included applications. This profile utilizes select OpenCL, NVIDIA CUDA and OpenMP test binaries at the moment. Learn more via the OpenBenchmarking.org test page.
Result
OpenBenchmarking.org Seconds, Fewer Is Better Rodinia 3.1 Test: OpenMP LavaMD EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 60 120 180 240 300 SE +/- 0.05, N = 3 SE +/- 0.51, N = 3 SE +/- 0.20, N = 3 SE +/- 0.16, N = 3 SE +/- 0.13, N = 3 SE +/- 0.11, N = 3 SE +/- 0.12, N = 3 SE +/- 0.08, N = 3 SE +/- 0.06, N = 3 SE +/- 0.08, N = 3 SE +/- 0.19, N = 3 SE +/- 0.02, N = 3 SE +/- 0.03, N = 3 SE +/- 0.09, N = 3 296.69 200.35 157.17 147.38 103.00 85.01 87.56 79.11 64.21 63.47 54.65 54.71 243.84 125.53 1. (CXX) g++ options: -O2 -lOpenCL
Result Confidence
OpenBenchmarking.org Seconds, Fewer Is Better Rodinia 3.1 Test: OpenMP LavaMD EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 50 100 150 200 250 Min: 296.63 / Avg: 296.69 / Max: 296.79 Min: 199.81 / Avg: 200.35 / Max: 201.37 Min: 156.97 / Avg: 157.17 / Max: 157.56 Min: 147.07 / Avg: 147.38 / Max: 147.56 Min: 102.75 / Avg: 103 / Max: 103.2 Min: 84.8 / Avg: 85 / Max: 85.18 Min: 87.32 / Avg: 87.56 / Max: 87.75 Min: 79.03 / Avg: 79.11 / Max: 79.27 Min: 64.09 / Avg: 64.21 / Max: 64.3 Min: 63.31 / Avg: 63.47 / Max: 63.56 Min: 54.27 / Avg: 54.65 / Max: 54.89 Min: 54.68 / Avg: 54.71 / Max: 54.75 Min: 243.81 / Avg: 243.84 / Max: 243.89 Min: 125.35 / Avg: 125.53 / Max: 125.64 1. (CXX) g++ options: -O2 -lOpenCL
OSPray Intel OSPray is a portable ray-tracing engine for high-performance, high-fidenlity scientific visualizations. OSPray builds off Intel's Embree and Intel SPMD Program Compiler (ISPC) components as part of the oneAPI rendering toolkit. Learn more via the OpenBenchmarking.org test page.
Result
OpenBenchmarking.org FPS, More Is Better OSPray 1.8.5 Demo: NASA Streamlines - Renderer: SciVis EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 20 40 60 80 100 SE +/- 0.00, N = 3 SE +/- 0.00, N = 4 SE +/- 0.00, N = 5 SE +/- 0.00, N = 5 SE +/- 0.00, N = 6 SE +/- 0.00, N = 6 SE +/- 0.49, N = 6 SE +/- 0.00, N = 7 SE +/- 0.00, N = 7 SE +/- 0.00, N = 7 SE +/- 0.00, N = 7 SE +/- 0.00, N = 4 SE +/- 0.18, N = 5 14.29 21.74 27.78 29.41 41.67 50.00 47.62 55.07 66.67 66.67 76.92 76.92 17.24 29.59 MIN: 13.89 / MAX: 14.49 MIN: 20.83 / MAX: 22.22 MIN: 26.32 MIN: 27.78 MIN: 38.46 / MAX: 43.48 MIN: 45.45 / MAX: 52.63 MIN: 45.45 / MAX: 50 MIN: 50 / MAX: 55.56 MIN: 58.82 / MAX: 71.43 MIN: 62.5 / MAX: 71.43 MIN: 62.5 / MAX: 83.33 MIN: 71.43 / MAX: 83.33 MIN: 16.67 / MAX: 17.86 MIN: 27.78 / MAX: 31.25
FPS Per Watt
OpenBenchmarking.org FPS Per Watt, More Is Better OSPray 1.8.5 Demo: NASA Streamlines - Renderer: SciVis EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 0.1755 0.351 0.5265 0.702 0.8775 0.22 0.29 0.38 0.34 0.44 0.57 0.47 0.59 0.71 0.65 0.78 0.76 0.18 0.21
Result Confidence
OpenBenchmarking.org FPS, More Is Better OSPray 1.8.5 Demo: NASA Streamlines - Renderer: SciVis EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 15 30 45 60 75 Min: 14.29 / Avg: 14.29 / Max: 14.29 Min: 21.74 / Avg: 21.74 / Max: 21.74 Min: 27.78 / Avg: 27.78 / Max: 27.78 Min: 29.41 / Avg: 29.41 / Max: 29.41 Min: 41.67 / Avg: 41.67 / Max: 41.67 Min: 47.62 / Avg: 47.62 / Max: 47.62 Min: 52.63 / Avg: 55.07 / Max: 55.56 Min: 66.67 / Avg: 66.67 / Max: 66.67 Min: 66.67 / Avg: 66.67 / Max: 66.67 Min: 76.92 / Avg: 76.92 / Max: 76.92 Min: 76.92 / Avg: 76.92 / Max: 76.92 Min: 17.24 / Avg: 17.24 / Max: 17.24 Min: 29.41 / Avg: 29.59 / Max: 30.3
LuxCoreRender LuxCoreRender is an open-source physically based renderer. This test profile is focused on running LuxCoreRender on the CPU as opposed to the OpenCL version. Learn more via the OpenBenchmarking.org test page.
Result
OpenBenchmarking.org M samples/sec, More Is Better LuxCoreRender 2.3 Scene: Rainbow Colors and Prism EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 2 4 6 8 10 SE +/- 0.00, N = 3 SE +/- 0.01, N = 3 SE +/- 0.01, N = 3 SE +/- 0.02, N = 3 SE +/- 0.03, N = 3 SE +/- 0.05, N = 3 SE +/- 0.06, N = 3 SE +/- 0.01, N = 3 SE +/- 0.01, N = 3 SE +/- 0.05, N = 3 SE +/- 0.04, N = 3 SE +/- 0.07, N = 3 SE +/- 0.01, N = 3 SE +/- 0.02, N = 3 1.50 2.14 2.74 2.91 4.17 5.04 4.92 5.54 6.75 6.81 7.92 7.82 1.84 3.57 MIN: 1.48 / MAX: 1.54 MIN: 2.08 / MAX: 2.17 MIN: 2.69 / MAX: 2.78 MIN: 2.88 / MAX: 2.96 MIN: 4.11 / MAX: 4.26 MIN: 4.94 / MAX: 5.12 MIN: 4.81 / MAX: 5.05 MIN: 5.5 / MAX: 5.57 MIN: 6.64 / MAX: 6.79 MIN: 6.61 / MAX: 6.89 MIN: 7.72 / MAX: 8.01 MIN: 7.53 / MAX: 7.98 MIN: 1.81 / MAX: 1.92 MIN: 3.48 / MAX: 3.63
M samples/sec Per Watt
OpenBenchmarking.org M samples/sec Per Watt, More Is Better LuxCoreRender 2.3 Scene: Rainbow Colors and Prism EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 0.009 0.018 0.027 0.036 0.045 0.02 0.02 0.03 0.02 0.03 0.03 0.03 0.03 0.04 0.04 0.04 0.04 0.01 0.02
Result Confidence
OpenBenchmarking.org M samples/sec, More Is Better LuxCoreRender 2.3 Scene: Rainbow Colors and Prism EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 3 6 9 12 15 Min: 1.5 / Avg: 1.5 / Max: 1.51 Min: 2.12 / Avg: 2.14 / Max: 2.15 Min: 2.73 / Avg: 2.74 / Max: 2.76 Min: 2.89 / Avg: 2.91 / Max: 2.95 Min: 4.11 / Avg: 4.17 / Max: 4.22 Min: 4.94 / Avg: 5.04 / Max: 5.12 Min: 4.81 / Avg: 4.92 / Max: 5.01 Min: 5.52 / Avg: 5.54 / Max: 5.55 Min: 6.73 / Avg: 6.75 / Max: 6.78 Min: 6.71 / Avg: 6.81 / Max: 6.88 Min: 7.83 / Avg: 7.92 / Max: 7.98 Min: 7.71 / Avg: 7.82 / Max: 7.94 Min: 1.83 / Avg: 1.84 / Max: 1.87 Min: 3.53 / Avg: 3.57 / Max: 3.6
LuxCoreRender LuxCoreRender is an open-source physically based renderer. This test profile is focused on running LuxCoreRender on the CPU as opposed to the OpenCL version. Learn more via the OpenBenchmarking.org test page.
Result
OpenBenchmarking.org M samples/sec, More Is Better LuxCoreRender 2.3 Scene: DLSC EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 2 4 6 8 10 SE +/- 0.01, N = 3 SE +/- 0.01, N = 3 SE +/- 0.01, N = 3 SE +/- 0.02, N = 3 SE +/- 0.01, N = 3 SE +/- 0.06, N = 3 SE +/- 0.05, N = 3 SE +/- 0.04, N = 3 SE +/- 0.05, N = 3 SE +/- 0.04, N = 3 SE +/- 0.04, N = 3 SE +/- 0.03, N = 3 SE +/- 0.01, N = 3 SE +/- 0.01, N = 3 1.38 1.98 2.53 2.68 3.83 4.65 4.54 5.03 6.13 6.19 7.21 7.04 1.68 3.27 MIN: 1.34 / MAX: 1.42 MIN: 1.91 / MAX: 2.03 MIN: 2.46 / MAX: 2.62 MIN: 2.58 / MAX: 2.77 MIN: 3.74 / MAX: 4.01 MIN: 4.49 / MAX: 5.07 MIN: 4.38 / MAX: 4.8 MIN: 4.8 / MAX: 5.35 MIN: 5.97 / MAX: 6.57 MIN: 6.04 / MAX: 6.75 MIN: 7.03 / MAX: 7.62 MIN: 6.88 / MAX: 7.39 MIN: 1.61 / MAX: 1.72 MIN: 3.18 / MAX: 3.41
M samples/sec Per Watt
OpenBenchmarking.org M samples/sec Per Watt, More Is Better LuxCoreRender 2.3 Scene: DLSC EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 0.009 0.018 0.027 0.036 0.045 0.02 0.02 0.03 0.02 0.03 0.03 0.03 0.03 0.04 0.03 0.04 0.04 0.01 0.01
Result Confidence
OpenBenchmarking.org M samples/sec, More Is Better LuxCoreRender 2.3 Scene: DLSC EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 3 6 9 12 15 Min: 1.37 / Avg: 1.38 / Max: 1.39 Min: 1.97 / Avg: 1.98 / Max: 1.99 Min: 2.52 / Avg: 2.53 / Max: 2.55 Min: 2.66 / Avg: 2.68 / Max: 2.71 Min: 3.81 / Avg: 3.83 / Max: 3.84 Min: 4.58 / Avg: 4.65 / Max: 4.76 Min: 4.47 / Avg: 4.54 / Max: 4.64 Min: 4.96 / Avg: 5.03 / Max: 5.09 Min: 6.07 / Avg: 6.13 / Max: 6.22 Min: 6.14 / Avg: 6.19 / Max: 6.26 Min: 7.13 / Avg: 7.21 / Max: 7.27 Min: 6.98 / Avg: 7.04 / Max: 7.07 Min: 1.66 / Avg: 1.68 / Max: 1.69 Min: 3.26 / Avg: 3.27 / Max: 3.29
ASTC Encoder ASTC Encoder (astcenc) is for the Adaptive Scalable Texture Compression (ASTC) format commonly used with OpenGL, OpenGL ES, and Vulkan graphics APIs. This test profile does a coding test of both compression/decompression. Learn more via the OpenBenchmarking.org test page.
Result
OpenBenchmarking.org Seconds, Fewer Is Better ASTC Encoder 2.0 Preset: Thorough EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 8 16 24 32 40 SE +/- 0.01, N = 3 SE +/- 0.01, N = 3 SE +/- 0.01, N = 3 SE +/- 0.01, N = 3 SE +/- 0.00, N = 3 SE +/- 0.00, N = 4 SE +/- 0.00, N = 4 SE +/- 0.00, N = 4 SE +/- 0.00, N = 4 SE +/- 0.01, N = 4 SE +/- 0.00, N = 4 SE +/- 0.01, N = 3 SE +/- 0.01, N = 3 33.15 22.40 17.73 16.68 11.71 9.73 9.99 9.08 7.42 6.38 6.35 27.16 14.02 1. (CXX) g++ options: -std=c++14 -fvisibility=hidden -O3 -flto -mfpmath=sse -mavx2 -mpopcnt -lpthread
Result Confidence
OpenBenchmarking.org Seconds, Fewer Is Better ASTC Encoder 2.0 Preset: Thorough EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 7 14 21 28 35 Min: 33.13 / Avg: 33.15 / Max: 33.18 Min: 22.39 / Avg: 22.4 / Max: 22.42 Min: 17.72 / Avg: 17.73 / Max: 17.74 Min: 16.67 / Avg: 16.68 / Max: 16.69 Min: 11.71 / Avg: 11.71 / Max: 11.72 Min: 9.73 / Avg: 9.73 / Max: 9.74 Min: 9.99 / Avg: 9.99 / Max: 9.99 Min: 9.08 / Avg: 9.08 / Max: 9.08 Min: 7.41 / Avg: 7.42 / Max: 7.42 Min: 6.36 / Avg: 6.38 / Max: 6.4 Min: 6.35 / Avg: 6.35 / Max: 6.36 Min: 27.15 / Avg: 27.16 / Max: 27.17 Min: 14 / Avg: 14.02 / Max: 14.03 1. (CXX) g++ options: -std=c++14 -fvisibility=hidden -O3 -flto -mfpmath=sse -mavx2 -mpopcnt -lpthread
OpenVINO This is a test of the Intel OpenVINO, a toolkit around neural networks, using its built-in benchmarking support and analyzing the throughput and latency for various models. Learn more via the OpenBenchmarking.org test page.
Result
OpenBenchmarking.org FPS, More Is Better OpenVINO 2021.1 Model: Face Detection 0106 FP32 - Device: CPU EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 3 6 9 12 15 SE +/- 0.01, N = 3 SE +/- 0.02, N = 3 SE +/- 0.02, N = 3 SE +/- 0.00, N = 3 SE +/- 0.03, N = 3 SE +/- 0.01, N = 3 SE +/- 0.01, N = 3 SE +/- 0.05, N = 3 SE +/- 0.01, N = 3 SE +/- 0.01, N = 3 SE +/- 0.01, N = 3 SE +/- 0.02, N = 3 SE +/- 0.01, N = 3 SE +/- 0.00, N = 3 1.74 2.47 3.23 3.32 4.73 5.72 5.68 6.13 7.22 7.79 8.98 7.88 2.16 4.02
Result Confidence
OpenBenchmarking.org FPS, More Is Better OpenVINO 2021.1 Model: Face Detection 0106 FP32 - Device: CPU EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 3 6 9 12 15 Min: 1.71 / Avg: 1.74 / Max: 1.76 Min: 2.44 / Avg: 2.47 / Max: 2.5 Min: 3.2 / Avg: 3.23 / Max: 3.25 Min: 3.31 / Avg: 3.32 / Max: 3.32 Min: 4.68 / Avg: 4.73 / Max: 4.79 Min: 5.7 / Avg: 5.72 / Max: 5.74 Min: 5.67 / Avg: 5.68 / Max: 5.69 Min: 6.03 / Avg: 6.13 / Max: 6.19 Min: 7.19 / Avg: 7.22 / Max: 7.24 Min: 7.78 / Avg: 7.79 / Max: 7.81 Min: 8.97 / Avg: 8.98 / Max: 9.01 Min: 7.84 / Avg: 7.88 / Max: 7.9 Min: 2.14 / Avg: 2.16 / Max: 2.18 Min: 4.02 / Avg: 4.02 / Max: 4.03
Result
OpenBenchmarking.org FPS, More Is Better OpenVINO 2021.1 Model: Person Detection 0106 FP32 - Device: CPU EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 2 4 6 8 10 SE +/- 0.01, N = 3 SE +/- 0.01, N = 3 SE +/- 0.01, N = 3 SE +/- 0.01, N = 3 SE +/- 0.01, N = 3 SE +/- 0.02, N = 3 SE +/- 0.01, N = 3 SE +/- 0.01, N = 3 SE +/- 0.01, N = 3 SE +/- 0.01, N = 3 SE +/- 0.01, N = 3 SE +/- 0.01, N = 3 SE +/- 0.00, N = 3 SE +/- 0.01, N = 3 1.28 1.81 2.38 2.51 3.51 4.36 4.19 4.70 5.53 5.67 6.60 6.05 1.64 2.98
Result Confidence
OpenBenchmarking.org FPS, More Is Better OpenVINO 2021.1 Model: Person Detection 0106 FP32 - Device: CPU EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 3 6 9 12 15 Min: 1.27 / Avg: 1.28 / Max: 1.29 Min: 1.8 / Avg: 1.81 / Max: 1.82 Min: 2.37 / Avg: 2.38 / Max: 2.39 Min: 2.5 / Avg: 2.51 / Max: 2.52 Min: 3.5 / Avg: 3.51 / Max: 3.53 Min: 4.32 / Avg: 4.36 / Max: 4.4 Min: 4.18 / Avg: 4.19 / Max: 4.2 Min: 4.69 / Avg: 4.7 / Max: 4.72 Min: 5.52 / Avg: 5.53 / Max: 5.54 Min: 5.66 / Avg: 5.67 / Max: 5.68 Min: 6.58 / Avg: 6.6 / Max: 6.63 Min: 6.03 / Avg: 6.05 / Max: 6.06 Min: 1.64 / Avg: 1.64 / Max: 1.65 Min: 2.97 / Avg: 2.98 / Max: 2.99
Result
OpenBenchmarking.org FPS, More Is Better OpenVINO 2021.1 Model: Person Detection 0106 FP16 - Device: CPU EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 2 4 6 8 10 SE +/- 0.00, N = 3 SE +/- 0.01, N = 3 SE +/- 0.01, N = 3 SE +/- 0.01, N = 3 SE +/- 0.01, N = 3 SE +/- 0.02, N = 3 SE +/- 0.01, N = 3 SE +/- 0.01, N = 3 SE +/- 0.02, N = 3 SE +/- 0.01, N = 3 SE +/- 0.01, N = 3 SE +/- 0.01, N = 3 SE +/- 0.01, N = 3 SE +/- 0.01, N = 3 1.29 1.81 2.37 2.51 3.53 4.37 4.20 4.74 5.53 5.67 6.62 6.02 1.66 2.99
Result Confidence
OpenBenchmarking.org FPS, More Is Better OpenVINO 2021.1 Model: Person Detection 0106 FP16 - Device: CPU EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 3 6 9 12 15 Min: 1.29 / Avg: 1.29 / Max: 1.3 Min: 1.8 / Avg: 1.81 / Max: 1.82 Min: 2.34 / Avg: 2.37 / Max: 2.38 Min: 2.5 / Avg: 2.51 / Max: 2.52 Min: 3.52 / Avg: 3.53 / Max: 3.56 Min: 4.33 / Avg: 4.37 / Max: 4.4 Min: 4.19 / Avg: 4.2 / Max: 4.21 Min: 4.72 / Avg: 4.74 / Max: 4.75 Min: 5.51 / Avg: 5.53 / Max: 5.56 Min: 5.66 / Avg: 5.67 / Max: 5.68 Min: 6.6 / Avg: 6.62 / Max: 6.64 Min: 6.01 / Avg: 6.02 / Max: 6.03 Min: 1.65 / Avg: 1.66 / Max: 1.67 Min: 2.97 / Avg: 2.99 / Max: 3.01
Result
OpenBenchmarking.org FPS, More Is Better OpenVINO 2021.1 Model: Face Detection 0106 FP16 - Device: CPU EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 3 6 9 12 15 SE +/- 0.01, N = 3 SE +/- 0.01, N = 3 SE +/- 0.01, N = 3 SE +/- 0.01, N = 3 SE +/- 0.02, N = 3 SE +/- 0.00, N = 3 SE +/- 0.00, N = 3 SE +/- 0.02, N = 3 SE +/- 0.01, N = 3 SE +/- 0.01, N = 3 SE +/- 0.00, N = 3 SE +/- 0.02, N = 3 SE +/- 0.02, N = 3 SE +/- 0.01, N = 3 1.75 2.47 3.16 3.31 4.76 5.73 5.68 6.17 7.20 7.81 8.97 7.88 2.16 4.04
Result Confidence
OpenBenchmarking.org FPS, More Is Better OpenVINO 2021.1 Model: Face Detection 0106 FP16 - Device: CPU EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 3 6 9 12 15 Min: 1.72 / Avg: 1.75 / Max: 1.76 Min: 2.45 / Avg: 2.47 / Max: 2.48 Min: 3.14 / Avg: 3.16 / Max: 3.18 Min: 3.3 / Avg: 3.31 / Max: 3.32 Min: 4.74 / Avg: 4.76 / Max: 4.8 Min: 5.73 / Avg: 5.73 / Max: 5.73 Min: 5.67 / Avg: 5.68 / Max: 5.68 Min: 6.13 / Avg: 6.17 / Max: 6.19 Min: 7.19 / Avg: 7.2 / Max: 7.22 Min: 7.8 / Avg: 7.81 / Max: 7.83 Min: 8.97 / Avg: 8.97 / Max: 8.97 Min: 7.84 / Avg: 7.88 / Max: 7.9 Min: 2.14 / Avg: 2.16 / Max: 2.2 Min: 4.02 / Avg: 4.04 / Max: 4.07
CloverLeaf CloverLeaf is a Lagrangian-Eulerian hydrodynamics benchmark. This test profile currently makes use of CloverLeaf's OpenMP version and benchmarked with the clover_bm.in input file (Problem 5). Learn more via the OpenBenchmarking.org test page.
Result
OpenBenchmarking.org Seconds, Fewer Is Better CloverLeaf Lagrangian-Eulerian Hydrodynamics EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 16 32 48 64 80 SE +/- 0.03, N = 3 SE +/- 0.05, N = 3 SE +/- 0.04, N = 3 SE +/- 0.09, N = 3 SE +/- 0.06, N = 3 SE +/- 0.04, N = 3 SE +/- 0.07, N = 4 SE +/- 0.03, N = 3 SE +/- 0.02, N = 4 SE +/- 0.08, N = 4 SE +/- 0.07, N = 4 SE +/- 0.05, N = 4 SE +/- 0.09, N = 3 SE +/- 0.06, N = 3 69.91 48.29 45.46 25.21 20.35 19.07 15.29 18.61 15.28 13.66 14.03 14.70 36.80 22.83 1. (F9X) gfortran options: -O3 -march=native -funroll-loops -fopenmp
Result Confidence
OpenBenchmarking.org Seconds, Fewer Is Better CloverLeaf Lagrangian-Eulerian Hydrodynamics EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 14 28 42 56 70 Min: 69.87 / Avg: 69.91 / Max: 69.96 Min: 48.21 / Avg: 48.29 / Max: 48.38 Min: 45.38 / Avg: 45.46 / Max: 45.52 Min: 25.12 / Avg: 25.21 / Max: 25.39 Min: 20.26 / Avg: 20.35 / Max: 20.46 Min: 19 / Avg: 19.07 / Max: 19.13 Min: 15.1 / Avg: 15.29 / Max: 15.4 Min: 18.57 / Avg: 18.61 / Max: 18.67 Min: 15.23 / Avg: 15.28 / Max: 15.32 Min: 13.55 / Avg: 13.66 / Max: 13.9 Min: 13.91 / Avg: 14.03 / Max: 14.23 Min: 14.59 / Avg: 14.7 / Max: 14.82 Min: 36.61 / Avg: 36.8 / Max: 36.9 Min: 22.76 / Avg: 22.83 / Max: 22.94 1. (F9X) gfortran options: -O3 -march=native -funroll-loops -fopenmp
ASKAP ASKAP is a set of benchmarks from the Australian SKA Pathfinder. The principal ASKAP benchmarks are the Hogbom Clean Benchmark (tHogbomClean) and Convolutional Resamping Benchmark (tConvolve) as well as some previous ASKAP benchmarks being included as well for OpenCL and CUDA execution of tConvolve. Learn more via the OpenBenchmarking.org test page.
Result
OpenBenchmarking.org Million Grid Points Per Second, More Is Better ASKAP 1.0 Test: tConvolve OpenMP - Degridding EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 1500 3000 4500 6000 7500 SE +/- 6.46, N = 4 SE +/- 10.02, N = 4 SE +/- 10.27, N = 4 SE +/- 37.73, N = 3 SE +/- 35.55, N = 4 SE +/- 0.00, N = 4 SE +/- 38.66, N = 4 SE +/- 0.00, N = 4 SE +/- 36.86, N = 4 SE +/- 40.59, N = 4 SE +/- 42.67, N = 4 SE +/- 47.34, N = 4 SE +/- 30.11, N = 2 SE +/- 3.57, N = 4 2616.81 3257.04 3317.93 5509.30 5726.60 5788.17 6455.40 5788.17 6302.57 6615.81 6699.07 7148.77 4004.08 1406.93 1. (CXX) g++ options: -O3 -fstrict-aliasing -fopenmp
Million Grid Points Per Second Per Watt
OpenBenchmarking.org Million Grid Points Per Second Per Watt, More Is Better ASKAP 1.0 Test: tConvolve OpenMP - Degridding EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 20 40 60 80 100 58.97 72.53 72.91 103.76 109.78 108.49 89.44 108.46 100.05 93.63 92.78 96.86 70.19 17.31
Result Confidence
OpenBenchmarking.org Million Grid Points Per Second, More Is Better ASKAP 1.0 Test: tConvolve OpenMP - Degridding EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 1200 2400 3600 4800 6000 Min: 2610.35 / Avg: 2616.81 / Max: 2636.2 Min: 3247.02 / Avg: 3257.04 / Max: 3287.11 Min: 3287.11 / Avg: 3317.93 / Max: 3328.2 Min: 5433.8 / Avg: 5509.27 / Max: 5547 Min: 5665.02 / Avg: 5726.6 / Max: 5788.17 Min: 5788.17 / Avg: 5788.17 / Max: 5788.17 Min: 6339.43 / Avg: 6455.4 / Max: 6494.05 Min: 5788.17 / Avg: 5788.17 / Max: 5788.17 Min: 6192 / Avg: 6302.57 / Max: 6339.43 Min: 6494.05 / Avg: 6615.81 / Max: 6656.4 Min: 6656.4 / Avg: 6699.07 / Max: 6827.08 Min: 7006.74 / Avg: 7148.77 / Max: 7196.11 Min: 3973.97 / Avg: 4004.08 / Max: 4034.18 Min: 1401.35 / Avg: 1406.93 / Max: 1416.26 1. (CXX) g++ options: -O3 -fstrict-aliasing -fopenmp
rays1bench This is a test of rays1bench, a simple path-tracer / ray-tracing that supports SSE and AVX instructions, multi-threading, and other features. This test profile is measuring the performance of the "large scene" in rays1bench. Learn more via the OpenBenchmarking.org test page.
Result
OpenBenchmarking.org mrays/s, More Is Better rays1bench 2020-01-09 Large Scene EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 50 100 150 200 250 SE +/- 0.08, N = 3 SE +/- 0.04, N = 4 SE +/- 0.06, N = 4 SE +/- 0.08, N = 5 SE +/- 0.04, N = 6 SE +/- 0.06, N = 6 SE +/- 0.06, N = 6 SE +/- 0.03, N = 6 SE +/- 0.08, N = 7 SE +/- 0.11, N = 7 SE +/- 0.21, N = 7 SE +/- 0.20, N = 7 SE +/- 0.01, N = 4 SE +/- 0.10, N = 5 48.61 68.51 84.54 90.37 134.19 167.75 163.00 182.59 217.70 218.73 243.25 243.57 59.60 109.91
mrays/s Per Watt
OpenBenchmarking.org mrays/s Per Watt, More Is Better rays1bench 2020-01-09 Large Scene EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 0.5378 1.0756 1.6134 2.1512 2.689 0.68 0.85 1.09 0.97 1.34 1.81 1.54 1.85 2.24 2.04 2.39 2.33 0.54 0.69
Result Confidence
OpenBenchmarking.org mrays/s, More Is Better rays1bench 2020-01-09 Large Scene EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 40 80 120 160 200 Min: 48.46 / Avg: 48.61 / Max: 48.73 Min: 68.41 / Avg: 68.51 / Max: 68.59 Min: 84.42 / Avg: 84.54 / Max: 84.72 Min: 90.09 / Avg: 90.37 / Max: 90.53 Min: 134.04 / Avg: 134.19 / Max: 134.3 Min: 167.52 / Avg: 167.75 / Max: 167.95 Min: 162.8 / Avg: 163 / Max: 163.17 Min: 182.51 / Avg: 182.59 / Max: 182.66 Min: 217.39 / Avg: 217.7 / Max: 217.92 Min: 218.36 / Avg: 218.73 / Max: 219.13 Min: 242.31 / Avg: 243.25 / Max: 243.89 Min: 242.82 / Avg: 243.57 / Max: 244.37 Min: 59.57 / Avg: 59.6 / Max: 59.62 Min: 109.61 / Avg: 109.91 / Max: 110.19
TensorFlow Lite This is a benchmark of the TensorFlow Lite implementation. The current Linux support is limited to running on CPUs. This test profile is measuring the average inference time. Learn more via the OpenBenchmarking.org test page.
Result
OpenBenchmarking.org Microseconds, Fewer Is Better TensorFlow Lite 2020-08-23 Model: Mobilenet Quant EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 40K 80K 120K 160K 200K SE +/- 20.79, N = 3 SE +/- 28.48, N = 3 SE +/- 47.75, N = 3 SE +/- 15.21, N = 3 SE +/- 40.77, N = 3 SE +/- 44.27, N = 3 SE +/- 69.37, N = 3 SE +/- 72.07, N = 3 SE +/- 518.49, N = 3 SE +/- 392.20, N = 3 SE +/- 61.64, N = 3 SE +/- 118.11, N = 3 SE +/- 13.05, N = 3 SE +/- 61.58, N = 3 165426.0 120119.0 86277.6 82490.4 62904.1 47911.7 49078.5 45118.1 50401.8 45818.8 33024.0 36468.8 136023.0 70154.5
Result Confidence
OpenBenchmarking.org Microseconds, Fewer Is Better TensorFlow Lite 2020-08-23 Model: Mobilenet Quant EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 30K 60K 90K 120K 150K Min: 165394 / Avg: 165426 / Max: 165465 Min: 120062 / Avg: 120118.67 / Max: 120152 Min: 86198 / Avg: 86277.57 / Max: 86363.1 Min: 82465 / Avg: 82490.43 / Max: 82517.6 Min: 62851.8 / Avg: 62904.07 / Max: 62984.4 Min: 47856.7 / Avg: 47911.7 / Max: 47999.3 Min: 48987 / Avg: 49078.53 / Max: 49214.6 Min: 45013.3 / Avg: 45118.1 / Max: 45256.2 Min: 49377.6 / Avg: 50401.83 / Max: 51054.3 Min: 45327.1 / Avg: 45818.77 / Max: 46593.9 Min: 32924.1 / Avg: 33024 / Max: 33136.5 Min: 36258.5 / Avg: 36468.83 / Max: 36667.1 Min: 135998 / Avg: 136023 / Max: 136042 Min: 70069.3 / Avg: 70154.47 / Max: 70274.1
Result
OpenBenchmarking.org Microseconds, Fewer Is Better TensorFlow Lite 2020-08-23 Model: Mobilenet Float EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 30K 60K 90K 120K 150K SE +/- 22.85, N = 3 SE +/- 107.22, N = 3 SE +/- 63.38, N = 3 SE +/- 21.22, N = 3 SE +/- 193.63, N = 3 SE +/- 76.82, N = 3 SE +/- 28.71, N = 3 SE +/- 86.41, N = 3 SE +/- 194.69, N = 3 SE +/- 322.42, N = 3 SE +/- 187.50, N = 3 SE +/- 280.28, N = 3 SE +/- 599.00, N = 3 SE +/- 13.80, N = 3 160713.0 117060.0 84723.5 80320.5 61419.9 47083.4 48084.7 43977.9 48507.4 45436.6 32085.5 35037.4 133236.0 68637.6
Result Confidence
OpenBenchmarking.org Microseconds, Fewer Is Better TensorFlow Lite 2020-08-23 Model: Mobilenet Float EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 30K 60K 90K 120K 150K Min: 160685 / Avg: 160712.67 / Max: 160758 Min: 116941 / Avg: 117060 / Max: 117274 Min: 84636.8 / Avg: 84723.47 / Max: 84846.9 Min: 80284 / Avg: 80320.5 / Max: 80357.5 Min: 61061.3 / Avg: 61419.9 / Max: 61725.8 Min: 46946.3 / Avg: 47083.37 / Max: 47212 Min: 48044.8 / Avg: 48084.67 / Max: 48140.4 Min: 43815.4 / Avg: 43977.87 / Max: 44110.1 Min: 48205.1 / Avg: 48507.43 / Max: 48871.1 Min: 44937.4 / Avg: 45436.6 / Max: 46039.7 Min: 31772.4 / Avg: 32085.53 / Max: 32420.8 Min: 34603.7 / Avg: 35037.37 / Max: 35561.8 Min: 132636 / Avg: 133236 / Max: 134434 Min: 68610.2 / Avg: 68637.6 / Max: 68654.2
PostgreSQL pgbench This is a benchmark of PostgreSQL using pgbench for facilitating the database benchmarks. Learn more via the OpenBenchmarking.org test page.
Result
OpenBenchmarking.org ms, Fewer Is Better PostgreSQL pgbench 13.0 Scaling Factor: 100 - Clients: 100 - Mode: Read Only - Average Latency EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 0.1222 0.2444 0.3666 0.4888 0.611 SE +/- 0.001, N = 3 SE +/- 0.001, N = 3 SE +/- 0.001, N = 3 SE +/- 0.000, N = 3 SE +/- 0.000, N = 3 SE +/- 0.000, N = 3 SE +/- 0.000, N = 3 SE +/- 0.000, N = 3 SE +/- 0.000, N = 3 SE +/- 0.000, N = 3 SE +/- 0.000, N = 3 SE +/- 0.000, N = 3 SE +/- 0.001, N = 3 SE +/- 0.000, N = 3 0.543 0.359 0.290 0.280 0.201 0.164 0.173 0.153 0.120 0.120 0.109 0.112 0.464 0.263 1. (CC) gcc options: -fno-strict-aliasing -fwrapv -O2 -lpgcommon -lpgport -lpq -lpthread -lrt -ldl -lm
Result Confidence
OpenBenchmarking.org ms, Fewer Is Better PostgreSQL pgbench 13.0 Scaling Factor: 100 - Clients: 100 - Mode: Read Only - Average Latency EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 2 4 6 8 10 Min: 0.54 / Avg: 0.54 / Max: 0.54 Min: 0.36 / Avg: 0.36 / Max: 0.36 Min: 0.29 / Avg: 0.29 / Max: 0.29 Min: 0.28 / Avg: 0.28 / Max: 0.28 Min: 0.2 / Avg: 0.2 / Max: 0.2 Min: 0.16 / Avg: 0.16 / Max: 0.16 Min: 0.17 / Avg: 0.17 / Max: 0.17 Min: 0.15 / Avg: 0.15 / Max: 0.15 Min: 0.12 / Avg: 0.12 / Max: 0.12 Min: 0.12 / Avg: 0.12 / Max: 0.12 Min: 0.11 / Avg: 0.11 / Max: 0.11 Min: 0.11 / Avg: 0.11 / Max: 0.11 Min: 0.46 / Avg: 0.46 / Max: 0.47 Min: 0.26 / Avg: 0.26 / Max: 0.26 1. (CC) gcc options: -fno-strict-aliasing -fwrapv -O2 -lpgcommon -lpgport -lpq -lpthread -lrt -ldl -lm
Result
OpenBenchmarking.org TPS, More Is Better PostgreSQL pgbench 13.0 Scaling Factor: 100 - Clients: 100 - Mode: Read Only EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 200K 400K 600K 800K 1000K SE +/- 258.28, N = 3 SE +/- 527.65, N = 3 SE +/- 721.66, N = 3 SE +/- 406.00, N = 3 SE +/- 1145.86, N = 3 SE +/- 1605.99, N = 3 SE +/- 1146.88, N = 3 SE +/- 684.57, N = 3 SE +/- 2696.01, N = 3 SE +/- 492.11, N = 3 SE +/- 2726.39, N = 3 SE +/- 3714.01, N = 3 SE +/- 196.73, N = 3 SE +/- 501.41, N = 3 184251 278510 344598 357781 499138 610667 578340 654914 832509 835457 915523 897453 215617 381184 1. (CC) gcc options: -fno-strict-aliasing -fwrapv -O2 -lpgcommon -lpgport -lpq -lpthread -lrt -ldl -lm
Result Confidence
OpenBenchmarking.org TPS, More Is Better PostgreSQL pgbench 13.0 Scaling Factor: 100 - Clients: 100 - Mode: Read Only EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 160K 320K 480K 640K 800K Min: 183809.92 / Avg: 184251.3 / Max: 184704.38 Min: 277469.8 / Avg: 278509.56 / Max: 279185.65 Min: 343314.32 / Avg: 344597.63 / Max: 345811.31 Min: 357317.88 / Avg: 357781.31 / Max: 358590.46 Min: 497224.75 / Avg: 499138.43 / Max: 501187.22 Min: 608958.8 / Avg: 610666.61 / Max: 613876.39 Min: 576053.18 / Avg: 578339.82 / Max: 579639.5 Min: 654192.39 / Avg: 654914.4 / Max: 656282.85 Min: 827135.25 / Avg: 832508.89 / Max: 835580.98 Min: 834632.97 / Avg: 835456.65 / Max: 836335.05 Min: 911128.88 / Avg: 915522.69 / Max: 920516.11 Min: 891671.21 / Avg: 897453.24 / Max: 904382.54 Min: 215250.14 / Avg: 215616.98 / Max: 215923.6 Min: 380600.92 / Avg: 381183.76 / Max: 382181.9 1. (CC) gcc options: -fno-strict-aliasing -fwrapv -O2 -lpgcommon -lpgport -lpq -lpthread -lrt -ldl -lm
OpenFOAM OpenFOAM is the leading free, open source software for computational fluid dynamics (CFD). Learn more via the OpenBenchmarking.org test page.
Result
OpenBenchmarking.org Seconds, Fewer Is Better OpenFOAM 8 Input: Motorbike 30M EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 30 60 90 120 150 SE +/- 0.30, N = 3 SE +/- 0.08, N = 3 SE +/- 0.05, N = 3 SE +/- 0.17, N = 3 SE +/- 0.08, N = 3 SE +/- 0.06, N = 3 SE +/- 0.09, N = 3 SE +/- 0.09, N = 3 SE +/- 0.09, N = 3 SE +/- 0.07, N = 3 SE +/- 0.10, N = 3 SE +/- 0.18, N = 3 SE +/- 0.11, N = 3 SE +/- 0.05, N = 3 113.16 67.23 56.57 40.87 33.81 30.62 26.53 29.62 25.17 23.43 22.83 23.35 60.50 39.89 1. (CXX) g++ options: -std=c++11 -m64 -O3 -ftemplate-depth-100 -fPIC -fuse-ld=bfd -Xlinker --add-needed --no-as-needed -ldynamicMesh -ldecompose -lgenericPatchFields -lmetisDecomp -lscotchDecomp -llagrangian -lregionModels -lOpenFOAM -ldl -lm
Result Confidence
OpenBenchmarking.org Seconds, Fewer Is Better OpenFOAM 8 Input: Motorbike 30M EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 20 40 60 80 100 Min: 112.77 / Avg: 113.16 / Max: 113.75 Min: 67.08 / Avg: 67.23 / Max: 67.35 Min: 56.49 / Avg: 56.57 / Max: 56.65 Min: 40.67 / Avg: 40.87 / Max: 41.21 Min: 33.73 / Avg: 33.81 / Max: 33.97 Min: 30.52 / Avg: 30.62 / Max: 30.71 Min: 26.35 / Avg: 26.53 / Max: 26.65 Min: 29.5 / Avg: 29.62 / Max: 29.8 Min: 25.06 / Avg: 25.17 / Max: 25.35 Min: 23.3 / Avg: 23.43 / Max: 23.53 Min: 22.63 / Avg: 22.83 / Max: 22.97 Min: 23.06 / Avg: 23.35 / Max: 23.68 Min: 60.32 / Avg: 60.5 / Max: 60.7 Min: 39.79 / Avg: 39.89 / Max: 39.94 1. (CXX) g++ options: -std=c++11 -m64 -O3 -ftemplate-depth-100 -fPIC -fuse-ld=bfd -Xlinker --add-needed --no-as-needed -ldynamicMesh -ldecompose -lgenericPatchFields -lmetisDecomp -lscotchDecomp -llagrangian -lregionModels -lOpenFOAM -ldl -lm
TensorFlow Lite This is a benchmark of the TensorFlow Lite implementation. The current Linux support is limited to running on CPUs. This test profile is measuring the average inference time. Learn more via the OpenBenchmarking.org test page.
Result
OpenBenchmarking.org Microseconds, Fewer Is Better TensorFlow Lite 2020-08-23 Model: Inception V4 EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 700K 1400K 2100K 2800K 3500K SE +/- 1129.29, N = 3 SE +/- 436.36, N = 3 SE +/- 565.25, N = 3 SE +/- 272.21, N = 3 SE +/- 1233.46, N = 3 SE +/- 487.90, N = 3 SE +/- 143.80, N = 3 SE +/- 425.74, N = 3 SE +/- 907.34, N = 3 SE +/- 1781.71, N = 3 SE +/- 3136.75, N = 3 SE +/- 6069.08, N = 3 SE +/- 227.03, N = 3 SE +/- 192.21, N = 3 3472940 2493747 1820153 1742890 1366410 1006347 1034367 943229 978828 938691 700833 764269 2872227 1499183
Result Confidence
OpenBenchmarking.org Microseconds, Fewer Is Better TensorFlow Lite 2020-08-23 Model: Inception V4 EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 600K 1200K 1800K 2400K 3000K Min: 3471470 / Avg: 3472940 / Max: 3475160 Min: 2492910 / Avg: 2493746.67 / Max: 2494380 Min: 1819400 / Avg: 1820153.33 / Max: 1821260 Min: 1742350 / Avg: 1742890 / Max: 1743220 Min: 1365020 / Avg: 1366410 / Max: 1368870 Min: 1005560 / Avg: 1006346.67 / Max: 1007240 Min: 1034080 / Avg: 1034366.67 / Max: 1034530 Min: 942378 / Avg: 943229 / Max: 943679 Min: 977917 / Avg: 978828.33 / Max: 980643 Min: 935608 / Avg: 938691 / Max: 941780 Min: 695393 / Avg: 700833.33 / Max: 706259 Min: 752152 / Avg: 764269 / Max: 770948 Min: 2871920 / Avg: 2872226.67 / Max: 2872670 Min: 1498800 / Avg: 1499183.33 / Max: 1499400
Blender Blender is an open-source 3D creation software project. This test is of Blender's Cycles benchmark with various sample files. GPU computing via OpenCL or CUDA is supported. Learn more via the OpenBenchmarking.org test page.
Result
OpenBenchmarking.org Seconds, Fewer Is Better Blender 2.90 Blend File: BMW27 - Compute: CPU-Only EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 40 80 120 160 200 SE +/- 1.01, N = 3 SE +/- 0.34, N = 3 SE +/- 0.34, N = 3 SE +/- 0.95, N = 3 SE +/- 0.08, N = 3 SE +/- 0.37, N = 3 SE +/- 0.21, N = 3 SE +/- 0.06, N = 3 SE +/- 0.42, N = 3 SE +/- 0.19, N = 3 SE +/- 0.27, N = 3 SE +/- 0.12, N = 3 SE +/- 0.25, N = 3 SE +/- 0.27, N = 3 198.45 136.20 108.34 102.29 69.84 60.75 61.25 55.32 46.59 45.78 40.33 40.07 156.31 83.45
Result Confidence
OpenBenchmarking.org Seconds, Fewer Is Better Blender 2.90 Blend File: BMW27 - Compute: CPU-Only EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 40 80 120 160 200 Min: 196.87 / Avg: 198.45 / Max: 200.33 Min: 135.6 / Avg: 136.2 / Max: 136.76 Min: 107.74 / Avg: 108.34 / Max: 108.92 Min: 100.63 / Avg: 102.29 / Max: 103.93 Min: 69.76 / Avg: 69.84 / Max: 69.99 Min: 60 / Avg: 60.75 / Max: 61.17 Min: 60.93 / Avg: 61.25 / Max: 61.64 Min: 55.22 / Avg: 55.32 / Max: 55.43 Min: 45.95 / Avg: 46.59 / Max: 47.39 Min: 45.39 / Avg: 45.78 / Max: 45.99 Min: 39.99 / Avg: 40.33 / Max: 40.86 Min: 39.84 / Avg: 40.07 / Max: 40.23 Min: 155.93 / Avg: 156.31 / Max: 156.78 Min: 83.1 / Avg: 83.45 / Max: 83.98
POV-Ray This is a test of POV-Ray, the Persistence of Vision Raytracer. POV-Ray is used to create 3D graphics using ray-tracing. Learn more via the OpenBenchmarking.org test page.
Result
OpenBenchmarking.org Seconds, Fewer Is Better POV-Ray 3.7.0.7 Trace Time EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 13 26 39 52 65 SE +/- 0.24, N = 3 SE +/- 0.04, N = 3 SE +/- 0.05, N = 3 SE +/- 0.01, N = 3 SE +/- 0.05, N = 3 SE +/- 0.01, N = 3 SE +/- 0.02, N = 3 SE +/- 0.01, N = 3 SE +/- 0.04, N = 4 SE +/- 0.04, N = 4 SE +/- 0.03, N = 4 SE +/- 0.02, N = 4 SE +/- 0.02, N = 3 SE +/- 0.02, N = 3 55.78 38.41 30.51 28.70 20.46 17.14 17.67 15.94 13.27 13.27 11.50 11.50 45.47 24.18 1. (CXX) g++ options: -pipe -O3 -ffast-math -march=native -pthread -lSDL -lSM -lICE -lX11 -lIlmImf -lImath -lHalf -lIex -lIexMath -lIlmThread -lpthread -ltiff -ljpeg -lpng -lz -lrt -lm -lboost_thread -lboost_system
Result Confidence
OpenBenchmarking.org Seconds, Fewer Is Better POV-Ray 3.7.0.7 Trace Time EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 11 22 33 44 55 Min: 55.44 / Avg: 55.78 / Max: 56.24 Min: 38.36 / Avg: 38.41 / Max: 38.49 Min: 30.42 / Avg: 30.51 / Max: 30.57 Min: 28.69 / Avg: 28.7 / Max: 28.72 Min: 20.41 / Avg: 20.46 / Max: 20.56 Min: 17.12 / Avg: 17.14 / Max: 17.17 Min: 17.65 / Avg: 17.67 / Max: 17.7 Min: 15.92 / Avg: 15.94 / Max: 15.96 Min: 13.17 / Avg: 13.27 / Max: 13.35 Min: 13.19 / Avg: 13.27 / Max: 13.35 Min: 11.4 / Avg: 11.5 / Max: 11.56 Min: 11.45 / Avg: 11.5 / Max: 11.55 Min: 45.44 / Avg: 45.47 / Max: 45.5 Min: 24.15 / Avg: 24.18 / Max: 24.23 1. (CXX) g++ options: -pipe -O3 -ffast-math -march=native -pthread -lSDL -lSM -lICE -lX11 -lIlmImf -lImath -lHalf -lIex -lIexMath -lIlmThread -lpthread -ltiff -ljpeg -lpng -lz -lrt -lm -lboost_thread -lboost_system
Blender Blender is an open-source 3D creation software project. This test is of Blender's Cycles benchmark with various sample files. GPU computing via OpenCL or CUDA is supported. Learn more via the OpenBenchmarking.org test page.
Result
OpenBenchmarking.org Seconds, Fewer Is Better Blender 2.90 Blend File: Fishy Cat - Compute: CPU-Only EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 60 120 180 240 300 SE +/- 0.21, N = 3 SE +/- 0.81, N = 3 SE +/- 0.24, N = 3 SE +/- 0.08, N = 3 SE +/- 0.46, N = 3 SE +/- 0.04, N = 3 SE +/- 0.30, N = 3 SE +/- 0.12, N = 3 SE +/- 0.22, N = 3 SE +/- 0.14, N = 3 SE +/- 0.03, N = 3 SE +/- 0.11, N = 3 SE +/- 0.04, N = 3 SE +/- 0.20, N = 3 267.24 177.65 139.46 129.81 91.81 78.01 78.94 72.27 62.72 61.93 55.82 55.40 207.12 108.40
Result Confidence
OpenBenchmarking.org Seconds, Fewer Is Better Blender 2.90 Blend File: Fishy Cat - Compute: CPU-Only EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 50 100 150 200 250 Min: 267.03 / Avg: 267.24 / Max: 267.66 Min: 176.74 / Avg: 177.65 / Max: 179.26 Min: 139.16 / Avg: 139.46 / Max: 139.93 Min: 129.68 / Avg: 129.81 / Max: 129.95 Min: 90.99 / Avg: 91.81 / Max: 92.58 Min: 77.95 / Avg: 78.01 / Max: 78.08 Min: 78.44 / Avg: 78.94 / Max: 79.47 Min: 72.03 / Avg: 72.27 / Max: 72.43 Min: 62.45 / Avg: 62.72 / Max: 63.15 Min: 61.67 / Avg: 61.93 / Max: 62.15 Min: 55.77 / Avg: 55.82 / Max: 55.85 Min: 55.2 / Avg: 55.4 / Max: 55.58 Min: 207.06 / Avg: 207.12 / Max: 207.19 Min: 108.03 / Avg: 108.4 / Max: 108.72
oneDNN This is a test of the Intel oneDNN as an Intel-optimized library for Deep Neural Networks and making use of its built-in benchdnn functionality. The result is the total perf time reported. Intel oneDNN was formerly known as DNNL (Deep Neural Network Library) and MKL-DNN before being rebranded as part of the Intel oneAPI initiative. Learn more via the OpenBenchmarking.org test page.
Result
OpenBenchmarking.org ms, Fewer Is Better oneDNN 2.0 Harness: Deconvolution Batch shapes_1d - Data Type: u8s8f32 - Engine: CPU EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 2 4 6 8 10 SE +/- 0.02294, N = 3 SE +/- 0.00535, N = 3 SE +/- 0.02527, N = 3 SE +/- 0.00946, N = 3 SE +/- 0.02587, N = 3 SE +/- 0.00464, N = 3 SE +/- 0.00309, N = 3 SE +/- 0.00531, N = 3 SE +/- 0.00201, N = 3 SE +/- 0.00608, N = 3 SE +/- 0.00798, N = 3 SE +/- 0.00645, N = 3 SE +/- 0.00611, N = 3 SE +/- 0.02104, N = 3 8.67154 5.25331 6.06333 6.03497 5.92204 2.15194 2.20543 2.06983 1.99707 1.93042 1.79874 1.88842 7.23763 5.49605 MIN: 8.41 MIN: 5.07 MIN: 5.87 MIN: 5.92 MIN: 5.79 MIN: 2.02 MIN: 2.05 MIN: 2 MIN: 1.91 MIN: 1.82 MIN: 1.69 MIN: 1.8 MIN: 7.01 MIN: 5.32 1. (CXX) g++ options: -O3 -std=c++11 -fopenmp -msse4.1 -fPIC -pie -lpthread
Result Confidence
OpenBenchmarking.org ms, Fewer Is Better oneDNN 2.0 Harness: Deconvolution Batch shapes_1d - Data Type: u8s8f32 - Engine: CPU EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 3 6 9 12 15 Min: 8.63 / Avg: 8.67 / Max: 8.71 Min: 5.25 / Avg: 5.25 / Max: 5.26 Min: 6.02 / Avg: 6.06 / Max: 6.1 Min: 6.02 / Avg: 6.03 / Max: 6.04 Min: 5.89 / Avg: 5.92 / Max: 5.97 Min: 2.15 / Avg: 2.15 / Max: 2.16 Min: 2.2 / Avg: 2.21 / Max: 2.21 Min: 2.06 / Avg: 2.07 / Max: 2.08 Min: 1.99 / Avg: 2 / Max: 2 Min: 1.92 / Avg: 1.93 / Max: 1.94 Min: 1.78 / Avg: 1.8 / Max: 1.81 Min: 1.88 / Avg: 1.89 / Max: 1.9 Min: 7.23 / Avg: 7.24 / Max: 7.25 Min: 5.46 / Avg: 5.5 / Max: 5.54 1. (CXX) g++ options: -O3 -std=c++11 -fopenmp -msse4.1 -fPIC -pie -lpthread
TensorFlow Lite This is a benchmark of the TensorFlow Lite implementation. The current Linux support is limited to running on CPUs. This test profile is measuring the average inference time. Learn more via the OpenBenchmarking.org test page.
Result
OpenBenchmarking.org Microseconds, Fewer Is Better TensorFlow Lite 2020-08-23 Model: Inception ResNet V2 EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 700K 1400K 2100K 2800K 3500K SE +/- 326.24, N = 3 SE +/- 518.11, N = 3 SE +/- 1027.95, N = 3 SE +/- 366.38, N = 3 SE +/- 1259.14, N = 3 SE +/- 466.83, N = 3 SE +/- 386.91, N = 3 SE +/- 149.07, N = 3 SE +/- 1818.31, N = 3 SE +/- 837.49, N = 3 SE +/- 4181.60, N = 3 SE +/- 6234.46, N = 7 SE +/- 314.32, N = 3 SE +/- 1646.01, N = 3 3136920 2242950 1639167 1567070 1206790 897884 921865 840604 893517 830730 655279 702607 2592970 1346153
Result Confidence
OpenBenchmarking.org Microseconds, Fewer Is Better TensorFlow Lite 2020-08-23 Model: Inception ResNet V2 EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 500K 1000K 1500K 2000K 2500K Min: 3136350 / Avg: 3136920 / Max: 3137480 Min: 2241960 / Avg: 2242950 / Max: 2243710 Min: 1637410 / Avg: 1639166.67 / Max: 1640970 Min: 1566650 / Avg: 1567070 / Max: 1567800 Min: 1205130 / Avg: 1206790 / Max: 1209260 Min: 897006 / Avg: 897884 / Max: 898598 Min: 921416 / Avg: 921864.67 / Max: 922635 Min: 840370 / Avg: 840604 / Max: 840881 Min: 889933 / Avg: 893516.67 / Max: 895844 Min: 829366 / Avg: 830730.33 / Max: 832254 Min: 649807 / Avg: 655278.67 / Max: 663492 Min: 690630 / Avg: 702607 / Max: 737249 Min: 2592570 / Avg: 2592970 / Max: 2593590 Min: 1343550 / Avg: 1346153.33 / Max: 1349200
oneDNN This is a test of the Intel oneDNN as an Intel-optimized library for Deep Neural Networks and making use of its built-in benchdnn functionality. The result is the total perf time reported. Intel oneDNN was formerly known as DNNL (Deep Neural Network Library) and MKL-DNN before being rebranded as part of the Intel oneAPI initiative. Learn more via the OpenBenchmarking.org test page.
Result
OpenBenchmarking.org ms, Fewer Is Better oneDNN 2.0 Harness: Deconvolution Batch shapes_3d - Data Type: u8s8f32 - Engine: CPU EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 2 4 6 8 10 SE +/- 0.00235, N = 9 SE +/- 0.00336, N = 9 SE +/- 0.00324, N = 9 SE +/- 0.00304, N = 9 SE +/- 0.00168, N = 9 SE +/- 0.00338, N = 9 SE +/- 0.00104, N = 9 SE +/- 0.00215, N = 9 SE +/- 0.00157, N = 9 SE +/- 0.00625, N = 9 SE +/- 0.00834, N = 9 SE +/- 0.00637, N = 9 SE +/- 0.00176, N = 9 SE +/- 0.00628, N = 9 6.79445 4.52758 3.45290 3.34663 2.38306 1.94845 1.98809 1.89624 1.55494 1.53915 1.43124 1.49446 5.58260 3.02897 MIN: 6.75 MIN: 4.47 MIN: 3.34 MIN: 3.25 MIN: 2.33 MIN: 1.82 MIN: 1.83 MIN: 1.77 MIN: 1.42 MIN: 1.37 MIN: 1.26 MIN: 1.36 MIN: 5.52 MIN: 2.92 1. (CXX) g++ options: -O3 -std=c++11 -fopenmp -msse4.1 -fPIC -pie -lpthread
Result Confidence
OpenBenchmarking.org ms, Fewer Is Better oneDNN 2.0 Harness: Deconvolution Batch shapes_3d - Data Type: u8s8f32 - Engine: CPU EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 3 6 9 12 15 Min: 6.79 / Avg: 6.79 / Max: 6.81 Min: 4.51 / Avg: 4.53 / Max: 4.54 Min: 3.44 / Avg: 3.45 / Max: 3.47 Min: 3.33 / Avg: 3.35 / Max: 3.36 Min: 2.38 / Avg: 2.38 / Max: 2.39 Min: 1.94 / Avg: 1.95 / Max: 1.97 Min: 1.98 / Avg: 1.99 / Max: 1.99 Min: 1.89 / Avg: 1.9 / Max: 1.91 Min: 1.55 / Avg: 1.55 / Max: 1.56 Min: 1.52 / Avg: 1.54 / Max: 1.57 Min: 1.41 / Avg: 1.43 / Max: 1.48 Min: 1.48 / Avg: 1.49 / Max: 1.53 Min: 5.57 / Avg: 5.58 / Max: 5.59 Min: 2.99 / Avg: 3.03 / Max: 3.05 1. (CXX) g++ options: -O3 -std=c++11 -fopenmp -msse4.1 -fPIC -pie -lpthread
LAMMPS Molecular Dynamics Simulator LAMMPS is a classical molecular dynamics code, and an acronym for Large-scale Atomic/Molecular Massively Parallel Simulator. Learn more via the OpenBenchmarking.org test page.
Result
OpenBenchmarking.org ns/day, More Is Better LAMMPS Molecular Dynamics Simulator 29Oct2020 Model: 20k Atoms EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 6 12 18 24 30 SE +/- 0.007, N = 3 SE +/- 0.023, N = 3 SE +/- 0.021, N = 3 SE +/- 0.009, N = 3 SE +/- 0.010, N = 3 SE +/- 0.059, N = 3 SE +/- 0.016, N = 3 SE +/- 0.062, N = 3 SE +/- 0.112, N = 3 SE +/- 0.029, N = 3 SE +/- 0.056, N = 3 SE +/- 0.024, N = 3 SE +/- 0.004, N = 3 SE +/- 0.053, N = 3 5.406 7.737 9.889 10.602 14.907 17.614 17.525 18.156 22.046 22.442 25.206 24.818 6.705 11.757 1. (CXX) g++ options: -O3 -pthread -lm
ns/day Per Watt
OpenBenchmarking.org ns/day Per Watt, More Is Better LAMMPS Molecular Dynamics Simulator 29Oct2020 Model: 20k Atoms EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 0.0315 0.063 0.0945 0.126 0.1575 0.07 0.08 0.10 0.09 0.10 0.12 0.10 0.11 0.13 0.11 0.14 0.13 0.06 0.06
Result Confidence
OpenBenchmarking.org ns/day, More Is Better LAMMPS Molecular Dynamics Simulator 29Oct2020 Model: 20k Atoms EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 6 12 18 24 30 Min: 5.39 / Avg: 5.41 / Max: 5.41 Min: 7.71 / Avg: 7.74 / Max: 7.78 Min: 9.85 / Avg: 9.89 / Max: 9.92 Min: 10.58 / Avg: 10.6 / Max: 10.62 Min: 14.89 / Avg: 14.91 / Max: 14.93 Min: 17.51 / Avg: 17.61 / Max: 17.71 Min: 17.5 / Avg: 17.53 / Max: 17.55 Min: 18.03 / Avg: 18.16 / Max: 18.22 Min: 21.83 / Avg: 22.05 / Max: 22.19 Min: 22.4 / Avg: 22.44 / Max: 22.5 Min: 25.11 / Avg: 25.21 / Max: 25.31 Min: 24.78 / Avg: 24.82 / Max: 24.86 Min: 6.7 / Avg: 6.7 / Max: 6.71 Min: 11.66 / Avg: 11.76 / Max: 11.85 1. (CXX) g++ options: -O3 -pthread -lm
GROMACS The GROMACS (GROningen MAchine for Chemical Simulations) molecular dynamics package testing on the CPU with the water_GMX50 data. Learn more via the OpenBenchmarking.org test page.
Result
OpenBenchmarking.org Ns Per Day, More Is Better GROMACS 2020.3 Water Benchmark EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 1.0217 2.0434 3.0651 4.0868 5.1085 SE +/- 0.003, N = 3 SE +/- 0.001, N = 3 SE +/- 0.001, N = 3 SE +/- 0.004, N = 3 SE +/- 0.001, N = 3 SE +/- 0.011, N = 3 SE +/- 0.008, N = 3 SE +/- 0.002, N = 3 SE +/- 0.004, N = 3 SE +/- 0.013, N = 3 SE +/- 0.008, N = 3 SE +/- 0.003, N = 3 SE +/- 0.003, N = 3 SE +/- 0.005, N = 3 0.985 1.409 1.677 2.014 2.741 3.128 3.267 3.323 3.863 4.117 4.541 4.373 1.345 1.995 1. (CXX) g++ options: -O3 -pthread -lrt -lpthread -lm
Ns Per Day Per Watt
OpenBenchmarking.org Ns Per Day Per Watt, More Is Better GROMACS 2020.3 Water Benchmark EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 0.0068 0.0136 0.0204 0.0272 0.034 0.01 0.01 0.02 0.02 0.02 0.02 0.02 0.02 0.02 0.02 0.03 0.02 0.01 0.01
Result Confidence
OpenBenchmarking.org Ns Per Day, More Is Better GROMACS 2020.3 Water Benchmark EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 2 4 6 8 10 Min: 0.98 / Avg: 0.99 / Max: 0.99 Min: 1.41 / Avg: 1.41 / Max: 1.41 Min: 1.68 / Avg: 1.68 / Max: 1.68 Min: 2.01 / Avg: 2.01 / Max: 2.02 Min: 2.74 / Avg: 2.74 / Max: 2.74 Min: 3.11 / Avg: 3.13 / Max: 3.14 Min: 3.25 / Avg: 3.27 / Max: 3.28 Min: 3.32 / Avg: 3.32 / Max: 3.33 Min: 3.86 / Avg: 3.86 / Max: 3.87 Min: 4.09 / Avg: 4.12 / Max: 4.13 Min: 4.53 / Avg: 4.54 / Max: 4.55 Min: 4.37 / Avg: 4.37 / Max: 4.38 Min: 1.34 / Avg: 1.35 / Max: 1.35 Min: 1.99 / Avg: 2 / Max: 2.01 1. (CXX) g++ options: -O3 -pthread -lrt -lpthread -lm
oneDNN This is a test of the Intel oneDNN as an Intel-optimized library for Deep Neural Networks and making use of its built-in benchdnn functionality. The result is the total perf time reported. Intel oneDNN was formerly known as DNNL (Deep Neural Network Library) and MKL-DNN before being rebranded as part of the Intel oneAPI initiative. Learn more via the OpenBenchmarking.org test page.
Result
OpenBenchmarking.org ms, Fewer Is Better oneDNN 2.0 Harness: Matrix Multiply Batch Shapes Transformer - Data Type: u8s8f32 - Engine: CPU EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 0.8063 1.6126 2.4189 3.2252 4.0315 SE +/- 0.001594, N = 4 SE +/- 0.001298, N = 4 SE +/- 0.001269, N = 4 SE +/- 0.001219, N = 4 SE +/- 0.009261, N = 15 SE +/- 0.003967, N = 4 SE +/- 0.001948, N = 4 SE +/- 0.005244, N = 4 SE +/- 0.000788, N = 4 SE +/- 0.001659, N = 4 SE +/- 0.000537, N = 4 SE +/- 0.002127, N = 4 SE +/- 0.000640, N = 4 SE +/- 0.001361, N = 4 3.583630 2.493720 1.913050 1.841780 1.295990 1.073990 1.104860 1.015820 0.868024 0.863146 0.780803 0.800643 3.012920 1.565030 MIN: 3.54 MIN: 2.45 MIN: 1.87 MIN: 1.82 MIN: 1.25 MIN: 0.98 MIN: 0.99 MIN: 0.98 MIN: 0.81 MIN: 0.77 MIN: 0.7 MIN: 0.76 MIN: 2.73 MIN: 1.54 1. (CXX) g++ options: -O3 -std=c++11 -fopenmp -msse4.1 -fPIC -pie -lpthread
Result Confidence
OpenBenchmarking.org ms, Fewer Is Better oneDNN 2.0 Harness: Matrix Multiply Batch Shapes Transformer - Data Type: u8s8f32 - Engine: CPU EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 2 4 6 8 10 Min: 3.58 / Avg: 3.58 / Max: 3.59 Min: 2.49 / Avg: 2.49 / Max: 2.5 Min: 1.91 / Avg: 1.91 / Max: 1.92 Min: 1.84 / Avg: 1.84 / Max: 1.85 Min: 1.27 / Avg: 1.3 / Max: 1.37 Min: 1.07 / Avg: 1.07 / Max: 1.08 Min: 1.1 / Avg: 1.1 / Max: 1.11 Min: 1 / Avg: 1.02 / Max: 1.03 Min: 0.87 / Avg: 0.87 / Max: 0.87 Min: 0.86 / Avg: 0.86 / Max: 0.87 Min: 0.78 / Avg: 0.78 / Max: 0.78 Min: 0.79 / Avg: 0.8 / Max: 0.8 Min: 3.01 / Avg: 3.01 / Max: 3.01 Min: 1.56 / Avg: 1.57 / Max: 1.57 1. (CXX) g++ options: -O3 -std=c++11 -fopenmp -msse4.1 -fPIC -pie -lpthread
Apache Cassandra This is a benchmark of the Apache Cassandra NoSQL database management system making use of cassandra-stress. Learn more via the OpenBenchmarking.org test page.
Result
OpenBenchmarking.org Op/s, More Is Better Apache Cassandra 3.11.4 Test: Writes EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 50K 100K 150K 200K 250K SE +/- 244.34, N = 3 SE +/- 388.59, N = 3 SE +/- 936.51, N = 3 SE +/- 1793.27, N = 3 SE +/- 2693.44, N = 3 SE +/- 2790.65, N = 3 SE +/- 2221.55, N = 3 SE +/- 2207.46, N = 15 SE +/- 1126.54, N = 3 SE +/- 1690.31, N = 3 SE +/- 2776.27, N = 3 SE +/- 1230.73, N = 3 SE +/- 224.51, N = 3 SE +/- 1803.14, N = 3 51734 93155 136442 135260 200705 233730 211361 236524 230871 215576 219380 227564 58118 144123
Op/s Per Watt
OpenBenchmarking.org Op/s Per Watt, More Is Better Apache Cassandra 3.11.4 Test: Writes EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 400 800 1200 1600 2000 837.71 1222.04 1607.35 1456.94 1745.18 1934.28 1502.63 2007.98 1765.84 1507.25 1537.85 1563.40 654.20 945.02
Result Confidence
OpenBenchmarking.org Op/s, More Is Better Apache Cassandra 3.11.4 Test: Writes EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 40K 80K 120K 160K 200K Min: 51248 / Avg: 51734.33 / Max: 52019 Min: 92380 / Avg: 93154.67 / Max: 93596 Min: 134572 / Avg: 136442 / Max: 137469 Min: 131775 / Avg: 135259.67 / Max: 137737 Min: 197409 / Avg: 200705 / Max: 206043 Min: 228668 / Avg: 233730 / Max: 238297 Min: 208632 / Avg: 211361 / Max: 215762 Min: 227162 / Avg: 236524.33 / Max: 255532 Min: 229505 / Avg: 230871.33 / Max: 233106 Min: 212562 / Avg: 215576 / Max: 218409 Min: 214454 / Avg: 219380 / Max: 224062 Min: 225103 / Avg: 227564.33 / Max: 228816 Min: 57842 / Avg: 58118.33 / Max: 58563 Min: 141196 / Avg: 144123.33 / Max: 147411
ASKAP ASKAP is a set of benchmarks from the Australian SKA Pathfinder. The principal ASKAP benchmarks are the Hogbom Clean Benchmark (tHogbomClean) and Convolutional Resamping Benchmark (tConvolve) as well as some previous ASKAP benchmarks being included as well for OpenCL and CUDA execution of tConvolve. Learn more via the OpenBenchmarking.org test page.
Result
OpenBenchmarking.org Million Grid Points Per Second, More Is Better ASKAP 1.0 Test: tConvolve OpenMP - Gridding EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 2K 4K 6K 8K 10K SE +/- 7.61, N = 4 SE +/- 17.38, N = 4 SE +/- 0.00, N = 4 SE +/- 57.68, N = 5 SE +/- 72.46, N = 4 SE +/- 79.54, N = 4 SE +/- 63.04, N = 4 SE +/- 67.99, N = 4 SE +/- 77.48, N = 4 SE +/- 81.97, N = 4 SE +/- 0.00, N = 4 SE +/- 0.00, N = 4 SE +/- 35.30, N = 4 SE +/- 0.00, N = 4 2840.13 4004.08 4294.45 5503.59 6379.88 6617.90 8257.47 6658.48 8454.70 9427.17 9509.14 9509.14 4035.11 2113.14 1. (CXX) g++ options: -O3 -fstrict-aliasing -fopenmp
Result Confidence
OpenBenchmarking.org Million Grid Points Per Second, More Is Better ASKAP 1.0 Test: tConvolve OpenMP - Gridding EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 1700 3400 5100 6800 8500 Min: 2832.51 / Avg: 2840.13 / Max: 2862.97 Min: 3973.97 / Avg: 4004.08 / Max: 4034.18 Min: 4294.45 / Avg: 4294.45 / Max: 4294.45 Min: 5325.12 / Avg: 5503.59 / Max: 5665.02 Min: 6192 / Avg: 6379.88 / Max: 6494.05 Min: 6494.05 / Avg: 6617.9 / Max: 6827.08 Min: 8068.36 / Avg: 8257.47 / Max: 8320.5 Min: 6494.05 / Avg: 6658.48 / Max: 6827.08 Min: 8320.5 / Avg: 8454.7 / Max: 8588.9 Min: 9181.24 / Avg: 9427.17 / Max: 9509.14 Min: 9509.14 / Avg: 9509.14 / Max: 9509.14 Min: 9509.14 / Avg: 9509.14 / Max: 9509.14 Min: 3973.97 / Avg: 4035.11 / Max: 4096.25 Min: 2113.14 / Avg: 2113.14 / Max: 2113.14 1. (CXX) g++ options: -O3 -fstrict-aliasing -fopenmp
Intel Open Image Denoise Open Image Denoise is a denoising library for ray-tracing and part of the oneAPI rendering toolkit. Learn more via the OpenBenchmarking.org test page.
Result
OpenBenchmarking.org Images / Sec, More Is Better Intel Open Image Denoise 1.2.0 Scene: Memorial EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 7 14 21 28 35 SE +/- 0.00, N = 3 SE +/- 0.00, N = 3 SE +/- 0.01, N = 3 SE +/- 0.12, N = 6 SE +/- 0.01, N = 4 SE +/- 0.01, N = 5 SE +/- 0.01, N = 5 SE +/- 0.01, N = 5 SE +/- 0.02, N = 6 SE +/- 0.04, N = 6 SE +/- 0.03, N = 6 SE +/- 0.01, N = 3 SE +/- 0.02, N = 4 6.55 9.03 11.34 12.18 17.17 20.25 20.14 21.55 26.13 29.41 27.67 7.94 14.24
Images / Sec Per Watt
OpenBenchmarking.org Images / Sec Per Watt, More Is Better Intel Open Image Denoise 1.2.0 Scene: Memorial EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 0.0473 0.0946 0.1419 0.1892 0.2365 0.08 0.10 0.12 0.11 0.13 0.16 0.15 0.16 0.20 0.21 0.20 0.06 0.07
Result Confidence
OpenBenchmarking.org Images / Sec, More Is Better Intel Open Image Denoise 1.2.0 Scene: Memorial EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 7 14 21 28 35 Min: 6.54 / Avg: 6.55 / Max: 6.55 Min: 9.02 / Avg: 9.03 / Max: 9.03 Min: 11.34 / Avg: 11.34 / Max: 11.36 Min: 11.56 / Avg: 12.18 / Max: 12.32 Min: 17.16 / Avg: 17.17 / Max: 17.19 Min: 20.23 / Avg: 20.25 / Max: 20.28 Min: 20.11 / Avg: 20.14 / Max: 20.18 Min: 21.52 / Avg: 21.55 / Max: 21.6 Min: 26.05 / Avg: 26.13 / Max: 26.17 Min: 29.29 / Avg: 29.41 / Max: 29.54 Min: 27.55 / Avg: 27.67 / Max: 27.73 Min: 7.92 / Avg: 7.94 / Max: 7.96 Min: 14.2 / Avg: 14.24 / Max: 14.27
ebizzy This is a test of ebizzy, a program to generate workloads resembling web server workloads. Learn more via the OpenBenchmarking.org test page.
Result
OpenBenchmarking.org Records/s, More Is Better ebizzy 0.3 EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 600K 1200K 1800K 2400K 3000K SE +/- 4933.88, N = 3 SE +/- 906.56, N = 3 SE +/- 8956.45, N = 3 SE +/- 8057.83, N = 3 SE +/- 15686.47, N = 3 SE +/- 10663.27, N = 3 SE +/- 15669.57, N = 3 SE +/- 8453.72, N = 3 SE +/- 24033.50, N = 3 SE +/- 37169.94, N = 3 SE +/- 34594.95, N = 12 SE +/- 25794.01, N = 15 SE +/- 6904.71, N = 7 SE +/- 7117.75, N = 3 623272 883965 1021990 1208466 1721854 1947836 1977325 2136850 2456511 2719388 2762647 2701767 776880 1475280 1. (CC) gcc options: -pthread -lpthread -O3 -march=native
Records/s Per Watt
OpenBenchmarking.org Records/s Per Watt, More Is Better ebizzy 0.3 EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 4K 8K 12K 16K 20K 7399.84 9696.42 11127.27 10725.42 12779.06 14373.63 13352.11 13548.39 15696.63 15813.47 16672.76 16026.57 5966.03 7194.42
Result Confidence
OpenBenchmarking.org Records/s, More Is Better ebizzy 0.3 EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 500K 1000K 1500K 2000K 2500K Min: 616705 / Avg: 623272 / Max: 632934 Min: 882270 / Avg: 883965 / Max: 885370 Min: 1009030 / Avg: 1021990 / Max: 1039179 Min: 1192406 / Avg: 1208466.33 / Max: 1217652 Min: 1691610 / Avg: 1721854 / Max: 1744199 Min: 1926759 / Avg: 1947835.67 / Max: 1961193 Min: 1951917 / Avg: 1977324.67 / Max: 2005917 Min: 2127912 / Avg: 2136850 / Max: 2153748 Min: 2420178 / Avg: 2456510.67 / Max: 2501931 Min: 2645052 / Avg: 2719388 / Max: 2757214 Min: 2508914 / Avg: 2762646.92 / Max: 2926207 Min: 2510210 / Avg: 2701767.07 / Max: 2845248 Min: 747575 / Avg: 776880.43 / Max: 796470 Min: 1461618 / Avg: 1475280 / Max: 1485575 1. (CC) gcc options: -pthread -lpthread -O3 -march=native
Tungsten Renderer Tungsten is a C++ physically based renderer that makes use of Intel's Embree ray tracing library. Learn more via the OpenBenchmarking.org test page.
Result
OpenBenchmarking.org Seconds, Fewer Is Better Tungsten Renderer 0.2.2 Scene: Hair EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 8 16 24 32 40 SE +/- 0.03115, N = 3 SE +/- 0.03918, N = 3 SE +/- 0.03890, N = 3 SE +/- 0.02745, N = 3 SE +/- 0.02622, N = 4 SE +/- 0.00983, N = 5 SE +/- 0.03618, N = 5 SE +/- 0.02895, N = 5 SE +/- 0.04134, N = 5 SE +/- 0.03455, N = 5 SE +/- 0.02077, N = 6 SE +/- 0.02278, N = 6 SE +/- 0.01111, N = 3 SE +/- 0.03705, N = 4 32.53880 21.99580 17.65420 16.61750 12.26230 10.57400 10.81310 9.92849 8.71953 8.56828 7.55093 7.50706 26.51610 14.13270 1. (CXX) g++ options: -std=c++0x -march=znver1 -msse2 -msse3 -mssse3 -msse4.1 -msse4.2 -msse4a -mfma -mbmi2 -mno-avx -mno-avx2 -mno-xop -mno-fma4 -mno-avx512f -mno-avx512vl -mno-avx512pf -mno-avx512er -mno-avx512cd -mno-avx512dq -mno-avx512bw -mno-avx512ifma -mno-avx512vbmi -fstrict-aliasing -O3 -rdynamic -lIlmImf -lIlmThread -lImath -lHalf -lIex -lz -ljpeg -lpthread -ldl
Result Confidence
OpenBenchmarking.org Seconds, Fewer Is Better Tungsten Renderer 0.2.2 Scene: Hair EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 7 14 21 28 35 Min: 32.48 / Avg: 32.54 / Max: 32.59 Min: 21.93 / Avg: 22 / Max: 22.07 Min: 17.6 / Avg: 17.65 / Max: 17.73 Min: 16.56 / Avg: 16.62 / Max: 16.65 Min: 12.21 / Avg: 12.26 / Max: 12.33 Min: 10.56 / Avg: 10.57 / Max: 10.61 Min: 10.71 / Avg: 10.81 / Max: 10.91 Min: 9.86 / Avg: 9.93 / Max: 10.01 Min: 8.63 / Avg: 8.72 / Max: 8.86 Min: 8.43 / Avg: 8.57 / Max: 8.61 Min: 7.5 / Avg: 7.55 / Max: 7.63 Min: 7.46 / Avg: 7.51 / Max: 7.59 Min: 26.5 / Avg: 26.52 / Max: 26.54 Min: 14.08 / Avg: 14.13 / Max: 14.23 1. (CXX) g++ options: -std=c++0x -march=znver1 -msse2 -msse3 -mssse3 -msse4.1 -msse4.2 -msse4a -mfma -mbmi2 -mno-avx -mno-avx2 -mno-xop -mno-fma4 -mno-avx512f -mno-avx512vl -mno-avx512pf -mno-avx512er -mno-avx512cd -mno-avx512dq -mno-avx512bw -mno-avx512ifma -mno-avx512vbmi -fstrict-aliasing -O3 -rdynamic -lIlmImf -lIlmThread -lImath -lHalf -lIex -lz -ljpeg -lpthread -ldl
TensorFlow Lite This is a benchmark of the TensorFlow Lite implementation. The current Linux support is limited to running on CPUs. This test profile is measuring the average inference time. Learn more via the OpenBenchmarking.org test page.
Result
OpenBenchmarking.org Microseconds, Fewer Is Better TensorFlow Lite 2020-08-23 Model: SqueezeNet EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 50K 100K 150K 200K 250K SE +/- 202.36, N = 3 SE +/- 82.39, N = 3 SE +/- 38.26, N = 3 SE +/- 25.85, N = 3 SE +/- 6.99, N = 3 SE +/- 126.18, N = 3 SE +/- 39.58, N = 3 SE +/- 77.46, N = 3 SE +/- 74.34, N = 3 SE +/- 111.10, N = 3 SE +/- 174.48, N = 3 SE +/- 39.50, N = 3 SE +/- 44.74, N = 3 SE +/- 132.22, N = 3 242480.0 173807.0 129293.0 123947.0 93404.1 75080.0 77264.7 70622.9 68430.4 65104.4 56195.5 61679.6 201258.0 107391.0
Result Confidence
OpenBenchmarking.org Microseconds, Fewer Is Better TensorFlow Lite 2020-08-23 Model: SqueezeNet EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 40K 80K 120K 160K 200K Min: 242075 / Avg: 242479.67 / Max: 242688 Min: 173701 / Avg: 173806.67 / Max: 173969 Min: 129222 / Avg: 129293.33 / Max: 129353 Min: 123895 / Avg: 123946.67 / Max: 123974 Min: 93391.7 / Avg: 93404.1 / Max: 93415.9 Min: 74862.2 / Avg: 75080 / Max: 75299.3 Min: 77193.3 / Avg: 77264.7 / Max: 77330 Min: 70510.4 / Avg: 70622.9 / Max: 70771.4 Min: 68340.5 / Avg: 68430.4 / Max: 68577.9 Min: 64904.3 / Avg: 65104.43 / Max: 65288.1 Min: 55903.9 / Avg: 56195.5 / Max: 56507.3 Min: 61602.1 / Avg: 61679.57 / Max: 61731.7 Min: 201180 / Avg: 201257.67 / Max: 201335 Min: 107127 / Avg: 107390.67 / Max: 107540
Tungsten Renderer Tungsten is a C++ physically based renderer that makes use of Intel's Embree ray tracing library. Learn more via the OpenBenchmarking.org test page.
Result
OpenBenchmarking.org Seconds, Fewer Is Better Tungsten Renderer 0.2.2 Scene: Non-Exponential EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 3 6 9 12 15 SE +/- 0.02902, N = 4 SE +/- 0.01455, N = 5 SE +/- 0.01670, N = 7 SE +/- 0.00686, N = 6 SE +/- 0.01244, N = 7 SE +/- 0.00918, N = 9 SE +/- 0.00744, N = 8 SE +/- 0.00498, N = 9 SE +/- 0.01129, N = 9 SE +/- 0.06689, N = 15 SE +/- 0.01113, N = 9 SE +/- 0.00885, N = 9 SE +/- 0.02852, N = 5 SE +/- 0.01335, N = 7 11.96540 9.83106 6.21815 6.36513 5.71426 3.56555 3.70234 3.47096 3.31262 3.19889 2.80142 2.88175 10.90090 5.84607 1. (CXX) g++ options: -std=c++0x -march=znver1 -msse2 -msse3 -mssse3 -msse4.1 -msse4.2 -msse4a -mfma -mbmi2 -mno-avx -mno-avx2 -mno-xop -mno-fma4 -mno-avx512f -mno-avx512vl -mno-avx512pf -mno-avx512er -mno-avx512cd -mno-avx512dq -mno-avx512bw -mno-avx512ifma -mno-avx512vbmi -fstrict-aliasing -O3 -rdynamic -lIlmImf -lIlmThread -lImath -lHalf -lIex -lz -ljpeg -lpthread -ldl
Result Confidence
OpenBenchmarking.org Seconds, Fewer Is Better Tungsten Renderer 0.2.2 Scene: Non-Exponential EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 3 6 9 12 15 Min: 11.89 / Avg: 11.97 / Max: 12.03 Min: 9.79 / Avg: 9.83 / Max: 9.88 Min: 6.17 / Avg: 6.22 / Max: 6.29 Min: 6.35 / Avg: 6.37 / Max: 6.39 Min: 5.67 / Avg: 5.71 / Max: 5.76 Min: 3.5 / Avg: 3.57 / Max: 3.61 Min: 3.66 / Avg: 3.7 / Max: 3.73 Min: 3.44 / Avg: 3.47 / Max: 3.49 Min: 3.27 / Avg: 3.31 / Max: 3.37 Min: 2.55 / Avg: 3.2 / Max: 3.35 Min: 2.77 / Avg: 2.8 / Max: 2.88 Min: 2.85 / Avg: 2.88 / Max: 2.93 Min: 10.84 / Avg: 10.9 / Max: 11 Min: 5.8 / Avg: 5.85 / Max: 5.89 1. (CXX) g++ options: -std=c++0x -march=znver1 -msse2 -msse3 -mssse3 -msse4.1 -msse4.2 -msse4a -mfma -mbmi2 -mno-avx -mno-avx2 -mno-xop -mno-fma4 -mno-avx512f -mno-avx512vl -mno-avx512pf -mno-avx512er -mno-avx512cd -mno-avx512dq -mno-avx512bw -mno-avx512ifma -mno-avx512vbmi -fstrict-aliasing -O3 -rdynamic -lIlmImf -lIlmThread -lImath -lHalf -lIex -lz -ljpeg -lpthread -ldl
Parboil The Parboil Benchmarks from the IMPACT Research Group at University of Illinois are a set of throughput computing applications for looking at computing architecture and compilers. Parboil test-cases support OpenMP, OpenCL, and CUDA multi-processing environments. However, at this time the test profile is just making use of the OpenMP and OpenCL test workloads. Learn more via the OpenBenchmarking.org test page.
Result
OpenBenchmarking.org Seconds, Fewer Is Better Parboil 2.5 Test: OpenMP CUTCP EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 0.7261 1.4522 2.1783 2.9044 3.6305 SE +/- 0.016438, N = 9 SE +/- 0.006375, N = 9 SE +/- 0.005522, N = 11 SE +/- 0.010317, N = 11 SE +/- 0.003909, N = 12 SE +/- 0.006410, N = 12 SE +/- 0.006800, N = 12 SE +/- 0.005531, N = 12 SE +/- 0.001391, N = 13 SE +/- 0.001666, N = 13 SE +/- 0.001641, N = 13 SE +/- 0.002056, N = 13 SE +/- 0.019546, N = 10 SE +/- 0.007208, N = 11 3.227103 2.965136 1.783589 1.873804 1.561688 1.149282 1.256882 1.134961 0.890726 0.902611 0.762238 0.773474 2.796277 1.715944 1. (CXX) g++ options: -lm -lpthread -lgomp -O3 -ffast-math -fopenmp
Result Confidence
OpenBenchmarking.org Seconds, Fewer Is Better Parboil 2.5 Test: OpenMP CUTCP EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 2 4 6 8 10 Min: 3.17 / Avg: 3.23 / Max: 3.29 Min: 2.92 / Avg: 2.97 / Max: 2.99 Min: 1.76 / Avg: 1.78 / Max: 1.82 Min: 1.83 / Avg: 1.87 / Max: 1.93 Min: 1.54 / Avg: 1.56 / Max: 1.59 Min: 1.12 / Avg: 1.15 / Max: 1.18 Min: 1.22 / Avg: 1.26 / Max: 1.3 Min: 1.11 / Avg: 1.13 / Max: 1.17 Min: 0.88 / Avg: 0.89 / Max: 0.9 Min: 0.89 / Avg: 0.9 / Max: 0.91 Min: 0.75 / Avg: 0.76 / Max: 0.77 Min: 0.76 / Avg: 0.77 / Max: 0.79 Min: 2.71 / Avg: 2.8 / Max: 2.88 Min: 1.66 / Avg: 1.72 / Max: 1.74 1. (CXX) g++ options: -lm -lpthread -lgomp -O3 -ffast-math -fopenmp
oneDNN This is a test of the Intel oneDNN as an Intel-optimized library for Deep Neural Networks and making use of its built-in benchdnn functionality. The result is the total perf time reported. Intel oneDNN was formerly known as DNNL (Deep Neural Network Library) and MKL-DNN before being rebranded as part of the Intel oneAPI initiative. Learn more via the OpenBenchmarking.org test page.
Result
OpenBenchmarking.org ms, Fewer Is Better oneDNN 2.0 Harness: Matrix Multiply Batch Shapes Transformer - Data Type: f32 - Engine: CPU EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 0.4541 0.9082 1.3623 1.8164 2.2705 SE +/- 0.005714, N = 4 SE +/- 0.000447, N = 4 SE +/- 0.000258, N = 4 SE +/- 0.000863, N = 4 SE +/- 0.000660, N = 4 SE +/- 0.000902, N = 4 SE +/- 0.005528, N = 6 SE +/- 0.000738, N = 4 SE +/- 0.004962, N = 15 SE +/- 0.003528, N = 4 SE +/- 0.005359, N = 5 SE +/- 0.002887, N = 4 SE +/- 0.001580, N = 4 SE +/- 0.001140, N = 4 2.018380 1.093440 0.875749 0.802272 0.592308 0.537636 0.553444 0.500521 0.533961 0.484219 0.517023 0.587443 1.160170 0.660419 MIN: 1.95 MIN: 0.96 MIN: 0.74 MIN: 0.72 MIN: 0.56 MIN: 0.51 MIN: 0.49 MIN: 0.48 MIN: 0.49 MIN: 0.46 MIN: 0.47 MIN: 0.54 MIN: 1.13 MIN: 0.62 1. (CXX) g++ options: -O3 -std=c++11 -fopenmp -msse4.1 -fPIC -pie -lpthread
Result Confidence
OpenBenchmarking.org ms, Fewer Is Better oneDNN 2.0 Harness: Matrix Multiply Batch Shapes Transformer - Data Type: f32 - Engine: CPU EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 2 4 6 8 10 Min: 2 / Avg: 2.02 / Max: 2.03 Min: 1.09 / Avg: 1.09 / Max: 1.09 Min: 0.88 / Avg: 0.88 / Max: 0.88 Min: 0.8 / Avg: 0.8 / Max: 0.8 Min: 0.59 / Avg: 0.59 / Max: 0.59 Min: 0.54 / Avg: 0.54 / Max: 0.54 Min: 0.54 / Avg: 0.55 / Max: 0.58 Min: 0.5 / Avg: 0.5 / Max: 0.5 Min: 0.51 / Avg: 0.53 / Max: 0.57 Min: 0.48 / Avg: 0.48 / Max: 0.49 Min: 0.5 / Avg: 0.52 / Max: 0.53 Min: 0.58 / Avg: 0.59 / Max: 0.6 Min: 1.16 / Avg: 1.16 / Max: 1.16 Min: 0.66 / Avg: 0.66 / Max: 0.66 1. (CXX) g++ options: -O3 -std=c++11 -fopenmp -msse4.1 -fPIC -pie -lpthread
LAMMPS Molecular Dynamics Simulator LAMMPS is a classical molecular dynamics code, and an acronym for Large-scale Atomic/Molecular Massively Parallel Simulator. Learn more via the OpenBenchmarking.org test page.
Result
OpenBenchmarking.org ns/day, More Is Better LAMMPS Molecular Dynamics Simulator 29Oct2020 Model: Rhodopsin Protein EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 5 10 15 20 25 SE +/- 0.002, N = 8 SE +/- 0.008, N = 9 SE +/- 0.026, N = 10 SE +/- 0.024, N = 10 SE +/- 0.089, N = 15 SE +/- 0.286, N = 15 SE +/- 0.178, N = 15 SE +/- 0.252, N = 15 SE +/- 0.286, N = 15 SE +/- 0.291, N = 15 SE +/- 0.301, N = 15 SE +/- 0.257, N = 15 SE +/- 0.003, N = 9 SE +/- 0.028, N = 11 5.237 7.582 9.685 10.374 14.038 15.685 16.265 16.564 18.506 19.328 21.763 19.997 6.470 11.521 1. (CXX) g++ options: -O3 -pthread -lm
ns/day Per Watt
OpenBenchmarking.org ns/day Per Watt, More Is Better LAMMPS Molecular Dynamics Simulator 29Oct2020 Model: Rhodopsin Protein EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 0.0653 0.1306 0.1959 0.2612 0.3265 0.11 0.15 0.18 0.18 0.23 0.25 0.22 0.26 0.26 0.25 0.29 0.25 0.10 0.14
Result Confidence
OpenBenchmarking.org ns/day, More Is Better LAMMPS Molecular Dynamics Simulator 29Oct2020 Model: Rhodopsin Protein EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 5 10 15 20 25 Min: 5.23 / Avg: 5.24 / Max: 5.25 Min: 7.55 / Avg: 7.58 / Max: 7.61 Min: 9.59 / Avg: 9.69 / Max: 9.82 Min: 10.19 / Avg: 10.37 / Max: 10.46 Min: 13.39 / Avg: 14.04 / Max: 14.46 Min: 13.34 / Avg: 15.69 / Max: 17.35 Min: 14.97 / Avg: 16.27 / Max: 17.08 Min: 14.32 / Avg: 16.56 / Max: 18.32 Min: 17.37 / Avg: 18.51 / Max: 20.7 Min: 18.26 / Avg: 19.33 / Max: 21.71 Min: 20.67 / Avg: 21.76 / Max: 24.47 Min: 19.07 / Avg: 20 / Max: 22.21 Min: 6.45 / Avg: 6.47 / Max: 6.49 Min: 11.4 / Avg: 11.52 / Max: 11.65 1. (CXX) g++ options: -O3 -pthread -lm
Stress-NG Stress-NG is a Linux stress tool developed by Colin King of Canonical. Learn more via the OpenBenchmarking.org test page.
Result
OpenBenchmarking.org Bogo Ops/s, More Is Better Stress-NG 0.11.07 Test: Socket Activity EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 4K 8K 12K 16K 20K SE +/- 24.34, N = 3 SE +/- 8.24, N = 3 SE +/- 16.90, N = 3 SE +/- 6.53, N = 3 SE +/- 16.45, N = 3 SE +/- 30.09, N = 3 SE +/- 125.44, N = 9 SE +/- 32.93, N = 3 SE +/- 24.65, N = 3 SE +/- 64.33, N = 3 SE +/- 57.10, N = 3 SE +/- 13.57, N = 3 SE +/- 17.97, N = 3 4965.96 7332.82 9134.72 9499.33 13570.83 16396.57 15568.24 17266.21 18192.32 19990.75 19577.03 5638.53 8415.19 1. (CC) gcc options: -O2 -std=gnu99 -lm -laio -lbsd -lcrypt -lrt -lz -ldl -lpthread -lc
Bogo Ops/s Per Watt
OpenBenchmarking.org Bogo Ops/s Per Watt, More Is Better Stress-NG 0.11.07 Test: Socket Activity EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 30 60 90 120 150 67.53 75.36 93.40 79.41 92.04 114.89 98.20 104.78 110.23 115.18 109.94 51.33 42.43
Result Confidence
OpenBenchmarking.org Bogo Ops/s, More Is Better Stress-NG 0.11.07 Test: Socket Activity EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 3K 6K 9K 12K 15K Min: 4920.56 / Avg: 4965.96 / Max: 5003.89 Min: 7316.76 / Avg: 7332.82 / Max: 7344.03 Min: 9104 / Avg: 9134.72 / Max: 9162.29 Min: 9488.78 / Avg: 9499.33 / Max: 9511.28 Min: 13539.78 / Avg: 13570.83 / Max: 13595.76 Min: 16363.28 / Avg: 16396.57 / Max: 16456.63 Min: 14571.02 / Avg: 15568.24 / Max: 15743.07 Min: 17206.64 / Avg: 17266.21 / Max: 17320.33 Min: 18145.03 / Avg: 18192.32 / Max: 18228.03 Min: 19911.11 / Avg: 19990.75 / Max: 20118.07 Min: 19482.9 / Avg: 19577.03 / Max: 19680.11 Min: 5624.62 / Avg: 5638.53 / Max: 5665.66 Min: 8394.92 / Avg: 8415.19 / Max: 8451.03 1. (CC) gcc options: -O2 -std=gnu99 -lm -laio -lbsd -lcrypt -lrt -lz -ldl -lpthread -lc
Zstd Compression This test measures the time needed to compress a sample file (an Ubuntu ISO) using Zstd compression. Learn more via the OpenBenchmarking.org test page.
Result
OpenBenchmarking.org MB/s, More Is Better Zstd Compression 1.4.5 Compression Level: 19 EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 30 60 90 120 150 SE +/- 0.06, N = 3 SE +/- 0.06, N = 3 SE +/- 0.12, N = 3 SE +/- 0.03, N = 3 SE +/- 0.09, N = 3 SE +/- 0.09, N = 3 SE +/- 0.00, N = 3 SE +/- 0.15, N = 3 SE +/- 0.15, N = 3 SE +/- 0.12, N = 3 SE +/- 0.55, N = 3 SE +/- 1.22, N = 3 SE +/- 0.03, N = 3 SE +/- 0.79, N = 3 37.3 55.2 66.4 73.8 96.9 114.3 122.7 114.4 125.7 130.1 149.6 147.5 47.0 76.1 1. (CC) gcc options: -O3 -pthread -lz -llzma
MB/s Per Watt
OpenBenchmarking.org MB/s Per Watt, More Is Better Zstd Compression 1.4.5 Compression Level: 19 EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 0.3218 0.6436 0.9654 1.2872 1.609 0.66 0.89 1.01 1.00 1.20 1.38 1.17 1.43 1.33 1.24 1.38 1.31 0.63 0.69
Result Confidence
OpenBenchmarking.org MB/s, More Is Better Zstd Compression 1.4.5 Compression Level: 19 EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 30 60 90 120 150 Min: 37.2 / Avg: 37.3 / Max: 37.4 Min: 55.1 / Avg: 55.2 / Max: 55.3 Min: 66.2 / Avg: 66.4 / Max: 66.6 Min: 73.8 / Avg: 73.83 / Max: 73.9 Min: 96.8 / Avg: 96.93 / Max: 97.1 Min: 114.2 / Avg: 114.33 / Max: 114.5 Min: 122.7 / Avg: 122.7 / Max: 122.7 Min: 114.2 / Avg: 114.4 / Max: 114.7 Min: 125.4 / Avg: 125.67 / Max: 125.9 Min: 129.9 / Avg: 130.1 / Max: 130.3 Min: 148.7 / Avg: 149.6 / Max: 150.6 Min: 145.1 / Avg: 147.53 / Max: 148.8 Min: 47 / Avg: 47.03 / Max: 47.1 Min: 74.9 / Avg: 76.13 / Max: 77.6 1. (CC) gcc options: -O3 -pthread -lz -llzma
NWChem NWChem is an open-source high performance computational chemistry package. Per NWChem's documentation, "NWChem aims to provide its users with computational chemistry tools that are scalable both in their ability to treat large scientific computational chemistry problems efficiently, and in their use of available parallel computing resources from high-performance parallel supercomputers to conventional workstation clusters." Learn more via the OpenBenchmarking.org test page.
OpenBenchmarking.org Seconds, Fewer Is Better NWChem 7.0.2 Input: C240 Buckyball EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7662 EPYC 7702 EPYC 7F52 2K 4K 6K 8K 10K 8844.1 7056.0 6676.4 4709.5 3678.8 3653.6 3653.9 2716.7 2220.7 2247.0 5684.6 1. (F9X) gfortran options: -lnwctask -lccsd -lmcscf -lselci -lmp2 -lmoints -lstepper -ldriver -loptim -lnwdft -lgradients -lcphf -lesp -lddscf -ldangchang -lguess -lhessian -lvib -lnwcutil -lrimp2 -lproperty -lsolvation -lnwints -lprepar -lnwmd -lnwpw -lofpw -lpaw -lpspw -lband -lnwpwlib -lcafe -lspace -lanalyze -lqhop -lpfft -ldplot -ldrdy -lvscf -lqmmm -lqmd -letrans -ltce -lbq -lmm -lcons -lperfm -ldntmc -lccca -ldimqm -lga -larmci -lpeigs -l64to32 -lopenblas -lpthread -lrt -llapack -lnwcblas -lmpi_usempif08 -lmpi_mpifh -lmpi -lcomex -lm -m64 -ffast-math -std=legacy -fdefault-integer-8 -finline-functions -O2
LeelaChessZero LeelaChessZero (lc0 / lczero) is a chess engine automated vian neural networks. This test profile can be used for OpenCL, CUDA + cuDNN, and BLAS (CPU-based) benchmarking. Learn more via the OpenBenchmarking.org test page.
Result
OpenBenchmarking.org Nodes Per Second, More Is Better LeelaChessZero 0.26 Backend: Eigen EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 600 1200 1800 2400 3000 SE +/- 8.88, N = 3 SE +/- 11.79, N = 9 SE +/- 11.49, N = 9 SE +/- 12.27, N = 9 SE +/- 5.90, N = 3 SE +/- 14.82, N = 9 SE +/- 20.90, N = 3 SE +/- 9.84, N = 3 SE +/- 31.31, N = 9 SE +/- 37.70, N = 9 SE +/- 29.49, N = 9 SE +/- 26.03, N = 3 SE +/- 16.37, N = 9 SE +/- 17.43, N = 5 681 925 1051 1233 1439 1539 1769 1617 1927 2311 2408 2686 1104 1699 1. (CXX) g++ options: -flto -pthread
Nodes Per Second Per Watt
OpenBenchmarking.org Nodes Per Second Per Watt, More Is Better LeelaChessZero 0.26 Backend: Eigen EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 4 8 12 16 20 8.61 10.05 11.06 10.97 10.56 11.09 11.26 10.30 12.55 13.41 14.75 15.06 8.98 8.39
Result Confidence
OpenBenchmarking.org Nodes Per Second, More Is Better LeelaChessZero 0.26 Backend: Eigen EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 500 1000 1500 2000 2500 Min: 663 / Avg: 680.67 / Max: 691 Min: 870 / Avg: 924.56 / Max: 993 Min: 1008 / Avg: 1051.22 / Max: 1107 Min: 1194 / Avg: 1232.78 / Max: 1292 Min: 1432 / Avg: 1439.33 / Max: 1451 Min: 1454 / Avg: 1538.78 / Max: 1593 Min: 1729 / Avg: 1769.33 / Max: 1799 Min: 1597 / Avg: 1616.67 / Max: 1627 Min: 1773 / Avg: 1926.89 / Max: 2050 Min: 2112 / Avg: 2311.33 / Max: 2527 Min: 2310 / Avg: 2408 / Max: 2551 Min: 2634 / Avg: 2685.67 / Max: 2717 Min: 1024 / Avg: 1103.67 / Max: 1176 Min: 1639 / Avg: 1699.2 / Max: 1747 1. (CXX) g++ options: -flto -pthread
Appleseed Appleseed is an open-source production renderer focused on physically-based global illumination rendering engine primarily designed for animation and visual effects. Learn more via the OpenBenchmarking.org test page.
OpenBenchmarking.org Seconds, Fewer Is Better Appleseed 2.0 Beta Scene: Disney Material EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 60 120 180 240 300 265.54 195.08 151.86 149.34 105.69 87.51 89.01 81.83 73.33 70.49 67.33 67.74 225.09 118.48
Basis Universal Basis Universal is a GPU texture codoec. This test times how long it takes to convert sRGB PNGs into Basis Univeral assets with various settings. Learn more via the OpenBenchmarking.org test page.
Result
OpenBenchmarking.org Seconds, Fewer Is Better Basis Universal 1.12 Settings: UASTC Level 3 EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 16 32 48 64 80 SE +/- 0.01, N = 3 SE +/- 0.01, N = 3 SE +/- 0.03, N = 3 SE +/- 0.00, N = 3 SE +/- 0.00, N = 3 SE +/- 0.01, N = 3 SE +/- 0.01, N = 3 SE +/- 0.01, N = 3 SE +/- 0.01, N = 3 SE +/- 0.00, N = 3 SE +/- 0.00, N = 3 SE +/- 0.01, N = 3 SE +/- 0.01, N = 3 73.43 51.77 41.24 39.75 29.16 25.28 25.88 23.97 20.80 18.66 18.87 60.40 33.80 1. (CXX) g++ options: -std=c++11 -fvisibility=hidden -fPIC -fno-strict-aliasing -O3 -rdynamic -lm -lpthread
Result Confidence
OpenBenchmarking.org Seconds, Fewer Is Better Basis Universal 1.12 Settings: UASTC Level 3 EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 14 28 42 56 70 Min: 73.43 / Avg: 73.43 / Max: 73.44 Min: 51.75 / Avg: 51.77 / Max: 51.78 Min: 41.2 / Avg: 41.24 / Max: 41.3 Min: 39.75 / Avg: 39.75 / Max: 39.76 Min: 29.15 / Avg: 29.16 / Max: 29.17 Min: 25.27 / Avg: 25.28 / Max: 25.31 Min: 25.87 / Avg: 25.88 / Max: 25.91 Min: 23.96 / Avg: 23.97 / Max: 23.98 Min: 20.77 / Avg: 20.8 / Max: 20.82 Min: 18.65 / Avg: 18.66 / Max: 18.66 Min: 18.86 / Avg: 18.87 / Max: 18.88 Min: 60.39 / Avg: 60.4 / Max: 60.41 Min: 33.79 / Avg: 33.8 / Max: 33.81 1. (CXX) g++ options: -std=c++11 -fvisibility=hidden -fPIC -fno-strict-aliasing -O3 -rdynamic -lm -lpthread
NCNN NCNN is a high performance neural network inference framework optimized for mobile and other platforms developed by Tencent. Learn more via the OpenBenchmarking.org test page.
Result
OpenBenchmarking.org ms, Fewer Is Better NCNN 20201218 Target: CPU - Model: regnety_400m EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 30 60 90 120 150 SE +/- 0.30, N = 3 SE +/- 0.04, N = 3 SE +/- 0.34, N = 3 SE +/- 0.51, N = 3 SE +/- 0.47, N = 3 SE +/- 0.89, N = 3 SE +/- 0.60, N = 11 SE +/- 1.20, N = 3 SE +/- 2.91, N = 3 SE +/- 1.44, N = 12 SE +/- 1.58, N = 9 SE +/- 0.92, N = 9 SE +/- 0.20, N = 3 SE +/- 0.05, N = 3 31.16 34.24 40.27 41.35 51.09 60.77 66.90 61.29 91.90 93.95 115.48 119.33 32.16 46.30 MIN: 30.33 / MAX: 33.9 MIN: 33.82 / MAX: 47.56 MIN: 38.44 / MAX: 167.34 MIN: 40.02 / MAX: 44.02 MIN: 49.4 / MAX: 53.35 MIN: 58.26 / MAX: 140.56 MIN: 63.42 / MAX: 212.32 MIN: 59.46 / MAX: 72.41 MIN: 86.84 / MAX: 102.42 MIN: 86.48 / MAX: 1086.99 MIN: 104.38 / MAX: 272.84 MIN: 110.56 / MAX: 268.86 MIN: 31.34 / MAX: 32.97 MIN: 45.45 / MAX: 121.75 1. (CXX) g++ options: -O3 -rdynamic -lgomp -lpthread
Result Confidence
OpenBenchmarking.org ms, Fewer Is Better NCNN 20201218 Target: CPU - Model: regnety_400m EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 20 40 60 80 100 Min: 30.61 / Avg: 31.16 / Max: 31.62 Min: 34.18 / Avg: 34.24 / Max: 34.32 Min: 39.89 / Avg: 40.27 / Max: 40.94 Min: 40.41 / Avg: 41.35 / Max: 42.16 Min: 50.14 / Avg: 51.09 / Max: 51.59 Min: 59.06 / Avg: 60.77 / Max: 62.06 Min: 64.25 / Avg: 66.9 / Max: 69.82 Min: 60 / Avg: 61.29 / Max: 63.69 Min: 88.94 / Avg: 91.9 / Max: 97.72 Min: 87.38 / Avg: 93.95 / Max: 100.86 Min: 105.72 / Avg: 115.48 / Max: 120.7 Min: 113.13 / Avg: 119.33 / Max: 122.46 Min: 31.76 / Avg: 32.16 / Max: 32.37 Min: 46.2 / Avg: 46.3 / Max: 46.36 1. (CXX) g++ options: -O3 -rdynamic -lgomp -lpthread
SVT-AV1 This is a test of the Intel Open Visual Cloud Scalable Video Technology SVT-AV1 CPU-based multi-threaded video encoder for the AV1 video format with a sample 1080p YUV video file. Learn more via the OpenBenchmarking.org test page.
Result
OpenBenchmarking.org Frames Per Second, More Is Better SVT-AV1 0.8 Encoder Mode: Enc Mode 8 - Input: 1080p EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 20 40 60 80 100 SE +/- 0.07, N = 4 SE +/- 0.11, N = 4 SE +/- 0.09, N = 5 SE +/- 0.17, N = 5 SE +/- 0.03, N = 6 SE +/- 0.25, N = 6 SE +/- 0.17, N = 6 SE +/- 0.18, N = 6 SE +/- 0.20, N = 5 SE +/- 0.16, N = 5 SE +/- 0.32, N = 5 SE +/- 0.27, N = 5 SE +/- 0.03, N = 4 SE +/- 0.21, N = 5 21.76 30.38 35.38 37.04 54.87 57.32 56.53 59.94 62.40 63.21 83.40 79.82 26.13 42.84 1. (CXX) g++ options: -O3 -fcommon -fPIE -fPIC -pie
Frames Per Second Per Watt
OpenBenchmarking.org Frames Per Second Per Watt, More Is Better SVT-AV1 0.8 Encoder Mode: Enc Mode 8 - Input: 1080p EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 0.2003 0.4006 0.6009 0.8012 1.0015 0.33 0.41 0.49 0.44 0.61 0.68 0.56 0.68 0.69 0.62 0.89 0.83 0.28 0.32
Result Confidence
OpenBenchmarking.org Frames Per Second, More Is Better SVT-AV1 0.8 Encoder Mode: Enc Mode 8 - Input: 1080p EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 16 32 48 64 80 Min: 21.59 / Avg: 21.76 / Max: 21.91 Min: 30.14 / Avg: 30.38 / Max: 30.6 Min: 35.07 / Avg: 35.38 / Max: 35.57 Min: 36.48 / Avg: 37.04 / Max: 37.5 Min: 54.76 / Avg: 54.87 / Max: 54.97 Min: 56.32 / Avg: 57.32 / Max: 57.97 Min: 56.08 / Avg: 56.53 / Max: 57.07 Min: 59.31 / Avg: 59.94 / Max: 60.53 Min: 61.9 / Avg: 62.4 / Max: 62.94 Min: 62.71 / Avg: 63.21 / Max: 63.66 Min: 82.2 / Avg: 83.4 / Max: 84.06 Min: 79.13 / Avg: 79.82 / Max: 80.5 Min: 26.07 / Avg: 26.13 / Max: 26.22 Min: 42.28 / Avg: 42.84 / Max: 43.39 1. (CXX) g++ options: -O3 -fcommon -fPIE -fPIC -pie
Parboil The Parboil Benchmarks from the IMPACT Research Group at University of Illinois are a set of throughput computing applications for looking at computing architecture and compilers. Parboil test-cases support OpenMP, OpenCL, and CUDA multi-processing environments. However, at this time the test profile is just making use of the OpenMP and OpenCL test workloads. Learn more via the OpenBenchmarking.org test page.
Result
OpenBenchmarking.org Seconds, Fewer Is Better Parboil 2.5 Test: OpenMP MRI Gridding EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 30 60 90 120 150 SE +/- 0.88, N = 3 SE +/- 0.24, N = 3 SE +/- 0.21, N = 3 SE +/- 0.11, N = 3 SE +/- 0.03, N = 3 SE +/- 0.22, N = 3 SE +/- 0.28, N = 3 SE +/- 0.29, N = 3 SE +/- 0.29, N = 3 SE +/- 0.83, N = 3 SE +/- 0.63, N = 3 SE +/- 0.77, N = 3 SE +/- 0.15, N = 3 SE +/- 0.24, N = 3 75.43 51.65 62.29 95.77 65.42 76.19 128.29 75.44 93.48 95.40 109.30 110.47 34.04 49.01 1. (CXX) g++ options: -lm -lpthread -lgomp -O3 -ffast-math -fopenmp
Result Confidence
OpenBenchmarking.org Seconds, Fewer Is Better Parboil 2.5 Test: OpenMP MRI Gridding EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 20 40 60 80 100 Min: 73.67 / Avg: 75.43 / Max: 76.37 Min: 51.36 / Avg: 51.65 / Max: 52.13 Min: 61.91 / Avg: 62.29 / Max: 62.65 Min: 95.59 / Avg: 95.77 / Max: 95.96 Min: 65.38 / Avg: 65.42 / Max: 65.48 Min: 75.76 / Avg: 76.19 / Max: 76.51 Min: 127.98 / Avg: 128.29 / Max: 128.85 Min: 75.01 / Avg: 75.44 / Max: 76 Min: 93.04 / Avg: 93.48 / Max: 94.02 Min: 93.75 / Avg: 95.4 / Max: 96.31 Min: 108.54 / Avg: 109.3 / Max: 110.55 Min: 109.25 / Avg: 110.47 / Max: 111.89 Min: 33.82 / Avg: 34.04 / Max: 34.32 Min: 48.58 / Avg: 49.01 / Max: 49.42 1. (CXX) g++ options: -lm -lpthread -lgomp -O3 -ffast-math -fopenmp
oneDNN This is a test of the Intel oneDNN as an Intel-optimized library for Deep Neural Networks and making use of its built-in benchdnn functionality. The result is the total perf time reported. Intel oneDNN was formerly known as DNNL (Deep Neural Network Library) and MKL-DNN before being rebranded as part of the Intel oneAPI initiative. Learn more via the OpenBenchmarking.org test page.
Result
OpenBenchmarking.org ms, Fewer Is Better oneDNN 2.0 Harness: IP Shapes 3D - Data Type: u8s8f32 - Engine: CPU EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 0.4004 0.8008 1.2012 1.6016 2.002 SE +/- 0.002555, N = 5 SE +/- 0.003339, N = 5 SE +/- 0.003097, N = 5 SE +/- 0.001293, N = 5 SE +/- 0.003852, N = 5 SE +/- 0.001432, N = 5 SE +/- 0.002578, N = 5 SE +/- 0.003216, N = 5 SE +/- 0.005510, N = 5 SE +/- 0.002582, N = 5 SE +/- 0.000841, N = 5 SE +/- 0.001522, N = 5 SE +/- 0.006135, N = 5 SE +/- 0.002832, N = 5 1.779470 1.038950 0.816826 0.601288 0.711317 0.990316 0.641197 1.000426 1.132370 0.813280 1.146010 1.162730 0.798217 0.489983 MIN: 1.6 MIN: 0.95 MIN: 0.74 MIN: 0.56 MIN: 0.66 MIN: 0.95 MIN: 0.58 MIN: 0.94 MIN: 1.07 MIN: 0.76 MIN: 1.09 MIN: 1.1 MIN: 0.75 MIN: 0.45 1. (CXX) g++ options: -O3 -std=c++11 -fopenmp -msse4.1 -fPIC -pie -lpthread
Result Confidence
OpenBenchmarking.org ms, Fewer Is Better oneDNN 2.0 Harness: IP Shapes 3D - Data Type: u8s8f32 - Engine: CPU EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 2 4 6 8 10 Min: 1.78 / Avg: 1.78 / Max: 1.79 Min: 1.03 / Avg: 1.04 / Max: 1.05 Min: 0.81 / Avg: 0.82 / Max: 0.83 Min: 0.6 / Avg: 0.6 / Max: 0.6 Min: 0.7 / Avg: 0.71 / Max: 0.72 Min: 0.99 / Avg: 0.99 / Max: 1 Min: 0.63 / Avg: 0.64 / Max: 0.65 Min: 0.99 / Avg: 1 / Max: 1.01 Min: 1.11 / Avg: 1.13 / Max: 1.14 Min: 0.81 / Avg: 0.81 / Max: 0.82 Min: 1.14 / Avg: 1.15 / Max: 1.15 Min: 1.16 / Avg: 1.16 / Max: 1.17 Min: 0.79 / Avg: 0.8 / Max: 0.82 Min: 0.48 / Avg: 0.49 / Max: 0.5 1. (CXX) g++ options: -O3 -std=c++11 -fopenmp -msse4.1 -fPIC -pie -lpthread
Timed Linux Kernel Compilation This test times how long it takes to build the Linux kernel in a default configuration. Learn more via the OpenBenchmarking.org test page.
Result
OpenBenchmarking.org Seconds, Fewer Is Better Timed Linux Kernel Compilation 5.4 Time To Compile EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 20 40 60 80 100 SE +/- 0.42, N = 3 SE +/- 0.59, N = 3 SE +/- 0.75, N = 3 SE +/- 0.65, N = 4 SE +/- 0.47, N = 4 SE +/- 0.42, N = 4 SE +/- 0.42, N = 4 SE +/- 0.41, N = 4 SE +/- 0.30, N = 6 SE +/- 0.30, N = 6 SE +/- 0.28, N = 6 SE +/- 0.26, N = 7 SE +/- 0.46, N = 3 SE +/- 0.43, N = 3 101.09 69.61 57.91 53.40 41.50 36.39 36.85 34.55 30.21 30.08 27.98 28.13 79.66 46.91
Result Confidence
OpenBenchmarking.org Seconds, Fewer Is Better Timed Linux Kernel Compilation 5.4 Time To Compile EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 20 40 60 80 100 Min: 100.61 / Avg: 101.09 / Max: 101.92 Min: 68.52 / Avg: 69.61 / Max: 70.53 Min: 56.64 / Avg: 57.91 / Max: 59.25 Min: 52.39 / Avg: 53.4 / Max: 55.3 Min: 40.71 / Avg: 41.5 / Max: 42.85 Min: 35.93 / Avg: 36.39 / Max: 37.65 Min: 36.38 / Avg: 36.85 / Max: 38.1 Min: 34.07 / Avg: 34.55 / Max: 35.78 Min: 29.87 / Avg: 30.21 / Max: 31.71 Min: 29.67 / Avg: 30.08 / Max: 31.58 Min: 27.59 / Avg: 27.98 / Max: 29.37 Min: 27.79 / Avg: 28.13 / Max: 29.66 Min: 79.06 / Avg: 79.66 / Max: 80.57 Min: 46.21 / Avg: 46.91 / Max: 47.7
LeelaChessZero LeelaChessZero (lc0 / lczero) is a chess engine automated vian neural networks. This test profile can be used for OpenCL, CUDA + cuDNN, and BLAS (CPU-based) benchmarking. Learn more via the OpenBenchmarking.org test page.
Result
OpenBenchmarking.org Nodes Per Second, More Is Better LeelaChessZero 0.26 Backend: BLAS EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 600 1200 1800 2400 3000 SE +/- 4.36, N = 3 SE +/- 7.54, N = 3 SE +/- 3.71, N = 3 SE +/- 13.76, N = 9 SE +/- 20.26, N = 3 SE +/- 23.71, N = 9 SE +/- 22.27, N = 9 SE +/- 20.09, N = 3 SE +/- 27.18, N = 3 SE +/- 26.91, N = 3 SE +/- 41.44, N = 9 SE +/- 14.38, N = 3 SE +/- 22.57, N = 9 SE +/- 31.35, N = 9 747 946 1042 1253 1521 1559 1735 1666 1969 2203 2376 2699 1052 1758 1. (CXX) g++ options: -flto -pthread
Nodes Per Second Per Watt
OpenBenchmarking.org Nodes Per Second Per Watt, More Is Better LeelaChessZero 0.26 Backend: BLAS EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 4 8 12 16 20 9.44 10.33 11.09 11.29 11.26 11.37 11.33 10.83 12.82 12.86 14.58 14.95 8.98 8.60
Result Confidence
OpenBenchmarking.org Nodes Per Second, More Is Better LeelaChessZero 0.26 Backend: BLAS EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 500 1000 1500 2000 2500 Min: 739 / Avg: 747 / Max: 754 Min: 931 / Avg: 945.67 / Max: 956 Min: 1035 / Avg: 1042.33 / Max: 1047 Min: 1190 / Avg: 1253.33 / Max: 1313 Min: 1492 / Avg: 1521 / Max: 1560 Min: 1445 / Avg: 1559.33 / Max: 1649 Min: 1624 / Avg: 1734.78 / Max: 1815 Min: 1626 / Avg: 1665.67 / Max: 1691 Min: 1916 / Avg: 1969 / Max: 2006 Min: 2155 / Avg: 2203.33 / Max: 2248 Min: 2146 / Avg: 2376 / Max: 2558 Min: 2683 / Avg: 2699.33 / Max: 2728 Min: 958 / Avg: 1052.44 / Max: 1142 Min: 1652 / Avg: 1758 / Max: 1943 1. (CXX) g++ options: -flto -pthread
oneDNN This is a test of the Intel oneDNN as an Intel-optimized library for Deep Neural Networks and making use of its built-in benchdnn functionality. The result is the total perf time reported. Intel oneDNN was formerly known as DNNL (Deep Neural Network Library) and MKL-DNN before being rebranded as part of the Intel oneAPI initiative. Learn more via the OpenBenchmarking.org test page.
Result
OpenBenchmarking.org ms, Fewer Is Better oneDNN 2.0 Harness: Recurrent Neural Network Training - Data Type: u8s8f32 - Engine: CPU EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 900 1800 2700 3600 4500 SE +/- 1.97, N = 3 SE +/- 3.17, N = 3 SE +/- 2.25, N = 3 SE +/- 0.38, N = 3 SE +/- 1.08, N = 3 SE +/- 2.18, N = 3 SE +/- 5.23, N = 3 SE +/- 2.43, N = 3 SE +/- 1.92, N = 3 SE +/- 2.03, N = 3 SE +/- 11.35, N = 3 SE +/- 3.86, N = 3 SE +/- 0.89, N = 3 SE +/- 6.65, N = 3 4347.66 3057.08 2834.09 2410.23 1674.66 2743.71 2230.35 2721.87 1352.62 1210.04 2230.18 2296.53 3345.67 2013.24 MIN: 4308.62 MIN: 3044.36 MIN: 2799.34 MIN: 2395.31 MIN: 1660.31 MIN: 2727.14 MIN: 2212.66 MIN: 2708.11 MIN: 1333.53 MIN: 1190.59 MIN: 2194.78 MIN: 2270.01 MIN: 3327 MIN: 1992.69 1. (CXX) g++ options: -O3 -std=c++11 -fopenmp -msse4.1 -fPIC -pie -lpthread
Result Confidence
OpenBenchmarking.org ms, Fewer Is Better oneDNN 2.0 Harness: Recurrent Neural Network Training - Data Type: u8s8f32 - Engine: CPU EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 800 1600 2400 3200 4000 Min: 4343.96 / Avg: 4347.66 / Max: 4350.69 Min: 3051.79 / Avg: 3057.08 / Max: 3062.75 Min: 2829.71 / Avg: 2834.09 / Max: 2837.17 Min: 2409.5 / Avg: 2410.23 / Max: 2410.77 Min: 1672.87 / Avg: 1674.66 / Max: 1676.6 Min: 2741.09 / Avg: 2743.71 / Max: 2748.05 Min: 2221.2 / Avg: 2230.35 / Max: 2239.31 Min: 2718.51 / Avg: 2721.87 / Max: 2726.6 Min: 1350.2 / Avg: 1352.62 / Max: 1356.42 Min: 1206.71 / Avg: 1210.04 / Max: 1213.71 Min: 2212.51 / Avg: 2230.18 / Max: 2251.36 Min: 2288.81 / Avg: 2296.53 / Max: 2300.61 Min: 3344.19 / Avg: 3345.67 / Max: 3347.26 Min: 2003.33 / Avg: 2013.24 / Max: 2025.88 1. (CXX) g++ options: -O3 -std=c++11 -fopenmp -msse4.1 -fPIC -pie -lpthread
Result
OpenBenchmarking.org ms, Fewer Is Better oneDNN 2.0 Harness: Recurrent Neural Network Training - Data Type: bf16bf16bf16 - Engine: CPU EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 900 1800 2700 3600 4500 SE +/- 4.35, N = 3 SE +/- 0.81, N = 3 SE +/- 1.77, N = 3 SE +/- 3.71, N = 3 SE +/- 0.94, N = 3 SE +/- 4.79, N = 3 SE +/- 5.96, N = 3 SE +/- 2.51, N = 3 SE +/- 1.28, N = 3 SE +/- 3.66, N = 3 SE +/- 0.34, N = 3 SE +/- 9.75, N = 3 SE +/- 2.55, N = 3 SE +/- 0.63, N = 3 4348.88 3059.19 2835.35 2407.93 1673.31 2740.52 2221.37 2716.54 1350.13 1211.54 2203.16 2314.36 3348.06 1997.39 MIN: 4311.94 MIN: 3051.11 MIN: 2800.15 MIN: 2392.45 MIN: 1660.31 MIN: 2722.51 MIN: 2198.48 MIN: 2705.25 MIN: 1333.75 MIN: 1187.15 MIN: 2183.71 MIN: 2276.78 MIN: 3331.21 MIN: 1989.1 1. (CXX) g++ options: -O3 -std=c++11 -fopenmp -msse4.1 -fPIC -pie -lpthread
Result Confidence
OpenBenchmarking.org ms, Fewer Is Better oneDNN 2.0 Harness: Recurrent Neural Network Training - Data Type: bf16bf16bf16 - Engine: CPU EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 800 1600 2400 3200 4000 Min: 4341.28 / Avg: 4348.88 / Max: 4356.33 Min: 3057.83 / Avg: 3059.19 / Max: 3060.62 Min: 2831.82 / Avg: 2835.35 / Max: 2837.39 Min: 2401.58 / Avg: 2407.93 / Max: 2414.43 Min: 1671.47 / Avg: 1673.31 / Max: 1674.53 Min: 2731.74 / Avg: 2740.52 / Max: 2748.21 Min: 2213.13 / Avg: 2221.37 / Max: 2232.96 Min: 2713.68 / Avg: 2716.54 / Max: 2721.54 Min: 1347.63 / Avg: 1350.13 / Max: 1351.85 Min: 1207.18 / Avg: 1211.54 / Max: 1218.81 Min: 2202.51 / Avg: 2203.16 / Max: 2203.65 Min: 2296.67 / Avg: 2314.36 / Max: 2330.29 Min: 3342.99 / Avg: 3348.06 / Max: 3351.09 Min: 1996.27 / Avg: 1997.39 / Max: 1998.44 1. (CXX) g++ options: -O3 -std=c++11 -fopenmp -msse4.1 -fPIC -pie -lpthread
Result
OpenBenchmarking.org ms, Fewer Is Better oneDNN 2.0 Harness: Recurrent Neural Network Training - Data Type: f32 - Engine: CPU EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 900 1800 2700 3600 4500 SE +/- 5.10, N = 3 SE +/- 1.59, N = 3 SE +/- 1.43, N = 3 SE +/- 2.99, N = 3 SE +/- 0.54, N = 3 SE +/- 5.60, N = 3 SE +/- 2.63, N = 3 SE +/- 1.42, N = 3 SE +/- 1.32, N = 3 SE +/- 0.57, N = 3 SE +/- 8.27, N = 3 SE +/- 5.75, N = 3 SE +/- 0.86, N = 3 SE +/- 2.05, N = 3 4345.12 3056.05 2836.68 2412.79 1672.24 2738.42 2214.79 2718.68 1350.55 1213.58 2221.33 2306.33 3345.10 2013.75 MIN: 4298.14 MIN: 3041.35 MIN: 2798.53 MIN: 2397.68 MIN: 1658.48 MIN: 2722.76 MIN: 2191.84 MIN: 2705.41 MIN: 1331.05 MIN: 1190.99 MIN: 2189.19 MIN: 2274.33 MIN: 3322.56 MIN: 1995.38 1. (CXX) g++ options: -O3 -std=c++11 -fopenmp -msse4.1 -fPIC -pie -lpthread
Result Confidence
OpenBenchmarking.org ms, Fewer Is Better oneDNN 2.0 Harness: Recurrent Neural Network Training - Data Type: f32 - Engine: CPU EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 800 1600 2400 3200 4000 Min: 4339.98 / Avg: 4345.12 / Max: 4355.32 Min: 3053.73 / Avg: 3056.05 / Max: 3059.09 Min: 2834.78 / Avg: 2836.68 / Max: 2839.49 Min: 2408.58 / Avg: 2412.79 / Max: 2418.57 Min: 1671.4 / Avg: 1672.24 / Max: 1673.25 Min: 2731.04 / Avg: 2738.42 / Max: 2749.41 Min: 2209.9 / Avg: 2214.79 / Max: 2218.93 Min: 2716.43 / Avg: 2718.68 / Max: 2721.31 Min: 1347.94 / Avg: 1350.55 / Max: 1352.2 Min: 1212.83 / Avg: 1213.58 / Max: 1214.69 Min: 2206.05 / Avg: 2221.33 / Max: 2234.44 Min: 2294.83 / Avg: 2306.33 / Max: 2312.48 Min: 3343.83 / Avg: 3345.1 / Max: 3346.73 Min: 2010.58 / Avg: 2013.75 / Max: 2017.58 1. (CXX) g++ options: -O3 -std=c++11 -fopenmp -msse4.1 -fPIC -pie -lpthread
Facebook RocksDB This is a benchmark of Facebook's RocksDB as an embeddable persistent key-value store for fast storage based on Google's LevelDB. Learn more via the OpenBenchmarking.org test page.
Result
OpenBenchmarking.org Op/s, More Is Better Facebook RocksDB 6.3.6 Test: Random Fill Sync EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 70K 140K 210K 280K 350K SE +/- 204.78, N = 3 SE +/- 223.01, N = 3 SE +/- 203.74, N = 3 SE +/- 607.97, N = 3 SE +/- 219.22, N = 3 SE +/- 622.13, N = 3 SE +/- 344.84, N = 3 SE +/- 749.32, N = 3 SE +/- 768.33, N = 3 SE +/- 735.95, N = 3 SE +/- 166.32, N = 3 SE +/- 175.05, N = 3 SE +/- 436.15, N = 3 94371 131583 163535 163248 216427 259353 253689 258759 331300 331791 333412 287115 100843 172585 1. (CXX) g++ options: -O3 -march=native -std=c++11 -fno-builtin-memcmp -fno-rtti -rdynamic -lpthread
Op/s Per Watt
OpenBenchmarking.org Op/s Per Watt, More Is Better Facebook RocksDB 6.3.6 Test: Random Fill Sync EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 700 1400 2100 2800 3500 2127.71 2715.04 3041.80 2693.49 3035.68 3252.08 2535.97 3314.42 3130.89 2741.84 2353.30 2752.63 1654.28 1704.39
Result Confidence
OpenBenchmarking.org Op/s, More Is Better Facebook RocksDB 6.3.6 Test: Random Fill Sync EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 60K 120K 180K 240K 300K Min: 93963 / Avg: 94371 / Max: 94606 Min: 131216 / Avg: 131583 / Max: 131986 Min: 163163 / Avg: 163535 / Max: 163865 Min: 215402 / Avg: 216427 / Max: 217506 Min: 259071 / Avg: 259353.33 / Max: 259785 Min: 252478 / Avg: 253689 / Max: 254542 Min: 258263 / Avg: 258759 / Max: 259422 Min: 329808 / Avg: 331300 / Max: 332168 Min: 330767 / Avg: 331790.67 / Max: 333295 Min: 332027 / Avg: 333412 / Max: 334536 Min: 286867 / Avg: 287115 / Max: 287431 Min: 100631 / Avg: 100842.67 / Max: 101190 Min: 171773 / Avg: 172585 / Max: 173267 1. (CXX) g++ options: -O3 -march=native -std=c++11 -fno-builtin-memcmp -fno-rtti -rdynamic -lpthread
Timed MPlayer Compilation This test times how long it takes to build the MPlayer open-source media player program. Learn more via the OpenBenchmarking.org test page.
Result
OpenBenchmarking.org Seconds, Fewer Is Better Timed MPlayer Compilation 1.4 Time To Compile EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 10 20 30 40 50 SE +/- 0.03, N = 3 SE +/- 0.03, N = 3 SE +/- 0.02, N = 3 SE +/- 0.01, N = 3 SE +/- 0.05, N = 3 SE +/- 0.03, N = 3 SE +/- 0.02, N = 3 SE +/- 0.07, N = 4 SE +/- 0.03, N = 4 SE +/- 0.04, N = 4 SE +/- 0.03, N = 4 SE +/- 0.04, N = 4 SE +/- 0.02, N = 3 SE +/- 0.07, N = 3 45.59 31.14 26.27 24.06 18.59 16.46 16.38 15.69 13.82 13.71 12.96 12.99 35.25 20.57
Result Confidence
OpenBenchmarking.org Seconds, Fewer Is Better Timed MPlayer Compilation 1.4 Time To Compile EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 9 18 27 36 45 Min: 45.54 / Avg: 45.59 / Max: 45.62 Min: 31.1 / Avg: 31.14 / Max: 31.21 Min: 26.23 / Avg: 26.27 / Max: 26.29 Min: 24.05 / Avg: 24.06 / Max: 24.07 Min: 18.5 / Avg: 18.59 / Max: 18.68 Min: 16.42 / Avg: 16.46 / Max: 16.52 Min: 16.35 / Avg: 16.38 / Max: 16.42 Min: 15.6 / Avg: 15.69 / Max: 15.9 Min: 13.75 / Avg: 13.82 / Max: 13.87 Min: 13.64 / Avg: 13.71 / Max: 13.81 Min: 12.87 / Avg: 12.96 / Max: 13.01 Min: 12.91 / Avg: 12.99 / Max: 13.09 Min: 35.21 / Avg: 35.25 / Max: 35.28 Min: 20.43 / Avg: 20.57 / Max: 20.67
FFTE FFTE is a package by Daisuke Takahashi to compute Discrete Fourier Transforms of 1-, 2- and 3- dimensional sequences of length (2^p)*(3^q)*(5^r). Learn more via the OpenBenchmarking.org test page.
Result
OpenBenchmarking.org MFLOPS, More Is Better FFTE 7.0 N=256, 3D Complex FFT Routine EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 30K 60K 90K 120K 150K SE +/- 139.55, N = 9 SE +/- 22.37, N = 11 SE +/- 71.59, N = 9 SE +/- 80.44, N = 9 SE +/- 134.09, N = 10 SE +/- 160.95, N = 8 SE +/- 154.09, N = 8 SE +/- 143.74, N = 9 SE +/- 375.36, N = 8 SE +/- 641.51, N = 9 SE +/- 1366.04, N = 15 SE +/- 1033.87, N = 15 SE +/- 37.94, N = 10 SE +/- 308.97, N = 9 44242.98 61838.52 76796.04 84316.23 111563.84 136276.50 135786.94 144583.87 135838.12 149967.74 155375.98 145868.29 54800.99 71767.96 1. (F9X) gfortran options: -O3 -fomit-frame-pointer -fopenmp
MFLOPS Per Watt
OpenBenchmarking.org MFLOPS Per Watt, More Is Better FFTE 7.0 N=256, 3D Complex FFT Routine EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 300 600 900 1200 1500 839.58 1139.68 1200.32 1116.04 1403.88 1457.28 1272.00 1396.95 1263.45 1309.22 1389.25 1260.43 805.56 604.59
Result Confidence
OpenBenchmarking.org MFLOPS, More Is Better FFTE 7.0 N=256, 3D Complex FFT Routine EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 30K 60K 90K 120K 150K Min: 43253.52 / Avg: 44242.98 / Max: 44735.98 Min: 61730.3 / Avg: 61838.52 / Max: 61950.09 Min: 76508.11 / Avg: 76796.04 / Max: 77062.73 Min: 83921.86 / Avg: 84316.23 / Max: 84643.19 Min: 110544.87 / Avg: 111563.84 / Max: 112037.3 Min: 135695.57 / Avg: 136276.5 / Max: 136949.63 Min: 135207.86 / Avg: 135786.94 / Max: 136435.92 Min: 143957.47 / Avg: 144583.87 / Max: 145193.47 Min: 133822.4 / Avg: 135838.12 / Max: 137193.41 Min: 148789.93 / Avg: 149967.74 / Max: 154980.74 Min: 151616.85 / Avg: 155375.98 / Max: 173605.93 Min: 143378.84 / Avg: 145868.29 / Max: 159924 Min: 54543.54 / Avg: 54800.99 / Max: 54955.54 Min: 70448.73 / Avg: 71767.96 / Max: 73371.09 1. (F9X) gfortran options: -O3 -fomit-frame-pointer -fopenmp
Kvazaar This is a test of Kvazaar as a CPU-based H.265 video encoder written in the C programming language and optimized in Assembly. Kvazaar is the winner of the 2016 ACM Open-Source Software Competition and developed at the Ultra Video Group, Tampere University, Finland. Learn more via the OpenBenchmarking.org test page.
Result
OpenBenchmarking.org Frames Per Second, More Is Better Kvazaar 2.0 Video Input: Bosphorus 4K - Video Preset: Medium EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 4 8 12 16 20 SE +/- 0.00, N = 3 SE +/- 0.00, N = 3 SE +/- 0.02, N = 3 SE +/- 0.01, N = 3 SE +/- 0.02, N = 3 SE +/- 0.01, N = 3 SE +/- 0.02, N = 3 SE +/- 0.01, N = 3 SE +/- 0.01, N = 3 SE +/- 0.02, N = 3 SE +/- 0.02, N = 3 SE +/- 0.01, N = 3 SE +/- 0.01, N = 3 SE +/- 0.01, N = 3 4.72 6.49 8.61 9.15 11.22 13.97 13.65 14.94 15.50 15.94 16.44 14.94 5.73 10.66 1. (CC) gcc options: -pthread -ftree-vectorize -fvisibility=hidden -O2 -lpthread -lm -lrt
Frames Per Second Per Watt
OpenBenchmarking.org Frames Per Second Per Watt, More Is Better Kvazaar 2.0 Video Input: Bosphorus 4K - Video Preset: Medium EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 0.0225 0.045 0.0675 0.09 0.1125 0.06 0.07 0.09 0.08 0.08 0.10 0.09 0.09 0.10 0.09 0.10 0.09 0.05 0.05
Result Confidence
OpenBenchmarking.org Frames Per Second, More Is Better Kvazaar 2.0 Video Input: Bosphorus 4K - Video Preset: Medium EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 4 8 12 16 20 Min: 4.72 / Avg: 4.72 / Max: 4.73 Min: 6.48 / Avg: 6.49 / Max: 6.49 Min: 8.58 / Avg: 8.61 / Max: 8.63 Min: 9.13 / Avg: 9.15 / Max: 9.17 Min: 11.18 / Avg: 11.22 / Max: 11.24 Min: 13.95 / Avg: 13.97 / Max: 13.98 Min: 13.61 / Avg: 13.65 / Max: 13.67 Min: 14.93 / Avg: 14.94 / Max: 14.95 Min: 15.49 / Avg: 15.5 / Max: 15.51 Min: 15.92 / Avg: 15.94 / Max: 15.97 Min: 16.42 / Avg: 16.44 / Max: 16.48 Min: 14.93 / Avg: 14.94 / Max: 14.97 Min: 5.71 / Avg: 5.73 / Max: 5.74 Min: 10.64 / Avg: 10.66 / Max: 10.69 1. (CC) gcc options: -pthread -ftree-vectorize -fvisibility=hidden -O2 -lpthread -lm -lrt
GPAW GPAW is a density-functional theory (DFT) Python code based on the projector-augmented wave (PAW) method and the atomic simulation environment (ASE). Learn more via the OpenBenchmarking.org test page.
Result
OpenBenchmarking.org Seconds, Fewer Is Better GPAW 20.1 Input: Carbon Nanotube EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 60 120 180 240 300 SE +/- 0.67, N = 3 SE +/- 0.37, N = 3 SE +/- 0.09, N = 3 SE +/- 0.19, N = 3 SE +/- 0.46, N = 3 SE +/- 0.20, N = 3 SE +/- 0.02, N = 3 SE +/- 0.27, N = 3 SE +/- 0.11, N = 3 SE +/- 0.26, N = 3 SE +/- 0.05, N = 3 SE +/- 0.15, N = 3 SE +/- 0.20, N = 3 SE +/- 0.87, N = 3 271.16 205.89 177.91 139.15 116.41 105.67 93.24 103.30 86.74 79.98 78.39 81.06 200.41 165.41 1. (CC) gcc options: -pthread -shared -fwrapv -O2 -lxc -lblas -lmpi
Result Confidence
OpenBenchmarking.org Seconds, Fewer Is Better GPAW 20.1 Input: Carbon Nanotube EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 50 100 150 200 250 Min: 270.41 / Avg: 271.16 / Max: 272.49 Min: 205.17 / Avg: 205.89 / Max: 206.37 Min: 177.8 / Avg: 177.9 / Max: 178.09 Min: 138.85 / Avg: 139.15 / Max: 139.52 Min: 115.76 / Avg: 116.41 / Max: 117.3 Min: 105.35 / Avg: 105.67 / Max: 106.04 Min: 93.21 / Avg: 93.24 / Max: 93.28 Min: 102.87 / Avg: 103.3 / Max: 103.79 Min: 86.54 / Avg: 86.74 / Max: 86.91 Min: 79.56 / Avg: 79.98 / Max: 80.47 Min: 78.29 / Avg: 78.39 / Max: 78.44 Min: 80.78 / Avg: 81.06 / Max: 81.29 Min: 200.15 / Avg: 200.41 / Max: 200.81 Min: 163.66 / Avg: 165.41 / Max: 166.3 1. (CC) gcc options: -pthread -shared -fwrapv -O2 -lxc -lblas -lmpi
oneDNN This is a test of the Intel oneDNN as an Intel-optimized library for Deep Neural Networks and making use of its built-in benchdnn functionality. The result is the total perf time reported. Intel oneDNN was formerly known as DNNL (Deep Neural Network Library) and MKL-DNN before being rebranded as part of the Intel oneAPI initiative. Learn more via the OpenBenchmarking.org test page.
Result
OpenBenchmarking.org ms, Fewer Is Better oneDNN 2.0 Harness: Deconvolution Batch shapes_3d - Data Type: f32 - Engine: CPU EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 2 4 6 8 10 SE +/- 0.00735, N = 9 SE +/- 0.00724, N = 9 SE +/- 0.00482, N = 9 SE +/- 0.00474, N = 9 SE +/- 0.00636, N = 9 SE +/- 0.00414, N = 9 SE +/- 0.00881, N = 9 SE +/- 0.00582, N = 9 SE +/- 0.00950, N = 9 SE +/- 0.01930, N = 15 SE +/- 0.02912, N = 15 SE +/- 0.03302, N = 15 SE +/- 0.00118, N = 9 SE +/- 0.00511, N = 9 8.27184 6.29135 5.08328 4.72608 3.34633 3.68833 3.60130 3.44118 2.55335 2.40380 2.52363 2.82015 6.46398 3.92737 MIN: 8 MIN: 6.07 MIN: 4.73 MIN: 4.52 MIN: 3.15 MIN: 3.26 MIN: 3.22 MIN: 3.03 MIN: 2.41 MIN: 2.23 MIN: 2.25 MIN: 2.49 MIN: 6.38 MIN: 3.81 1. (CXX) g++ options: -O3 -std=c++11 -fopenmp -msse4.1 -fPIC -pie -lpthread
Result Confidence
OpenBenchmarking.org ms, Fewer Is Better oneDNN 2.0 Harness: Deconvolution Batch shapes_3d - Data Type: f32 - Engine: CPU EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 3 6 9 12 15 Min: 8.23 / Avg: 8.27 / Max: 8.29 Min: 6.26 / Avg: 6.29 / Max: 6.32 Min: 5.06 / Avg: 5.08 / Max: 5.11 Min: 4.71 / Avg: 4.73 / Max: 4.74 Min: 3.33 / Avg: 3.35 / Max: 3.39 Min: 3.67 / Avg: 3.69 / Max: 3.7 Min: 3.57 / Avg: 3.6 / Max: 3.64 Min: 3.42 / Avg: 3.44 / Max: 3.47 Min: 2.52 / Avg: 2.55 / Max: 2.62 Min: 2.29 / Avg: 2.4 / Max: 2.52 Min: 2.43 / Avg: 2.52 / Max: 2.85 Min: 2.71 / Avg: 2.82 / Max: 3.12 Min: 6.46 / Avg: 6.46 / Max: 6.47 Min: 3.89 / Avg: 3.93 / Max: 3.94 1. (CXX) g++ options: -O3 -std=c++11 -fopenmp -msse4.1 -fPIC -pie -lpthread
PlaidML This test profile uses PlaidML deep learning framework developed by Intel for offering up various benchmarks. Learn more via the OpenBenchmarking.org test page.
Result
OpenBenchmarking.org FPS, More Is Better PlaidML FP16: No - Mode: Inference - Network: VGG19 - Device: CPU EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 7 14 21 28 35 SE +/- 0.06, N = 3 SE +/- 0.12, N = 3 SE +/- 0.06, N = 3 SE +/- 0.06, N = 3 SE +/- 0.12, N = 3 SE +/- 0.21, N = 3 SE +/- 0.04, N = 3 SE +/- 0.14, N = 3 SE +/- 0.02, N = 3 SE +/- 0.12, N = 3 SE +/- 0.26, N = 3 SE +/- 0.05, N = 3 SE +/- 0.06, N = 3 SE +/- 0.12, N = 3 9.30 13.67 16.61 17.39 23.34 26.51 25.35 27.67 27.50 29.37 31.84 26.49 12.06 20.00
FPS Per Watt
OpenBenchmarking.org FPS Per Watt, More Is Better PlaidML FP16: No - Mode: Inference - Network: VGG19 - Device: CPU EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 0.054 0.108 0.162 0.216 0.27 0.11 0.15 0.18 0.16 0.19 0.22 0.19 0.21 0.22 0.20 0.24 0.21 0.09 0.11
Result Confidence
OpenBenchmarking.org FPS, More Is Better PlaidML FP16: No - Mode: Inference - Network: VGG19 - Device: CPU EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 7 14 21 28 35 Min: 9.23 / Avg: 9.3 / Max: 9.41 Min: 13.44 / Avg: 13.67 / Max: 13.83 Min: 16.52 / Avg: 16.61 / Max: 16.72 Min: 17.26 / Avg: 17.39 / Max: 17.46 Min: 23.11 / Avg: 23.34 / Max: 23.52 Min: 26.11 / Avg: 26.51 / Max: 26.82 Min: 25.31 / Avg: 25.35 / Max: 25.42 Min: 27.53 / Avg: 27.67 / Max: 27.96 Min: 27.47 / Avg: 27.5 / Max: 27.53 Min: 29.23 / Avg: 29.37 / Max: 29.61 Min: 31.48 / Avg: 31.84 / Max: 32.35 Min: 26.42 / Avg: 26.49 / Max: 26.59 Min: 11.98 / Avg: 12.06 / Max: 12.18 Min: 19.79 / Avg: 20 / Max: 20.19
GROMACS The GROMACS (GROningen MAchine for Chemical Simulations) molecular dynamics package testing on the CPU with the water_GMX50 data. Learn more via the OpenBenchmarking.org test page.
Result
OpenBenchmarking.org Ns Per Day, More Is Better GROMACS 2021 Input: water_GMX50_bare EPYC 7272 EPYC 7282 EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 1.0199 2.0398 3.0597 4.0796 5.0995 SE +/- 0.001, N = 3 SE +/- 0.001, N = 3 SE +/- 0.002, N = 3 SE +/- 0.007, N = 3 SE +/- 0.004, N = 3 SE +/- 0.005, N = 3 SE +/- 0.001, N = 3 SE +/- 0.001, N = 3 SE +/- 0.006, N = 3 1.407 1.675 3.140 3.256 3.317 4.533 4.371 1.348 2.313 1. (CXX) g++ options: -O3 -pthread
Ns Per Day Per Watt
OpenBenchmarking.org Ns Per Day Per Watt, More Is Better GROMACS 2021 Input: water_GMX50_bare EPYC 7282 EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7662 EPYC 7F32 EPYC 7F52 0.0068 0.0136 0.0204 0.0272 0.034 0.02 0.02 0.02 0.02 0.03 0.01 0.01
Result Confidence
OpenBenchmarking.org Ns Per Day, More Is Better GROMACS 2021 Input: water_GMX50_bare EPYC 7272 EPYC 7282 EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 2 4 6 8 10 Min: 1.41 / Avg: 1.41 / Max: 1.41 Min: 1.67 / Avg: 1.68 / Max: 1.68 Min: 3.14 / Avg: 3.14 / Max: 3.14 Min: 3.24 / Avg: 3.26 / Max: 3.27 Min: 3.31 / Avg: 3.32 / Max: 3.33 Min: 4.52 / Avg: 4.53 / Max: 4.54 Min: 4.37 / Avg: 4.37 / Max: 4.37 Min: 1.35 / Avg: 1.35 / Max: 1.35 Min: 2.31 / Avg: 2.31 / Max: 2.33 1. (CXX) g++ options: -O3 -pthread
PlaidML This test profile uses PlaidML deep learning framework developed by Intel for offering up various benchmarks. Learn more via the OpenBenchmarking.org test page.
Result
OpenBenchmarking.org FPS, More Is Better PlaidML FP16: No - Mode: Inference - Network: VGG16 - Device: CPU EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 9 18 27 36 45 SE +/- 0.15, N = 3 SE +/- 0.22, N = 3 SE +/- 0.05, N = 3 SE +/- 0.10, N = 3 SE +/- 0.12, N = 3 SE +/- 0.19, N = 3 SE +/- 0.11, N = 3 SE +/- 0.37, N = 3 SE +/- 0.16, N = 3 SE +/- 0.45, N = 3 SE +/- 0.46, N = 4 SE +/- 0.28, N = 3 SE +/- 0.07, N = 3 SE +/- 0.09, N = 3 11.41 16.79 20.34 21.24 27.81 32.05 30.36 33.33 32.68 35.25 37.38 31.89 14.67 24.29
FPS Per Watt
OpenBenchmarking.org FPS Per Watt, More Is Better PlaidML FP16: No - Mode: Inference - Network: VGG16 - Device: CPU EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 0.063 0.126 0.189 0.252 0.315 0.14 0.19 0.23 0.20 0.23 0.28 0.23 0.27 0.27 0.25 0.28 0.26 0.11 0.13
Result Confidence
OpenBenchmarking.org FPS, More Is Better PlaidML FP16: No - Mode: Inference - Network: VGG16 - Device: CPU EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 8 16 24 32 40 Min: 11.13 / Avg: 11.41 / Max: 11.63 Min: 16.5 / Avg: 16.79 / Max: 17.22 Min: 20.24 / Avg: 20.34 / Max: 20.43 Min: 21.13 / Avg: 21.24 / Max: 21.44 Min: 27.57 / Avg: 27.81 / Max: 27.96 Min: 31.69 / Avg: 32.05 / Max: 32.3 Min: 30.21 / Avg: 30.36 / Max: 30.58 Min: 32.65 / Avg: 33.33 / Max: 33.94 Min: 32.38 / Avg: 32.68 / Max: 32.94 Min: 34.41 / Avg: 35.25 / Max: 35.93 Min: 36.33 / Avg: 37.38 / Max: 38.57 Min: 31.34 / Avg: 31.89 / Max: 32.28 Min: 14.6 / Avg: 14.67 / Max: 14.82 Min: 24.18 / Avg: 24.29 / Max: 24.46
Rodinia Rodinia is a suite focused upon accelerating compute-intensive applications with accelerators. CUDA, OpenMP, and OpenCL parallel models are supported by the included applications. This profile utilizes select OpenCL, NVIDIA CUDA and OpenMP test binaries at the moment. Learn more via the OpenBenchmarking.org test page.
Result
OpenBenchmarking.org Seconds, Fewer Is Better Rodinia 3.1 Test: OpenMP CFD Solver EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 6 12 18 24 30 SE +/- 0.030, N = 3 SE +/- 0.065, N = 3 SE +/- 0.009, N = 4 SE +/- 0.022, N = 4 SE +/- 0.007, N = 4 SE +/- 0.030, N = 5 SE +/- 0.057, N = 5 SE +/- 0.005, N = 5 SE +/- 0.083, N = 6 SE +/- 0.073, N = 5 SE +/- 0.051, N = 15 SE +/- 0.066, N = 8 SE +/- 0.078, N = 3 SE +/- 0.022, N = 4 25.374 18.134 14.792 15.445 11.577 9.892 9.858 9.806 8.405 8.434 7.747 7.819 22.218 13.530 1. (CXX) g++ options: -O2 -lOpenCL
Result Confidence
OpenBenchmarking.org Seconds, Fewer Is Better Rodinia 3.1 Test: OpenMP CFD Solver EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 6 12 18 24 30 Min: 25.33 / Avg: 25.37 / Max: 25.43 Min: 18.02 / Avg: 18.13 / Max: 18.24 Min: 14.76 / Avg: 14.79 / Max: 14.8 Min: 15.41 / Avg: 15.44 / Max: 15.51 Min: 11.57 / Avg: 11.58 / Max: 11.6 Min: 9.81 / Avg: 9.89 / Max: 9.96 Min: 9.76 / Avg: 9.86 / Max: 10.08 Min: 9.79 / Avg: 9.81 / Max: 9.82 Min: 8.14 / Avg: 8.41 / Max: 8.71 Min: 8.16 / Avg: 8.43 / Max: 8.59 Min: 7.37 / Avg: 7.75 / Max: 8.02 Min: 7.45 / Avg: 7.82 / Max: 8.05 Min: 22.12 / Avg: 22.22 / Max: 22.37 Min: 13.49 / Avg: 13.53 / Max: 13.59 1. (CXX) g++ options: -O2 -lOpenCL
NAS Parallel Benchmarks NPB, NAS Parallel Benchmarks, is a benchmark developed by NASA for high-end computer systems. This test profile currently uses the MPI version of NPB. This test profile offers selecting the different NPB tests/problems and varying problem sizes. Learn more via the OpenBenchmarking.org test page.
oneDNN This is a test of the Intel oneDNN as an Intel-optimized library for Deep Neural Networks and making use of its built-in benchdnn functionality. The result is the total perf time reported. Intel oneDNN was formerly known as DNNL (Deep Neural Network Library) and MKL-DNN before being rebranded as part of the Intel oneAPI initiative. Learn more via the OpenBenchmarking.org test page.
Result
OpenBenchmarking.org ms, Fewer Is Better oneDNN 2.0 Harness: Recurrent Neural Network Inference - Data Type: f32 - Engine: CPU EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 500 1000 1500 2000 2500 SE +/- 2.26, N = 3 SE +/- 2.69, N = 3 SE +/- 3.12, N = 3 SE +/- 0.19, N = 3 SE +/- 0.91, N = 3 SE +/- 5.72, N = 3 SE +/- 1.51, N = 3 SE +/- 4.31, N = 3 SE +/- 2.70, N = 3 SE +/- 1.28, N = 3 SE +/- 1.17, N = 3 SE +/- 3.54, N = 3 SE +/- 0.51, N = 3 SE +/- 1.61, N = 3 2397.56 2022.45 1882.64 1229.69 972.93 902.26 813.12 890.48 787.43 732.81 793.20 874.44 1745.54 997.85 MIN: 2367.09 MIN: 2012.67 MIN: 1853.21 MIN: 1221.64 MIN: 960.02 MIN: 882.8 MIN: 799.88 MIN: 867.03 MIN: 769.99 MIN: 712.9 MIN: 776.66 MIN: 847.07 MIN: 1733.89 MIN: 987.15 1. (CXX) g++ options: -O3 -std=c++11 -fopenmp -msse4.1 -fPIC -pie -lpthread
Result Confidence
OpenBenchmarking.org ms, Fewer Is Better oneDNN 2.0 Harness: Recurrent Neural Network Inference - Data Type: f32 - Engine: CPU EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 400 800 1200 1600 2000 Min: 2394.02 / Avg: 2397.56 / Max: 2401.75 Min: 2018.73 / Avg: 2022.45 / Max: 2027.68 Min: 1876.41 / Avg: 1882.64 / Max: 1885.98 Min: 1229.46 / Avg: 1229.69 / Max: 1230.06 Min: 971.59 / Avg: 972.93 / Max: 974.66 Min: 890.83 / Avg: 902.26 / Max: 908.5 Min: 810.1 / Avg: 813.12 / Max: 814.7 Min: 882.05 / Avg: 890.48 / Max: 896.25 Min: 782.55 / Avg: 787.43 / Max: 791.88 Min: 731.06 / Avg: 732.81 / Max: 735.31 Min: 790.85 / Avg: 793.2 / Max: 794.46 Min: 868.68 / Avg: 874.44 / Max: 880.89 Min: 1744.59 / Avg: 1745.54 / Max: 1746.31 Min: 995.25 / Avg: 997.85 / Max: 1000.79 1. (CXX) g++ options: -O3 -std=c++11 -fopenmp -msse4.1 -fPIC -pie -lpthread
Timed LLVM Compilation This test times how long it takes to build the LLVM compiler. Learn more via the OpenBenchmarking.org test page.
Result
OpenBenchmarking.org Seconds, Fewer Is Better Timed LLVM Compilation 10.0 Time To Compile EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 160 320 480 640 800 SE +/- 2.05, N = 3 SE +/- 0.47, N = 3 SE +/- 3.68, N = 3 SE +/- 5.04, N = 4 SE +/- 3.16, N = 9 SE +/- 2.29, N = 3 SE +/- 1.56, N = 3 SE +/- 1.12, N = 3 SE +/- 1.44, N = 3 SE +/- 1.29, N = 3 SE +/- 0.89, N = 3 SE +/- 1.73, N = 3 SE +/- 0.89, N = 3 SE +/- 2.67, N = 3 763.56 529.62 440.00 404.33 312.70 289.36 280.78 275.35 245.40 243.92 233.51 234.21 581.30 343.39
Result Confidence
OpenBenchmarking.org Seconds, Fewer Is Better Timed LLVM Compilation 10.0 Time To Compile EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 130 260 390 520 650 Min: 759.57 / Avg: 763.56 / Max: 766.35 Min: 528.7 / Avg: 529.62 / Max: 530.26 Min: 432.97 / Avg: 440 / Max: 445.42 Min: 391.86 / Avg: 404.33 / Max: 414.08 Min: 297.71 / Avg: 312.7 / Max: 321.97 Min: 286.12 / Avg: 289.36 / Max: 293.79 Min: 278.05 / Avg: 280.78 / Max: 283.44 Min: 273.43 / Avg: 275.35 / Max: 277.3 Min: 242.68 / Avg: 245.4 / Max: 247.61 Min: 241.53 / Avg: 243.91 / Max: 245.95 Min: 232.12 / Avg: 233.51 / Max: 235.17 Min: 230.9 / Avg: 234.2 / Max: 236.76 Min: 579.68 / Avg: 581.3 / Max: 582.76 Min: 340.62 / Avg: 343.39 / Max: 348.73
oneDNN This is a test of the Intel oneDNN as an Intel-optimized library for Deep Neural Networks and making use of its built-in benchdnn functionality. The result is the total perf time reported. Intel oneDNN was formerly known as DNNL (Deep Neural Network Library) and MKL-DNN before being rebranded as part of the Intel oneAPI initiative. Learn more via the OpenBenchmarking.org test page.
Result
OpenBenchmarking.org ms, Fewer Is Better oneDNN 2.0 Harness: Recurrent Neural Network Inference - Data Type: u8s8f32 - Engine: CPU EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 500 1000 1500 2000 2500 SE +/- 3.61, N = 3 SE +/- 4.61, N = 3 SE +/- 5.33, N = 3 SE +/- 0.54, N = 3 SE +/- 1.57, N = 3 SE +/- 2.58, N = 3 SE +/- 1.32, N = 3 SE +/- 1.35, N = 3 SE +/- 2.09, N = 3 SE +/- 3.28, N = 3 SE +/- 1.88, N = 3 SE +/- 2.81, N = 3 SE +/- 0.95, N = 3 SE +/- 3.97, N = 3 2397.22 2032.88 1886.30 1227.56 974.12 919.61 812.99 886.88 784.82 734.40 793.23 878.20 1742.79 998.67 MIN: 2370.41 MIN: 2016.92 MIN: 1851.55 MIN: 1218.44 MIN: 962.55 MIN: 906.32 MIN: 799.51 MIN: 865.5 MIN: 771.05 MIN: 716.82 MIN: 777.03 MIN: 851.72 MIN: 1728.82 MIN: 987.09 1. (CXX) g++ options: -O3 -std=c++11 -fopenmp -msse4.1 -fPIC -pie -lpthread
Result Confidence
OpenBenchmarking.org ms, Fewer Is Better oneDNN 2.0 Harness: Recurrent Neural Network Inference - Data Type: u8s8f32 - Engine: CPU EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 400 800 1200 1600 2000 Min: 2392.08 / Avg: 2397.22 / Max: 2404.17 Min: 2023.66 / Avg: 2032.88 / Max: 2037.71 Min: 1876.6 / Avg: 1886.3 / Max: 1894.99 Min: 1226.72 / Avg: 1227.56 / Max: 1228.57 Min: 971.07 / Avg: 974.12 / Max: 976.32 Min: 916.98 / Avg: 919.61 / Max: 924.77 Min: 810.37 / Avg: 812.99 / Max: 814.64 Min: 884.18 / Avg: 886.88 / Max: 888.33 Min: 780.67 / Avg: 784.82 / Max: 787.4 Min: 728.04 / Avg: 734.4 / Max: 738.94 Min: 791.29 / Avg: 793.23 / Max: 796.99 Min: 873.24 / Avg: 878.2 / Max: 882.97 Min: 1741.68 / Avg: 1742.79 / Max: 1744.69 Min: 991.29 / Avg: 998.67 / Max: 1004.91 1. (CXX) g++ options: -O3 -std=c++11 -fopenmp -msse4.1 -fPIC -pie -lpthread
Result
OpenBenchmarking.org ms, Fewer Is Better oneDNN 2.0 Harness: Recurrent Neural Network Inference - Data Type: bf16bf16bf16 - Engine: CPU EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 500 1000 1500 2000 2500 SE +/- 4.09, N = 3 SE +/- 1.28, N = 3 SE +/- 4.32, N = 3 SE +/- 1.03, N = 3 SE +/- 0.65, N = 3 SE +/- 5.94, N = 3 SE +/- 2.11, N = 3 SE +/- 1.82, N = 3 SE +/- 1.66, N = 3 SE +/- 2.51, N = 3 SE +/- 0.96, N = 3 SE +/- 3.99, N = 3 SE +/- 2.16, N = 3 SE +/- 0.99, N = 3 2398.98 2029.28 1884.70 1228.50 972.77 917.61 814.03 888.54 782.65 735.82 792.55 875.71 1744.75 999.14 MIN: 2367.55 MIN: 2020.38 MIN: 1853.9 MIN: 1219.05 MIN: 962.66 MIN: 892.04 MIN: 801.22 MIN: 872.96 MIN: 769.36 MIN: 715.63 MIN: 773.96 MIN: 846.67 MIN: 1731.94 MIN: 991.16 1. (CXX) g++ options: -O3 -std=c++11 -fopenmp -msse4.1 -fPIC -pie -lpthread
Result Confidence
OpenBenchmarking.org ms, Fewer Is Better oneDNN 2.0 Harness: Recurrent Neural Network Inference - Data Type: bf16bf16bf16 - Engine: CPU EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 400 800 1200 1600 2000 Min: 2391.8 / Avg: 2398.98 / Max: 2405.96 Min: 2026.92 / Avg: 2029.28 / Max: 2031.33 Min: 1878.26 / Avg: 1884.7 / Max: 1892.91 Min: 1226.65 / Avg: 1228.5 / Max: 1230.2 Min: 971.9 / Avg: 972.77 / Max: 974.05 Min: 907.1 / Avg: 917.61 / Max: 927.67 Min: 810.97 / Avg: 814.03 / Max: 818.07 Min: 885.37 / Avg: 888.54 / Max: 891.69 Min: 779.51 / Avg: 782.65 / Max: 785.17 Min: 731.42 / Avg: 735.82 / Max: 740.12 Min: 791.43 / Avg: 792.55 / Max: 794.46 Min: 869.12 / Avg: 875.71 / Max: 882.9 Min: 1742.54 / Avg: 1744.75 / Max: 1749.07 Min: 997.98 / Avg: 999.14 / Max: 1001.1 1. (CXX) g++ options: -O3 -std=c++11 -fopenmp -msse4.1 -fPIC -pie -lpthread
Result
OpenBenchmarking.org ms, Fewer Is Better oneDNN 2.0 Harness: IP Shapes 1D - Data Type: f32 - Engine: CPU EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 1.0662 2.1324 3.1986 4.2648 5.331 SE +/- 0.00331, N = 4 SE +/- 0.00316, N = 4 SE +/- 0.00488, N = 4 SE +/- 0.00144, N = 4 SE +/- 0.00090, N = 4 SE +/- 0.00185, N = 4 SE +/- 0.00891, N = 4 SE +/- 0.00341, N = 4 SE +/- 0.00439, N = 4 SE +/- 0.00906, N = 4 SE +/- 0.01406, N = 4 SE +/- 0.00178, N = 4 SE +/- 0.00382, N = 4 SE +/- 0.01053, N = 4 4.73866 3.80955 3.44668 2.41082 1.82951 1.59300 1.61502 1.47222 1.59938 1.46775 1.48981 1.70360 3.56020 1.98035 MIN: 4.55 MIN: 3.44 MIN: 2.92 MIN: 2.2 MIN: 1.74 MIN: 1.51 MIN: 1.5 MIN: 1.41 MIN: 1.51 MIN: 1.39 MIN: 1.33 MIN: 1.48 MIN: 3.44 MIN: 1.86 1. (CXX) g++ options: -O3 -std=c++11 -fopenmp -msse4.1 -fPIC -pie -lpthread
Result Confidence
OpenBenchmarking.org ms, Fewer Is Better oneDNN 2.0 Harness: IP Shapes 1D - Data Type: f32 - Engine: CPU EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 2 4 6 8 10 Min: 4.73 / Avg: 4.74 / Max: 4.74 Min: 3.8 / Avg: 3.81 / Max: 3.81 Min: 3.43 / Avg: 3.45 / Max: 3.45 Min: 2.41 / Avg: 2.41 / Max: 2.41 Min: 1.83 / Avg: 1.83 / Max: 1.83 Min: 1.59 / Avg: 1.59 / Max: 1.6 Min: 1.6 / Avg: 1.62 / Max: 1.64 Min: 1.46 / Avg: 1.47 / Max: 1.48 Min: 1.59 / Avg: 1.6 / Max: 1.61 Min: 1.45 / Avg: 1.47 / Max: 1.49 Min: 1.45 / Avg: 1.49 / Max: 1.52 Min: 1.7 / Avg: 1.7 / Max: 1.71 Min: 3.55 / Avg: 3.56 / Max: 3.57 Min: 1.96 / Avg: 1.98 / Max: 2.01 1. (CXX) g++ options: -O3 -std=c++11 -fopenmp -msse4.1 -fPIC -pie -lpthread
Tungsten Renderer Tungsten is a C++ physically based renderer that makes use of Intel's Embree ray tracing library. Learn more via the OpenBenchmarking.org test page.
Result
OpenBenchmarking.org Seconds, Fewer Is Better Tungsten Renderer 0.2.2 Scene: Volumetric Caustic EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 4 8 12 16 20 SE +/- 0.01019, N = 4 SE +/- 0.06509, N = 5 SE +/- 0.04707, N = 6 SE +/- 0.03030, N = 6 SE +/- 0.01885, N = 7 SE +/- 0.00220, N = 8 SE +/- 0.00562, N = 7 SE +/- 0.00749, N = 8 SE +/- 0.00349, N = 8 SE +/- 0.00169, N = 8 SE +/- 0.00245, N = 8 SE +/- 0.00214, N = 8 SE +/- 0.08977, N = 4 SE +/- 0.05079, N = 6 13.92660 9.81098 7.40074 7.46871 5.27499 4.69550 4.84256 4.54904 4.36372 4.36145 4.32609 4.46261 12.41410 6.56276 1. (CXX) g++ options: -std=c++0x -march=znver1 -msse2 -msse3 -mssse3 -msse4.1 -msse4.2 -msse4a -mfma -mbmi2 -mno-avx -mno-avx2 -mno-xop -mno-fma4 -mno-avx512f -mno-avx512vl -mno-avx512pf -mno-avx512er -mno-avx512cd -mno-avx512dq -mno-avx512bw -mno-avx512ifma -mno-avx512vbmi -fstrict-aliasing -O3 -rdynamic -lIlmImf -lIlmThread -lImath -lHalf -lIex -lz -ljpeg -lpthread -ldl
Result Confidence
OpenBenchmarking.org Seconds, Fewer Is Better Tungsten Renderer 0.2.2 Scene: Volumetric Caustic EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 4 8 12 16 20 Min: 13.91 / Avg: 13.93 / Max: 13.96 Min: 9.7 / Avg: 9.81 / Max: 10.01 Min: 7.21 / Avg: 7.4 / Max: 7.56 Min: 7.35 / Avg: 7.47 / Max: 7.56 Min: 5.21 / Avg: 5.27 / Max: 5.33 Min: 4.68 / Avg: 4.7 / Max: 4.7 Min: 4.83 / Avg: 4.84 / Max: 4.87 Min: 4.51 / Avg: 4.55 / Max: 4.57 Min: 4.35 / Avg: 4.36 / Max: 4.38 Min: 4.35 / Avg: 4.36 / Max: 4.37 Min: 4.32 / Avg: 4.33 / Max: 4.34 Min: 4.46 / Avg: 4.46 / Max: 4.47 Min: 12.18 / Avg: 12.41 / Max: 12.6 Min: 6.4 / Avg: 6.56 / Max: 6.75 1. (CXX) g++ options: -std=c++0x -march=znver1 -msse2 -msse3 -mssse3 -msse4.1 -msse4.2 -msse4a -mfma -mbmi2 -mno-avx -mno-avx2 -mno-xop -mno-fma4 -mno-avx512f -mno-avx512vl -mno-avx512pf -mno-avx512er -mno-avx512cd -mno-avx512dq -mno-avx512bw -mno-avx512ifma -mno-avx512vbmi -fstrict-aliasing -O3 -rdynamic -lIlmImf -lIlmThread -lImath -lHalf -lIex -lz -ljpeg -lpthread -ldl
Rodinia Rodinia is a suite focused upon accelerating compute-intensive applications with accelerators. CUDA, OpenMP, and OpenCL parallel models are supported by the included applications. This profile utilizes select OpenCL, NVIDIA CUDA and OpenMP test binaries at the moment. Learn more via the OpenBenchmarking.org test page.
Result
OpenBenchmarking.org Seconds, Fewer Is Better Rodinia 3.1 Test: OpenMP Leukocyte EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 30 60 90 120 150 SE +/- 0.41, N = 3 SE +/- 0.53, N = 3 SE +/- 0.76, N = 10 SE +/- 1.14, N = 3 SE +/- 0.25, N = 3 SE +/- 0.26, N = 3 SE +/- 0.42, N = 3 SE +/- 0.28, N = 3 SE +/- 0.82, N = 15 SE +/- 0.47, N = 15 SE +/- 0.47, N = 3 SE +/- 0.61, N = 14 SE +/- 0.11, N = 3 SE +/- 0.52, N = 3 148.20 107.97 99.72 98.19 59.65 57.98 59.44 57.68 47.43 46.53 47.37 48.72 130.98 90.52 1. (CXX) g++ options: -O2 -lOpenCL
Result Confidence
OpenBenchmarking.org Seconds, Fewer Is Better Rodinia 3.1 Test: OpenMP Leukocyte EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 30 60 90 120 150 Min: 147.55 / Avg: 148.2 / Max: 148.96 Min: 106.91 / Avg: 107.97 / Max: 108.52 Min: 96.18 / Avg: 99.72 / Max: 103.91 Min: 96.7 / Avg: 98.19 / Max: 100.44 Min: 59.34 / Avg: 59.65 / Max: 60.14 Min: 57.58 / Avg: 57.98 / Max: 58.48 Min: 58.61 / Avg: 59.44 / Max: 59.95 Min: 57.12 / Avg: 57.68 / Max: 57.99 Min: 44.96 / Avg: 47.42 / Max: 54.58 Min: 44.25 / Avg: 46.53 / Max: 49.64 Min: 46.63 / Avg: 47.37 / Max: 48.23 Min: 46.16 / Avg: 48.72 / Max: 52.95 Min: 130.76 / Avg: 130.98 / Max: 131.14 Min: 89.7 / Avg: 90.52 / Max: 91.49 1. (CXX) g++ options: -O2 -lOpenCL
SVT-VP9 This is a test of the Intel Open Visual Cloud Scalable Video Technology SVT-VP9 CPU-based multi-threaded video encoder for the VP9 video format with a sample 1080p YUV video file. Learn more via the OpenBenchmarking.org test page.
Result
OpenBenchmarking.org Frames Per Second, More Is Better SVT-VP9 0.1 Tuning: PSNR/SSIM Optimized - Input: Bosphorus 1080p EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 100 200 300 400 500 SE +/- 0.15, N = 8 SE +/- 0.45, N = 9 SE +/- 0.35, N = 10 SE +/- 0.29, N = 10 SE +/- 0.86, N = 11 SE +/- 0.76, N = 11 SE +/- 1.03, N = 11 SE +/- 0.74, N = 11 SE +/- 0.97, N = 10 SE +/- 0.61, N = 10 SE +/- 0.96, N = 10 SE +/- 3.60, N = 15 SE +/- 0.26, N = 8 SE +/- 0.36, N = 10 144.32 239.47 295.80 316.49 413.09 437.88 426.52 459.14 445.92 458.24 448.08 409.36 167.08 263.13 1. (CC) gcc options: -O3 -fcommon -fPIE -fPIC -fvisibility=hidden -pie -rdynamic -lpthread -lrt -lm
Frames Per Second Per Watt
OpenBenchmarking.org Frames Per Second Per Watt, More Is Better SVT-VP9 0.1 Tuning: PSNR/SSIM Optimized - Input: Bosphorus 1080p EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 2 4 6 8 10 2.72 4.25 5.47 5.07 6.59 7.27 5.70 7.38 6.57 6.14 5.97 5.28 2.34 2.76
Result Confidence
OpenBenchmarking.org Frames Per Second, More Is Better SVT-VP9 0.1 Tuning: PSNR/SSIM Optimized - Input: Bosphorus 1080p EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 80 160 240 320 400 Min: 143.85 / Avg: 144.32 / Max: 145.1 Min: 237.06 / Avg: 239.47 / Max: 241.16 Min: 293.54 / Avg: 295.8 / Max: 297.47 Min: 315.62 / Avg: 316.49 / Max: 317.97 Min: 407.89 / Avg: 413.09 / Max: 416.67 Min: 434.47 / Avg: 437.88 / Max: 443.13 Min: 419.29 / Avg: 426.52 / Max: 430.73 Min: 454.55 / Avg: 459.14 / Max: 462.25 Min: 441.83 / Avg: 445.92 / Max: 451.13 Min: 456.27 / Avg: 458.24 / Max: 462.61 Min: 442.15 / Avg: 448.08 / Max: 452.83 Min: 379.51 / Avg: 409.36 / Max: 426.74 Min: 165.84 / Avg: 167.08 / Max: 168.07 Min: 260.87 / Avg: 263.13 / Max: 264.67 1. (CC) gcc options: -O3 -fcommon -fPIE -fPIC -fvisibility=hidden -pie -rdynamic -lpthread -lrt -lm
Appleseed Appleseed is an open-source production renderer focused on physically-based global illumination rendering engine primarily designed for animation and visual effects. Learn more via the OpenBenchmarking.org test page.
OpenBenchmarking.org Seconds, Fewer Is Better Appleseed 2.0 Beta Scene: Emily EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 110 220 330 440 550 487.37 333.25 275.81 260.98 194.53 170.48 172.91 161.64 154.73 153.98 153.46 154.44 381.37 226.80
oneDNN This is a test of the Intel oneDNN as an Intel-optimized library for Deep Neural Networks and making use of its built-in benchdnn functionality. The result is the total perf time reported. Intel oneDNN was formerly known as DNNL (Deep Neural Network Library) and MKL-DNN before being rebranded as part of the Intel oneAPI initiative. Learn more via the OpenBenchmarking.org test page.
Result
OpenBenchmarking.org ms, Fewer Is Better oneDNN 2.0 Harness: Convolution Batch Shapes Auto - Data Type: u8s8f32 - Engine: CPU EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 3 6 9 12 15 SE +/- 0.04608, N = 7 SE +/- 0.00984, N = 7 SE +/- 0.03193, N = 7 SE +/- 0.00742, N = 7 SE +/- 0.00525, N = 7 SE +/- 0.01750, N = 7 SE +/- 0.01167, N = 7 SE +/- 0.00813, N = 7 SE +/- 0.00723, N = 7 SE +/- 0.00965, N = 7 SE +/- 0.01107, N = 7 SE +/- 0.00551, N = 7 SE +/- 0.04127, N = 7 SE +/- 0.03514, N = 7 10.95820 7.60505 6.76242 5.45400 4.25111 3.97043 3.61268 3.97699 3.84018 3.54316 3.50412 3.55892 9.15124 6.91561 MIN: 10.24 MIN: 7.15 MIN: 6.41 MIN: 5.12 MIN: 4.06 MIN: 3.86 MIN: 3.49 MIN: 3.87 MIN: 3.75 MIN: 3.43 MIN: 3.39 MIN: 3.47 MIN: 8.56 MIN: 6.67 1. (CXX) g++ options: -O3 -std=c++11 -fopenmp -msse4.1 -fPIC -pie -lpthread
Result Confidence
OpenBenchmarking.org ms, Fewer Is Better oneDNN 2.0 Harness: Convolution Batch Shapes Auto - Data Type: u8s8f32 - Engine: CPU EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 3 6 9 12 15 Min: 10.75 / Avg: 10.96 / Max: 11.12 Min: 7.56 / Avg: 7.61 / Max: 7.64 Min: 6.64 / Avg: 6.76 / Max: 6.85 Min: 5.41 / Avg: 5.45 / Max: 5.47 Min: 4.23 / Avg: 4.25 / Max: 4.27 Min: 3.92 / Avg: 3.97 / Max: 4.03 Min: 3.55 / Avg: 3.61 / Max: 3.64 Min: 3.94 / Avg: 3.98 / Max: 4 Min: 3.81 / Avg: 3.84 / Max: 3.86 Min: 3.52 / Avg: 3.54 / Max: 3.59 Min: 3.47 / Avg: 3.5 / Max: 3.54 Min: 3.54 / Avg: 3.56 / Max: 3.58 Min: 9.06 / Avg: 9.15 / Max: 9.39 Min: 6.79 / Avg: 6.92 / Max: 7.05 1. (CXX) g++ options: -O3 -std=c++11 -fopenmp -msse4.1 -fPIC -pie -lpthread
ASKAP ASKAP is a set of benchmarks from the Australian SKA Pathfinder. The principal ASKAP benchmarks are the Hogbom Clean Benchmark (tHogbomClean) and Convolutional Resamping Benchmark (tConvolve) as well as some previous ASKAP benchmarks being included as well for OpenCL and CUDA execution of tConvolve. Learn more via the OpenBenchmarking.org test page.
Result
OpenBenchmarking.org Iterations Per Second, More Is Better ASKAP 1.0 Test: Hogbom Clean OpenMP EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 100 200 300 400 500 SE +/- 1.09, N = 3 SE +/- 2.09, N = 3 SE +/- 2.18, N = 3 SE +/- 0.62, N = 3 SE +/- 3.44, N = 3 SE +/- 1.71, N = 3 SE +/- 0.64, N = 3 SE +/- 1.71, N = 3 SE +/- 0.98, N = 3 SE +/- 0.00, N = 3 SE +/- 1.71, N = 3 SE +/- 2.16, N = 3 SE +/- 1.74, N = 3 SE +/- 0.57, N = 3 351.71 370.39 378.81 432.28 432.33 439.25 439.24 439.25 411.53 432.90 439.25 432.92 380.73 140.92 1. (CXX) g++ options: -O3 -fstrict-aliasing -fopenmp
Iterations Per Second Per Watt
OpenBenchmarking.org Iterations Per Second Per Watt, More Is Better ASKAP 1.0 Test: Hogbom Clean OpenMP EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 2 4 6 8 10 7.29 7.49 7.57 7.45 7.39 7.30 5.38 7.49 5.89 5.46 5.45 5.10 6.05 1.59
Result Confidence
OpenBenchmarking.org Iterations Per Second, More Is Better ASKAP 1.0 Test: Hogbom Clean OpenMP EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 80 160 240 320 400 Min: 349.65 / Avg: 351.71 / Max: 353.36 Min: 366.3 / Avg: 370.39 / Max: 373.13 Min: 374.53 / Avg: 378.81 / Max: 381.68 Min: 431.03 / Avg: 432.28 / Max: 432.9 Min: 425.53 / Avg: 432.33 / Max: 436.68 Min: 436.68 / Avg: 439.25 / Max: 442.48 Min: 438.6 / Avg: 439.24 / Max: 440.53 Min: 436.68 / Avg: 439.25 / Max: 442.48 Min: 409.84 / Avg: 411.53 / Max: 413.22 Min: 432.9 / Avg: 432.9 / Max: 432.9 Min: 436.68 / Avg: 439.25 / Max: 442.48 Min: 429.19 / Avg: 432.92 / Max: 436.68 Min: 377.36 / Avg: 380.73 / Max: 383.14 Min: 140.25 / Avg: 140.92 / Max: 142.05 1. (CXX) g++ options: -O3 -fstrict-aliasing -fopenmp
oneDNN This is a test of the Intel oneDNN as an Intel-optimized library for Deep Neural Networks and making use of its built-in benchdnn functionality. The result is the total perf time reported. Intel oneDNN was formerly known as DNNL (Deep Neural Network Library) and MKL-DNN before being rebranded as part of the Intel oneAPI initiative. Learn more via the OpenBenchmarking.org test page.
Result
OpenBenchmarking.org ms, Fewer Is Better oneDNN 2.0 Harness: Deconvolution Batch shapes_1d - Data Type: f32 - Engine: CPU EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 2 4 6 8 10 SE +/- 0.02020, N = 3 SE +/- 0.00923, N = 3 SE +/- 0.01071, N = 3 SE +/- 0.01740, N = 3 SE +/- 0.00832, N = 3 SE +/- 0.01343, N = 3 SE +/- 0.01295, N = 3 SE +/- 0.00152, N = 3 SE +/- 0.01668, N = 15 SE +/- 0.02012, N = 3 SE +/- 0.01627, N = 15 SE +/- 0.00813, N = 3 SE +/- 0.06606, N = 3 SE +/- 0.00961, N = 3 6.12261 4.44077 3.50175 3.28377 2.48977 2.19727 2.22242 2.04866 2.15794 1.98726 2.02231 2.33519 5.03236 2.75743 MIN: 5.93 MIN: 4.2 MIN: 3.1 MIN: 3.08 MIN: 2.4 MIN: 2.12 MIN: 2.06 MIN: 1.99 MIN: 1.99 MIN: 1.87 MIN: 1.84 MIN: 2.08 MIN: 4.86 MIN: 2.63 1. (CXX) g++ options: -O3 -std=c++11 -fopenmp -msse4.1 -fPIC -pie -lpthread
Result Confidence
OpenBenchmarking.org ms, Fewer Is Better oneDNN 2.0 Harness: Deconvolution Batch shapes_1d - Data Type: f32 - Engine: CPU EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 2 4 6 8 10 Min: 6.1 / Avg: 6.12 / Max: 6.16 Min: 4.43 / Avg: 4.44 / Max: 4.46 Min: 3.49 / Avg: 3.5 / Max: 3.52 Min: 3.25 / Avg: 3.28 / Max: 3.3 Min: 2.48 / Avg: 2.49 / Max: 2.51 Min: 2.18 / Avg: 2.2 / Max: 2.22 Min: 2.21 / Avg: 2.22 / Max: 2.25 Min: 2.05 / Avg: 2.05 / Max: 2.05 Min: 2.07 / Avg: 2.16 / Max: 2.28 Min: 1.95 / Avg: 1.99 / Max: 2.02 Min: 1.93 / Avg: 2.02 / Max: 2.15 Min: 2.32 / Avg: 2.34 / Max: 2.35 Min: 4.94 / Avg: 5.03 / Max: 5.16 Min: 2.74 / Avg: 2.76 / Max: 2.77 1. (CXX) g++ options: -O3 -std=c++11 -fopenmp -msse4.1 -fPIC -pie -lpthread
NAS Parallel Benchmarks NPB, NAS Parallel Benchmarks, is a benchmark developed by NASA for high-end computer systems. This test profile currently uses the MPI version of NPB. This test profile offers selecting the different NPB tests/problems and varying problem sizes. Learn more via the OpenBenchmarking.org test page.
Result
OpenBenchmarking.org Total Mop/s, More Is Better NAS Parallel Benchmarks 3.4 Test / Class: LU.C EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 20K 40K 60K 80K 100K SE +/- 12.95, N = 3 SE +/- 24.66, N = 3 SE +/- 22.56, N = 3 SE +/- 3.68, N = 3 SE +/- 81.46, N = 3 SE +/- 106.91, N = 3 SE +/- 26.26, N = 3 SE +/- 207.08, N = 3 SE +/- 82.31, N = 3 SE +/- 281.17, N = 3 SE +/- 298.03, N = 3 SE +/- 34.41, N = 3 SE +/- 31.62, N = 3 SE +/- 82.34, N = 3 33816.48 43321.38 49617.92 61041.27 74421.61 78846.96 86547.28 79644.88 95079.41 99557.23 103985.91 102548.95 43172.51 44891.69 1. (F9X) gfortran options: -O3 -march=native -pthread -lmpi_usempif08 -lmpi_mpifh -lmpi 2. Open MPI 4.0.3
Total Mop/s Per Watt
OpenBenchmarking.org Total Mop/s Per Watt, More Is Better NAS Parallel Benchmarks 3.4 Test / Class: LU.C EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 140 280 420 560 700 486.72 529.25 573.26 593.84 607.37 616.99 572.31 638.72 655.10 602.66 660.15 629.05 419.08 297.36
Result Confidence
OpenBenchmarking.org Total Mop/s, More Is Better NAS Parallel Benchmarks 3.4 Test / Class: LU.C EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 20K 40K 60K 80K 100K Min: 33792.21 / Avg: 33816.48 / Max: 33836.43 Min: 43285.83 / Avg: 43321.38 / Max: 43368.77 Min: 49572.87 / Avg: 49617.92 / Max: 49642.69 Min: 61034.85 / Avg: 61041.27 / Max: 61047.59 Min: 74315 / Avg: 74421.61 / Max: 74581.6 Min: 78710.27 / Avg: 78846.96 / Max: 79057.7 Min: 86498.25 / Avg: 86547.28 / Max: 86588.09 Min: 79399.38 / Avg: 79644.88 / Max: 80056.49 Min: 94922.44 / Avg: 95079.41 / Max: 95200.87 Min: 98994.91 / Avg: 99557.23 / Max: 99842.55 Min: 103567 / Avg: 103985.91 / Max: 104562.59 Min: 102490.22 / Avg: 102548.95 / Max: 102609.37 Min: 43122.35 / Avg: 43172.51 / Max: 43230.93 Min: 44754.21 / Avg: 44891.69 / Max: 45038.95 1. (F9X) gfortran options: -O3 -march=native -pthread -lmpi_usempif08 -lmpi_mpifh -lmpi 2. Open MPI 4.0.3
PostgreSQL pgbench This is a benchmark of PostgreSQL using pgbench for facilitating the database benchmarks. Learn more via the OpenBenchmarking.org test page.
Result
OpenBenchmarking.org TPS, More Is Better PostgreSQL pgbench 13.0 Scaling Factor: 100 - Clients: 250 - Mode: Read Write EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 12K 24K 36K 48K 60K SE +/- 5.29, N = 3 SE +/- 98.97, N = 3 SE +/- 44.96, N = 3 SE +/- 306.40, N = 6 SE +/- 510.25, N = 4 SE +/- 468.05, N = 3 SE +/- 489.37, N = 5 SE +/- 320.52, N = 13 SE +/- 725.42, N = 3 SE +/- 308.59, N = 3 SE +/- 734.82, N = 3 SE +/- 365.68, N = 3 SE +/- 32.87, N = 3 SE +/- 92.29, N = 3 17709 25170 32115 30313 41273 45671 44343 46655 51444 50381 54318 52181 20541 28193 1. (CC) gcc options: -fno-strict-aliasing -fwrapv -O2 -lpgcommon -lpgport -lpq -lpthread -lrt -ldl -lm
Result Confidence
OpenBenchmarking.org TPS, More Is Better PostgreSQL pgbench 13.0 Scaling Factor: 100 - Clients: 250 - Mode: Read Write EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 9K 18K 27K 36K 45K Min: 17702.56 / Avg: 17709.27 / Max: 17719.71 Min: 25002.83 / Avg: 25170.22 / Max: 25345.42 Min: 32033.65 / Avg: 32115.45 / Max: 32188.7 Min: 29631.74 / Avg: 30313.35 / Max: 31648.97 Min: 40219.85 / Avg: 41272.74 / Max: 42149.61 Min: 45084.17 / Avg: 45670.73 / Max: 46595.8 Min: 42733.56 / Avg: 44342.61 / Max: 45416.75 Min: 46038.91 / Avg: 46655.09 / Max: 50394.39 Min: 50134.59 / Avg: 51444.21 / Max: 52639.74 Min: 49982.78 / Avg: 50381.39 / Max: 50988.76 Min: 53010.6 / Avg: 54318.48 / Max: 55552.89 Min: 51458.66 / Avg: 52181.25 / Max: 52640.41 Min: 20498.68 / Avg: 20541.36 / Max: 20606 Min: 28026.73 / Avg: 28193.29 / Max: 28345.44 1. (CC) gcc options: -fno-strict-aliasing -fwrapv -O2 -lpgcommon -lpgport -lpq -lpthread -lrt -ldl -lm
Result
OpenBenchmarking.org ms, Fewer Is Better PostgreSQL pgbench 13.0 Scaling Factor: 100 - Clients: 250 - Mode: Read Write - Average Latency EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 4 8 12 16 20 SE +/- 0.004, N = 3 SE +/- 0.040, N = 3 SE +/- 0.011, N = 3 SE +/- 0.082, N = 6 SE +/- 0.075, N = 4 SE +/- 0.056, N = 3 SE +/- 0.063, N = 5 SE +/- 0.034, N = 13 SE +/- 0.069, N = 3 SE +/- 0.031, N = 3 SE +/- 0.063, N = 3 SE +/- 0.034, N = 3 SE +/- 0.020, N = 3 SE +/- 0.029, N = 3 14.123 9.939 7.791 8.258 6.067 5.481 5.648 5.369 4.872 4.972 4.617 4.804 12.176 8.876 1. (CC) gcc options: -fno-strict-aliasing -fwrapv -O2 -lpgcommon -lpgport -lpq -lpthread -lrt -ldl -lm
Result Confidence
OpenBenchmarking.org ms, Fewer Is Better PostgreSQL pgbench 13.0 Scaling Factor: 100 - Clients: 250 - Mode: Read Write - Average Latency EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 4 8 12 16 20 Min: 14.12 / Avg: 14.12 / Max: 14.13 Min: 9.87 / Avg: 9.94 / Max: 10.01 Min: 7.77 / Avg: 7.79 / Max: 7.81 Min: 7.91 / Avg: 8.26 / Max: 8.44 Min: 5.94 / Avg: 6.07 / Max: 6.22 Min: 5.37 / Avg: 5.48 / Max: 5.55 Min: 5.51 / Avg: 5.65 / Max: 5.86 Min: 4.97 / Avg: 5.37 / Max: 5.44 Min: 4.76 / Avg: 4.87 / Max: 5 Min: 4.91 / Avg: 4.97 / Max: 5.01 Min: 4.51 / Avg: 4.62 / Max: 4.73 Min: 4.76 / Avg: 4.8 / Max: 4.87 Min: 12.14 / Avg: 12.18 / Max: 12.2 Min: 8.83 / Avg: 8.88 / Max: 8.93 1. (CC) gcc options: -fno-strict-aliasing -fwrapv -O2 -lpgcommon -lpgport -lpq -lpthread -lrt -ldl -lm
dav1d Dav1d is an open-source, speedy AV1 video decoder. This test profile times how long it takes to decode sample AV1 video content. Learn more via the OpenBenchmarking.org test page.
Result
OpenBenchmarking.org FPS, More Is Better dav1d 0.8.1 Video Input: Summer Nature 4K EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 100 200 300 400 500 SE +/- 0.14, N = 3 SE +/- 0.16, N = 3 SE +/- 0.22, N = 3 SE +/- 0.23, N = 3 SE +/- 0.61, N = 3 SE +/- 0.16, N = 3 SE +/- 0.29, N = 3 SE +/- 0.75, N = 3 SE +/- 0.66, N = 3 SE +/- 0.17, N = 3 SE +/- 0.74, N = 3 SE +/- 0.34, N = 3 SE +/- 0.27, N = 3 SE +/- 0.46, N = 3 150.43 203.40 239.84 245.60 328.54 361.72 349.99 367.19 406.93 416.96 457.27 437.31 168.17 244.17 MIN: 141.09 / MAX: 170.16 MIN: 187.66 / MAX: 232.21 MIN: 211 / MAX: 275.93 MIN: 210.68 / MAX: 281.84 MIN: 249.05 / MAX: 376.65 MIN: 287.95 / MAX: 416.23 MIN: 266.02 / MAX: 399.72 MIN: 288.65 / MAX: 424.55 MIN: 257.69 / MAX: 456.39 MIN: 251.44 / MAX: 465 MIN: 225.33 / MAX: 494.73 MIN: 217.67 / MAX: 473.18 MIN: 157.91 / MAX: 191.26 MIN: 200.55 / MAX: 270.42 1. (CC) gcc options: -pthread
FPS Per Watt
OpenBenchmarking.org FPS Per Watt, More Is Better dav1d 0.8.1 Video Input: Summer Nature 4K EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 1.107 2.214 3.321 4.428 5.535 2.51 3.13 3.73 3.32 4.14 4.62 3.54 4.91 4.65 4.61 4.92 4.45 2.00 2.06
Result Confidence
OpenBenchmarking.org FPS, More Is Better dav1d 0.8.1 Video Input: Summer Nature 4K EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 80 160 240 320 400 Min: 150.28 / Avg: 150.43 / Max: 150.7 Min: 203.1 / Avg: 203.4 / Max: 203.66 Min: 239.57 / Avg: 239.84 / Max: 240.27 Min: 245.22 / Avg: 245.6 / Max: 246 Min: 327.42 / Avg: 328.54 / Max: 329.53 Min: 361.4 / Avg: 361.72 / Max: 361.91 Min: 349.42 / Avg: 349.99 / Max: 350.39 Min: 365.83 / Avg: 367.19 / Max: 368.43 Min: 405.7 / Avg: 406.93 / Max: 407.97 Min: 416.77 / Avg: 416.96 / Max: 417.29 Min: 455.84 / Avg: 457.27 / Max: 458.3 Min: 436.66 / Avg: 437.31 / Max: 437.79 Min: 167.67 / Avg: 168.17 / Max: 168.6 Min: 243.51 / Avg: 244.17 / Max: 245.05 1. (CC) gcc options: -pthread
Kvazaar This is a test of Kvazaar as a CPU-based H.265 video encoder written in the C programming language and optimized in Assembly. Kvazaar is the winner of the 2016 ACM Open-Source Software Competition and developed at the Ultra Video Group, Tampere University, Finland. Learn more via the OpenBenchmarking.org test page.
Result
OpenBenchmarking.org Frames Per Second, More Is Better Kvazaar 2.0 Video Input: Bosphorus 4K - Video Preset: Very Fast EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 9 18 27 36 45 SE +/- 0.01, N = 3 SE +/- 0.01, N = 3 SE +/- 0.03, N = 3 SE +/- 0.01, N = 3 SE +/- 0.05, N = 3 SE +/- 0.01, N = 3 SE +/- 0.01, N = 3 SE +/- 0.01, N = 3 SE +/- 0.02, N = 3 SE +/- 0.03, N = 4 SE +/- 0.01, N = 4 SE +/- 0.04, N = 3 SE +/- 0.02, N = 3 SE +/- 0.01, N = 3 12.98 17.83 21.70 22.94 26.61 33.25 32.72 35.06 35.81 37.39 39.15 36.07 15.56 26.31 1. (CC) gcc options: -pthread -ftree-vectorize -fvisibility=hidden -O2 -lpthread -lm -lrt
Frames Per Second Per Watt
OpenBenchmarking.org Frames Per Second Per Watt, More Is Better Kvazaar 2.0 Video Input: Bosphorus 4K - Video Preset: Very Fast EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 0.0608 0.1216 0.1824 0.2432 0.304 0.17 0.19 0.24 0.21 0.21 0.26 0.23 0.25 0.26 0.24 0.27 0.25 0.13 0.13
Result Confidence
OpenBenchmarking.org Frames Per Second, More Is Better Kvazaar 2.0 Video Input: Bosphorus 4K - Video Preset: Very Fast EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 8 16 24 32 40 Min: 12.97 / Avg: 12.98 / Max: 12.99 Min: 17.82 / Avg: 17.83 / Max: 17.84 Min: 21.66 / Avg: 21.7 / Max: 21.75 Min: 22.92 / Avg: 22.94 / Max: 22.97 Min: 26.56 / Avg: 26.61 / Max: 26.7 Min: 33.24 / Avg: 33.25 / Max: 33.26 Min: 32.69 / Avg: 32.72 / Max: 32.73 Min: 35.04 / Avg: 35.06 / Max: 35.09 Min: 35.77 / Avg: 35.81 / Max: 35.84 Min: 37.31 / Avg: 37.39 / Max: 37.44 Min: 39.12 / Avg: 39.15 / Max: 39.19 Min: 36 / Avg: 36.07 / Max: 36.11 Min: 15.54 / Avg: 15.56 / Max: 15.61 Min: 26.29 / Avg: 26.31 / Max: 26.33 1. (CC) gcc options: -pthread -ftree-vectorize -fvisibility=hidden -O2 -lpthread -lm -lrt
Basis Universal Basis Universal is a GPU texture codoec. This test times how long it takes to convert sRGB PNGs into Basis Univeral assets with various settings. Learn more via the OpenBenchmarking.org test page.
Result
OpenBenchmarking.org Seconds, Fewer Is Better Basis Universal 1.12 Settings: UASTC Level 2 EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 9 18 27 36 45 SE +/- 0.00, N = 3 SE +/- 0.01, N = 3 SE +/- 0.02, N = 3 SE +/- 0.02, N = 3 SE +/- 0.01, N = 3 SE +/- 0.02, N = 4 SE +/- 0.01, N = 3 SE +/- 0.00, N = 4 SE +/- 0.01, N = 4 SE +/- 0.00, N = 4 SE +/- 0.01, N = 4 SE +/- 0.00, N = 3 SE +/- 0.00, N = 3 39.67 29.24 24.24 23.34 18.17 16.31 16.70 15.64 14.24 13.21 13.30 32.63 19.86 1. (CXX) g++ options: -std=c++11 -fvisibility=hidden -fPIC -fno-strict-aliasing -O3 -rdynamic -lm -lpthread
Result Confidence
OpenBenchmarking.org Seconds, Fewer Is Better Basis Universal 1.12 Settings: UASTC Level 2 EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 8 16 24 32 40 Min: 39.66 / Avg: 39.67 / Max: 39.67 Min: 29.23 / Avg: 29.24 / Max: 29.27 Min: 24.19 / Avg: 24.24 / Max: 24.27 Min: 23.32 / Avg: 23.34 / Max: 23.38 Min: 18.16 / Avg: 18.17 / Max: 18.17 Min: 16.28 / Avg: 16.31 / Max: 16.38 Min: 16.69 / Avg: 16.7 / Max: 16.71 Min: 15.63 / Avg: 15.64 / Max: 15.64 Min: 14.23 / Avg: 14.24 / Max: 14.25 Min: 13.2 / Avg: 13.21 / Max: 13.22 Min: 13.28 / Avg: 13.3 / Max: 13.33 Min: 32.63 / Avg: 32.63 / Max: 32.64 Min: 19.86 / Avg: 19.86 / Max: 19.87 1. (CXX) g++ options: -std=c++11 -fvisibility=hidden -fPIC -fno-strict-aliasing -O3 -rdynamic -lm -lpthread
miniFE MiniFE Finite Element is an application for unstructured implicit finite element codes. Learn more via the OpenBenchmarking.org test page.
Result
OpenBenchmarking.org CG Mflops, More Is Better miniFE 2.2 Problem Size: Small EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 4K 8K 12K 16K 20K SE +/- 10.40, N = 3 SE +/- 16.20, N = 3 SE +/- 1.40, N = 3 SE +/- 24.99, N = 3 SE +/- 5.98, N = 3 SE +/- 22.39, N = 3 SE +/- 8.80, N = 3 SE +/- 5.12, N = 3 SE +/- 68.31, N = 3 SE +/- 29.81, N = 3 SE +/- 5.01, N = 3 SE +/- 34.52, N = 3 SE +/- 8.04, N = 3 SE +/- 66.01, N = 14 10156.60 10066.60 10003.60 17082.40 16743.60 16649.50 19645.40 16649.70 18424.10 19436.30 19256.70 19155.40 17351.20 6787.06 1. (CXX) g++ options: -O3 -fopenmp -pthread -lmpi_cxx -lmpi
CG Mflops Per Watt
OpenBenchmarking.org CG Mflops Per Watt, More Is Better miniFE 2.2 Problem Size: Small EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 40 80 120 160 200 147.34 132.41 128.37 181.39 160.96 152.21 152.28 157.73 149.38 140.60 142.84 139.02 167.09 52.66
Result Confidence
OpenBenchmarking.org CG Mflops, More Is Better miniFE 2.2 Problem Size: Small EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 3K 6K 9K 12K 15K Min: 10136.2 / Avg: 10156.6 / Max: 10170.3 Min: 10034.4 / Avg: 10066.63 / Max: 10085.6 Min: 10000.9 / Avg: 10003.63 / Max: 10005.5 Min: 17033.7 / Avg: 17082.43 / Max: 17116.4 Min: 16735 / Avg: 16743.6 / Max: 16755.1 Min: 16604.7 / Avg: 16649.47 / Max: 16672.4 Min: 19632.2 / Avg: 19645.43 / Max: 19662.1 Min: 16643.8 / Avg: 16649.7 / Max: 16659.9 Min: 18336.1 / Avg: 18424.1 / Max: 18558.6 Min: 19380.5 / Avg: 19436.3 / Max: 19482.4 Min: 19250.6 / Avg: 19256.67 / Max: 19266.6 Min: 19088.2 / Avg: 19155.37 / Max: 19202.8 Min: 17335.9 / Avg: 17351.17 / Max: 17363.2 Min: 5976.74 / Avg: 6787.06 / Max: 6965.65 1. (CXX) g++ options: -O3 -fopenmp -pthread -lmpi_cxx -lmpi
oneDNN This is a test of the Intel oneDNN as an Intel-optimized library for Deep Neural Networks and making use of its built-in benchdnn functionality. The result is the total perf time reported. Intel oneDNN was formerly known as DNNL (Deep Neural Network Library) and MKL-DNN before being rebranded as part of the Intel oneAPI initiative. Learn more via the OpenBenchmarking.org test page.
Result
OpenBenchmarking.org ms, Fewer Is Better oneDNN 2.0 Harness: IP Shapes 1D - Data Type: u8s8f32 - Engine: CPU EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 0.7576 1.5152 2.2728 3.0304 3.788 SE +/- 0.00108, N = 4 SE +/- 0.00157, N = 4 SE +/- 0.00098, N = 4 SE +/- 0.00055, N = 4 SE +/- 0.00089, N = 4 SE +/- 0.00119, N = 4 SE +/- 0.00172, N = 4 SE +/- 0.00302, N = 4 SE +/- 0.01048, N = 4 SE +/- 0.00473, N = 4 SE +/- 0.01452, N = 4 SE +/- 0.01081, N = 4 SE +/- 0.00055, N = 4 SE +/- 0.00643, N = 4 3.36727 2.43760 1.80647 1.74975 1.43487 1.18204 1.21230 1.16402 1.73007 1.66750 1.74199 1.80598 2.79034 1.52143 MIN: 3.3 MIN: 2.4 MIN: 1.75 MIN: 1.72 MIN: 1.4 MIN: 1.13 MIN: 1.14 MIN: 1.12 MIN: 1.5 MIN: 1.4 MIN: 1.45 MIN: 1.54 MIN: 2.71 MIN: 1.48 1. (CXX) g++ options: -O3 -std=c++11 -fopenmp -msse4.1 -fPIC -pie -lpthread
Result Confidence
OpenBenchmarking.org ms, Fewer Is Better oneDNN 2.0 Harness: IP Shapes 1D - Data Type: u8s8f32 - Engine: CPU EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 2 4 6 8 10 Min: 3.37 / Avg: 3.37 / Max: 3.37 Min: 2.43 / Avg: 2.44 / Max: 2.44 Min: 1.8 / Avg: 1.81 / Max: 1.81 Min: 1.75 / Avg: 1.75 / Max: 1.75 Min: 1.43 / Avg: 1.43 / Max: 1.44 Min: 1.18 / Avg: 1.18 / Max: 1.19 Min: 1.21 / Avg: 1.21 / Max: 1.22 Min: 1.16 / Avg: 1.16 / Max: 1.17 Min: 1.72 / Avg: 1.73 / Max: 1.76 Min: 1.65 / Avg: 1.67 / Max: 1.67 Min: 1.72 / Avg: 1.74 / Max: 1.78 Min: 1.78 / Avg: 1.81 / Max: 1.83 Min: 2.79 / Avg: 2.79 / Max: 2.79 Min: 1.51 / Avg: 1.52 / Max: 1.54 1. (CXX) g++ options: -O3 -std=c++11 -fopenmp -msse4.1 -fPIC -pie -lpthread
YafaRay YafaRay is an open-source physically based montecarlo ray-tracing engine. Learn more via the OpenBenchmarking.org test page.
Result
OpenBenchmarking.org Seconds, Fewer Is Better YafaRay 3.4.1 Total Time For Sample Scene EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 40 80 120 160 200 SE +/- 0.97, N = 3 SE +/- 0.80, N = 3 SE +/- 1.06, N = 3 SE +/- 1.37, N = 3 SE +/- 1.05, N = 3 SE +/- 0.38, N = 3 SE +/- 0.21, N = 3 SE +/- 0.43, N = 3 SE +/- 0.43, N = 14 SE +/- 0.60, N = 15 SE +/- 0.74, N = 3 SE +/- 0.72, N = 15 SE +/- 0.41, N = 3 SE +/- 1.73, N = 3 186.18 131.03 102.53 110.94 80.50 70.70 85.56 64.92 64.88 67.66 66.48 67.25 172.35 127.45 1. (CXX) g++ options: -std=c++11 -O3 -ffast-math -rdynamic -ldl -lImath -lIlmImf -lIex -lHalf -lz -lIlmThread -lxml2 -lfreetype -lpthread
Result Confidence
OpenBenchmarking.org Seconds, Fewer Is Better YafaRay 3.4.1 Total Time For Sample Scene EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 30 60 90 120 150 Min: 184.7 / Avg: 186.18 / Max: 188.01 Min: 129.53 / Avg: 131.03 / Max: 132.24 Min: 100.59 / Avg: 102.53 / Max: 104.24 Min: 108.85 / Avg: 110.94 / Max: 113.51 Min: 79.1 / Avg: 80.5 / Max: 82.54 Min: 69.95 / Avg: 70.7 / Max: 71.18 Min: 85.16 / Avg: 85.56 / Max: 85.86 Min: 64.15 / Avg: 64.92 / Max: 65.62 Min: 61.7 / Avg: 64.88 / Max: 67.09 Min: 64.7 / Avg: 67.66 / Max: 71.97 Min: 65.27 / Avg: 66.48 / Max: 67.84 Min: 61.8 / Avg: 67.25 / Max: 71.05 Min: 171.56 / Avg: 172.35 / Max: 172.91 Min: 124 / Avg: 127.45 / Max: 129.28 1. (CXX) g++ options: -std=c++11 -O3 -ffast-math -rdynamic -ldl -lImath -lIlmImf -lIex -lHalf -lz -lIlmThread -lxml2 -lfreetype -lpthread
PostgreSQL pgbench This is a benchmark of PostgreSQL using pgbench for facilitating the database benchmarks. Learn more via the OpenBenchmarking.org test page.
Result
OpenBenchmarking.org TPS, More Is Better PostgreSQL pgbench 13.0 Scaling Factor: 100 - Clients: 100 - Mode: Read Write EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 13K 26K 39K 52K 65K SE +/- 18.98, N = 3 SE +/- 91.21, N = 3 SE +/- 309.38, N = 15 SE +/- 447.90, N = 12 SE +/- 387.48, N = 3 SE +/- 406.89, N = 15 SE +/- 174.06, N = 3 SE +/- 676.58, N = 3 SE +/- 709.54, N = 3 SE +/- 539.78, N = 3 SE +/- 229.52, N = 3 SE +/- 486.09, N = 3 SE +/- 63.04, N = 3 SE +/- 337.73, N = 15 21334 31896 38586 38458 47662 51794 47615 52325 56945 58889 60949 55699 24137 37152 1. (CC) gcc options: -fno-strict-aliasing -fwrapv -O2 -lpgcommon -lpgport -lpq -lpthread -lrt -ldl -lm
Result Confidence
OpenBenchmarking.org TPS, More Is Better PostgreSQL pgbench 13.0 Scaling Factor: 100 - Clients: 100 - Mode: Read Write EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 11K 22K 33K 44K 55K Min: 21301.63 / Avg: 21333.63 / Max: 21367.31 Min: 31714.82 / Avg: 31895.88 / Max: 32005.63 Min: 36728.54 / Avg: 38586.13 / Max: 40215.78 Min: 36956.38 / Avg: 38457.92 / Max: 41415.74 Min: 47265.69 / Avg: 47661.51 / Max: 48436.42 Min: 49652.94 / Avg: 51793.61 / Max: 54520.15 Min: 47424.2 / Avg: 47614.55 / Max: 47962.14 Min: 51433.97 / Avg: 52325.08 / Max: 53652.51 Min: 55594.88 / Avg: 56944.6 / Max: 57999 Min: 57853.09 / Avg: 58888.92 / Max: 59670.2 Min: 60636.54 / Avg: 60949.34 / Max: 61396.7 Min: 54882.69 / Avg: 55699.33 / Max: 56564.47 Min: 24025.48 / Avg: 24137.33 / Max: 24243.66 Min: 35001.56 / Avg: 37152.01 / Max: 39986.56 1. (CC) gcc options: -fno-strict-aliasing -fwrapv -O2 -lpgcommon -lpgport -lpq -lpthread -lrt -ldl -lm
Timed FFmpeg Compilation This test times how long it takes to build the FFmpeg multimedia library. Learn more via the OpenBenchmarking.org test page.
Result
OpenBenchmarking.org Seconds, Fewer Is Better Timed FFmpeg Compilation 4.2.2 Time To Compile EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 15 30 45 60 75 SE +/- 0.06, N = 3 SE +/- 0.10, N = 3 SE +/- 0.06, N = 3 SE +/- 0.06, N = 3 SE +/- 0.03, N = 3 SE +/- 0.03, N = 3 SE +/- 0.07, N = 3 SE +/- 0.02, N = 3 SE +/- 0.03, N = 3 SE +/- 0.02, N = 3 SE +/- 0.02, N = 3 SE +/- 0.06, N = 3 SE +/- 0.01, N = 3 SE +/- 0.04, N = 3 68.50 49.92 42.86 39.74 32.07 29.12 29.23 27.86 25.50 25.21 23.98 24.03 54.15 33.98
Result Confidence
OpenBenchmarking.org Seconds, Fewer Is Better Timed FFmpeg Compilation 4.2.2 Time To Compile EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 13 26 39 52 65 Min: 68.42 / Avg: 68.5 / Max: 68.63 Min: 49.75 / Avg: 49.92 / Max: 50.11 Min: 42.78 / Avg: 42.86 / Max: 42.98 Min: 39.64 / Avg: 39.74 / Max: 39.84 Min: 32.01 / Avg: 32.07 / Max: 32.1 Min: 29.07 / Avg: 29.12 / Max: 29.19 Min: 29.13 / Avg: 29.23 / Max: 29.37 Min: 27.84 / Avg: 27.86 / Max: 27.89 Min: 25.47 / Avg: 25.5 / Max: 25.56 Min: 25.18 / Avg: 25.21 / Max: 25.25 Min: 23.93 / Avg: 23.98 / Max: 24.01 Min: 23.95 / Avg: 24.03 / Max: 24.14 Min: 54.13 / Avg: 54.15 / Max: 54.16 Min: 33.92 / Avg: 33.98 / Max: 34.07
PostgreSQL pgbench This is a benchmark of PostgreSQL using pgbench for facilitating the database benchmarks. Learn more via the OpenBenchmarking.org test page.
Result
OpenBenchmarking.org ms, Fewer Is Better PostgreSQL pgbench 13.0 Scaling Factor: 100 - Clients: 100 - Mode: Read Write - Average Latency EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 1.0553 2.1106 3.1659 4.2212 5.2765 SE +/- 0.004, N = 3 SE +/- 0.009, N = 3 SE +/- 0.021, N = 15 SE +/- 0.029, N = 12 SE +/- 0.017, N = 3 SE +/- 0.015, N = 15 SE +/- 0.008, N = 3 SE +/- 0.024, N = 3 SE +/- 0.022, N = 3 SE +/- 0.016, N = 3 SE +/- 0.006, N = 3 SE +/- 0.016, N = 3 SE +/- 0.011, N = 3 SE +/- 0.024, N = 15 4.690 3.137 2.596 2.606 2.101 1.935 2.103 1.915 1.759 1.701 1.643 1.798 4.145 2.697 1. (CC) gcc options: -fno-strict-aliasing -fwrapv -O2 -lpgcommon -lpgport -lpq -lpthread -lrt -ldl -lm
Result Confidence
OpenBenchmarking.org ms, Fewer Is Better PostgreSQL pgbench 13.0 Scaling Factor: 100 - Clients: 100 - Mode: Read Write - Average Latency EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 2 4 6 8 10 Min: 4.68 / Avg: 4.69 / Max: 4.7 Min: 3.13 / Avg: 3.14 / Max: 3.16 Min: 2.49 / Avg: 2.6 / Max: 2.73 Min: 2.42 / Avg: 2.61 / Max: 2.71 Min: 2.07 / Avg: 2.1 / Max: 2.12 Min: 1.84 / Avg: 1.94 / Max: 2.02 Min: 2.09 / Avg: 2.1 / Max: 2.11 Min: 1.87 / Avg: 1.91 / Max: 1.95 Min: 1.73 / Avg: 1.76 / Max: 1.8 Min: 1.68 / Avg: 1.7 / Max: 1.73 Min: 1.63 / Avg: 1.64 / Max: 1.65 Min: 1.77 / Avg: 1.8 / Max: 1.82 Min: 4.13 / Avg: 4.14 / Max: 4.16 Min: 2.5 / Avg: 2.7 / Max: 2.86 1. (CC) gcc options: -fno-strict-aliasing -fwrapv -O2 -lpgcommon -lpgport -lpq -lpthread -lrt -ldl -lm
TTSIOD 3D Renderer A portable GPL 3D software renderer that supports OpenMP and Intel Threading Building Blocks with many different rendering modes. This version does not use OpenGL but is entirely CPU/software based. Learn more via the OpenBenchmarking.org test page.
Result
OpenBenchmarking.org FPS, More Is Better TTSIOD 3D Renderer 2.3b Phong Rendering With Soft-Shadow Mapping EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 200 400 600 800 1000 SE +/- 0.73, N = 3 SE +/- 0.85, N = 3 SE +/- 1.34, N = 3 SE +/- 1.71, N = 3 SE +/- 2.84, N = 3 SE +/- 2.79, N = 3 SE +/- 3.72, N = 3 SE +/- 1.67, N = 3 SE +/- 6.72, N = 12 SE +/- 12.71, N = 3 SE +/- 3.57, N = 3 SE +/- 4.91, N = 3 SE +/- 0.88, N = 3 SE +/- 0.21, N = 3 327.45 457.13 563.20 551.97 721.30 857.99 849.27 858.47 933.04 889.39 873.42 792.50 359.54 589.10 1. (CXX) g++ options: -O3 -fomit-frame-pointer -ffast-math -mtune=native -flto -msse -mrecip -mfpmath=sse -msse2 -mssse3 -lSDL -fopenmp -fwhole-program -lstdc++
FPS Per Watt
OpenBenchmarking.org FPS Per Watt, More Is Better TTSIOD 3D Renderer 2.3b Phong Rendering With Soft-Shadow Mapping EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 3 6 9 12 15 5.67 6.96 8.15 7.06 7.79 8.75 7.17 9.07 8.10 6.80 6.31 5.54 4.41 4.63
Result Confidence
OpenBenchmarking.org FPS, More Is Better TTSIOD 3D Renderer 2.3b Phong Rendering With Soft-Shadow Mapping EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 160 320 480 640 800 Min: 326.51 / Avg: 327.45 / Max: 328.88 Min: 455.79 / Avg: 457.13 / Max: 458.72 Min: 561.8 / Avg: 563.2 / Max: 565.87 Min: 548.55 / Avg: 551.97 / Max: 553.8 Min: 716.79 / Avg: 721.3 / Max: 726.53 Min: 853.39 / Avg: 857.99 / Max: 863.04 Min: 843.53 / Avg: 849.27 / Max: 856.24 Min: 855.29 / Avg: 858.47 / Max: 860.96 Min: 896.62 / Avg: 933.04 / Max: 961.45 Min: 864.6 / Avg: 889.39 / Max: 906.7 Min: 866.7 / Avg: 873.42 / Max: 878.89 Min: 782.72 / Avg: 792.5 / Max: 798.09 Min: 357.91 / Avg: 359.54 / Max: 360.93 Min: 588.69 / Avg: 589.1 / Max: 589.38 1. (CXX) g++ options: -O3 -fomit-frame-pointer -ffast-math -mtune=native -flto -msse -mrecip -mfpmath=sse -msse2 -mssse3 -lSDL -fopenmp -fwhole-program -lstdc++
dav1d Dav1d is an open-source, speedy AV1 video decoder. This test profile times how long it takes to decode sample AV1 video content. Learn more via the OpenBenchmarking.org test page.
Result
OpenBenchmarking.org FPS, More Is Better dav1d 0.8.1 Video Input: Summer Nature 1080p EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 300 600 900 1200 1500 SE +/- 0.82, N = 3 SE +/- 0.90, N = 3 SE +/- 0.46, N = 3 SE +/- 0.73, N = 3 SE +/- 2.68, N = 3 SE +/- 1.87, N = 3 SE +/- 1.15, N = 3 SE +/- 0.47, N = 3 SE +/- 3.10, N = 3 SE +/- 1.10, N = 3 SE +/- 3.75, N = 3 SE +/- 1.60, N = 3 SE +/- 0.28, N = 3 SE +/- 1.44, N = 3 419.19 555.11 644.23 634.51 847.40 932.75 880.57 937.44 1044.25 1070.09 1193.66 1050.99 453.36 651.36 MIN: 370.7 / MAX: 456.84 MIN: 463.4 / MAX: 605.59 MIN: 503.48 / MAX: 704.1 MIN: 482.67 / MAX: 693.38 MIN: 566.75 / MAX: 939.62 MIN: 659.65 / MAX: 1047.61 MIN: 567.79 / MAX: 985.57 MIN: 659.51 / MAX: 1052.41 MIN: 554.63 / MAX: 1157.48 MIN: 574.58 / MAX: 1186.8 MIN: 500.62 / MAX: 1329.43 MIN: 478.51 / MAX: 1166.67 MIN: 400.76 / MAX: 488.59 MIN: 480.87 / MAX: 706.63 1. (CC) gcc options: -pthread
FPS Per Watt
OpenBenchmarking.org FPS Per Watt, More Is Better dav1d 0.8.1 Video Input: Summer Nature 1080p EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 4 8 12 16 20 8.74 11.35 12.88 10.93 14.37 15.80 11.30 16.36 15.42 14.70 15.54 13.08 7.06 7.40
Result Confidence
OpenBenchmarking.org FPS, More Is Better dav1d 0.8.1 Video Input: Summer Nature 1080p EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 200 400 600 800 1000 Min: 417.79 / Avg: 419.19 / Max: 420.62 Min: 553.68 / Avg: 555.11 / Max: 556.76 Min: 643.31 / Avg: 644.23 / Max: 644.7 Min: 633.06 / Avg: 634.51 / Max: 635.27 Min: 842.07 / Avg: 847.4 / Max: 850.64 Min: 929.58 / Avg: 932.75 / Max: 936.06 Min: 879.23 / Avg: 880.57 / Max: 882.86 Min: 936.52 / Avg: 937.44 / Max: 938.02 Min: 1038.12 / Avg: 1044.25 / Max: 1048.12 Min: 1068.71 / Avg: 1070.09 / Max: 1072.27 Min: 1186.16 / Avg: 1193.66 / Max: 1197.47 Min: 1048.15 / Avg: 1050.99 / Max: 1053.7 Min: 452.94 / Avg: 453.36 / Max: 453.9 Min: 648.52 / Avg: 651.36 / Max: 653.25 1. (CC) gcc options: -pthread
x265 This is a simple test of the x265 encoder run on the CPU with 1080p and 4K options for H.265 video encode performance with x265. Learn more via the OpenBenchmarking.org test page.
Result
OpenBenchmarking.org Frames Per Second, More Is Better x265 3.4 Video Input: Bosphorus 4K EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 6 12 18 24 30 SE +/- 0.09, N = 3 SE +/- 0.07, N = 3 SE +/- 0.04, N = 3 SE +/- 0.09, N = 3 SE +/- 0.08, N = 3 SE +/- 0.03, N = 3 SE +/- 0.05, N = 3 SE +/- 0.07, N = 3 SE +/- 0.06, N = 3 SE +/- 0.08, N = 3 SE +/- 0.21, N = 3 SE +/- 0.08, N = 3 SE +/- 0.13, N = 4 SE +/- 0.12, N = 3 9.20 17.09 20.03 20.44 23.84 25.13 23.71 25.21 25.36 25.23 25.65 25.04 10.20 20.00 1. (CXX) g++ options: -O3 -rdynamic -lpthread -lrt -ldl -lnuma
Frames Per Second Per Watt
OpenBenchmarking.org Frames Per Second Per Watt, More Is Better x265 3.4 Video Input: Bosphorus 4K EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 0.0518 0.1036 0.1554 0.2072 0.259 0.14 0.20 0.23 0.20 0.21 0.22 0.18 0.23 0.21 0.18 0.20 0.18 0.11 0.12
Result Confidence
OpenBenchmarking.org Frames Per Second, More Is Better x265 3.4 Video Input: Bosphorus 4K EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 6 12 18 24 30 Min: 9.07 / Avg: 9.2 / Max: 9.37 Min: 16.96 / Avg: 17.09 / Max: 17.21 Min: 19.97 / Avg: 20.03 / Max: 20.1 Min: 20.34 / Avg: 20.44 / Max: 20.61 Min: 23.72 / Avg: 23.84 / Max: 23.98 Min: 25.08 / Avg: 25.13 / Max: 25.16 Min: 23.64 / Avg: 23.71 / Max: 23.81 Min: 25.09 / Avg: 25.21 / Max: 25.34 Min: 25.3 / Avg: 25.36 / Max: 25.48 Min: 25.14 / Avg: 25.23 / Max: 25.39 Min: 25.41 / Avg: 25.65 / Max: 26.06 Min: 24.94 / Avg: 25.04 / Max: 25.19 Min: 9.85 / Avg: 10.2 / Max: 10.45 Min: 19.78 / Avg: 20 / Max: 20.2 1. (CXX) g++ options: -O3 -rdynamic -lpthread -lrt -ldl -lnuma
Timed Godot Game Engine Compilation This test times how long it takes to compile the Godot Game Engine. Godot is a popular, open-source, cross-platform 2D/3D game engine and is built using the SCons build system and targeting the X11 platform. Learn more via the OpenBenchmarking.org test page.
Result
OpenBenchmarking.org Seconds, Fewer Is Better Timed Godot Game Engine Compilation 3.2.3 Time To Compile EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 40 80 120 160 200 SE +/- 0.30, N = 3 SE +/- 0.14, N = 3 SE +/- 0.26, N = 3 SE +/- 0.07, N = 3 SE +/- 0.12, N = 3 SE +/- 0.17, N = 3 SE +/- 0.10, N = 3 SE +/- 0.10, N = 3 SE +/- 0.17, N = 3 SE +/- 0.07, N = 3 SE +/- 0.17, N = 3 SE +/- 0.31, N = 3 SE +/- 0.21, N = 3 SE +/- 0.32, N = 3 172.13 122.41 103.74 96.77 76.16 69.42 69.62 66.57 62.48 61.81 62.27 62.56 136.62 84.21
Result Confidence
OpenBenchmarking.org Seconds, Fewer Is Better Timed Godot Game Engine Compilation 3.2.3 Time To Compile EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 30 60 90 120 150 Min: 171.71 / Avg: 172.13 / Max: 172.7 Min: 122.19 / Avg: 122.41 / Max: 122.67 Min: 103.26 / Avg: 103.74 / Max: 104.13 Min: 96.64 / Avg: 96.77 / Max: 96.88 Min: 75.93 / Avg: 76.16 / Max: 76.36 Min: 69.16 / Avg: 69.42 / Max: 69.74 Min: 69.45 / Avg: 69.62 / Max: 69.79 Min: 66.45 / Avg: 66.57 / Max: 66.76 Min: 62.24 / Avg: 62.48 / Max: 62.81 Min: 61.69 / Avg: 61.81 / Max: 61.9 Min: 61.99 / Avg: 62.27 / Max: 62.58 Min: 62.22 / Avg: 62.56 / Max: 63.19 Min: 136.37 / Avg: 136.62 / Max: 137.03 Min: 83.58 / Avg: 84.21 / Max: 84.54
SVT-AV1 This is a test of the Intel Open Visual Cloud Scalable Video Technology SVT-AV1 CPU-based multi-threaded video encoder for the AV1 video format with a sample 1080p YUV video file. Learn more via the OpenBenchmarking.org test page.
Result
OpenBenchmarking.org Frames Per Second, More Is Better SVT-AV1 0.8 Encoder Mode: Enc Mode 4 - Input: 1080p EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 2 4 6 8 10 SE +/- 0.008, N = 3 SE +/- 0.008, N = 3 SE +/- 0.006, N = 3 SE +/- 0.017, N = 3 SE +/- 0.043, N = 3 SE +/- 0.032, N = 3 SE +/- 0.048, N = 4 SE +/- 0.032, N = 4 SE +/- 0.012, N = 3 SE +/- 0.039, N = 4 SE +/- 0.060, N = 3 SE +/- 0.003, N = 3 SE +/- 0.023, N = 3 SE +/- 0.035, N = 4 2.536 3.593 4.225 4.506 5.563 5.866 5.958 6.091 6.494 6.678 6.966 6.752 3.184 5.333 1. (CXX) g++ options: -O3 -fcommon -fPIE -fPIC -pie
Frames Per Second Per Watt
OpenBenchmarking.org Frames Per Second Per Watt, More Is Better SVT-AV1 0.8 Encoder Mode: Enc Mode 4 - Input: 1080p EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 0.0135 0.027 0.0405 0.054 0.0675 0.04 0.04 0.05 0.05 0.05 0.06 0.05 0.06 0.06 0.06 0.06 0.06 0.03 0.03
Result Confidence
OpenBenchmarking.org Frames Per Second, More Is Better SVT-AV1 0.8 Encoder Mode: Enc Mode 4 - Input: 1080p EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 3 6 9 12 15 Min: 2.52 / Avg: 2.54 / Max: 2.55 Min: 3.58 / Avg: 3.59 / Max: 3.61 Min: 4.22 / Avg: 4.23 / Max: 4.24 Min: 4.47 / Avg: 4.51 / Max: 4.53 Min: 5.48 / Avg: 5.56 / Max: 5.61 Min: 5.8 / Avg: 5.87 / Max: 5.91 Min: 5.88 / Avg: 5.96 / Max: 6.09 Min: 6.04 / Avg: 6.09 / Max: 6.18 Min: 6.47 / Avg: 6.49 / Max: 6.51 Min: 6.57 / Avg: 6.68 / Max: 6.75 Min: 6.88 / Avg: 6.97 / Max: 7.08 Min: 6.75 / Avg: 6.75 / Max: 6.76 Min: 3.14 / Avg: 3.18 / Max: 3.21 Min: 5.23 / Avg: 5.33 / Max: 5.39 1. (CXX) g++ options: -O3 -fcommon -fPIE -fPIC -pie
x264 This is a simple test of the x264 encoder run on the CPU (OpenCL support disabled) with a sample video file. Learn more via the OpenBenchmarking.org test page.
Result
OpenBenchmarking.org Frames Per Second, More Is Better x264 2019-12-17 H.264 Video Encoding EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 50 100 150 200 250 SE +/- 0.37, N = 6 SE +/- 0.60, N = 7 SE +/- 0.71, N = 8 SE +/- 0.59, N = 8 SE +/- 0.75, N = 9 SE +/- 1.00, N = 9 SE +/- 0.75, N = 9 SE +/- 0.83, N = 9 SE +/- 1.18, N = 15 SE +/- 1.24, N = 15 SE +/- 1.83, N = 15 SE +/- 1.78, N = 15 SE +/- 0.33, N = 7 SE +/- 0.76, N = 9 78.21 117.14 142.37 150.45 174.63 182.42 181.15 188.45 198.00 203.74 210.69 198.58 95.50 173.50 1. (CC) gcc options: -ldl -lavformat -lavcodec -lavutil -lswscale -m64 -lm -lpthread -O3 -ffast-math -std=gnu99 -fPIC -fomit-frame-pointer -fno-tree-vectorize
Frames Per Second Per Watt
OpenBenchmarking.org Frames Per Second Per Watt, More Is Better x264 2019-12-17 H.264 Video Encoding EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 0.5355 1.071 1.6065 2.142 2.6775 1.31 1.74 2.16 2.01 2.12 2.32 1.93 2.38 2.30 2.08 2.22 2.06 1.14 1.47
Result Confidence
OpenBenchmarking.org Frames Per Second, More Is Better x264 2019-12-17 H.264 Video Encoding EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 40 80 120 160 200 Min: 76.63 / Avg: 78.21 / Max: 79.16 Min: 113.91 / Avg: 117.14 / Max: 119.03 Min: 137.77 / Avg: 142.37 / Max: 143.62 Min: 146.52 / Avg: 150.45 / Max: 151.9 Min: 169.05 / Avg: 174.63 / Max: 176.72 Min: 175.43 / Avg: 182.42 / Max: 186.12 Min: 175.43 / Avg: 181.15 / Max: 183.15 Min: 183.08 / Avg: 188.45 / Max: 190.79 Min: 182.68 / Avg: 198 / Max: 201.65 Min: 187.17 / Avg: 203.74 / Max: 207.43 Min: 187.36 / Avg: 210.69 / Max: 218.31 Min: 179.11 / Avg: 198.58 / Max: 206.01 Min: 94.18 / Avg: 95.5 / Max: 96.44 Min: 167.66 / Avg: 173.5 / Max: 175.1 1. (CC) gcc options: -ldl -lavformat -lavcodec -lavutil -lswscale -m64 -lm -lpthread -O3 -ffast-math -std=gnu99 -fPIC -fomit-frame-pointer -fno-tree-vectorize
TensorFlow Lite This is a benchmark of the TensorFlow Lite implementation. The current Linux support is limited to running on CPUs. This test profile is measuring the average inference time. Learn more via the OpenBenchmarking.org test page.
Result
OpenBenchmarking.org Microseconds, Fewer Is Better TensorFlow Lite 2020-08-23 Model: NASNet Mobile EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 50K 100K 150K 200K 250K SE +/- 42.10, N = 3 SE +/- 219.52, N = 3 SE +/- 183.23, N = 3 SE +/- 652.17, N = 3 SE +/- 414.30, N = 3 SE +/- 797.17, N = 15 SE +/- 115.78, N = 3 SE +/- 115.93, N = 3 SE +/- 275.99, N = 3 SE +/- 34.51, N = 3 SE +/- 833.99, N = 6 SE +/- 718.53, N = 15 SE +/- 54.60, N = 3 SE +/- 244.85, N = 3 212253.0 177540.0 151235.0 144445.0 105046.0 85462.8 84263.5 79313.6 92153.2 86140.6 88093.7 95873.7 177928.0 126743.0
Result Confidence
OpenBenchmarking.org Microseconds, Fewer Is Better TensorFlow Lite 2020-08-23 Model: NASNet Mobile EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 40K 80K 120K 160K 200K Min: 212188 / Avg: 212253.33 / Max: 212332 Min: 177299 / Avg: 177539.67 / Max: 177978 Min: 150900 / Avg: 151235.33 / Max: 151531 Min: 143270 / Avg: 144444.67 / Max: 145523 Min: 104457 / Avg: 105045.67 / Max: 105845 Min: 82675.3 / Avg: 85462.75 / Max: 91289.3 Min: 84034.6 / Avg: 84263.47 / Max: 84408.4 Min: 79189.4 / Avg: 79313.63 / Max: 79545.3 Min: 91707.3 / Avg: 92153.17 / Max: 92657.9 Min: 86071.8 / Avg: 86140.57 / Max: 86180.1 Min: 85520.1 / Avg: 88093.72 / Max: 91636.7 Min: 91993.6 / Avg: 95873.69 / Max: 100262 Min: 177860 / Avg: 177928 / Max: 178036 Min: 126253 / Avg: 126742.67 / Max: 126993
NAS Parallel Benchmarks NPB, NAS Parallel Benchmarks, is a benchmark developed by NASA for high-end computer systems. This test profile currently uses the MPI version of NPB. This test profile offers selecting the different NPB tests/problems and varying problem sizes. Learn more via the OpenBenchmarking.org test page.
Kvazaar This is a test of Kvazaar as a CPU-based H.265 video encoder written in the C programming language and optimized in Assembly. Kvazaar is the winner of the 2016 ACM Open-Source Software Competition and developed at the Ultra Video Group, Tampere University, Finland. Learn more via the OpenBenchmarking.org test page.
Result
OpenBenchmarking.org Frames Per Second, More Is Better Kvazaar 2.0 Video Input: Bosphorus 4K - Video Preset: Ultra Fast EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 13 26 39 52 65 SE +/- 0.02, N = 3 SE +/- 0.05, N = 3 SE +/- 0.03, N = 4 SE +/- 0.03, N = 4 SE +/- 0.05, N = 4 SE +/- 0.05, N = 5 SE +/- 0.03, N = 5 SE +/- 0.05, N = 5 SE +/- 0.48, N = 5 SE +/- 0.16, N = 5 SE +/- 0.44, N = 5 SE +/- 0.54, N = 5 SE +/- 0.04, N = 3 SE +/- 0.02, N = 4 23.11 31.39 39.65 41.52 48.33 54.92 54.07 56.98 55.99 59.59 58.64 53.52 27.16 47.17 1. (CC) gcc options: -pthread -ftree-vectorize -fvisibility=hidden -O2 -lpthread -lm -lrt
Frames Per Second Per Watt
OpenBenchmarking.org Frames Per Second Per Watt, More Is Better Kvazaar 2.0 Video Input: Bosphorus 4K - Video Preset: Ultra Fast EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 0.1058 0.2116 0.3174 0.4232 0.529 0.31 0.35 0.45 0.40 0.40 0.47 0.40 0.47 0.43 0.40 0.42 0.41 0.24 0.26
Result Confidence
OpenBenchmarking.org Frames Per Second, More Is Better Kvazaar 2.0 Video Input: Bosphorus 4K - Video Preset: Ultra Fast EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 12 24 36 48 60 Min: 23.08 / Avg: 23.11 / Max: 23.14 Min: 31.34 / Avg: 31.39 / Max: 31.49 Min: 39.58 / Avg: 39.65 / Max: 39.69 Min: 41.47 / Avg: 41.52 / Max: 41.57 Min: 48.24 / Avg: 48.33 / Max: 48.45 Min: 54.78 / Avg: 54.92 / Max: 55.03 Min: 54 / Avg: 54.07 / Max: 54.14 Min: 56.85 / Avg: 56.98 / Max: 57.12 Min: 55.17 / Avg: 55.99 / Max: 57.85 Min: 59.13 / Avg: 59.59 / Max: 59.95 Min: 57.87 / Avg: 58.64 / Max: 60.27 Min: 52.03 / Avg: 53.52 / Max: 54.9 Min: 27.11 / Avg: 27.16 / Max: 27.23 Min: 47.11 / Avg: 47.17 / Max: 47.21 1. (CC) gcc options: -pthread -ftree-vectorize -fvisibility=hidden -O2 -lpthread -lm -lrt
Sysbench This is a benchmark of Sysbench with CPU and memory sub-tests. Learn more via the OpenBenchmarking.org test page.
Result
OpenBenchmarking.org Events Per Second, More Is Better Sysbench 2018-07-28 Test: Memory EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 2M 4M 6M 8M 10M SE +/- 12382.78, N = 5 SE +/- 1918.40, N = 5 SE +/- 11575.58, N = 5 SE +/- 780.60, N = 5 SE +/- 6709.34, N = 5 SE +/- 5458.69, N = 5 SE +/- 61191.25, N = 15 SE +/- 8561.16, N = 5 SE +/- 14871.56, N = 5 SE +/- 35042.66, N = 5 SE +/- 11992.02, N = 5 SE +/- 717.93, N = 5 SE +/- 17904.29, N = 5 5942474.37 7232205.30 7880986.59 4502591.45 5614019.49 6612746.50 4720934.26 6618850.24 6380400.35 6374595.12 6302136.65 4656182.26 3087955.63 1. (CC) gcc options: -pthread -O3 -funroll-loops -ggdb3 -march=amdfam10 -rdynamic -ldl -laio -lm
Events Per Second Per Watt
OpenBenchmarking.org Events Per Second Per Watt, More Is Better Sysbench 2018-07-28 Test: Memory EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 30K 60K 90K 120K 150K 141909.12 160055.91 162496.00 83787.81 93633.65 103730.05 57649.40 105418.49 80342.22 66221.01 62605.70 84636.76 37471.23
Result Confidence
OpenBenchmarking.org Events Per Second, More Is Better Sysbench 2018-07-28 Test: Memory EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 1.4M 2.8M 4.2M 5.6M 7M Min: 5895950.69 / Avg: 5942474.37 / Max: 5962905.57 Min: 7225906.31 / Avg: 7232205.3 / Max: 7236184.18 Min: 7856776.88 / Avg: 7880986.59 / Max: 7920212.37 Min: 4500022.71 / Avg: 4502591.45 / Max: 4504708.71 Min: 5602311.72 / Avg: 5614019.49 / Max: 5638809.43 Min: 6604337.31 / Avg: 6612746.5 / Max: 6634214.25 Min: 4407088.34 / Avg: 4720934.26 / Max: 5255661.79 Min: 6607713.8 / Avg: 6618850.24 / Max: 6652865.09 Min: 6349678.61 / Avg: 6380400.35 / Max: 6428305.03 Min: 6319346.34 / Avg: 6374595.12 / Max: 6505001.22 Min: 6269344.44 / Avg: 6302136.65 / Max: 6328806.52 Min: 4654731.01 / Avg: 4656182.26 / Max: 4658759.57 Min: 3067897.69 / Avg: 3087955.63 / Max: 3159400.31 1. (CC) gcc options: -pthread -O3 -funroll-loops -ggdb3 -march=amdfam10 -rdynamic -ldl -laio -lm
NAS Parallel Benchmarks NPB, NAS Parallel Benchmarks, is a benchmark developed by NASA for high-end computer systems. This test profile currently uses the MPI version of NPB. This test profile offers selecting the different NPB tests/problems and varying problem sizes. Learn more via the OpenBenchmarking.org test page.
Result
OpenBenchmarking.org Total Mop/s, More Is Better NAS Parallel Benchmarks 3.4 Test / Class: FT.C EPYC 7232P EPYC 7282 EPYC 7302P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 12K 24K 36K 48K 60K SE +/- 23.87, N = 3 SE +/- 23.10, N = 4 SE +/- 19.15, N = 4 SE +/- 36.50, N = 5 SE +/- 17.78, N = 5 SE +/- 17.91, N = 5 SE +/- 50.60, N = 5 SE +/- 40.27, N = 5 SE +/- 10.84, N = 4 SE +/- 44.41, N = 3 21822.06 29526.97 37175.20 46206.33 49235.92 47098.22 55668.63 55136.50 27284.69 22117.17 1. (F9X) gfortran options: -O3 -march=native -pthread -lmpi_usempif08 -lmpi_mpifh -lmpi 2. Open MPI 4.0.3
Total Mop/s Per Watt
OpenBenchmarking.org Total Mop/s Per Watt, More Is Better NAS Parallel Benchmarks 3.4 Test / Class: FT.C EPYC 7232P EPYC 7282 EPYC 7302P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 100 200 300 400 500 297.55 373.22 398.01 440.80 395.37 436.08 419.28 399.60 260.77 153.51
Result Confidence
OpenBenchmarking.org Total Mop/s, More Is Better NAS Parallel Benchmarks 3.4 Test / Class: FT.C EPYC 7232P EPYC 7282 EPYC 7302P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 10K 20K 30K 40K 50K Min: 21777.28 / Avg: 21822.06 / Max: 21858.76 Min: 29462.38 / Avg: 29526.97 / Max: 29571 Min: 37140.1 / Avg: 37175.2 / Max: 37216.01 Min: 46062.44 / Avg: 46206.33 / Max: 46260.89 Min: 49168.13 / Avg: 49235.92 / Max: 49272.59 Min: 47048.85 / Avg: 47098.22 / Max: 47153.11 Min: 55491.76 / Avg: 55668.63 / Max: 55799.49 Min: 55002.69 / Avg: 55136.5 / Max: 55211.78 Min: 27272.21 / Avg: 27284.69 / Max: 27317.11 Min: 22040.65 / Avg: 22117.17 / Max: 22194.48 1. (F9X) gfortran options: -O3 -march=native -pthread -lmpi_usempif08 -lmpi_mpifh -lmpi 2. Open MPI 4.0.3
High Performance Conjugate Gradient HPCG is the High Performance Conjugate Gradient and is a new scientific benchmark from Sandia National Lans focused for super-computer testing with modern real-world workloads compared to HPCC. Learn more via the OpenBenchmarking.org test page.
Result
OpenBenchmarking.org GFLOP/s, More Is Better High Performance Conjugate Gradient 3.1 EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 4 8 12 16 20 SE +/- 0.00542, N = 3 SE +/- 0.00448, N = 3 SE +/- 0.00263, N = 3 SE +/- 0.07483, N = 3 SE +/- 0.01008, N = 3 SE +/- 0.00324, N = 3 SE +/- 0.00249, N = 3 SE +/- 0.00275, N = 3 SE +/- 0.00667, N = 3 SE +/- 0.00479, N = 3 SE +/- 0.00378, N = 3 SE +/- 0.03096, N = 3 SE +/- 0.06375, N = 3 SE +/- 0.05299, N = 11 8.64661 9.09743 9.05154 15.63290 15.56290 15.29200 17.96770 15.27940 16.64940 17.68500 17.38630 17.30750 12.95600 7.08925 1. (CXX) g++ options: -O3 -ffast-math -ftree-vectorize -pthread -lmpi_cxx -lmpi
GFLOP/s Per Watt
OpenBenchmarking.org GFLOP/s Per Watt, More Is Better High Performance Conjugate Gradient 3.1 EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 0.0315 0.063 0.0945 0.126 0.1575 0.11 0.11 0.10 0.14 0.12 0.11 0.10 0.12 0.10 0.10 0.09 0.09 0.11 0.05
Result Confidence
OpenBenchmarking.org GFLOP/s, More Is Better High Performance Conjugate Gradient 3.1 EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 5 10 15 20 25 Min: 8.64 / Avg: 8.65 / Max: 8.66 Min: 9.09 / Avg: 9.1 / Max: 9.1 Min: 9.05 / Avg: 9.05 / Max: 9.05 Min: 15.51 / Avg: 15.63 / Max: 15.77 Min: 15.55 / Avg: 15.56 / Max: 15.58 Min: 15.29 / Avg: 15.29 / Max: 15.3 Min: 17.96 / Avg: 17.97 / Max: 17.97 Min: 15.28 / Avg: 15.28 / Max: 15.28 Min: 16.64 / Avg: 16.65 / Max: 16.66 Min: 17.68 / Avg: 17.69 / Max: 17.69 Min: 17.38 / Avg: 17.39 / Max: 17.39 Min: 17.25 / Avg: 17.31 / Max: 17.34 Min: 12.86 / Avg: 12.96 / Max: 13.08 Min: 6.64 / Avg: 7.09 / Max: 7.27 1. (CXX) g++ options: -O3 -ffast-math -ftree-vectorize -pthread -lmpi_cxx -lmpi
OpenFOAM OpenFOAM is the leading free, open source software for computational fluid dynamics (CFD). Learn more via the OpenBenchmarking.org test page.
Result
OpenBenchmarking.org Seconds, Fewer Is Better OpenFOAM 8 Input: Motorbike 60M EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 120 240 360 480 600 SE +/- 0.29, N = 3 SE +/- 1.13, N = 3 SE +/- 0.84, N = 3 SE +/- 0.15, N = 3 SE +/- 0.21, N = 3 SE +/- 0.44, N = 3 SE +/- 0.57, N = 3 SE +/- 0.59, N = 3 SE +/- 0.13, N = 3 SE +/- 0.31, N = 3 SE +/- 0.24, N = 3 SE +/- 0.04, N = 3 SE +/- 0.36, N = 3 SE +/- 1.71, N = 3 573.04 530.10 520.45 313.64 314.06 320.20 236.99 319.87 260.78 233.73 232.98 233.34 362.74 454.84 1. (CXX) g++ options: -std=c++11 -m64 -O3 -ftemplate-depth-100 -fPIC -fuse-ld=bfd -Xlinker --add-needed --no-as-needed -ldynamicMesh -ldecompose -lgenericPatchFields -lmetisDecomp -lscotchDecomp -llagrangian -lregionModels -lOpenFOAM -ldl -lm
Result Confidence
OpenBenchmarking.org Seconds, Fewer Is Better OpenFOAM 8 Input: Motorbike 60M EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 100 200 300 400 500 Min: 572.49 / Avg: 573.04 / Max: 573.47 Min: 528.05 / Avg: 530.1 / Max: 531.94 Min: 518.85 / Avg: 520.45 / Max: 521.68 Min: 313.39 / Avg: 313.64 / Max: 313.91 Min: 313.84 / Avg: 314.06 / Max: 314.48 Min: 319.73 / Avg: 320.2 / Max: 321.08 Min: 235.98 / Avg: 236.99 / Max: 237.94 Min: 319.1 / Avg: 319.87 / Max: 321.04 Min: 260.58 / Avg: 260.78 / Max: 261.02 Min: 233.28 / Avg: 233.73 / Max: 234.33 Min: 232.55 / Avg: 232.98 / Max: 233.38 Min: 233.29 / Avg: 233.34 / Max: 233.42 Min: 362.09 / Avg: 362.74 / Max: 363.35 Min: 452.49 / Avg: 454.84 / Max: 458.16 1. (CXX) g++ options: -std=c++11 -m64 -O3 -ftemplate-depth-100 -fPIC -fuse-ld=bfd -Xlinker --add-needed --no-as-needed -ldynamicMesh -ldecompose -lgenericPatchFields -lmetisDecomp -lscotchDecomp -llagrangian -lregionModels -lOpenFOAM -ldl -lm
dav1d Dav1d is an open-source, speedy AV1 video decoder. This test profile times how long it takes to decode sample AV1 video content. Learn more via the OpenBenchmarking.org test page.
Result
OpenBenchmarking.org FPS, More Is Better dav1d 0.8.1 Video Input: Chimera 1080p EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 200 400 600 800 1000 SE +/- 0.34, N = 3 SE +/- 1.45, N = 3 SE +/- 0.66, N = 3 SE +/- 0.72, N = 3 SE +/- 1.22, N = 3 SE +/- 0.95, N = 3 SE +/- 2.20, N = 3 SE +/- 0.52, N = 3 SE +/- 2.26, N = 3 SE +/- 0.45, N = 3 SE +/- 2.82, N = 3 SE +/- 3.47, N = 3 SE +/- 0.38, N = 3 SE +/- 1.86, N = 3 473.82 624.79 712.26 698.08 839.06 937.73 892.42 939.90 1095.40 1116.83 1158.08 983.61 496.11 671.07 MIN: 365.77 / MAX: 674.59 MIN: 483.27 / MAX: 784.91 MIN: 546.18 / MAX: 898.36 MIN: 539.13 / MAX: 873.36 MIN: 646.27 / MAX: 1067.76 MIN: 687.68 / MAX: 1200.87 MIN: 641.23 / MAX: 1144.96 MIN: 689.36 / MAX: 1207.51 MIN: 671.87 / MAX: 1406.03 MIN: 672.49 / MAX: 1434.66 MIN: 644.06 / MAX: 1489.95 MIN: 616.84 / MAX: 1260.07 MIN: 390.79 / MAX: 704.31 MIN: 524.48 / MAX: 829.64 1. (CC) gcc options: -pthread
FPS Per Watt
OpenBenchmarking.org FPS Per Watt, More Is Better dav1d 0.8.1 Video Input: Chimera 1080p EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 4 8 12 16 20 10.24 13.08 15.03 12.61 14.96 16.80 11.84 17.37 16.67 15.55 15.25 12.64 7.83 8.07
Result Confidence
OpenBenchmarking.org FPS, More Is Better dav1d 0.8.1 Video Input: Chimera 1080p EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 200 400 600 800 1000 Min: 473.15 / Avg: 473.82 / Max: 474.25 Min: 622.12 / Avg: 624.79 / Max: 627.09 Min: 711 / Avg: 712.26 / Max: 713.24 Min: 697.03 / Avg: 698.08 / Max: 699.47 Min: 837.5 / Avg: 839.06 / Max: 841.47 Min: 935.96 / Avg: 937.73 / Max: 939.19 Min: 888.17 / Avg: 892.42 / Max: 895.56 Min: 938.86 / Avg: 939.9 / Max: 940.47 Min: 1091.59 / Avg: 1095.4 / Max: 1099.4 Min: 1116.14 / Avg: 1116.83 / Max: 1117.68 Min: 1153.84 / Avg: 1158.08 / Max: 1163.42 Min: 977.12 / Avg: 983.61 / Max: 988.98 Min: 495.72 / Avg: 496.11 / Max: 496.87 Min: 667.49 / Avg: 671.07 / Max: 673.75 1. (CC) gcc options: -pthread
NAS Parallel Benchmarks NPB, NAS Parallel Benchmarks, is a benchmark developed by NASA for high-end computer systems. This test profile currently uses the MPI version of NPB. This test profile offers selecting the different NPB tests/problems and varying problem sizes. Learn more via the OpenBenchmarking.org test page.
Result
OpenBenchmarking.org Total Mop/s, More Is Better NAS Parallel Benchmarks 3.4 Test / Class: MG.C EPYC 7232P EPYC 7282 EPYC 7302P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 11K 22K 33K 44K 55K SE +/- 37.32, N = 7 SE +/- 23.57, N = 6 SE +/- 17.34, N = 8 SE +/- 76.06, N = 8 SE +/- 218.93, N = 8 SE +/- 86.13, N = 8 SE +/- 122.43, N = 8 SE +/- 224.56, N = 8 SE +/- 20.16, N = 8 SE +/- 80.46, N = 5 30311.94 29776.81 47349.29 44082.95 52022.76 44205.80 52245.23 51795.61 45336.89 21714.65 1. (F9X) gfortran options: -O3 -march=native -pthread -lmpi_usempif08 -lmpi_mpifh -lmpi 2. Open MPI 4.0.3
Total Mop/s Per Watt
OpenBenchmarking.org Total Mop/s Per Watt, More Is Better NAS Parallel Benchmarks 3.4 Test / Class: MG.C EPYC 7232P EPYC 7282 EPYC 7302P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 140 280 420 560 700 525.61 463.71 660.02 538.87 520.26 555.62 490.40 476.11 592.89 197.31
Result Confidence
OpenBenchmarking.org Total Mop/s, More Is Better NAS Parallel Benchmarks 3.4 Test / Class: MG.C EPYC 7232P EPYC 7282 EPYC 7302P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 9K 18K 27K 36K 45K Min: 30136.45 / Avg: 30311.94 / Max: 30404.24 Min: 29684.13 / Avg: 29776.81 / Max: 29837.83 Min: 47278.3 / Avg: 47349.29 / Max: 47425.88 Min: 43772.91 / Avg: 44082.95 / Max: 44328.66 Min: 50688.93 / Avg: 52022.76 / Max: 52586.47 Min: 43844.26 / Avg: 44205.8 / Max: 44502.94 Min: 51776.39 / Avg: 52245.23 / Max: 52860.72 Min: 50825.97 / Avg: 51795.61 / Max: 52696.05 Min: 45233.69 / Avg: 45336.89 / Max: 45424.87 Min: 21536.77 / Avg: 21714.65 / Max: 22018.31 1. (F9X) gfortran options: -O3 -march=native -pthread -lmpi_usempif08 -lmpi_mpifh -lmpi 2. Open MPI 4.0.3
Incompact3D Incompact3d is a Fortran-MPI based, finite difference high-performance code for solving the incompressible Navier-Stokes equation and as many as you need scalar transport equations. Learn more via the OpenBenchmarking.org test page.
Result
OpenBenchmarking.org Seconds, Fewer Is Better Incompact3D 2020-09-17 Input: Cylinder EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 100 200 300 400 500 SE +/- 1.04, N = 3 SE +/- 0.37, N = 3 SE +/- 0.47, N = 3 SE +/- 0.25, N = 3 SE +/- 0.20, N = 3 SE +/- 0.52, N = 3 SE +/- 0.57, N = 3 SE +/- 0.39, N = 3 SE +/- 1.22, N = 3 SE +/- 0.73, N = 3 SE +/- 0.75, N = 3 SE +/- 0.50, N = 3 SE +/- 0.12, N = 3 SE +/- 0.68, N = 3 450.85 325.84 270.72 262.63 200.21 189.66 193.92 187.60 206.58 195.34 206.95 224.62 375.70 230.94 1. (F9X) gfortran options: -cpp -funroll-loops -floop-optimize -fcray-pointer -fbacktrace -pthread -lmpi_usempif08 -lmpi_mpifh -lmpi
Result Confidence
OpenBenchmarking.org Seconds, Fewer Is Better Incompact3D 2020-09-17 Input: Cylinder EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 80 160 240 320 400 Min: 449.53 / Avg: 450.85 / Max: 452.91 Min: 325.11 / Avg: 325.84 / Max: 326.32 Min: 270.13 / Avg: 270.72 / Max: 271.65 Min: 262.32 / Avg: 262.63 / Max: 263.13 Min: 199.84 / Avg: 200.21 / Max: 200.55 Min: 188.81 / Avg: 189.66 / Max: 190.61 Min: 192.99 / Avg: 193.92 / Max: 194.97 Min: 186.85 / Avg: 187.6 / Max: 188.17 Min: 204.79 / Avg: 206.58 / Max: 208.92 Min: 194.23 / Avg: 195.34 / Max: 196.73 Min: 206.04 / Avg: 206.95 / Max: 208.44 Min: 224.11 / Avg: 224.62 / Max: 225.62 Min: 375.47 / Avg: 375.7 / Max: 375.88 Min: 229.71 / Avg: 230.94 / Max: 232.08 1. (F9X) gfortran options: -cpp -funroll-loops -floop-optimize -fcray-pointer -fbacktrace -pthread -lmpi_usempif08 -lmpi_mpifh -lmpi
NAS Parallel Benchmarks NPB, NAS Parallel Benchmarks, is a benchmark developed by NASA for high-end computer systems. This test profile currently uses the MPI version of NPB. This test profile offers selecting the different NPB tests/problems and varying problem sizes. Learn more via the OpenBenchmarking.org test page.
Result
OpenBenchmarking.org Total Mop/s, More Is Better NAS Parallel Benchmarks 3.4 Test / Class: CG.C EPYC 7232P EPYC 7282 EPYC 7302P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 4K 8K 12K 16K 20K SE +/- 22.89, N = 4 SE +/- 18.07, N = 4 SE +/- 15.81, N = 5 SE +/- 69.28, N = 5 SE +/- 25.61, N = 5 SE +/- 30.70, N = 5 SE +/- 27.38, N = 5 SE +/- 15.75, N = 5 SE +/- 18.04, N = 4 SE +/- 43.06, N = 3 9844.95 9697.83 15688.57 14759.40 18019.01 14977.29 15230.23 15079.08 12350.87 7779.49 1. (F9X) gfortran options: -O3 -march=native -pthread -lmpi_usempif08 -lmpi_mpifh -lmpi 2. Open MPI 4.0.3
Total Mop/s Per Watt
OpenBenchmarking.org Total Mop/s Per Watt, More Is Better NAS Parallel Benchmarks 3.4 Test / Class: CG.C EPYC 7232P EPYC 7282 EPYC 7302P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 40 80 120 160 200 136.77 119.50 159.36 129.34 137.30 137.33 107.24 103.87 120.79 56.39
Result Confidence
OpenBenchmarking.org Total Mop/s, More Is Better NAS Parallel Benchmarks 3.4 Test / Class: CG.C EPYC 7232P EPYC 7282 EPYC 7302P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 3K 6K 9K 12K 15K Min: 9819.42 / Avg: 9844.95 / Max: 9913.54 Min: 9644.91 / Avg: 9697.83 / Max: 9725.86 Min: 15654.67 / Avg: 15688.57 / Max: 15744.56 Min: 14524.99 / Avg: 14759.4 / Max: 14889.39 Min: 17953.88 / Avg: 18019.01 / Max: 18084.24 Min: 14873.66 / Avg: 14977.29 / Max: 15062.42 Min: 15146.06 / Avg: 15230.23 / Max: 15316.01 Min: 15027.23 / Avg: 15079.08 / Max: 15122.17 Min: 12309.98 / Avg: 12350.87 / Max: 12395.51 Min: 7733.94 / Avg: 7779.49 / Max: 7865.57 1. (F9X) gfortran options: -O3 -march=native -pthread -lmpi_usempif08 -lmpi_mpifh -lmpi 2. Open MPI 4.0.3
NCNN NCNN is a high performance neural network inference framework optimized for mobile and other platforms developed by Tencent. Learn more via the OpenBenchmarking.org test page.
Result
OpenBenchmarking.org ms, Fewer Is Better NCNN 20201218 Target: CPU - Model: googlenet EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 8 16 24 32 40 SE +/- 0.03, N = 3 SE +/- 0.28, N = 3 SE +/- 0.48, N = 3 SE +/- 0.01, N = 3 SE +/- 0.02, N = 3 SE +/- 0.33, N = 3 SE +/- 0.29, N = 11 SE +/- 0.12, N = 3 SE +/- 0.14, N = 3 SE +/- 0.86, N = 12 SE +/- 1.29, N = 9 SE +/- 1.15, N = 9 SE +/- 0.10, N = 3 SE +/- 0.27, N = 3 17.87 17.58 18.84 16.83 17.64 20.35 21.93 19.94 23.97 27.68 34.00 36.76 16.32 21.84 MIN: 17.59 / MAX: 19.75 MIN: 17.05 / MAX: 18.64 MIN: 17.66 / MAX: 132.29 MIN: 16.42 / MAX: 20.42 MIN: 17.29 / MAX: 30.94 MIN: 19.39 / MAX: 62.1 MIN: 20.32 / MAX: 95.63 MIN: 19.43 / MAX: 22.28 MIN: 23.45 / MAX: 28.72 MIN: 23.41 / MAX: 138.56 MIN: 27.04 / MAX: 97.01 MIN: 28.46 / MAX: 174.17 MIN: 15.69 / MAX: 79.67 MIN: 20.88 / MAX: 25.6 1. (CXX) g++ options: -O3 -rdynamic -lgomp -lpthread
Result Confidence
OpenBenchmarking.org ms, Fewer Is Better NCNN 20201218 Target: CPU - Model: googlenet EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 8 16 24 32 40 Min: 17.81 / Avg: 17.87 / Max: 17.93 Min: 17.28 / Avg: 17.58 / Max: 18.13 Min: 18.11 / Avg: 18.84 / Max: 19.74 Min: 16.81 / Avg: 16.83 / Max: 16.84 Min: 17.62 / Avg: 17.64 / Max: 17.68 Min: 19.9 / Avg: 20.35 / Max: 20.99 Min: 20.81 / Avg: 21.93 / Max: 23.79 Min: 19.7 / Avg: 19.94 / Max: 20.06 Min: 23.7 / Avg: 23.97 / Max: 24.12 Min: 23.94 / Avg: 27.68 / Max: 33.93 Min: 29.81 / Avg: 34 / Max: 38.69 Min: 32.1 / Avg: 36.76 / Max: 42.47 Min: 16.12 / Avg: 16.32 / Max: 16.47 Min: 21.32 / Avg: 21.84 / Max: 22.24 1. (CXX) g++ options: -O3 -rdynamic -lgomp -lpthread
Rodinia Rodinia is a suite focused upon accelerating compute-intensive applications with accelerators. CUDA, OpenMP, and OpenCL parallel models are supported by the included applications. This profile utilizes select OpenCL, NVIDIA CUDA and OpenMP test binaries at the moment. Learn more via the OpenBenchmarking.org test page.
Result
OpenBenchmarking.org Seconds, Fewer Is Better Rodinia 3.1 Test: OpenMP Streamcluster EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 5 10 15 20 25 SE +/- 0.040, N = 4 SE +/- 0.079, N = 3 SE +/- 0.159, N = 8 SE +/- 0.034, N = 3 SE +/- 0.042, N = 4 SE +/- 0.007, N = 4 SE +/- 0.016, N = 5 SE +/- 0.022, N = 4 SE +/- 0.119, N = 4 SE +/- 0.074, N = 15 SE +/- 0.030, N = 5 SE +/- 0.017, N = 5 SE +/- 0.017, N = 3 SE +/- 0.049, N = 4 15.540 16.895 18.189 17.729 14.761 14.320 9.913 14.316 12.027 9.185 8.905 8.928 19.707 15.049 1. (CXX) g++ options: -O2 -lOpenCL
Result Confidence
OpenBenchmarking.org Seconds, Fewer Is Better Rodinia 3.1 Test: OpenMP Streamcluster EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 5 10 15 20 25 Min: 15.47 / Avg: 15.54 / Max: 15.65 Min: 16.76 / Avg: 16.9 / Max: 17.03 Min: 17.99 / Avg: 18.19 / Max: 19.3 Min: 17.66 / Avg: 17.73 / Max: 17.77 Min: 14.65 / Avg: 14.76 / Max: 14.83 Min: 14.31 / Avg: 14.32 / Max: 14.34 Min: 9.88 / Avg: 9.91 / Max: 9.97 Min: 14.25 / Avg: 14.32 / Max: 14.36 Min: 11.69 / Avg: 12.03 / Max: 12.26 Min: 9.06 / Avg: 9.19 / Max: 10.22 Min: 8.85 / Avg: 8.91 / Max: 9.02 Min: 8.9 / Avg: 8.93 / Max: 8.99 Min: 19.68 / Avg: 19.71 / Max: 19.74 Min: 14.94 / Avg: 15.05 / Max: 15.15 1. (CXX) g++ options: -O2 -lOpenCL
Timed ImageMagick Compilation This test times how long it takes to build ImageMagick. Learn more via the OpenBenchmarking.org test page.
Result
OpenBenchmarking.org Seconds, Fewer Is Better Timed ImageMagick Compilation 6.9.0 Time To Compile EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 9 18 27 36 45 SE +/- 0.17, N = 3 SE +/- 0.02, N = 3 SE +/- 0.16, N = 3 SE +/- 0.04, N = 3 SE +/- 0.07, N = 3 SE +/- 0.02, N = 3 SE +/- 0.06, N = 3 SE +/- 0.05, N = 3 SE +/- 0.09, N = 3 SE +/- 0.09, N = 3 SE +/- 0.10, N = 3 SE +/- 0.08, N = 3 SE +/- 0.10, N = 3 SE +/- 0.15, N = 3 37.72 28.22 25.46 23.55 20.43 19.41 19.27 18.94 18.06 17.67 17.19 17.12 28.60 21.63
Result Confidence
OpenBenchmarking.org Seconds, Fewer Is Better Timed ImageMagick Compilation 6.9.0 Time To Compile EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 8 16 24 32 40 Min: 37.4 / Avg: 37.72 / Max: 38.01 Min: 28.17 / Avg: 28.22 / Max: 28.26 Min: 25.14 / Avg: 25.46 / Max: 25.64 Min: 23.47 / Avg: 23.55 / Max: 23.6 Min: 20.3 / Avg: 20.43 / Max: 20.52 Min: 19.38 / Avg: 19.4 / Max: 19.45 Min: 19.16 / Avg: 19.27 / Max: 19.35 Min: 18.83 / Avg: 18.93 / Max: 19.02 Min: 17.88 / Avg: 18.06 / Max: 18.19 Min: 17.49 / Avg: 17.67 / Max: 17.79 Min: 16.99 / Avg: 17.19 / Max: 17.31 Min: 16.99 / Avg: 17.11 / Max: 17.27 Min: 28.39 / Avg: 28.6 / Max: 28.73 Min: 21.4 / Avg: 21.63 / Max: 21.91
OpenVINO This is a test of the Intel OpenVINO, a toolkit around neural networks, using its built-in benchmarking support and analyzing the throughput and latency for various models. Learn more via the OpenBenchmarking.org test page.
Result
OpenBenchmarking.org ms, Fewer Is Better OpenVINO 2021.1 Model: Face Detection 0106 FP16 - Device: CPU EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 900 1800 2700 3600 4500 SE +/- 14.48, N = 3 SE +/- 9.26, N = 3 SE +/- 7.78, N = 3 SE +/- 1.52, N = 3 SE +/- 12.54, N = 3 SE +/- 1.04, N = 3 SE +/- 1.33, N = 3 SE +/- 3.65, N = 3 SE +/- 2.44, N = 3 SE +/- 2.50, N = 3 SE +/- 0.31, N = 3 SE +/- 12.73, N = 3 SE +/- 19.31, N = 3 SE +/- 3.08, N = 3 2298.63 2434.17 2527.86 2414.74 2507.58 2794.25 2815.80 2579.79 3325.99 3059.05 3562.63 4029.98 1836.51 1976.70
Result Confidence
OpenBenchmarking.org ms, Fewer Is Better OpenVINO 2021.1 Model: Face Detection 0106 FP16 - Device: CPU EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 700 1400 2100 2800 3500 Min: 2271.79 / Avg: 2298.63 / Max: 2321.46 Min: 2418.87 / Avg: 2434.17 / Max: 2450.86 Min: 2515.93 / Avg: 2527.86 / Max: 2542.47 Min: 2412.09 / Avg: 2414.74 / Max: 2417.36 Min: 2482.49 / Avg: 2507.58 / Max: 2520.14 Min: 2792.4 / Avg: 2794.25 / Max: 2795.99 Min: 2813.23 / Avg: 2815.8 / Max: 2817.7 Min: 2575.39 / Avg: 2579.79 / Max: 2587.03 Min: 3322.37 / Avg: 3325.99 / Max: 3330.62 Min: 3056.48 / Avg: 3059.05 / Max: 3064.04 Min: 3562.19 / Avg: 3562.63 / Max: 3563.22 Min: 4015.57 / Avg: 4029.98 / Max: 4055.36 Min: 1797.95 / Avg: 1836.51 / Max: 1857.52 Min: 1971.22 / Avg: 1976.7 / Max: 1981.88
Result
OpenBenchmarking.org ms, Fewer Is Better OpenVINO 2021.1 Model: Face Detection 0106 FP32 - Device: CPU EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 900 1800 2700 3600 4500 SE +/- 17.95, N = 3 SE +/- 34.12, N = 3 SE +/- 13.37, N = 3 SE +/- 2.67, N = 3 SE +/- 3.50, N = 3 SE +/- 0.81, N = 3 SE +/- 2.24, N = 3 SE +/- 2.29, N = 3 SE +/- 3.41, N = 3 SE +/- 1.92, N = 3 SE +/- 0.45, N = 3 SE +/- 8.92, N = 3 SE +/- 14.55, N = 3 SE +/- 1.86, N = 3 2314.66 2406.22 2446.02 2413.45 2522.61 2791.54 2814.15 2572.36 3327.50 3069.38 3558.09 4030.53 1844.31 1980.56
Result Confidence
OpenBenchmarking.org ms, Fewer Is Better OpenVINO 2021.1 Model: Face Detection 0106 FP32 - Device: CPU EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 700 1400 2100 2800 3500 Min: 2283.58 / Avg: 2314.66 / Max: 2345.75 Min: 2355.5 / Avg: 2406.22 / Max: 2471.13 Min: 2426.14 / Avg: 2446.02 / Max: 2471.46 Min: 2410.34 / Avg: 2413.45 / Max: 2418.77 Min: 2516.2 / Avg: 2522.61 / Max: 2528.27 Min: 2789.93 / Avg: 2791.54 / Max: 2792.44 Min: 2809.91 / Avg: 2814.15 / Max: 2817.55 Min: 2567.84 / Avg: 2572.36 / Max: 2575.2 Min: 3322.21 / Avg: 3327.5 / Max: 3333.86 Min: 3065.61 / Avg: 3069.38 / Max: 3071.93 Min: 3557.24 / Avg: 3558.09 / Max: 3558.76 Min: 4020.18 / Avg: 4030.53 / Max: 4048.29 Min: 1815.75 / Avg: 1844.31 / Max: 1863.4 Min: 1978.38 / Avg: 1980.56 / Max: 1984.26
LULESH LULESH is the Livermore Unstructured Lagrangian Explicit Shock Hydrodynamics. Learn more via the OpenBenchmarking.org test page.
Result
OpenBenchmarking.org z/s, More Is Better LULESH 2.0.3 EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 3K 6K 9K 12K 15K SE +/- 11.79, N = 6 SE +/- 38.61, N = 6 SE +/- 15.52, N = 6 SE +/- 8.39, N = 6 SE +/- 9.05, N = 6 SE +/- 131.70, N = 5 SE +/- 43.36, N = 4 SE +/- 157.59, N = 4 SE +/- 60.62, N = 4 SE +/- 58.13, N = 4 SE +/- 142.13, N = 3 SE +/- 146.93, N = 12 SE +/- 12.34, N = 6 SE +/- 40.17, N = 6 6757.99 6871.93 6954.80 7954.15 8024.37 12840.64 13938.25 13099.62 13435.30 14015.66 14603.33 14612.21 8720.88 6839.17 1. (CXX) g++ options: -O3 -fopenmp -lm -pthread -lmpi_cxx -lmpi
z/s Per Watt
OpenBenchmarking.org z/s Per Watt, More Is Better LULESH 2.0.3 EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 30 60 90 120 150 117.45 116.78 119.53 122.94 122.19 123.94 113.53 125.40 118.64 109.48 95.62 91.64 114.72 69.83
Result Confidence
OpenBenchmarking.org z/s, More Is Better LULESH 2.0.3 EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 3K 6K 9K 12K 15K Min: 6718.89 / Avg: 6757.99 / Max: 6804.97 Min: 6730.47 / Avg: 6871.93 / Max: 6957.51 Min: 6907.71 / Avg: 6954.8 / Max: 7005.82 Min: 7941.34 / Avg: 7954.15 / Max: 7995.56 Min: 7986.3 / Avg: 8024.37 / Max: 8053.74 Min: 12361.8 / Avg: 12840.64 / Max: 13103.71 Min: 13879.03 / Avg: 13938.25 / Max: 14067.14 Min: 12632.05 / Avg: 13099.62 / Max: 13300.62 Min: 13262.26 / Avg: 13435.3 / Max: 13545.43 Min: 13885.31 / Avg: 14015.66 / Max: 14137.76 Min: 14340.08 / Avg: 14603.33 / Max: 14827.83 Min: 13024.64 / Avg: 14612.21 / Max: 14895.69 Min: 8666.52 / Avg: 8720.88 / Max: 8753.04 Min: 6733.72 / Avg: 6839.17 / Max: 6954.28 1. (CXX) g++ options: -O3 -fopenmp -lm -pthread -lmpi_cxx -lmpi
OpenVINO This is a test of the Intel OpenVINO, a toolkit around neural networks, using its built-in benchmarking support and analyzing the throughput and latency for various models. Learn more via the OpenBenchmarking.org test page.
Result
OpenBenchmarking.org ms, Fewer Is Better OpenVINO 2021.1 Model: Person Detection 0106 FP16 - Device: CPU EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 1100 2200 3300 4400 5500 SE +/- 3.19, N = 3 SE +/- 9.03, N = 3 SE +/- 2.79, N = 3 SE +/- 5.57, N = 3 SE +/- 14.72, N = 3 SE +/- 1.53, N = 3 SE +/- 10.25, N = 3 SE +/- 2.78, N = 3 SE +/- 5.33, N = 3 SE +/- 4.94, N = 3 SE +/- 6.15, N = 3 SE +/- 6.77, N = 3 SE +/- 4.62, N = 3 SE +/- 1.31, N = 3 3071.91 3264.49 3344.39 3145.89 3310.91 3578.09 3757.35 3276.52 4197.60 4132.13 4731.72 5170.99 2399.19 2643.39
Result Confidence
OpenBenchmarking.org ms, Fewer Is Better OpenVINO 2021.1 Model: Person Detection 0106 FP16 - Device: CPU EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 900 1800 2700 3600 4500 Min: 3065.98 / Avg: 3071.91 / Max: 3076.9 Min: 3253.32 / Avg: 3264.49 / Max: 3282.36 Min: 3340.81 / Avg: 3344.39 / Max: 3349.89 Min: 3138.42 / Avg: 3145.89 / Max: 3156.77 Min: 3286.85 / Avg: 3310.91 / Max: 3337.63 Min: 3576.1 / Avg: 3578.09 / Max: 3581.09 Min: 3741.86 / Avg: 3757.35 / Max: 3776.73 Min: 3273.17 / Avg: 3276.52 / Max: 3282.04 Min: 4187.64 / Avg: 4197.6 / Max: 4205.86 Min: 4122.78 / Avg: 4132.13 / Max: 4139.56 Min: 4723.88 / Avg: 4731.72 / Max: 4743.85 Min: 5162.09 / Avg: 5170.99 / Max: 5184.28 Min: 2393.6 / Avg: 2399.19 / Max: 2408.36 Min: 2641.61 / Avg: 2643.39 / Max: 2645.95
NAS Parallel Benchmarks NPB, NAS Parallel Benchmarks, is a benchmark developed by NASA for high-end computer systems. This test profile currently uses the MPI version of NPB. This test profile offers selecting the different NPB tests/problems and varying problem sizes. Learn more via the OpenBenchmarking.org test page.
Result
OpenBenchmarking.org Total Mop/s, More Is Better NAS Parallel Benchmarks 3.4 Test / Class: IS.D EPYC 7232P EPYC 7282 EPYC 7302P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 400 800 1200 1600 2000 SE +/- 2.89, N = 3 SE +/- 1.26, N = 3 SE +/- 2.26, N = 3 SE +/- 3.36, N = 3 SE +/- 1.95, N = 3 SE +/- 5.74, N = 3 SE +/- 11.89, N = 3 SE +/- 4.04, N = 3 SE +/- 5.70, N = 3 SE +/- 9.24, N = 3 1083.36 1422.07 1647.78 1884.31 1992.76 1885.98 2006.81 1971.50 1277.15 934.00 1. (F9X) gfortran options: -O3 -march=native -pthread -lmpi_usempif08 -lmpi_mpifh -lmpi 2. Open MPI 4.0.3
Total Mop/s Per Watt
OpenBenchmarking.org Total Mop/s Per Watt, More Is Better NAS Parallel Benchmarks 3.4 Test / Class: IS.D EPYC 7232P EPYC 7282 EPYC 7302P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 5 10 15 20 25 18.48 19.39 19.55 17.73 15.32 18.15 13.49 12.90 15.36 7.29
Result Confidence
OpenBenchmarking.org Total Mop/s, More Is Better NAS Parallel Benchmarks 3.4 Test / Class: IS.D EPYC 7232P EPYC 7282 EPYC 7302P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 300 600 900 1200 1500 Min: 1077.67 / Avg: 1083.36 / Max: 1087.08 Min: 1420.09 / Avg: 1422.07 / Max: 1424.4 Min: 1643.54 / Avg: 1647.78 / Max: 1651.27 Min: 1880.37 / Avg: 1884.31 / Max: 1890.99 Min: 1988.95 / Avg: 1992.76 / Max: 1995.4 Min: 1876.61 / Avg: 1885.98 / Max: 1896.4 Min: 1983.12 / Avg: 2006.81 / Max: 2020.44 Min: 1965.15 / Avg: 1971.5 / Max: 1979 Min: 1269.25 / Avg: 1277.15 / Max: 1288.21 Min: 920.59 / Avg: 934 / Max: 951.73 1. (F9X) gfortran options: -O3 -march=native -pthread -lmpi_usempif08 -lmpi_mpifh -lmpi 2. Open MPI 4.0.3
Build2 This test profile measures the time to bootstrap/install the build2 C++ build toolchain from source. Build2 is a cross-platform build toolchain for C/C++ code and features Cargo-like features. Learn more via the OpenBenchmarking.org test page.
Result
OpenBenchmarking.org Seconds, Fewer Is Better Build2 0.13 Time To Compile EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 30 60 90 120 150 SE +/- 0.29, N = 3 SE +/- 0.23, N = 3 SE +/- 0.07, N = 3 SE +/- 0.14, N = 3 SE +/- 0.10, N = 3 SE +/- 0.07, N = 3 SE +/- 0.16, N = 3 SE +/- 0.32, N = 3 SE +/- 0.16, N = 3 SE +/- 0.07, N = 3 SE +/- 0.09, N = 3 SE +/- 0.22, N = 3 SE +/- 0.15, N = 3 SE +/- 0.30, N = 3 145.44 105.71 94.35 87.66 76.65 74.20 74.48 71.46 69.86 69.43 68.29 67.97 113.26 75.85
Result Confidence
OpenBenchmarking.org Seconds, Fewer Is Better Build2 0.13 Time To Compile EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 30 60 90 120 150 Min: 145.08 / Avg: 145.44 / Max: 146.02 Min: 105.37 / Avg: 105.71 / Max: 106.15 Min: 94.22 / Avg: 94.35 / Max: 94.43 Min: 87.37 / Avg: 87.66 / Max: 87.82 Min: 76.5 / Avg: 76.65 / Max: 76.84 Min: 74.09 / Avg: 74.2 / Max: 74.34 Min: 74.18 / Avg: 74.48 / Max: 74.74 Min: 70.83 / Avg: 71.46 / Max: 71.85 Min: 69.58 / Avg: 69.86 / Max: 70.15 Min: 69.34 / Avg: 69.43 / Max: 69.57 Min: 68.11 / Avg: 68.29 / Max: 68.39 Min: 67.65 / Avg: 67.97 / Max: 68.39 Min: 113.02 / Avg: 113.26 / Max: 113.53 Min: 75.26 / Avg: 75.85 / Max: 76.19
OpenVINO This is a test of the Intel OpenVINO, a toolkit around neural networks, using its built-in benchmarking support and analyzing the throughput and latency for various models. Learn more via the OpenBenchmarking.org test page.
Result
OpenBenchmarking.org ms, Fewer Is Better OpenVINO 2021.1 Model: Person Detection 0106 FP32 - Device: CPU EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 1100 2200 3300 4400 5500 SE +/- 10.38, N = 3 SE +/- 8.60, N = 3 SE +/- 1.17, N = 3 SE +/- 5.33, N = 3 SE +/- 4.18, N = 3 SE +/- 1.62, N = 3 SE +/- 3.83, N = 3 SE +/- 5.09, N = 3 SE +/- 8.65, N = 3 SE +/- 14.85, N = 3 SE +/- 4.63, N = 3 SE +/- 6.37, N = 3 SE +/- 1.90, N = 3 SE +/- 4.58, N = 3 3090.58 3265.93 3342.13 3155.85 3315.63 3582.56 3754.85 3271.26 4203.81 4138.69 4732.73 5153.99 2409.03 2649.35
Result Confidence
OpenBenchmarking.org ms, Fewer Is Better OpenVINO 2021.1 Model: Person Detection 0106 FP32 - Device: CPU EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 900 1800 2700 3600 4500 Min: 3072.59 / Avg: 3090.58 / Max: 3108.55 Min: 3248.92 / Avg: 3265.93 / Max: 3276.67 Min: 3339.82 / Avg: 3342.13 / Max: 3343.55 Min: 3145.96 / Avg: 3155.85 / Max: 3164.23 Min: 3309.61 / Avg: 3315.63 / Max: 3323.66 Min: 3579.4 / Avg: 3582.56 / Max: 3584.73 Min: 3748.56 / Avg: 3754.85 / Max: 3761.77 Min: 3264.96 / Avg: 3271.26 / Max: 3281.33 Min: 4186.54 / Avg: 4203.81 / Max: 4213.33 Min: 4119.13 / Avg: 4138.69 / Max: 4167.82 Min: 4726.94 / Avg: 4732.73 / Max: 4741.89 Min: 5142.04 / Avg: 5153.99 / Max: 5163.81 Min: 2405.41 / Avg: 2409.03 / Max: 2411.84 Min: 2640.2 / Avg: 2649.35 / Max: 2654.02
Parboil The Parboil Benchmarks from the IMPACT Research Group at University of Illinois are a set of throughput computing applications for looking at computing architecture and compilers. Parboil test-cases support OpenMP, OpenCL, and CUDA multi-processing environments. However, at this time the test profile is just making use of the OpenMP and OpenCL test workloads. Learn more via the OpenBenchmarking.org test page.
Result
OpenBenchmarking.org Seconds, Fewer Is Better Parboil 2.5 Test: OpenMP LBM EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 10 20 30 40 50 SE +/- 0.14, N = 3 SE +/- 0.07, N = 3 SE +/- 0.02, N = 3 SE +/- 0.08, N = 3 SE +/- 0.07, N = 3 SE +/- 0.02, N = 3 SE +/- 0.11, N = 3 SE +/- 0.05, N = 3 SE +/- 0.26, N = 3 SE +/- 0.03, N = 3 SE +/- 0.26, N = 5 SE +/- 0.07, N = 3 SE +/- 0.03, N = 3 SE +/- 0.03, N = 3 45.76 42.95 46.07 24.92 29.02 27.60 22.94 27.64 26.47 21.94 23.82 23.32 27.25 35.42 1. (CXX) g++ options: -lm -lpthread -lgomp -O3 -ffast-math -fopenmp
Result Confidence
OpenBenchmarking.org Seconds, Fewer Is Better Parboil 2.5 Test: OpenMP LBM EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 9 18 27 36 45 Min: 45.56 / Avg: 45.76 / Max: 46.03 Min: 42.88 / Avg: 42.95 / Max: 43.08 Min: 46.05 / Avg: 46.07 / Max: 46.1 Min: 24.77 / Avg: 24.92 / Max: 25.05 Min: 28.89 / Avg: 29.02 / Max: 29.09 Min: 27.55 / Avg: 27.6 / Max: 27.63 Min: 22.73 / Avg: 22.94 / Max: 23.1 Min: 27.53 / Avg: 27.64 / Max: 27.7 Min: 26.02 / Avg: 26.47 / Max: 26.92 Min: 21.88 / Avg: 21.94 / Max: 21.99 Min: 23.2 / Avg: 23.82 / Max: 24.72 Min: 23.22 / Avg: 23.32 / Max: 23.46 Min: 27.2 / Avg: 27.25 / Max: 27.28 Min: 35.36 / Avg: 35.42 / Max: 35.47 1. (CXX) g++ options: -lm -lpthread -lgomp -O3 -ffast-math -fopenmp
WebP2 Image Encode This is a test of Google's libwebp2 library with the WebP2 image encode utility and using a sample 6000x4000 pixel JPEG image as the input, similar to the WebP/libwebp test profile. WebP2 is currently experimental and under heavy development as ultimately the successor to WebP. WebP2 supports 10-bit HDR, more efficienct lossy compression, improved lossless compression, animation support, and full multi-threading support compared to WebP. Learn more via the OpenBenchmarking.org test page.
Result
OpenBenchmarking.org Seconds, Fewer Is Better WebP2 Image Encode 20210126 Encode Settings: Quality 100, Lossless Compression EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 200 400 600 800 1000 SE +/- 0.56, N = 3 SE +/- 0.80, N = 3 SE +/- 0.30, N = 3 SE +/- 1.69, N = 3 SE +/- 0.25, N = 3 SE +/- 0.20, N = 3 SE +/- 0.13, N = 3 SE +/- 0.20, N = 3 SE +/- 0.09, N = 3 SE +/- 0.22, N = 3 SE +/- 0.41, N = 3 SE +/- 2.26, N = 3 SE +/- 0.43, N = 3 SE +/- 0.50, N = 3 954.80 680.90 580.07 562.07 467.70 467.43 474.59 467.51 481.50 473.76 474.55 481.95 778.66 475.39 1. (CXX) g++ options: -msse4.2 -fno-rtti -O3 -rdynamic -lpthread -ljpeg -lwebp -lwebpdemux
Result Confidence
OpenBenchmarking.org Seconds, Fewer Is Better WebP2 Image Encode 20210126 Encode Settings: Quality 100, Lossless Compression EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 200 400 600 800 1000 Min: 953.7 / Avg: 954.8 / Max: 955.56 Min: 679.66 / Avg: 680.9 / Max: 682.4 Min: 579.69 / Avg: 580.07 / Max: 580.65 Min: 558.73 / Avg: 562.07 / Max: 564.17 Min: 467.23 / Avg: 467.7 / Max: 468.09 Min: 467.12 / Avg: 467.43 / Max: 467.79 Min: 474.43 / Avg: 474.59 / Max: 474.85 Min: 467.15 / Avg: 467.51 / Max: 467.82 Min: 481.32 / Avg: 481.5 / Max: 481.6 Min: 473.32 / Avg: 473.76 / Max: 474.03 Min: 473.79 / Avg: 474.55 / Max: 475.18 Min: 477.74 / Avg: 481.95 / Max: 485.47 Min: 777.8 / Avg: 778.66 / Max: 779.18 Min: 474.62 / Avg: 475.39 / Max: 476.33 1. (CXX) g++ options: -msse4.2 -fno-rtti -O3 -rdynamic -lpthread -ljpeg -lwebp -lwebpdemux
Result
OpenBenchmarking.org Seconds, Fewer Is Better WebP2 Image Encode 20210126 Encode Settings: Quality 75, Compression Effort 7 EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 60 120 180 240 300 SE +/- 0.87, N = 3 SE +/- 0.65, N = 3 SE +/- 1.08, N = 3 SE +/- 1.62, N = 3 SE +/- 0.09, N = 3 SE +/- 0.05, N = 3 SE +/- 0.09, N = 3 SE +/- 0.04, N = 3 SE +/- 0.13, N = 3 SE +/- 0.03, N = 3 SE +/- 0.04, N = 3 SE +/- 0.47, N = 3 SE +/- 0.90, N = 3 SE +/- 0.46, N = 3 277.67 199.54 173.72 164.81 138.04 137.44 142.20 135.97 140.18 138.08 139.56 139.36 227.13 140.61 1. (CXX) g++ options: -msse4.2 -fno-rtti -O3 -rdynamic -lpthread -ljpeg -lwebp -lwebpdemux
Result Confidence
OpenBenchmarking.org Seconds, Fewer Is Better WebP2 Image Encode 20210126 Encode Settings: Quality 75, Compression Effort 7 EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 50 100 150 200 250 Min: 275.95 / Avg: 277.67 / Max: 278.78 Min: 198.32 / Avg: 199.54 / Max: 200.54 Min: 172.62 / Avg: 173.72 / Max: 175.87 Min: 161.8 / Avg: 164.81 / Max: 167.37 Min: 137.91 / Avg: 138.04 / Max: 138.21 Min: 137.39 / Avg: 137.44 / Max: 137.53 Min: 142.07 / Avg: 142.2 / Max: 142.38 Min: 135.9 / Avg: 135.97 / Max: 136.04 Min: 140 / Avg: 140.18 / Max: 140.43 Min: 138.03 / Avg: 138.08 / Max: 138.13 Min: 139.49 / Avg: 139.56 / Max: 139.6 Min: 138.86 / Avg: 139.36 / Max: 140.29 Min: 225.67 / Avg: 227.13 / Max: 228.77 Min: 140.07 / Avg: 140.61 / Max: 141.52 1. (CXX) g++ options: -msse4.2 -fno-rtti -O3 -rdynamic -lpthread -ljpeg -lwebp -lwebpdemux
Mobile Neural Network MNN is the Mobile Neural Network as a highly efficient, lightweight deep learning framework developed by Alibaba. Learn more via the OpenBenchmarking.org test page.
Result
OpenBenchmarking.org ms, Fewer Is Better Mobile Neural Network 1.1.1 Model: mobilenet-v1-1.0 EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 1.3001 2.6002 3.9003 5.2004 6.5005 SE +/- 0.007, N = 11 SE +/- 0.015, N = 4 SE +/- 0.060, N = 3 SE +/- 0.005, N = 15 SE +/- 0.012, N = 3 SE +/- 0.010, N = 3 SE +/- 0.008, N = 3 SE +/- 0.005, N = 15 SE +/- 0.004, N = 15 SE +/- 0.024, N = 3 SE +/- 0.006, N = 3 SE +/- 0.015, N = 3 SE +/- 0.002, N = 14 SE +/- 0.401, N = 3 3.917 5.322 4.081 3.856 3.213 2.927 3.003 2.836 3.022 3.056 3.073 3.187 3.625 5.778 MIN: 3.79 / MAX: 19.86 MIN: 5.22 / MAX: 13.18 MIN: 3.8 / MAX: 20.13 MIN: 3.74 / MAX: 20.71 MIN: 3.15 / MAX: 4.81 MIN: 2.87 / MAX: 5.27 MIN: 2.95 / MAX: 3.25 MIN: 2.77 / MAX: 4.94 MIN: 2.96 / MAX: 3.4 MIN: 2.98 / MAX: 3.31 MIN: 3.03 / MAX: 3.22 MIN: 3.13 / MAX: 3.28 MIN: 3.57 / MAX: 17.34 MIN: 4.65 / MAX: 7.24 1. (CXX) g++ options: -std=c++11 -O3 -fvisibility=hidden -fomit-frame-pointer -fstrict-aliasing -ffunction-sections -fdata-sections -ffast-math -fno-rtti -fno-exceptions -rdynamic -pthread -ldl
Result Confidence
OpenBenchmarking.org ms, Fewer Is Better Mobile Neural Network 1.1.1 Model: mobilenet-v1-1.0 EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 2 4 6 8 10 Min: 3.86 / Avg: 3.92 / Max: 3.95 Min: 5.3 / Avg: 5.32 / Max: 5.36 Min: 3.98 / Avg: 4.08 / Max: 4.18 Min: 3.82 / Avg: 3.86 / Max: 3.88 Min: 3.19 / Avg: 3.21 / Max: 3.23 Min: 2.92 / Avg: 2.93 / Max: 2.95 Min: 2.99 / Avg: 3 / Max: 3.02 Min: 2.81 / Avg: 2.84 / Max: 2.88 Min: 3.01 / Avg: 3.02 / Max: 3.05 Min: 3.02 / Avg: 3.06 / Max: 3.1 Min: 3.06 / Avg: 3.07 / Max: 3.09 Min: 3.17 / Avg: 3.19 / Max: 3.22 Min: 3.61 / Avg: 3.62 / Max: 3.64 Min: 5 / Avg: 5.78 / Max: 6.34 1. (CXX) g++ options: -std=c++11 -O3 -fvisibility=hidden -fomit-frame-pointer -fstrict-aliasing -ffunction-sections -fdata-sections -ffast-math -fno-rtti -fno-exceptions -rdynamic -pthread -ldl
WebP2 Image Encode This is a test of Google's libwebp2 library with the WebP2 image encode utility and using a sample 6000x4000 pixel JPEG image as the input, similar to the WebP/libwebp test profile. WebP2 is currently experimental and under heavy development as ultimately the successor to WebP. WebP2 supports 10-bit HDR, more efficienct lossy compression, improved lossless compression, animation support, and full multi-threading support compared to WebP. Learn more via the OpenBenchmarking.org test page.
Result
OpenBenchmarking.org Seconds, Fewer Is Better WebP2 Image Encode 20210126 Encode Settings: Quality 95, Compression Effort 7 EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 110 220 330 440 550 SE +/- 0.90, N = 3 SE +/- 2.81, N = 3 SE +/- 2.55, N = 3 SE +/- 0.98, N = 3 SE +/- 0.27, N = 3 SE +/- 0.13, N = 3 SE +/- 0.16, N = 3 SE +/- 0.19, N = 3 SE +/- 0.12, N = 3 SE +/- 0.24, N = 3 SE +/- 0.17, N = 3 SE +/- 0.12, N = 3 SE +/- 0.26, N = 3 SE +/- 1.43, N = 3 507.74 361.48 309.98 301.52 254.24 253.10 260.46 250.41 258.37 254.88 256.56 257.01 416.27 254.76 1. (CXX) g++ options: -msse4.2 -fno-rtti -O3 -rdynamic -lpthread -ljpeg -lwebp -lwebpdemux
Result Confidence
OpenBenchmarking.org Seconds, Fewer Is Better WebP2 Image Encode 20210126 Encode Settings: Quality 95, Compression Effort 7 EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 90 180 270 360 450 Min: 506.68 / Avg: 507.74 / Max: 509.53 Min: 356.31 / Avg: 361.48 / Max: 365.98 Min: 305.77 / Avg: 309.98 / Max: 314.59 Min: 300.37 / Avg: 301.52 / Max: 303.47 Min: 253.9 / Avg: 254.24 / Max: 254.77 Min: 252.84 / Avg: 253.1 / Max: 253.26 Min: 260.18 / Avg: 260.46 / Max: 260.72 Min: 250.08 / Avg: 250.41 / Max: 250.74 Min: 258.22 / Avg: 258.37 / Max: 258.61 Min: 254.57 / Avg: 254.88 / Max: 255.36 Min: 256.37 / Avg: 256.56 / Max: 256.9 Min: 256.86 / Avg: 257 / Max: 257.24 Min: 415.89 / Avg: 416.27 / Max: 416.76 Min: 252.29 / Avg: 254.76 / Max: 257.23 1. (CXX) g++ options: -msse4.2 -fno-rtti -O3 -rdynamic -lpthread -ljpeg -lwebp -lwebpdemux
Algebraic Multi-Grid Benchmark AMG is a parallel algebraic multigrid solver for linear systems arising from problems on unstructured grids. The driver provided with AMG builds linear systems for various 3-dimensional problems. Learn more via the OpenBenchmarking.org test page.
Result
OpenBenchmarking.org Figure Of Merit, More Is Better Algebraic Multi-Grid Benchmark 1.2 EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 200M 400M 600M 800M 1000M SE +/- 295157.17, N = 5 SE +/- 252656.85, N = 4 SE +/- 314598.13, N = 3 SE +/- 405072.19, N = 4 SE +/- 643499.89, N = 3 SE +/- 998206.04, N = 3 SE +/- 422202.49, N = 3 SE +/- 142607.92, N = 3 SE +/- 989060.38, N = 3 SE +/- 229126.62, N = 3 SE +/- 507394.80, N = 3 SE +/- 322962.48, N = 6 SE +/- 3149876.45, N = 4 449916460 457855350 455760633 788266875 778459433 774304800 909532667 774329467 856893400 883735200 878375333 809844583 643180925 1. (CC) gcc options: -lparcsr_ls -lparcsr_mv -lseq_mv -lIJ_mv -lkrylov -lHYPRE_utilities -lm -fopenmp -pthread -lmpi
Figure Of Merit Per Watt
OpenBenchmarking.org Figure Of Merit Per Watt, More Is Better Algebraic Multi-Grid Benchmark 1.2 EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 2M 4M 6M 8M 10M 7366263.78 6485573.10 5939960.67 8667240.71 7131421.00 6513520.25 6228384.62 6697956.10 5919717.78 5265803.49 5138262.51 9577991.03 4682548.38
Result Confidence
OpenBenchmarking.org Figure Of Merit, More Is Better Algebraic Multi-Grid Benchmark 1.2 EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 160M 320M 480M 640M 800M Min: 448913300 / Avg: 449916460 / Max: 450629100 Min: 457151100 / Avg: 457855350 / Max: 458299300 Min: 455133300 / Avg: 455760633.33 / Max: 456116200 Min: 787578900 / Avg: 788266875 / Max: 789313600 Min: 777565100 / Avg: 778459433.33 / Max: 779708100 Min: 772483400 / Avg: 774304800 / Max: 775923400 Min: 908914700 / Avg: 909532666.67 / Max: 910340000 Min: 774119000 / Avg: 774329466.67 / Max: 774601400 Min: 854937100 / Avg: 856893400 / Max: 858125300 Min: 883287900 / Avg: 883735200 / Max: 884045100 Min: 877829000 / Avg: 878375333.33 / Max: 879389100 Min: 808702900 / Avg: 809844583.33 / Max: 810642700 Min: 634035200 / Avg: 643180925 / Max: 647428500 1. (CC) gcc options: -lparcsr_ls -lparcsr_mv -lseq_mv -lIJ_mv -lkrylov -lHYPRE_utilities -lm -fopenmp -pthread -lmpi
dav1d Dav1d is an open-source, speedy AV1 video decoder. This test profile times how long it takes to decode sample AV1 video content. Learn more via the OpenBenchmarking.org test page.
Result
OpenBenchmarking.org FPS, More Is Better dav1d 0.8.1 Video Input: Chimera 1080p 10-bit EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 40 80 120 160 200 SE +/- 0.13, N = 3 SE +/- 0.17, N = 3 SE +/- 0.38, N = 3 SE +/- 0.09, N = 3 SE +/- 0.20, N = 3 SE +/- 0.08, N = 3 SE +/- 0.13, N = 3 SE +/- 0.16, N = 3 SE +/- 0.12, N = 3 SE +/- 0.28, N = 3 SE +/- 0.56, N = 3 SE +/- 0.31, N = 3 SE +/- 0.13, N = 3 SE +/- 0.17, N = 3 94.36 107.25 114.49 116.68 135.69 152.15 146.29 152.78 178.70 179.72 190.19 185.31 109.55 129.77 MIN: 60.14 / MAX: 225.56 MIN: 67.93 / MAX: 243.83 MIN: 72.02 / MAX: 259.87 MIN: 74.3 / MAX: 261.93 MIN: 85.88 / MAX: 272.31 MIN: 97.46 / MAX: 272.72 MIN: 94.75 / MAX: 256.37 MIN: 98.52 / MAX: 278.09 MIN: 121.07 / MAX: 277.42 MIN: 121.84 / MAX: 276.81 MIN: 126.93 / MAX: 307.7 MIN: 125.96 / MAX: 294.64 MIN: 70.77 / MAX: 249.84 MIN: 84.35 / MAX: 268.95 1. (CC) gcc options: -pthread
FPS Per Watt
OpenBenchmarking.org FPS Per Watt, More Is Better dav1d 0.8.1 Video Input: Chimera 1080p 10-bit EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 0.5828 1.1656 1.7484 2.3312 2.914 1.95 2.15 2.29 2.00 2.26 2.53 1.84 2.58 2.59 2.34 2.37 2.22 1.62 1.47
Result Confidence
OpenBenchmarking.org FPS, More Is Better dav1d 0.8.1 Video Input: Chimera 1080p 10-bit EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 30 60 90 120 150 Min: 94.18 / Avg: 94.36 / Max: 94.61 Min: 106.92 / Avg: 107.25 / Max: 107.46 Min: 113.88 / Avg: 114.49 / Max: 115.2 Min: 116.54 / Avg: 116.68 / Max: 116.86 Min: 135.36 / Avg: 135.69 / Max: 136.06 Min: 152.02 / Avg: 152.15 / Max: 152.28 Min: 146.03 / Avg: 146.29 / Max: 146.46 Min: 152.47 / Avg: 152.78 / Max: 153.01 Min: 178.47 / Avg: 178.7 / Max: 178.84 Min: 179.44 / Avg: 179.72 / Max: 180.27 Min: 189.1 / Avg: 190.19 / Max: 190.97 Min: 184.71 / Avg: 185.31 / Max: 185.73 Min: 109.41 / Avg: 109.55 / Max: 109.8 Min: 129.43 / Avg: 129.77 / Max: 129.97 1. (CC) gcc options: -pthread
ACES DGEMM This is a multi-threaded DGEMM benchmark. Learn more via the OpenBenchmarking.org test page.
Result
OpenBenchmarking.org GFLOP/s, More Is Better ACES DGEMM 1.0 Sustained Floating-Point Rate EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 4 8 12 16 20 SE +/- 0.010754, N = 3 SE +/- 0.008716, N = 3 SE +/- 0.037637, N = 3 SE +/- 0.017716, N = 3 SE +/- 0.025438, N = 3 SE +/- 0.066319, N = 3 SE +/- 0.072162, N = 3 SE +/- 0.091101, N = 3 SE +/- 0.083534, N = 3 SE +/- 0.030087, N = 3 SE +/- 0.099835, N = 4 SE +/- 0.163720, N = 4 SE +/- 0.039059, N = 3 SE +/- 0.028662, N = 3 1.583704 3.464003 4.452419 4.963715 7.208235 9.326909 9.828871 8.863336 12.735031 13.942465 16.881168 15.614812 3.011595 4.897653 1. (CC) gcc options: -O3 -march=native -fopenmp
GFLOP/s Per Watt
OpenBenchmarking.org GFLOP/s Per Watt, More Is Better ACES DGEMM 1.0 Sustained Floating-Point Rate EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 0.0248 0.0496 0.0744 0.0992 0.124 0.02 0.05 0.05 0.05 0.06 0.07 0.06 0.07 0.10 0.08 0.11 0.11 0.03 0.03
Result Confidence
OpenBenchmarking.org GFLOP/s, More Is Better ACES DGEMM 1.0 Sustained Floating-Point Rate EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 4 8 12 16 20 Min: 1.57 / Avg: 1.58 / Max: 1.61 Min: 3.45 / Avg: 3.46 / Max: 3.48 Min: 4.39 / Avg: 4.45 / Max: 4.52 Min: 4.93 / Avg: 4.96 / Max: 4.99 Min: 7.16 / Avg: 7.21 / Max: 7.24 Min: 9.25 / Avg: 9.33 / Max: 9.46 Min: 9.75 / Avg: 9.83 / Max: 9.97 Min: 8.68 / Avg: 8.86 / Max: 8.96 Min: 12.62 / Avg: 12.74 / Max: 12.9 Min: 13.91 / Avg: 13.94 / Max: 14 Min: 16.59 / Avg: 16.88 / Max: 17.02 Min: 15.39 / Avg: 15.61 / Max: 16.1 Min: 2.95 / Avg: 3.01 / Max: 3.08 Min: 4.85 / Avg: 4.9 / Max: 4.95 1. (CC) gcc options: -O3 -march=native -fopenmp
Facebook RocksDB This is a benchmark of Facebook's RocksDB as an embeddable persistent key-value store for fast storage based on Google's LevelDB. Learn more via the OpenBenchmarking.org test page.
Result
OpenBenchmarking.org Op/s, More Is Better Facebook RocksDB 6.3.6 Test: Sequential Fill EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 200K 400K 600K 800K 1000K SE +/- 6504.38, N = 3 SE +/- 198.51, N = 3 SE +/- 3857.18, N = 3 SE +/- 6451.00, N = 3 SE +/- 9904.69, N = 4 SE +/- 6414.70, N = 3 SE +/- 4243.12, N = 3 SE +/- 7271.02, N = 3 SE +/- 6981.82, N = 3 SE +/- 1276.30, N = 3 SE +/- 1119.16, N = 3 SE +/- 1138.19, N = 3 SE +/- 3955.87, N = 3 SE +/- 7660.92, N = 6 611302 705855 775796 756268 838224 881986 825374 885722 536242 527541 447191 451003 624502 756676 1. (CXX) g++ options: -O3 -march=native -std=c++11 -fno-builtin-memcmp -fno-rtti -rdynamic -lpthread
Op/s Per Watt
OpenBenchmarking.org Op/s Per Watt, More Is Better Facebook RocksDB 6.3.6 Test: Sequential Fill EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 2K 4K 6K 8K 10K 10036.15 9067.03 8813.61 7541.24 5925.99 6049.54 4999.98 5622.62 3850.07 3278.22 2634.77 2844.47 6995.00 4243.87
Result Confidence
OpenBenchmarking.org Op/s, More Is Better Facebook RocksDB 6.3.6 Test: Sequential Fill EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 150K 300K 450K 600K 750K Min: 598299 / Avg: 611302 / Max: 618139 Min: 705589 / Avg: 705854.67 / Max: 706243 Min: 771919 / Avg: 775795.67 / Max: 783510 Min: 749121 / Avg: 756268 / Max: 769144 Min: 809652 / Avg: 838224 / Max: 852941 Min: 872797 / Avg: 881986 / Max: 894334 Min: 820254 / Avg: 825374 / Max: 833795 Min: 875249 / Avg: 885722.33 / Max: 899696 Min: 528910 / Avg: 536242.33 / Max: 550200 Min: 525500 / Avg: 527540.67 / Max: 529889 Min: 445589 / Avg: 447191.33 / Max: 449346 Min: 449363 / Avg: 451002.67 / Max: 453190 Min: 617818 / Avg: 624501.67 / Max: 631510 Min: 736622 / Avg: 756676 / Max: 785060 1. (CXX) g++ options: -O3 -march=native -std=c++11 -fno-builtin-memcmp -fno-rtti -rdynamic -lpthread
WebP2 Image Encode This is a test of Google's libwebp2 library with the WebP2 image encode utility and using a sample 6000x4000 pixel JPEG image as the input, similar to the WebP/libwebp test profile. WebP2 is currently experimental and under heavy development as ultimately the successor to WebP. WebP2 supports 10-bit HDR, more efficienct lossy compression, improved lossless compression, animation support, and full multi-threading support compared to WebP. Learn more via the OpenBenchmarking.org test page.
Result
OpenBenchmarking.org Seconds, Fewer Is Better WebP2 Image Encode 20210126 Encode Settings: Quality 100, Compression Effort 5 EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 4 8 12 16 20 SE +/- 0.032, N = 4 SE +/- 0.018, N = 5 SE +/- 0.012, N = 5 SE +/- 0.020, N = 5 SE +/- 0.009, N = 6 SE +/- 0.027, N = 6 SE +/- 0.010, N = 6 SE +/- 0.015, N = 6 SE +/- 0.013, N = 6 SE +/- 0.006, N = 6 SE +/- 0.009, N = 6 SE +/- 0.012, N = 6 SE +/- 0.031, N = 4 SE +/- 0.012, N = 6 15.547 11.131 9.654 9.354 7.974 7.972 8.055 7.949 8.162 8.074 8.052 8.125 12.788 7.973 1. (CXX) g++ options: -msse4.2 -fno-rtti -O3 -rdynamic -lpthread -ljpeg -lwebp -lwebpdemux
Result Confidence
OpenBenchmarking.org Seconds, Fewer Is Better WebP2 Image Encode 20210126 Encode Settings: Quality 100, Compression Effort 5 EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 4 8 12 16 20 Min: 15.46 / Avg: 15.55 / Max: 15.62 Min: 11.09 / Avg: 11.13 / Max: 11.19 Min: 9.63 / Avg: 9.65 / Max: 9.69 Min: 9.31 / Avg: 9.35 / Max: 9.43 Min: 7.94 / Avg: 7.97 / Max: 8 Min: 7.91 / Avg: 7.97 / Max: 8.08 Min: 8.01 / Avg: 8.06 / Max: 8.08 Min: 7.92 / Avg: 7.95 / Max: 8.02 Min: 8.12 / Avg: 8.16 / Max: 8.21 Min: 8.05 / Avg: 8.07 / Max: 8.09 Min: 8.04 / Avg: 8.05 / Max: 8.09 Min: 8.1 / Avg: 8.13 / Max: 8.17 Min: 12.74 / Avg: 12.79 / Max: 12.88 Min: 7.94 / Avg: 7.97 / Max: 8.02 1. (CXX) g++ options: -msse4.2 -fno-rtti -O3 -rdynamic -lpthread -ljpeg -lwebp -lwebpdemux
ECP-CANDLE The CANDLE benchmark codes implement deep learning architectures relevant to problems in cancer. These architectures address problems at different biological scales, specifically problems at the molecular, cellular and population scales. Learn more via the OpenBenchmarking.org test page.
OpenBenchmarking.org Seconds, Fewer Is Better ECP-CANDLE 0.3 Benchmark: P3B1 EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 200 400 600 800 1000 715.21 623.78 655.45 574.77 576.98 577.65 586.67 566.99 584.61 590.56 604.15 649.31 668.99 1108.26
Facebook RocksDB This is a benchmark of Facebook's RocksDB as an embeddable persistent key-value store for fast storage based on Google's LevelDB. Learn more via the OpenBenchmarking.org test page.
Result
OpenBenchmarking.org Op/s, More Is Better Facebook RocksDB 6.3.6 Test: Random Fill EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 200K 400K 600K 800K 1000K SE +/- 6988.75, N = 3 SE +/- 6225.31, N = 6 SE +/- 9036.88, N = 4 SE +/- 5524.24, N = 9 SE +/- 10119.73, N = 3 SE +/- 6323.38, N = 3 SE +/- 2994.50, N = 3 SE +/- 4338.82, N = 3 SE +/- 4097.81, N = 3 SE +/- 3532.96, N = 3 SE +/- 227.93, N = 3 SE +/- 1303.40, N = 3 SE +/- 6471.76, N = 5 SE +/- 6124.02, N = 3 545816 656055 735381 692044 805066 846887 806814 860225 521910 518446 442864 451547 581407 699077 1. (CXX) g++ options: -O3 -march=native -std=c++11 -fno-builtin-memcmp -fno-rtti -rdynamic -lpthread
Op/s Per Watt
OpenBenchmarking.org Op/s Per Watt, More Is Better Facebook RocksDB 6.3.6 Test: Random Fill EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 2K 4K 6K 8K 10K 8529.54 8044.80 8078.17 6716.57 5637.77 5906.76 4922.99 5587.32 3855.32 3303.48 2783.45 3013.23 6147.22 3901.69
Result Confidence
OpenBenchmarking.org Op/s, More Is Better Facebook RocksDB 6.3.6 Test: Random Fill EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 150K 300K 450K 600K 750K Min: 533331 / Avg: 545816.33 / Max: 557501 Min: 638259 / Avg: 656055.33 / Max: 681884 Min: 722999 / Avg: 735381.25 / Max: 761712 Min: 669061 / Avg: 692043.67 / Max: 723569 Min: 794424 / Avg: 805065.67 / Max: 825296 Min: 835350 / Avg: 846887 / Max: 857142 Min: 801674 / Avg: 806813.67 / Max: 812046 Min: 851801 / Avg: 860225.33 / Max: 866240 Min: 516355 / Avg: 521910 / Max: 529906 Min: 513881 / Avg: 518445.67 / Max: 525399 Min: 442493 / Avg: 442864.33 / Max: 443279 Min: 449913 / Avg: 451547 / Max: 454123 Min: 569871 / Avg: 581407 / Max: 602220 Min: 687578 / Avg: 699077 / Max: 708479 1. (CXX) g++ options: -O3 -march=native -std=c++11 -fno-builtin-memcmp -fno-rtti -rdynamic -lpthread
NCNN NCNN is a high performance neural network inference framework optimized for mobile and other platforms developed by Tencent. Learn more via the OpenBenchmarking.org test page.
Result
OpenBenchmarking.org ms, Fewer Is Better NCNN 20201218 Target: CPU - Model: vgg16 EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 13 26 39 52 65 SE +/- 0.05, N = 3 SE +/- 0.13, N = 3 SE +/- 0.27, N = 3 SE +/- 0.12, N = 3 SE +/- 0.01, N = 3 SE +/- 0.12, N = 3 SE +/- 0.15, N = 11 SE +/- 0.07, N = 3 SE +/- 0.32, N = 3 SE +/- 0.19, N = 12 SE +/- 0.27, N = 9 SE +/- 0.17, N = 9 SE +/- 0.18, N = 3 SE +/- 0.15, N = 3 40.67 40.01 39.42 30.84 31.46 32.04 33.27 31.48 34.20 34.90 37.35 38.51 33.81 59.81 MIN: 40.35 / MAX: 43.91 MIN: 39.54 / MAX: 41.05 MIN: 38.3 / MAX: 143.19 MIN: 30.45 / MAX: 32.11 MIN: 31.24 / MAX: 33.08 MIN: 31.32 / MAX: 109.6 MIN: 31.92 / MAX: 108.33 MIN: 31.08 / MAX: 45.9 MIN: 33.04 / MAX: 37.52 MIN: 33.25 / MAX: 146.34 MIN: 35.01 / MAX: 111.55 MIN: 36.25 / MAX: 125.98 MIN: 33.39 / MAX: 80.53 MIN: 57.95 / MAX: 122.99 1. (CXX) g++ options: -O3 -rdynamic -lgomp -lpthread
Result Confidence
OpenBenchmarking.org ms, Fewer Is Better NCNN 20201218 Target: CPU - Model: vgg16 EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 12 24 36 48 60 Min: 40.61 / Avg: 40.67 / Max: 40.77 Min: 39.75 / Avg: 40.01 / Max: 40.15 Min: 38.92 / Avg: 39.42 / Max: 39.85 Min: 30.69 / Avg: 30.84 / Max: 31.08 Min: 31.45 / Avg: 31.46 / Max: 31.48 Min: 31.88 / Avg: 32.04 / Max: 32.28 Min: 32.69 / Avg: 33.27 / Max: 34.04 Min: 31.34 / Avg: 31.48 / Max: 31.56 Min: 33.59 / Avg: 34.2 / Max: 34.65 Min: 34.19 / Avg: 34.9 / Max: 36.02 Min: 35.99 / Avg: 37.35 / Max: 38.19 Min: 37.89 / Avg: 38.51 / Max: 39.47 Min: 33.62 / Avg: 33.81 / Max: 34.17 Min: 59.51 / Avg: 59.81 / Max: 60.01 1. (CXX) g++ options: -O3 -rdynamic -lgomp -lpthread
AI Benchmark Alpha AI Benchmark Alpha is a Python library for evaluating artificial intelligence (AI) performance on diverse hardware platforms and relies upon the TensorFlow machine learning library. Learn more via the OpenBenchmarking.org test page.
OpenBenchmarking.org Score, More Is Better AI Benchmark Alpha 0.1.2 Device Inference Score EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 500 1000 1500 2000 2500 1112 1372 1538 1660 1926 2022 2043 2107 2049 2125 2122 1965 1301 1456
Result
OpenBenchmarking.org ms, Fewer Is Better NCNN 20201218 Target: CPU - Model: mobilenet EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 8 16 24 32 40 SE +/- 0.10, N = 3 SE +/- 0.16, N = 3 SE +/- 0.10, N = 3 SE +/- 0.08, N = 3 SE +/- 0.07, N = 3 SE +/- 0.15, N = 3 SE +/- 0.18, N = 11 SE +/- 0.03, N = 3 SE +/- 0.37, N = 3 SE +/- 0.64, N = 12 SE +/- 0.82, N = 9 SE +/- 0.91, N = 9 SE +/- 0.10, N = 3 SE +/- 0.10, N = 3 22.33 20.06 20.46 19.70 19.52 21.14 23.59 20.43 26.50 28.92 35.78 35.58 20.54 24.14 MIN: 21.92 / MAX: 23.79 MIN: 19.5 / MAX: 23.62 MIN: 19.72 / MAX: 77.23 MIN: 19.2 / MAX: 20.45 MIN: 19.11 / MAX: 21.65 MIN: 20.56 / MAX: 35 MIN: 22.06 / MAX: 161.6 MIN: 19.91 / MAX: 33.27 MIN: 24.55 / MAX: 33.31 MIN: 24.32 / MAX: 41.88 MIN: 28.31 / MAX: 170.87 MIN: 29.55 / MAX: 165.69 MIN: 20.19 / MAX: 21.27 MIN: 23.55 / MAX: 25.73 1. (CXX) g++ options: -O3 -rdynamic -lgomp -lpthread
Result Confidence
OpenBenchmarking.org ms, Fewer Is Better NCNN 20201218 Target: CPU - Model: mobilenet EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 8 16 24 32 40 Min: 22.23 / Avg: 22.33 / Max: 22.53 Min: 19.75 / Avg: 20.06 / Max: 20.29 Min: 20.36 / Avg: 20.46 / Max: 20.66 Min: 19.56 / Avg: 19.7 / Max: 19.85 Min: 19.39 / Avg: 19.52 / Max: 19.6 Min: 20.98 / Avg: 21.14 / Max: 21.44 Min: 22.94 / Avg: 23.59 / Max: 24.92 Min: 20.38 / Avg: 20.43 / Max: 20.48 Min: 25.8 / Avg: 26.5 / Max: 27.04 Min: 26.74 / Avg: 28.92 / Max: 33.72 Min: 31.86 / Avg: 35.78 / Max: 39.06 Min: 31.5 / Avg: 35.58 / Max: 39.42 Min: 20.4 / Avg: 20.54 / Max: 20.73 Min: 24 / Avg: 24.14 / Max: 24.32 1. (CXX) g++ options: -O3 -rdynamic -lgomp -lpthread
Numenta Anomaly Benchmark Numenta Anomaly Benchmark (NAB) is a benchmark for evaluating algorithms for anomaly detection in streaming, real-time applications. It is comprised of over 50 labeled real-world and artificial timeseries data files plus a novel scoring mechanism designed for real-time applications. This test profile currently measures the time to run various detectors. Learn more via the OpenBenchmarking.org test page.
Result
OpenBenchmarking.org Seconds, Fewer Is Better Numenta Anomaly Benchmark 1.1 Detector: Earthgecko Skyline EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 30 60 90 120 150 SE +/- 1.44, N = 3 SE +/- 0.64, N = 3 SE +/- 1.07, N = 3 SE +/- 0.45, N = 3 SE +/- 0.58, N = 3 SE +/- 0.60, N = 3 SE +/- 0.65, N = 3 SE +/- 0.80, N = 3 SE +/- 1.10, N = 3 SE +/- 0.18, N = 3 SE +/- 0.45, N = 3 SE +/- 0.05, N = 3 SE +/- 0.92, N = 7 SE +/- 0.59, N = 3 141.25 101.59 96.85 88.32 85.76 85.73 86.70 83.83 86.06 85.03 84.79 84.83 98.52 75.23
Result Confidence
OpenBenchmarking.org Seconds, Fewer Is Better Numenta Anomaly Benchmark 1.1 Detector: Earthgecko Skyline EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 30 60 90 120 150 Min: 138.42 / Avg: 141.25 / Max: 143.09 Min: 100.3 / Avg: 101.59 / Max: 102.33 Min: 94.95 / Avg: 96.85 / Max: 98.65 Min: 87.53 / Avg: 88.32 / Max: 89.11 Min: 84.6 / Avg: 85.76 / Max: 86.43 Min: 85.04 / Avg: 85.73 / Max: 86.93 Min: 85.78 / Avg: 86.7 / Max: 87.96 Min: 82.24 / Avg: 83.83 / Max: 84.72 Min: 83.86 / Avg: 86.06 / Max: 87.25 Min: 84.8 / Avg: 85.03 / Max: 85.39 Min: 84.12 / Avg: 84.79 / Max: 85.64 Min: 84.74 / Avg: 84.83 / Max: 84.9 Min: 95.01 / Avg: 98.52 / Max: 100.63 Min: 74.45 / Avg: 75.23 / Max: 76.39
Timed HMMer Search This test searches through the Pfam database of profile hidden markov models. The search finds the domain structure of Drosophila Sevenless protein. Learn more via the OpenBenchmarking.org test page.
Result
OpenBenchmarking.org Seconds, Fewer Is Better Timed HMMer Search 3.3.1 Pfam Database Search EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 40 80 120 160 200 SE +/- 0.06, N = 3 SE +/- 0.10, N = 3 SE +/- 0.05, N = 3 SE +/- 0.04, N = 3 SE +/- 0.09, N = 3 SE +/- 0.04, N = 3 SE +/- 0.08, N = 3 SE +/- 0.04, N = 3 SE +/- 0.06, N = 3 SE +/- 0.06, N = 3 SE +/- 0.16, N = 3 SE +/- 0.18, N = 3 SE +/- 0.03, N = 3 SE +/- 0.08, N = 3 126.21 129.44 132.39 128.93 133.76 141.65 145.01 139.82 165.55 166.11 191.15 191.23 104.26 110.43 1. (CC) gcc options: -O3 -pthread -lhmmer -leasel -lm
Result Confidence
OpenBenchmarking.org Seconds, Fewer Is Better Timed HMMer Search 3.3.1 Pfam Database Search EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 40 80 120 160 200 Min: 126.1 / Avg: 126.21 / Max: 126.28 Min: 129.26 / Avg: 129.44 / Max: 129.62 Min: 132.35 / Avg: 132.39 / Max: 132.48 Min: 128.87 / Avg: 128.93 / Max: 129.01 Min: 133.6 / Avg: 133.76 / Max: 133.9 Min: 141.6 / Avg: 141.65 / Max: 141.72 Min: 144.87 / Avg: 145.01 / Max: 145.14 Min: 139.74 / Avg: 139.82 / Max: 139.89 Min: 165.45 / Avg: 165.55 / Max: 165.66 Min: 165.99 / Avg: 166.11 / Max: 166.19 Min: 190.84 / Avg: 191.15 / Max: 191.38 Min: 190.86 / Avg: 191.23 / Max: 191.42 Min: 104.21 / Avg: 104.26 / Max: 104.31 Min: 110.31 / Avg: 110.43 / Max: 110.57 1. (CC) gcc options: -O3 -pthread -lhmmer -leasel -lm
Stream-Dynamic This is an open-source AMD modified copy of the Stream memory benchmark catered towards running the RAM benchmark on systems with the AMD Optimizing C/C++ Compiler (AOCC) among other by-default optimizations aiming for an easy and standardized deployment. This test profile though will attempt to fall-back to GCC / Clang for systems lacking AOCC, otherwise there is the existing "stream" test profile. Learn more via the OpenBenchmarking.org test page.
Stream-Dynamic This is an open-source AMD modified copy of the Stream memory benchmark catered towards running the RAM benchmark on systems with the AMD Optimizing C/C++ Compiler (AOCC) among other by-default optimizations aiming for an easy and standardized deployment. This test profile though will attempt to fall-back to GCC / Clang for systems lacking AOCC, otherwise there is the existing "stream" test profile. Learn more via the OpenBenchmarking.org test page.
Numenta Anomaly Benchmark Numenta Anomaly Benchmark (NAB) is a benchmark for evaluating algorithms for anomaly detection in streaming, real-time applications. It is comprised of over 50 labeled real-world and artificial timeseries data files plus a novel scoring mechanism designed for real-time applications. This test profile currently measures the time to run various detectors. Learn more via the OpenBenchmarking.org test page.
Result
OpenBenchmarking.org Seconds, Fewer Is Better Numenta Anomaly Benchmark 1.1 Detector: Windowed Gaussian EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 3 6 9 12 15 SE +/- 0.047, N = 4 SE +/- 0.043, N = 5 SE +/- 0.033, N = 6 SE +/- 0.018, N = 6 SE +/- 0.041, N = 6 SE +/- 0.020, N = 6 SE +/- 0.044, N = 6 SE +/- 0.016, N = 6 SE +/- 0.025, N = 6 SE +/- 0.036, N = 6 SE +/- 0.038, N = 6 SE +/- 0.029, N = 6 SE +/- 0.034, N = 5 SE +/- 0.016, N = 6 11.912 8.798 8.105 7.645 7.121 6.989 7.220 6.900 7.033 7.063 6.971 6.930 9.790 6.586
Result Confidence
OpenBenchmarking.org Seconds, Fewer Is Better Numenta Anomaly Benchmark 1.1 Detector: Windowed Gaussian EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 3 6 9 12 15 Min: 11.83 / Avg: 11.91 / Max: 12.03 Min: 8.7 / Avg: 8.8 / Max: 8.93 Min: 8 / Avg: 8.1 / Max: 8.23 Min: 7.59 / Avg: 7.65 / Max: 7.7 Min: 6.99 / Avg: 7.12 / Max: 7.23 Min: 6.93 / Avg: 6.99 / Max: 7.06 Min: 7.06 / Avg: 7.22 / Max: 7.34 Min: 6.84 / Avg: 6.9 / Max: 6.95 Min: 6.95 / Avg: 7.03 / Max: 7.12 Min: 6.98 / Avg: 7.06 / Max: 7.22 Min: 6.85 / Avg: 6.97 / Max: 7.12 Min: 6.86 / Avg: 6.93 / Max: 7.04 Min: 9.66 / Avg: 9.79 / Max: 9.84 Min: 6.53 / Avg: 6.59 / Max: 6.62
Stream This benchmark tests the system memory (RAM) performance. Learn more via the OpenBenchmarking.org test page.
Result
OpenBenchmarking.org MB/s, More Is Better Stream 2013-01-17 Type: Triad EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 20K 40K 60K 80K 100K SE +/- 65.26, N = 5 SE +/- 2.27, N = 5 SE +/- 8.84, N = 5 SE +/- 5.88, N = 5 SE +/- 7.48, N = 5 SE +/- 19.43, N = 5 SE +/- 16.47, N = 5 SE +/- 36.22, N = 5 SE +/- 11.91, N = 5 SE +/- 21.10, N = 5 SE +/- 26.33, N = 5 SE +/- 59.32, N = 5 SE +/- 194.23, N = 5 56788.6 56066.6 55596.3 88105.7 87308.4 87239.8 99248.2 87057.0 96497.1 98343.2 98034.8 89567.2 72315.6 1. (CC) gcc options: -O3 -march=native -fopenmp
MB/s Per Watt
OpenBenchmarking.org MB/s Per Watt, More Is Better Stream 2013-01-17 Type: Triad EPYC 7232P EPYC 7302P EPYC 7402P 600 1200 1800 2400 3000 2060.05 2743.30 2788.51
Result Confidence
OpenBenchmarking.org MB/s, More Is Better Stream 2013-01-17 Type: Triad EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 20K 40K 60K 80K 100K Min: 56528 / Avg: 56788.62 / Max: 56863.9 Min: 56061.4 / Avg: 56066.58 / Max: 56074.5 Min: 55564.4 / Avg: 55596.28 / Max: 55617.5 Min: 88086.3 / Avg: 88105.74 / Max: 88121.8 Min: 87291.9 / Avg: 87308.42 / Max: 87333.6 Min: 87168 / Avg: 87239.76 / Max: 87282.1 Min: 99194.2 / Avg: 99248.22 / Max: 99293.1 Min: 86972.9 / Avg: 87057.04 / Max: 87161.9 Min: 96474.4 / Avg: 96497.14 / Max: 96541 Min: 98280 / Avg: 98343.22 / Max: 98393.4 Min: 97939.6 / Avg: 98034.8 / Max: 98096.1 Min: 89468.9 / Avg: 89567.18 / Max: 89800.2 Min: 71942.4 / Avg: 72315.56 / Max: 73068.3 1. (CC) gcc options: -O3 -march=native -fopenmp
Mobile Neural Network MNN is the Mobile Neural Network as a highly efficient, lightweight deep learning framework developed by Alibaba. Learn more via the OpenBenchmarking.org test page.
Result
OpenBenchmarking.org ms, Fewer Is Better Mobile Neural Network 1.1.1 Model: MobileNetV2_224 EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 2 4 6 8 10 SE +/- 0.030, N = 11 SE +/- 0.155, N = 4 SE +/- 0.033, N = 3 SE +/- 0.046, N = 15 SE +/- 0.026, N = 3 SE +/- 0.028, N = 3 SE +/- 0.022, N = 3 SE +/- 0.009, N = 15 SE +/- 0.008, N = 15 SE +/- 0.016, N = 3 SE +/- 0.022, N = 3 SE +/- 0.016, N = 3 SE +/- 0.017, N = 14 SE +/- 0.391, N = 3 4.944 5.930 5.855 5.772 5.270 4.820 4.821 4.713 4.852 4.825 4.920 5.067 4.578 8.171 MIN: 4.74 / MAX: 7.04 MIN: 5.53 / MAX: 20.6 MIN: 5.58 / MAX: 23.16 MIN: 5.46 / MAX: 20.47 MIN: 5.12 / MAX: 6.52 MIN: 4.67 / MAX: 6.92 MIN: 4.72 / MAX: 5.31 MIN: 4.51 / MAX: 6.85 MIN: 4.69 / MAX: 5.21 MIN: 4.71 / MAX: 5.16 MIN: 4.78 / MAX: 5.1 MIN: 4.95 / MAX: 5.21 MIN: 4.43 / MAX: 10.46 MIN: 7.28 / MAX: 12.17 1. (CXX) g++ options: -std=c++11 -O3 -fvisibility=hidden -fomit-frame-pointer -fstrict-aliasing -ffunction-sections -fdata-sections -ffast-math -fno-rtti -fno-exceptions -rdynamic -pthread -ldl
Result Confidence
OpenBenchmarking.org ms, Fewer Is Better Mobile Neural Network 1.1.1 Model: MobileNetV2_224 EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 3 6 9 12 15 Min: 4.81 / Avg: 4.94 / Max: 5.12 Min: 5.66 / Avg: 5.93 / Max: 6.37 Min: 5.81 / Avg: 5.86 / Max: 5.92 Min: 5.57 / Avg: 5.77 / Max: 6.19 Min: 5.23 / Avg: 5.27 / Max: 5.32 Min: 4.78 / Avg: 4.82 / Max: 4.87 Min: 4.8 / Avg: 4.82 / Max: 4.87 Min: 4.6 / Avg: 4.71 / Max: 4.75 Min: 4.78 / Avg: 4.85 / Max: 4.89 Min: 4.79 / Avg: 4.83 / Max: 4.84 Min: 4.88 / Avg: 4.92 / Max: 4.96 Min: 5.05 / Avg: 5.07 / Max: 5.1 Min: 4.51 / Avg: 4.58 / Max: 4.67 Min: 7.72 / Avg: 8.17 / Max: 8.95 1. (CXX) g++ options: -std=c++11 -O3 -fvisibility=hidden -fomit-frame-pointer -fstrict-aliasing -ffunction-sections -fdata-sections -ffast-math -fno-rtti -fno-exceptions -rdynamic -pthread -ldl
Ngspice Ngspice is an open-source SPICE circuit simulator. Ngspice was originally based on the Berkeley SPICE electronic circuit simulator. Ngspice supports basic threading using OpenMP. This test profile is making use of the ISCAS 85 benchmark circuits. Learn more via the OpenBenchmarking.org test page.
Result
OpenBenchmarking.org Seconds, Fewer Is Better Ngspice 34 Circuit: C7552 EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 50 100 150 200 250 SE +/- 2.36, N = 3 SE +/- 1.75, N = 3 SE +/- 1.05, N = 3 SE +/- 1.66, N = 3 SE +/- 1.09, N = 12 SE +/- 1.31, N = 12 SE +/- 1.35, N = 3 SE +/- 1.10, N = 3 SE +/- 1.19, N = 3 SE +/- 1.27, N = 12 SE +/- 2.04, N = 12 212.89 137.59 135.68 128.92 132.04 130.09 131.53 136.87 132.62 119.44 122.44 1. (CC) gcc options: -O0 -fopenmp -lm -lstdc++ -lfftw3 -lXaw -lXmu -lXt -lXext -lX11 -lSM -lICE
Result Confidence
OpenBenchmarking.org Seconds, Fewer Is Better Ngspice 34 Circuit: C7552 EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 40 80 120 160 200 Min: 209.86 / Avg: 212.89 / Max: 217.53 Min: 134.17 / Avg: 137.59 / Max: 139.97 Min: 133.59 / Avg: 135.68 / Max: 136.92 Min: 126.46 / Avg: 128.92 / Max: 132.08 Min: 125.23 / Avg: 132.04 / Max: 137.09 Min: 122.93 / Avg: 130.09 / Max: 137.37 Min: 128.85 / Avg: 131.53 / Max: 133.13 Min: 134.99 / Avg: 136.87 / Max: 138.8 Min: 130.9 / Avg: 132.62 / Max: 134.89 Min: 112.44 / Avg: 119.44 / Max: 126.77 Min: 113.19 / Avg: 122.44 / Max: 133.84 1. (CC) gcc options: -O0 -fopenmp -lm -lstdc++ -lfftw3 -lXaw -lXmu -lXt -lXext -lX11 -lSM -lICE
Stream This benchmark tests the system memory (RAM) performance. Learn more via the OpenBenchmarking.org test page.
Result
OpenBenchmarking.org MB/s, More Is Better Stream 2013-01-17 Type: Copy EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 20K 40K 60K 80K 100K SE +/- 9.94, N = 5 SE +/- 7.06, N = 5 SE +/- 2.37, N = 5 SE +/- 8.02, N = 5 SE +/- 5.59, N = 5 SE +/- 14.85, N = 5 SE +/- 10.31, N = 5 SE +/- 5.66, N = 5 SE +/- 15.41, N = 5 SE +/- 13.27, N = 5 SE +/- 31.65, N = 5 SE +/- 52.59, N = 5 SE +/- 330.72, N = 5 52390.0 51714.4 51093.1 80140.1 79677.2 79342.9 90663.2 79674.1 88717.2 90296.5 90511.8 82399.7 66901.1 1. (CC) gcc options: -O3 -march=native -fopenmp
MB/s Per Watt
OpenBenchmarking.org MB/s Per Watt, More Is Better Stream 2013-01-17 Type: Copy EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 200 400 600 800 1000 854.90 785.09 734.63 1003.43 902.05 844.44 762.36 873.56 790.62 678.70 648.19 973.24 560.85
Result Confidence
OpenBenchmarking.org MB/s, More Is Better Stream 2013-01-17 Type: Copy EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 16K 32K 48K 64K 80K Min: 52373.2 / Avg: 52390.04 / Max: 52428 Min: 51688.2 / Avg: 51714.44 / Max: 51726.5 Min: 51087.4 / Avg: 51093.14 / Max: 51100.2 Min: 80119.5 / Avg: 80140.14 / Max: 80160.6 Min: 79657.3 / Avg: 79677.16 / Max: 79688.5 Min: 79306.1 / Avg: 79342.9 / Max: 79388.7 Min: 90631.3 / Avg: 90663.16 / Max: 90687.7 Min: 79657.3 / Avg: 79674.1 / Max: 79689.4 Min: 88676.8 / Avg: 88717.18 / Max: 88755.4 Min: 90262 / Avg: 90296.46 / Max: 90328.8 Min: 90390.8 / Avg: 90511.82 / Max: 90564 Min: 82189.9 / Avg: 82399.72 / Max: 82465.6 Min: 65648.8 / Avg: 66901.12 / Max: 67581.9 1. (CC) gcc options: -O3 -march=native -fopenmp
Timed PHP Compilation This test times how long it takes to build PHP 7. Learn more via the OpenBenchmarking.org test page.
Result
OpenBenchmarking.org Seconds, Fewer Is Better Timed PHP Compilation 7.4.2 Time To Compile EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 20 40 60 80 100 SE +/- 0.05, N = 3 SE +/- 0.03, N = 3 SE +/- 0.06, N = 3 SE +/- 0.08, N = 3 SE +/- 0.02, N = 3 SE +/- 0.01, N = 3 SE +/- 0.02, N = 3 SE +/- 0.02, N = 3 SE +/- 0.03, N = 3 SE +/- 0.01, N = 3 SE +/- 0.05, N = 3 SE +/- 0.06, N = 3 SE +/- 0.01, N = 3 SE +/- 0.21, N = 3 75.33 60.20 55.22 52.75 47.41 45.44 46.10 44.55 43.84 43.82 43.06 42.56 59.56 46.54
Result Confidence
OpenBenchmarking.org Seconds, Fewer Is Better Timed PHP Compilation 7.4.2 Time To Compile EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 14 28 42 56 70 Min: 75.27 / Avg: 75.33 / Max: 75.44 Min: 60.16 / Avg: 60.2 / Max: 60.27 Min: 55.1 / Avg: 55.22 / Max: 55.29 Min: 52.62 / Avg: 52.75 / Max: 52.9 Min: 47.38 / Avg: 47.41 / Max: 47.44 Min: 45.42 / Avg: 45.44 / Max: 45.46 Min: 46.08 / Avg: 46.1 / Max: 46.13 Min: 44.52 / Avg: 44.55 / Max: 44.58 Min: 43.81 / Avg: 43.84 / Max: 43.91 Min: 43.8 / Avg: 43.82 / Max: 43.84 Min: 43 / Avg: 43.06 / Max: 43.15 Min: 42.5 / Avg: 42.56 / Max: 42.67 Min: 59.55 / Avg: 59.56 / Max: 59.58 Min: 46.12 / Avg: 46.54 / Max: 46.75
OCRMyPDF OCRMyPDF is an optical character recognition (OCR) text layer to scanned PDF files, producing new PDFs with the text now selectable/searchable/copy-paste capable. OCRMyPDF leverages the Tesseract OCR engine and is written in Python. Learn more via the OpenBenchmarking.org test page.
Result
OpenBenchmarking.org Seconds, Fewer Is Better OCRMyPDF 9.6.0+dfsg Processing 60 Page PDF Document EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 8 16 24 32 40 SE +/- 0.06, N = 3 SE +/- 0.05, N = 3 SE +/- 0.06, N = 3 SE +/- 0.10, N = 3 SE +/- 0.11, N = 3 SE +/- 0.11, N = 3 SE +/- 0.01, N = 3 SE +/- 0.11, N = 3 SE +/- 0.07, N = 3 SE +/- 0.05, N = 3 SE +/- 0.20, N = 3 SE +/- 0.11, N = 3 SE +/- 0.05, N = 3 33.02 26.90 24.23 23.39 20.87 19.38 19.94 18.66 18.86 18.79 18.73 27.20 19.86
Result Confidence
OpenBenchmarking.org Seconds, Fewer Is Better OCRMyPDF 9.6.0+dfsg Processing 60 Page PDF Document EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 7 14 21 28 35 Min: 32.94 / Avg: 33.02 / Max: 33.14 Min: 26.81 / Avg: 26.9 / Max: 26.96 Min: 24.11 / Avg: 24.23 / Max: 24.33 Min: 23.21 / Avg: 23.39 / Max: 23.54 Min: 20.74 / Avg: 20.87 / Max: 21.08 Min: 19.15 / Avg: 19.38 / Max: 19.51 Min: 19.92 / Avg: 19.94 / Max: 19.97 Min: 18.45 / Avg: 18.66 / Max: 18.82 Min: 18.73 / Avg: 18.85 / Max: 18.96 Min: 18.7 / Avg: 18.79 / Max: 18.88 Min: 18.39 / Avg: 18.73 / Max: 19.1 Min: 26.98 / Avg: 27.2 / Max: 27.33 Min: 19.76 / Avg: 19.86 / Max: 19.94
Stream This benchmark tests the system memory (RAM) performance. Learn more via the OpenBenchmarking.org test page.
Result
OpenBenchmarking.org MB/s, More Is Better Stream 2013-01-17 Type: Add EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 20K 40K 60K 80K 100K SE +/- 61.95, N = 5 SE +/- 9.00, N = 5 SE +/- 6.11, N = 5 SE +/- 17.97, N = 5 SE +/- 9.19, N = 5 SE +/- 13.36, N = 5 SE +/- 7.96, N = 5 SE +/- 16.89, N = 5 SE +/- 16.17, N = 5 SE +/- 29.12, N = 5 SE +/- 25.81, N = 5 SE +/- 18.23, N = 5 SE +/- 39.00, N = 5 56795.1 55911.6 55437.2 87568.8 86805.6 86677.2 97912.5 86737.7 95807.0 97180.9 97206.3 89255.4 72752.2 1. (CC) gcc options: -O3 -march=native -fopenmp
MB/s Per Watt
OpenBenchmarking.org MB/s Per Watt, More Is Better Stream 2013-01-17 Type: Add EPYC 7702 EPYC 7F52 500 1000 1500 2000 2500 2144.89 1709.94
Result Confidence
OpenBenchmarking.org MB/s, More Is Better Stream 2013-01-17 Type: Add EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 20K 40K 60K 80K 100K Min: 56547.6 / Avg: 56795.1 / Max: 56866.8 Min: 55883.1 / Avg: 55911.58 / Max: 55937.4 Min: 55417 / Avg: 55437.24 / Max: 55454.2 Min: 87527.2 / Avg: 87568.78 / Max: 87617.1 Min: 86780.2 / Avg: 86805.64 / Max: 86837.1 Min: 86645.7 / Avg: 86677.24 / Max: 86711.4 Min: 97891 / Avg: 97912.52 / Max: 97938.6 Min: 86695.7 / Avg: 86737.72 / Max: 86780.2 Min: 95762.2 / Avg: 95807.04 / Max: 95857.9 Min: 97111 / Avg: 97180.94 / Max: 97268.6 Min: 97146.6 / Avg: 97206.28 / Max: 97299.6 Min: 89196.2 / Avg: 89255.38 / Max: 89299.1 Min: 72639.1 / Avg: 72752.2 / Max: 72844.7 1. (CC) gcc options: -O3 -march=native -fopenmp
Stream-Dynamic This is an open-source AMD modified copy of the Stream memory benchmark catered towards running the RAM benchmark on systems with the AMD Optimizing C/C++ Compiler (AOCC) among other by-default optimizations aiming for an easy and standardized deployment. This test profile though will attempt to fall-back to GCC / Clang for systems lacking AOCC, otherwise there is the existing "stream" test profile. Learn more via the OpenBenchmarking.org test page.
Stream This benchmark tests the system memory (RAM) performance. Learn more via the OpenBenchmarking.org test page.
Result
OpenBenchmarking.org MB/s, More Is Better Stream 2013-01-17 Type: Scale EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 20K 40K 60K 80K 100K SE +/- 61.32, N = 5 SE +/- 4.61, N = 5 SE +/- 3.08, N = 5 SE +/- 10.74, N = 5 SE +/- 7.47, N = 5 SE +/- 12.22, N = 5 SE +/- 18.59, N = 5 SE +/- 14.00, N = 5 SE +/- 32.31, N = 5 SE +/- 21.55, N = 5 SE +/- 27.01, N = 5 SE +/- 30.51, N = 5 SE +/- 31.64, N = 5 52630.1 51978.2 51044.2 79703.5 79147.3 78638.6 89487.6 78399.9 86805.6 87848.1 87714.6 81753.0 67011.9 1. (CC) gcc options: -O3 -march=native -fopenmp
Result Confidence
OpenBenchmarking.org MB/s, More Is Better Stream 2013-01-17 Type: Scale EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 16K 32K 48K 64K 80K Min: 52385 / Avg: 52630.06 / Max: 52697.2 Min: 51965.2 / Avg: 51978.22 / Max: 51992.1 Min: 51038.4 / Avg: 51044.22 / Max: 51055.9 Min: 79669.6 / Avg: 79703.46 / Max: 79733 Min: 79125.7 / Avg: 79147.34 / Max: 79168.6 Min: 78592.9 / Avg: 78638.56 / Max: 78666.6 Min: 89445.1 / Avg: 89487.56 / Max: 89550.1 Min: 78366.2 / Avg: 78399.86 / Max: 78439.4 Min: 86725.2 / Avg: 86805.6 / Max: 86880.2 Min: 87786 / Avg: 87848.06 / Max: 87907.9 Min: 87618.6 / Avg: 87714.62 / Max: 87786 Min: 81720.5 / Avg: 81753 / Max: 81875 Min: 66926.2 / Avg: 67011.88 / Max: 67120.3 1. (CC) gcc options: -O3 -march=native -fopenmp
Stream-Dynamic This is an open-source AMD modified copy of the Stream memory benchmark catered towards running the RAM benchmark on systems with the AMD Optimizing C/C++ Compiler (AOCC) among other by-default optimizations aiming for an easy and standardized deployment. This test profile though will attempt to fall-back to GCC / Clang for systems lacking AOCC, otherwise there is the existing "stream" test profile. Learn more via the OpenBenchmarking.org test page.
Zstd Compression This test measures the time needed to compress a sample file (an Ubuntu ISO) using Zstd compression. Learn more via the OpenBenchmarking.org test page.
Result
OpenBenchmarking.org MB/s, More Is Better Zstd Compression 1.4.5 Compression Level: 3 EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 2K 4K 6K 8K 10K SE +/- 5.69, N = 3 SE +/- 6.17, N = 3 SE +/- 3.19, N = 3 SE +/- 34.67, N = 3 SE +/- 21.24, N = 3 SE +/- 18.74, N = 3 SE +/- 14.29, N = 3 SE +/- 4.93, N = 3 SE +/- 25.58, N = 3 SE +/- 34.97, N = 3 SE +/- 8.45, N = 3 SE +/- 33.88, N = 3 SE +/- 4.75, N = 3 SE +/- 20.53, N = 3 5123.2 6498.4 6706.2 7699.4 8033.0 7903.6 8476.3 7885.0 8172.0 8499.2 8287.7 8248.3 6573.9 7899.7 1. (CC) gcc options: -O3 -pthread -lz -llzma
MB/s Per Watt
OpenBenchmarking.org MB/s Per Watt, More Is Better Zstd Compression 1.4.5 Compression Level: 3 EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 30 60 90 120 150 101.96 122.04 123.70 124.18 124.95 121.39 100.70 121.69 108.55 102.10 98.16 94.05 96.70 86.38
Result Confidence
OpenBenchmarking.org MB/s, More Is Better Zstd Compression 1.4.5 Compression Level: 3 EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 1500 3000 4500 6000 7500 Min: 5117.2 / Avg: 5123.23 / Max: 5134.6 Min: 6486.1 / Avg: 6498.4 / Max: 6505.4 Min: 6700.4 / Avg: 6706.17 / Max: 6711.4 Min: 7651 / Avg: 7699.4 / Max: 7766.6 Min: 7990.6 / Avg: 8033.03 / Max: 8056 Min: 7870.9 / Avg: 7903.63 / Max: 7935.8 Min: 8449.2 / Avg: 8476.3 / Max: 8497.7 Min: 7875.6 / Avg: 7885 / Max: 7892.3 Min: 8129 / Avg: 8172.03 / Max: 8217.5 Min: 8460.8 / Avg: 8499.17 / Max: 8569 Min: 8277.2 / Avg: 8287.67 / Max: 8304.4 Min: 8204.5 / Avg: 8248.33 / Max: 8315 Min: 6567.3 / Avg: 6573.87 / Max: 6583.1 Min: 7860.7 / Avg: 7899.7 / Max: 7930.3 1. (CC) gcc options: -O3 -pthread -lz -llzma
AI Benchmark Alpha AI Benchmark Alpha is a Python library for evaluating artificial intelligence (AI) performance on diverse hardware platforms and relies upon the TensorFlow machine learning library. Learn more via the OpenBenchmarking.org test page.
FFTW FFTW is a C subroutine library for computing the discrete Fourier transform (DFT) in one or more dimensions. Learn more via the OpenBenchmarking.org test page.
Result
OpenBenchmarking.org Mflops, More Is Better FFTW 3.3.6 Build: Float + SSE - Size: 2D FFT Size 2048 EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 6K 12K 18K 24K 30K SE +/- 93.54, N = 3 SE +/- 254.46, N = 15 SE +/- 144.50, N = 3 SE +/- 238.46, N = 3 SE +/- 250.51, N = 6 SE +/- 275.94, N = 15 SE +/- 124.32, N = 3 SE +/- 218.98, N = 3 SE +/- 82.21, N = 3 SE +/- 82.48, N = 3 SE +/- 287.13, N = 3 SE +/- 294.57, N = 15 SE +/- 204.43, N = 3 SE +/- 239.23, N = 3 18378 24876 25601 26045 26769 26186 26305 26724 26303 26289 26867 26143 30037 26636 1. (CC) gcc options: -pthread -O3 -fomit-frame-pointer -mtune=native -malign-double -fstrict-aliasing -fno-schedule-insns -ffast-math -lm
Mflops Per Watt
OpenBenchmarking.org Mflops Per Watt, More Is Better FFTW 3.3.6 Build: Float + SSE - Size: 2D FFT Size 2048 EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 130 260 390 520 650 440.07 580.44 588.80 516.81 530.99 515.11 372.69 536.35 437.62 393.21 383.02 361.64 541.24 365.69
Result Confidence
OpenBenchmarking.org Mflops, More Is Better FFTW 3.3.6 Build: Float + SSE - Size: 2D FFT Size 2048 EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 5K 10K 15K 20K 25K Min: 18209 / Avg: 18378 / Max: 18532 Min: 23020 / Avg: 24876 / Max: 25801 Min: 25375 / Avg: 25601 / Max: 25870 Min: 25635 / Avg: 26045.33 / Max: 26461 Min: 26241 / Avg: 26768.83 / Max: 27891 Min: 23734 / Avg: 26185.6 / Max: 27586 Min: 26075 / Avg: 26304.67 / Max: 26502 Min: 26452 / Avg: 26723.67 / Max: 27157 Min: 26216 / Avg: 26302.67 / Max: 26467 Min: 26194 / Avg: 26288.67 / Max: 26453 Min: 26432 / Avg: 26866.67 / Max: 27409 Min: 23624 / Avg: 26142.87 / Max: 27261 Min: 29628 / Avg: 30036.67 / Max: 30252 Min: 26158 / Avg: 26636.33 / Max: 26885 1. (CC) gcc options: -pthread -O3 -fomit-frame-pointer -mtune=native -malign-double -fstrict-aliasing -fno-schedule-insns -ffast-math -lm
NCNN NCNN is a high performance neural network inference framework optimized for mobile and other platforms developed by Tencent. Learn more via the OpenBenchmarking.org test page.
Result
OpenBenchmarking.org ms, Fewer Is Better NCNN 20201218 Target: CPU - Model: resnet50 EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 8 16 24 32 40 SE +/- 0.22, N = 3 SE +/- 0.33, N = 3 SE +/- 0.09, N = 3 SE +/- 0.03, N = 3 SE +/- 0.07, N = 3 SE +/- 0.26, N = 3 SE +/- 0.04, N = 11 SE +/- 0.15, N = 3 SE +/- 0.25, N = 3 SE +/- 0.19, N = 12 SE +/- 0.12, N = 9 SE +/- 0.16, N = 9 SE +/- 0.09, N = 3 SE +/- 0.33, N = 3 28.19 26.83 25.17 21.88 22.79 24.32 24.62 23.55 28.57 27.83 32.73 33.98 23.75 35.47 MIN: 27.81 / MAX: 29.82 MIN: 26.22 / MAX: 41.74 MIN: 24.53 / MAX: 50.53 MIN: 21.64 / MAX: 23.37 MIN: 22.48 / MAX: 33.96 MIN: 23.62 / MAX: 27.07 MIN: 23.94 / MAX: 27.83 MIN: 23.01 / MAX: 26.62 MIN: 27.64 / MAX: 33.13 MIN: 26.6 / MAX: 234.67 MIN: 31.74 / MAX: 44.34 MIN: 31.83 / MAX: 59.59 MIN: 23.29 / MAX: 24.37 MIN: 34.12 / MAX: 114.69 1. (CXX) g++ options: -O3 -rdynamic -lgomp -lpthread
Result Confidence
OpenBenchmarking.org ms, Fewer Is Better NCNN 20201218 Target: CPU - Model: resnet50 EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 8 16 24 32 40 Min: 27.94 / Avg: 28.19 / Max: 28.64 Min: 26.36 / Avg: 26.83 / Max: 27.48 Min: 25.05 / Avg: 25.17 / Max: 25.35 Min: 21.81 / Avg: 21.88 / Max: 21.92 Min: 22.65 / Avg: 22.79 / Max: 22.86 Min: 23.81 / Avg: 24.32 / Max: 24.65 Min: 24.38 / Avg: 24.62 / Max: 24.86 Min: 23.25 / Avg: 23.55 / Max: 23.73 Min: 28.08 / Avg: 28.57 / Max: 28.9 Min: 27.17 / Avg: 27.83 / Max: 29.25 Min: 32.29 / Avg: 32.73 / Max: 33.15 Min: 33.16 / Avg: 33.98 / Max: 34.66 Min: 23.57 / Avg: 23.75 / Max: 23.86 Min: 34.82 / Avg: 35.47 / Max: 35.92 1. (CXX) g++ options: -O3 -rdynamic -lgomp -lpthread
Numenta Anomaly Benchmark Numenta Anomaly Benchmark (NAB) is a benchmark for evaluating algorithms for anomaly detection in streaming, real-time applications. It is comprised of over 50 labeled real-world and artificial timeseries data files plus a novel scoring mechanism designed for real-time applications. This test profile currently measures the time to run various detectors. Learn more via the OpenBenchmarking.org test page.
Result
OpenBenchmarking.org Seconds, Fewer Is Better Numenta Anomaly Benchmark 1.1 Detector: Relative Entropy EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 6 12 18 24 30 SE +/- 0.17, N = 3 SE +/- 0.17, N = 3 SE +/- 0.10, N = 3 SE +/- 0.17, N = 3 SE +/- 0.05, N = 4 SE +/- 0.15, N = 4 SE +/- 0.08, N = 4 SE +/- 0.06, N = 4 SE +/- 0.08, N = 4 SE +/- 0.13, N = 4 SE +/- 0.10, N = 4 SE +/- 0.03, N = 4 SE +/- 0.09, N = 3 SE +/- 0.08, N = 4 23.56 19.11 18.10 17.18 16.12 15.85 16.33 15.72 15.97 15.89 15.97 15.94 18.88 14.60
Result Confidence
OpenBenchmarking.org Seconds, Fewer Is Better Numenta Anomaly Benchmark 1.1 Detector: Relative Entropy EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 6 12 18 24 30 Min: 23.35 / Avg: 23.56 / Max: 23.91 Min: 18.77 / Avg: 19.11 / Max: 19.31 Min: 17.96 / Avg: 18.1 / Max: 18.29 Min: 17 / Avg: 17.18 / Max: 17.52 Min: 16.01 / Avg: 16.12 / Max: 16.23 Min: 15.61 / Avg: 15.85 / Max: 16.23 Min: 16.13 / Avg: 16.33 / Max: 16.51 Min: 15.6 / Avg: 15.72 / Max: 15.88 Min: 15.82 / Avg: 15.97 / Max: 16.13 Min: 15.65 / Avg: 15.89 / Max: 16.17 Min: 15.81 / Avg: 15.97 / Max: 16.23 Min: 15.88 / Avg: 15.94 / Max: 16.04 Min: 18.71 / Avg: 18.88 / Max: 19.01 Min: 14.38 / Avg: 14.6 / Max: 14.74
ASTC Encoder ASTC Encoder (astcenc) is for the Adaptive Scalable Texture Compression (ASTC) format commonly used with OpenGL, OpenGL ES, and Vulkan graphics APIs. This test profile does a coding test of both compression/decompression. Learn more via the OpenBenchmarking.org test page.
Result
OpenBenchmarking.org Seconds, Fewer Is Better ASTC Encoder 2.0 Preset: Medium EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 3 6 9 12 15 SE +/- 0.00, N = 5 SE +/- 0.00, N = 5 SE +/- 0.02, N = 5 SE +/- 0.01, N = 6 SE +/- 0.01, N = 6 SE +/- 0.01, N = 6 SE +/- 0.01, N = 6 SE +/- 0.01, N = 6 SE +/- 0.01, N = 6 SE +/- 0.01, N = 6 SE +/- 0.01, N = 6 SE +/- 0.01, N = 5 SE +/- 0.01, N = 6 5.82 9.38 8.63 8.30 7.47 7.17 7.33 7.02 6.93 6.78 6.68 9.04 7.10 1. (CXX) g++ options: -std=c++14 -fvisibility=hidden -O3 -flto -mfpmath=sse -mavx2 -mpopcnt -lpthread
Result Confidence
OpenBenchmarking.org Seconds, Fewer Is Better ASTC Encoder 2.0 Preset: Medium EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 3 6 9 12 15 Min: 5.81 / Avg: 5.82 / Max: 5.83 Min: 9.37 / Avg: 9.38 / Max: 9.39 Min: 8.59 / Avg: 8.63 / Max: 8.68 Min: 8.25 / Avg: 8.3 / Max: 8.34 Min: 7.43 / Avg: 7.47 / Max: 7.49 Min: 7.15 / Avg: 7.17 / Max: 7.18 Min: 7.31 / Avg: 7.33 / Max: 7.35 Min: 7.01 / Avg: 7.02 / Max: 7.04 Min: 6.89 / Avg: 6.93 / Max: 6.96 Min: 6.76 / Avg: 6.78 / Max: 6.8 Min: 6.64 / Avg: 6.68 / Max: 6.71 Min: 9.02 / Avg: 9.04 / Max: 9.06 Min: 7.07 / Avg: 7.1 / Max: 7.13 1. (CXX) g++ options: -std=c++14 -fvisibility=hidden -O3 -flto -mfpmath=sse -mavx2 -mpopcnt -lpthread
XZ Compression This test measures the time needed to compress a sample file (an Ubuntu file-system image) using XZ compression. Learn more via the OpenBenchmarking.org test page.
Result
OpenBenchmarking.org Seconds, Fewer Is Better XZ Compression 5.2.4 Compressing ubuntu-16.04.3-server-i386.img, Compression Level 9 EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 8 16 24 32 40 SE +/- 0.02, N = 3 SE +/- 0.07, N = 3 SE +/- 0.08, N = 3 SE +/- 0.19, N = 9 SE +/- 0.07, N = 3 SE +/- 0.09, N = 3 SE +/- 0.06, N = 3 SE +/- 0.07, N = 3 SE +/- 0.05, N = 3 SE +/- 0.08, N = 3 SE +/- 0.05, N = 3 SE +/- 0.12, N = 3 SE +/- 0.07, N = 3 SE +/- 0.11, N = 3 34.51 25.66 24.90 23.15 22.40 22.42 22.09 22.30 22.54 22.01 22.05 22.05 29.61 21.43 1. (CC) gcc options: -pthread -fvisibility=hidden -O2
Result Confidence
OpenBenchmarking.org Seconds, Fewer Is Better XZ Compression 5.2.4 Compressing ubuntu-16.04.3-server-i386.img, Compression Level 9 EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 7 14 21 28 35 Min: 34.46 / Avg: 34.51 / Max: 34.53 Min: 25.58 / Avg: 25.66 / Max: 25.79 Min: 24.75 / Avg: 24.9 / Max: 25.01 Min: 22.45 / Avg: 23.15 / Max: 23.78 Min: 22.31 / Avg: 22.4 / Max: 22.53 Min: 22.33 / Avg: 22.42 / Max: 22.59 Min: 22.03 / Avg: 22.09 / Max: 22.22 Min: 22.23 / Avg: 22.3 / Max: 22.43 Min: 22.49 / Avg: 22.54 / Max: 22.64 Min: 21.89 / Avg: 22.01 / Max: 22.17 Min: 22 / Avg: 22.05 / Max: 22.15 Min: 21.86 / Avg: 22.05 / Max: 22.28 Min: 29.47 / Avg: 29.61 / Max: 29.69 Min: 21.32 / Avg: 21.43 / Max: 21.65 1. (CC) gcc options: -pthread -fvisibility=hidden -O2
Appleseed Appleseed is an open-source production renderer focused on physically-based global illumination rendering engine primarily designed for animation and visual effects. Learn more via the OpenBenchmarking.org test page.
OpenBenchmarking.org Seconds, Fewer Is Better Appleseed 2.0 Beta Scene: Material Tester EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 60 120 180 240 300 278.32 210.16 177.85 191.51 173.05 173.53 186.27 173.16 182.38 185.01 187.07 188.84 247.66 192.28
Timed MrBayes Analysis This test performs a bayesian analysis of a set of primate genome sequences in order to estimate their phylogeny. Learn more via the OpenBenchmarking.org test page.
Result
OpenBenchmarking.org Seconds, Fewer Is Better Timed MrBayes Analysis 3.2.7 Primate Phylogeny Analysis EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 30 60 90 120 150 SE +/- 0.07, N = 3 SE +/- 0.05, N = 3 SE +/- 0.16, N = 3 SE +/- 0.21, N = 3 SE +/- 0.29, N = 3 SE +/- 0.21, N = 3 SE +/- 0.34, N = 3 SE +/- 0.07, N = 3 SE +/- 1.17, N = 4 SE +/- 0.17, N = 3 SE +/- 1.02, N = 3 SE +/- 0.25, N = 3 SE +/- 0.18, N = 3 SE +/- 0.24, N = 3 88.67 87.60 89.20 85.93 86.00 94.26 96.81 86.72 104.52 102.45 116.15 115.27 72.89 72.43 1. (CC) gcc options: -mmmx -msse -msse2 -msse3 -mssse3 -msse4.1 -msse4.2 -msse4a -msha -maes -mavx -mfma -mavx2 -mrdrnd -mbmi -mbmi2 -madx -mabm -O3 -std=c99 -pedantic -lm
Result Confidence
OpenBenchmarking.org Seconds, Fewer Is Better Timed MrBayes Analysis 3.2.7 Primate Phylogeny Analysis EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 20 40 60 80 100 Min: 88.6 / Avg: 88.67 / Max: 88.81 Min: 87.51 / Avg: 87.6 / Max: 87.67 Min: 88.88 / Avg: 89.2 / Max: 89.39 Min: 85.7 / Avg: 85.93 / Max: 86.35 Min: 85.64 / Avg: 86 / Max: 86.58 Min: 93.87 / Avg: 94.26 / Max: 94.59 Min: 96.44 / Avg: 96.81 / Max: 97.49 Min: 86.61 / Avg: 86.72 / Max: 86.86 Min: 103.18 / Avg: 104.52 / Max: 108.01 Min: 102.2 / Avg: 102.45 / Max: 102.77 Min: 115.11 / Avg: 116.15 / Max: 118.18 Min: 114.96 / Avg: 115.27 / Max: 115.77 Min: 72.56 / Avg: 72.89 / Max: 73.16 Min: 72.17 / Avg: 72.43 / Max: 72.9 1. (CC) gcc options: -mmmx -msse -msse2 -msse3 -mssse3 -msse4.1 -msse4.2 -msse4a -msha -maes -mavx -mfma -mavx2 -mrdrnd -mbmi -mbmi2 -madx -mabm -O3 -std=c99 -pedantic -lm
OpenVINO This is a test of the Intel OpenVINO, a toolkit around neural networks, using its built-in benchmarking support and analyzing the throughput and latency for various models. Learn more via the OpenBenchmarking.org test page.
Result
OpenBenchmarking.org ms, Fewer Is Better OpenVINO 2021.1 Model: Age Gender Recognition Retail 0013 FP32 - Device: CPU EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 0.2745 0.549 0.8235 1.098 1.3725 SE +/- 0.01, N = 4 SE +/- 0.00, N = 3 SE +/- 0.01, N = 4 SE +/- 0.00, N = 3 SE +/- 0.01, N = 3 SE +/- 0.00, N = 3 SE +/- 0.00, N = 3 SE +/- 0.00, N = 3 SE +/- 0.00, N = 3 SE +/- 0.00, N = 3 SE +/- 0.00, N = 3 SE +/- 0.00, N = 3 SE +/- 0.00, N = 3 SE +/- 0.00, N = 3 0.96 0.87 0.79 0.84 0.88 0.84 0.95 0.77 0.99 1.02 1.07 1.22 0.78 0.79
Result Confidence
OpenBenchmarking.org ms, Fewer Is Better OpenVINO 2021.1 Model: Age Gender Recognition Retail 0013 FP32 - Device: CPU EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 2 4 6 8 10 Min: 0.94 / Avg: 0.96 / Max: 0.99 Min: 0.87 / Avg: 0.87 / Max: 0.87 Min: 0.77 / Avg: 0.79 / Max: 0.81 Min: 0.83 / Avg: 0.84 / Max: 0.84 Min: 0.87 / Avg: 0.88 / Max: 0.91 Min: 0.83 / Avg: 0.84 / Max: 0.84 Min: 0.95 / Avg: 0.95 / Max: 0.95 Min: 0.77 / Avg: 0.77 / Max: 0.78 Min: 0.98 / Avg: 0.99 / Max: 0.99 Min: 1.01 / Avg: 1.02 / Max: 1.02 Min: 1.06 / Avg: 1.07 / Max: 1.07 Min: 1.21 / Avg: 1.22 / Max: 1.22 Min: 0.78 / Avg: 0.78 / Max: 0.79 Min: 0.78 / Avg: 0.79 / Max: 0.79
Result
OpenBenchmarking.org ms, Fewer Is Better OpenVINO 2021.1 Model: Age Gender Recognition Retail 0013 FP16 - Device: CPU EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 0.2723 0.5446 0.8169 1.0892 1.3615 SE +/- 0.01, N = 15 SE +/- 0.01, N = 3 SE +/- 0.01, N = 3 SE +/- 0.00, N = 3 SE +/- 0.01, N = 3 SE +/- 0.00, N = 3 SE +/- 0.00, N = 3 SE +/- 0.00, N = 3 SE +/- 0.00, N = 3 SE +/- 0.00, N = 3 SE +/- 0.00, N = 3 SE +/- 0.00, N = 3 SE +/- 0.01, N = 3 SE +/- 0.01, N = 3 0.98 0.89 0.78 0.84 0.92 0.84 0.95 0.77 0.99 1.02 1.06 1.21 0.79 0.81
Result Confidence
OpenBenchmarking.org ms, Fewer Is Better OpenVINO 2021.1 Model: Age Gender Recognition Retail 0013 FP16 - Device: CPU EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 2 4 6 8 10 Min: 0.91 / Avg: 0.98 / Max: 1.03 Min: 0.87 / Avg: 0.89 / Max: 0.91 Min: 0.77 / Avg: 0.78 / Max: 0.79 Min: 0.83 / Avg: 0.84 / Max: 0.84 Min: 0.91 / Avg: 0.92 / Max: 0.93 Min: 0.83 / Avg: 0.84 / Max: 0.84 Min: 0.95 / Avg: 0.95 / Max: 0.95 Min: 0.77 / Avg: 0.77 / Max: 0.78 Min: 0.99 / Avg: 0.99 / Max: 0.99 Min: 1.01 / Avg: 1.02 / Max: 1.02 Min: 1.06 / Avg: 1.06 / Max: 1.07 Min: 1.21 / Avg: 1.21 / Max: 1.21 Min: 0.78 / Avg: 0.79 / Max: 0.81 Min: 0.8 / Avg: 0.81 / Max: 0.82
Mobile Neural Network MNN is the Mobile Neural Network as a highly efficient, lightweight deep learning framework developed by Alibaba. Learn more via the OpenBenchmarking.org test page.
Result
OpenBenchmarking.org ms, Fewer Is Better Mobile Neural Network 1.1.1 Model: resnet-v2-50 EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 9 18 27 36 45 SE +/- 0.12, N = 11 SE +/- 0.11, N = 4 SE +/- 0.12, N = 3 SE +/- 0.09, N = 15 SE +/- 0.97, N = 3 SE +/- 0.12, N = 3 SE +/- 0.05, N = 3 SE +/- 0.05, N = 15 SE +/- 0.05, N = 15 SE +/- 0.03, N = 3 SE +/- 0.10, N = 3 SE +/- 0.07, N = 3 SE +/- 0.01, N = 14 SE +/- 0.19, N = 3 31.44 38.10 33.59 31.54 29.02 25.06 25.27 24.30 25.44 24.78 25.22 26.92 27.45 33.50 MIN: 30.44 / MAX: 49.82 MIN: 36.85 / MAX: 55.75 MIN: 32.54 / MAX: 48.77 MIN: 30.05 / MAX: 48.95 MIN: 27.23 / MAX: 33.12 MIN: 24.51 / MAX: 27.82 MIN: 24.96 / MAX: 28.42 MIN: 23.72 / MAX: 27.28 MIN: 24.73 / MAX: 28.58 MIN: 24.46 / MAX: 25.37 MIN: 24.73 / MAX: 27.24 MIN: 26.49 / MAX: 27.67 MIN: 27.01 / MAX: 58.07 MIN: 32.85 / MAX: 46.41 1. (CXX) g++ options: -std=c++11 -O3 -fvisibility=hidden -fomit-frame-pointer -fstrict-aliasing -ffunction-sections -fdata-sections -ffast-math -fno-rtti -fno-exceptions -rdynamic -pthread -ldl
Result Confidence
OpenBenchmarking.org ms, Fewer Is Better Mobile Neural Network 1.1.1 Model: resnet-v2-50 EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 8 16 24 32 40 Min: 30.9 / Avg: 31.44 / Max: 32.5 Min: 37.9 / Avg: 38.1 / Max: 38.42 Min: 33.39 / Avg: 33.59 / Max: 33.8 Min: 30.84 / Avg: 31.54 / Max: 32 Min: 27.93 / Avg: 29.02 / Max: 30.96 Min: 24.81 / Avg: 25.06 / Max: 25.18 Min: 25.2 / Avg: 25.27 / Max: 25.36 Min: 23.9 / Avg: 24.3 / Max: 24.57 Min: 25.04 / Avg: 25.44 / Max: 25.64 Min: 24.73 / Avg: 24.78 / Max: 24.82 Min: 25.03 / Avg: 25.22 / Max: 25.35 Min: 26.83 / Avg: 26.92 / Max: 27.06 Min: 27.35 / Avg: 27.44 / Max: 27.53 Min: 33.28 / Avg: 33.5 / Max: 33.89 1. (CXX) g++ options: -std=c++11 -O3 -fvisibility=hidden -fomit-frame-pointer -fstrict-aliasing -ffunction-sections -fdata-sections -ffast-math -fno-rtti -fno-exceptions -rdynamic -pthread -ldl
Tungsten Renderer Tungsten is a C++ physically based renderer that makes use of Intel's Embree ray tracing library. Learn more via the OpenBenchmarking.org test page.
Result
OpenBenchmarking.org Seconds, Fewer Is Better Tungsten Renderer 0.2.2 Scene: Water Caustic EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 8 16 24 32 40 SE +/- 0.41, N = 3 SE +/- 0.25, N = 3 SE +/- 0.03, N = 3 SE +/- 0.04, N = 3 SE +/- 0.03, N = 3 SE +/- 0.03, N = 3 SE +/- 0.01, N = 3 SE +/- 0.05, N = 3 SE +/- 0.03, N = 3 SE +/- 0.04, N = 3 SE +/- 0.02, N = 3 SE +/- 0.02, N = 3 SE +/- 0.22, N = 3 SE +/- 0.07, N = 3 33.92 29.95 26.79 26.02 23.87 23.11 23.55 22.64 22.65 22.55 22.13 21.97 28.10 24.42 1. (CXX) g++ options: -std=c++0x -march=znver1 -msse2 -msse3 -mssse3 -msse4.1 -msse4.2 -msse4a -mfma -mbmi2 -mno-avx -mno-avx2 -mno-xop -mno-fma4 -mno-avx512f -mno-avx512vl -mno-avx512pf -mno-avx512er -mno-avx512cd -mno-avx512dq -mno-avx512bw -mno-avx512ifma -mno-avx512vbmi -fstrict-aliasing -O3 -rdynamic -lIlmImf -lIlmThread -lImath -lHalf -lIex -lz -ljpeg -lpthread -ldl
Result Confidence
OpenBenchmarking.org Seconds, Fewer Is Better Tungsten Renderer 0.2.2 Scene: Water Caustic EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 7 14 21 28 35 Min: 33.49 / Avg: 33.92 / Max: 34.73 Min: 29.5 / Avg: 29.95 / Max: 30.34 Min: 26.76 / Avg: 26.79 / Max: 26.84 Min: 25.95 / Avg: 26.02 / Max: 26.08 Min: 23.81 / Avg: 23.87 / Max: 23.93 Min: 23.07 / Avg: 23.11 / Max: 23.16 Min: 23.54 / Avg: 23.55 / Max: 23.58 Min: 22.58 / Avg: 22.64 / Max: 22.73 Min: 22.58 / Avg: 22.65 / Max: 22.7 Min: 22.48 / Avg: 22.55 / Max: 22.63 Min: 22.09 / Avg: 22.13 / Max: 22.15 Min: 21.94 / Avg: 21.97 / Max: 21.99 Min: 27.88 / Avg: 28.1 / Max: 28.53 Min: 24.31 / Avg: 24.42 / Max: 24.54 1. (CXX) g++ options: -std=c++0x -march=znver1 -msse2 -msse3 -mssse3 -msse4.1 -msse4.2 -msse4a -mfma -mbmi2 -mno-avx -mno-avx2 -mno-xop -mno-fma4 -mno-avx512f -mno-avx512vl -mno-avx512pf -mno-avx512er -mno-avx512cd -mno-avx512dq -mno-avx512bw -mno-avx512ifma -mno-avx512vbmi -fstrict-aliasing -O3 -rdynamic -lIlmImf -lIlmThread -lImath -lHalf -lIex -lz -ljpeg -lpthread -ldl
Numenta Anomaly Benchmark Numenta Anomaly Benchmark (NAB) is a benchmark for evaluating algorithms for anomaly detection in streaming, real-time applications. It is comprised of over 50 labeled real-world and artificial timeseries data files plus a novel scoring mechanism designed for real-time applications. This test profile currently measures the time to run various detectors. Learn more via the OpenBenchmarking.org test page.
Result
OpenBenchmarking.org Seconds, Fewer Is Better Numenta Anomaly Benchmark 1.1 Detector: Bayesian Changepoint EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 10 20 30 40 50 SE +/- 0.11, N = 3 SE +/- 0.13, N = 3 SE +/- 0.48, N = 3 SE +/- 0.10, N = 3 SE +/- 0.24, N = 3 SE +/- 0.27, N = 3 SE +/- 0.11, N = 3 SE +/- 0.20, N = 3 SE +/- 0.14, N = 3 SE +/- 0.24, N = 3 SE +/- 0.35, N = 3 SE +/- 0.26, N = 3 SE +/- 0.22, N = 3 SE +/- 0.20, N = 3 45.21 38.07 36.35 34.84 34.31 32.65 33.43 32.87 33.96 33.60 33.41 33.27 35.67 29.45
Result Confidence
OpenBenchmarking.org Seconds, Fewer Is Better Numenta Anomaly Benchmark 1.1 Detector: Bayesian Changepoint EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 9 18 27 36 45 Min: 45 / Avg: 45.21 / Max: 45.37 Min: 37.91 / Avg: 38.07 / Max: 38.32 Min: 35.71 / Avg: 36.35 / Max: 37.28 Min: 34.65 / Avg: 34.84 / Max: 35.01 Min: 33.83 / Avg: 34.31 / Max: 34.61 Min: 32.15 / Avg: 32.64 / Max: 33.08 Min: 33.26 / Avg: 33.43 / Max: 33.62 Min: 32.54 / Avg: 32.87 / Max: 33.22 Min: 33.82 / Avg: 33.96 / Max: 34.23 Min: 33.36 / Avg: 33.6 / Max: 34.09 Min: 32.9 / Avg: 33.41 / Max: 34.08 Min: 32.84 / Avg: 33.27 / Max: 33.73 Min: 35.42 / Avg: 35.67 / Max: 36.1 Min: 29.13 / Avg: 29.45 / Max: 29.83
DaCapo Benchmark This test runs the DaCapo Benchmarks written in Java and intended to test system/CPU performance. Learn more via the OpenBenchmarking.org test page.
Result
OpenBenchmarking.org msec, Fewer Is Better DaCapo Benchmark 9.12-MR1 Java Test: Tradesoap EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 1100 2200 3300 4400 5500 SE +/- 47.23, N = 4 SE +/- 35.80, N = 6 SE +/- 23.50, N = 13 SE +/- 23.38, N = 5 SE +/- 36.08, N = 5 SE +/- 31.58, N = 20 SE +/- 38.48, N = 5 SE +/- 30.98, N = 5 SE +/- 25.46, N = 5 SE +/- 22.90, N = 5 SE +/- 23.53, N = 20 SE +/- 13.18, N = 4 SE +/- 17.61, N = 4 5021 3757 3492 3526 3310 3358 3497 3304 3550 3624 3626 4095 3288
Result Confidence
OpenBenchmarking.org msec, Fewer Is Better DaCapo Benchmark 9.12-MR1 Java Test: Tradesoap EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 900 1800 2700 3600 4500 Min: 4937 / Avg: 5020.5 / Max: 5136 Min: 3621 / Avg: 3757.17 / Max: 3836 Min: 3310 / Avg: 3491.92 / Max: 3632 Min: 3448 / Avg: 3526.2 / Max: 3591 Min: 3228 / Avg: 3310.2 / Max: 3400 Min: 3220 / Avg: 3358.3 / Max: 3805 Min: 3410 / Avg: 3496.6 / Max: 3597 Min: 3195 / Avg: 3303.6 / Max: 3360 Min: 3490 / Avg: 3550 / Max: 3631 Min: 3562 / Avg: 3624.4 / Max: 3691 Min: 3427 / Avg: 3625.95 / Max: 3913 Min: 4078 / Avg: 4095 / Max: 4134 Min: 3254 / Avg: 3287.75 / Max: 3330
ONNX Runtime ONNX Runtime is developed by Microsoft and partners as a open-source, cross-platform, high performance machine learning inferencing and training accelerator. This test profile runs the ONNX Runtime with various models available from the ONNX Zoo. Learn more via the OpenBenchmarking.org test page.
Result
OpenBenchmarking.org Inferences Per Minute, More Is Better ONNX Runtime 1.6 Model: shufflenet-v2-10 - Device: OpenMP CPU EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 2K 4K 6K 8K 10K SE +/- 15.37, N = 3 SE +/- 2.92, N = 3 SE +/- 45.05, N = 3 SE +/- 1.83, N = 3 SE +/- 18.32, N = 3 SE +/- 63.96, N = 12 SE +/- 105.59, N = 12 SE +/- 29.60, N = 3 SE +/- 70.17, N = 12 SE +/- 73.86, N = 12 SE +/- 46.88, N = 3 SE +/- 53.19, N = 12 SE +/- 45.76, N = 3 SE +/- 112.30, N = 4 8836 8721 8611 8975 8810 8421 8070 8698 7373 7221 6686 6478 9823 9348 1. (CXX) g++ options: -fopenmp -ffunction-sections -fdata-sections -O3 -ldl -lrt
Inferences Per Minute Per Watt
OpenBenchmarking.org Inferences Per Minute Per Watt, More Is Better ONNX Runtime 1.6 Model: shufflenet-v2-10 - Device: OpenMP CPU EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 40 80 120 160 200 172.02 154.91 142.11 129.62 108.45 96.92 74.72 101.89 68.55 59.42 50.67 46.15 135.13 82.09
Result Confidence
OpenBenchmarking.org Inferences Per Minute, More Is Better ONNX Runtime 1.6 Model: shufflenet-v2-10 - Device: OpenMP CPU EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 2K 4K 6K 8K 10K Min: 8814.5 / Avg: 8836.33 / Max: 8866 Min: 8717.5 / Avg: 8720.67 / Max: 8726.5 Min: 8522 / Avg: 8611.17 / Max: 8667 Min: 8973 / Avg: 8974.83 / Max: 8978.5 Min: 8780.5 / Avg: 8809.83 / Max: 8843.5 Min: 7942 / Avg: 8421.42 / Max: 8675.5 Min: 7492 / Avg: 8070 / Max: 8524 Min: 8644 / Avg: 8698 / Max: 8746 Min: 6932 / Avg: 7373.04 / Max: 7736 Min: 6810.5 / Avg: 7220.58 / Max: 7710.5 Min: 6618 / Avg: 6686.17 / Max: 6776 Min: 6037.5 / Avg: 6477.5 / Max: 6804 Min: 9743 / Avg: 9822.67 / Max: 9901.5 Min: 9037.5 / Avg: 9348.13 / Max: 9565.5 1. (CXX) g++ options: -fopenmp -ffunction-sections -fdata-sections -O3 -ldl -lrt
NCNN NCNN is a high performance neural network inference framework optimized for mobile and other platforms developed by Tencent. Learn more via the OpenBenchmarking.org test page.
Result
OpenBenchmarking.org ms, Fewer Is Better NCNN 20201218 Target: CPU - Model: squeezenet_ssd EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 8 16 24 32 40 SE +/- 0.01, N = 3 SE +/- 0.09, N = 3 SE +/- 0.08, N = 3 SE +/- 0.08, N = 3 SE +/- 0.05, N = 3 SE +/- 0.14, N = 3 SE +/- 0.05, N = 11 SE +/- 0.07, N = 3 SE +/- 0.03, N = 3 SE +/- 0.09, N = 12 SE +/- 0.15, N = 9 SE +/- 0.19, N = 9 SE +/- 0.05, N = 3 SE +/- 0.15, N = 3 27.97 22.62 22.85 22.45 23.02 23.73 25.94 24.52 28.94 28.68 32.09 33.16 25.76 25.20 MIN: 27.46 / MAX: 42.1 MIN: 22.05 / MAX: 23.63 MIN: 21.95 / MAX: 99.38 MIN: 21.7 / MAX: 24.03 MIN: 22.47 / MAX: 24.28 MIN: 22.99 / MAX: 25.94 MIN: 25.15 / MAX: 38.37 MIN: 24.07 / MAX: 27.01 MIN: 28.1 / MAX: 41.11 MIN: 27.54 / MAX: 42.27 MIN: 30.51 / MAX: 174.53 MIN: 31.64 / MAX: 127 MIN: 24.63 / MAX: 28.33 MIN: 24.28 / MAX: 26.66 1. (CXX) g++ options: -O3 -rdynamic -lgomp -lpthread
Result Confidence
OpenBenchmarking.org ms, Fewer Is Better NCNN 20201218 Target: CPU - Model: squeezenet_ssd EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 7 14 21 28 35 Min: 27.95 / Avg: 27.97 / Max: 27.99 Min: 22.44 / Avg: 22.62 / Max: 22.74 Min: 22.7 / Avg: 22.85 / Max: 22.98 Min: 22.32 / Avg: 22.45 / Max: 22.58 Min: 22.92 / Avg: 23.02 / Max: 23.09 Min: 23.45 / Avg: 23.73 / Max: 23.93 Min: 25.63 / Avg: 25.94 / Max: 26.21 Min: 24.41 / Avg: 24.52 / Max: 24.65 Min: 28.89 / Avg: 28.94 / Max: 28.98 Min: 28.28 / Avg: 28.68 / Max: 29.56 Min: 31.56 / Avg: 32.09 / Max: 32.7 Min: 32.47 / Avg: 33.16 / Max: 34.44 Min: 25.69 / Avg: 25.76 / Max: 25.86 Min: 24.91 / Avg: 25.2 / Max: 25.41 1. (CXX) g++ options: -O3 -rdynamic -lgomp -lpthread
BlogBench BlogBench is designed to replicate the load of a real-world busy file server by stressing the file-system with multiple threads of random reads, writes, and rewrites. The behavior is mimicked of that of a blog by creating blogs with content and pictures, modifying blog posts, adding comments to these blogs, and then reading the content of the blogs. All of these blogs generated are created locally with fake content and pictures. Learn more via the OpenBenchmarking.org test page.
Result
OpenBenchmarking.org Final Score, More Is Better BlogBench 1.1 Test: Read EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 400K 800K 1200K 1600K 2000K SE +/- 16960.13, N = 3 SE +/- 20232.46, N = 3 SE +/- 12175.94, N = 3 SE +/- 7235.14, N = 3 SE +/- 7805.03, N = 3 SE +/- 7760.40, N = 3 SE +/- 13194.50, N = 3 SE +/- 7106.01, N = 3 SE +/- 4883.16, N = 3 SE +/- 14031.09, N = 3 SE +/- 9874.65, N = 3 SE +/- 10548.76, N = 3 SE +/- 14389.61, N = 3 SE +/- 13461.20, N = 3 1944496 2023180 2043037 1898428 1959615 1950080 1636092 1923368 1771624 1583350 1397475 1372955 1772037 1676516 1. (CC) gcc options: -O2 -pthread
Final Score Per Watt
OpenBenchmarking.org Final Score Per Watt, More Is Better BlogBench 1.1 Test: Read EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 6K 12K 18K 24K 30K 29655.38 28304.98 27647.84 22851.81 21034.07 20067.14 14192.86 20274.62 15592.36 12835.03 10885.37 10196.91 19861.21 12966.29
Result Confidence
OpenBenchmarking.org Final Score, More Is Better BlogBench 1.1 Test: Read EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 400K 800K 1200K 1600K 2000K Min: 1916141 / Avg: 1944496.33 / Max: 1974796 Min: 1992185 / Avg: 2023179.67 / Max: 2061206 Min: 2022967 / Avg: 2043037.33 / Max: 2065016 Min: 1890301 / Avg: 1898428 / Max: 1912860 Min: 1944836 / Avg: 1959614.67 / Max: 1971357 Min: 1935120 / Avg: 1950080.33 / Max: 1961140 Min: 1610844 / Avg: 1636092.33 / Max: 1655363 Min: 1909275 / Avg: 1923368 / Max: 1932004 Min: 1764285 / Avg: 1771624.33 / Max: 1780874 Min: 1565457 / Avg: 1583350 / Max: 1611018 Min: 1384215 / Avg: 1397475 / Max: 1416780 Min: 1360224 / Avg: 1372955 / Max: 1393890 Min: 1743950 / Avg: 1772037 / Max: 1791514 Min: 1650220 / Avg: 1676515.67 / Max: 1694665 1. (CC) gcc options: -O2 -pthread
DaCapo Benchmark This test runs the DaCapo Benchmarks written in Java and intended to test system/CPU performance. Learn more via the OpenBenchmarking.org test page.
Result
OpenBenchmarking.org msec, Fewer Is Better DaCapo Benchmark 9.12-MR1 Java Test: H2 EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 1000 2000 3000 4000 5000 SE +/- 29.37, N = 5 SE +/- 22.48, N = 6 SE +/- 31.79, N = 5 SE +/- 38.29, N = 5 SE +/- 13.74, N = 5 SE +/- 22.77, N = 5 SE +/- 44.06, N = 5 SE +/- 15.11, N = 5 SE +/- 34.34, N = 5 SE +/- 39.23, N = 5 SE +/- 47.69, N = 5 SE +/- 31.43, N = 6 SE +/- 31.15, N = 7 3793 3552 3671 3633 3778 3917 4026 3861 4463 4773 4686 3316 3323
Result Confidence
OpenBenchmarking.org msec, Fewer Is Better DaCapo Benchmark 9.12-MR1 Java Test: H2 EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 800 1600 2400 3200 4000 Min: 3701 / Avg: 3792.8 / Max: 3886 Min: 3511 / Avg: 3551.67 / Max: 3657 Min: 3564 / Avg: 3671.2 / Max: 3763 Min: 3534 / Avg: 3633.2 / Max: 3722 Min: 3743 / Avg: 3778.2 / Max: 3810 Min: 3832 / Avg: 3917.4 / Max: 3957 Min: 3901 / Avg: 4025.6 / Max: 4157 Min: 3817 / Avg: 3860.6 / Max: 3906 Min: 4370 / Avg: 4463.2 / Max: 4566 Min: 4691 / Avg: 4773.4 / Max: 4896 Min: 4536 / Avg: 4686 / Max: 4799 Min: 3220 / Avg: 3315.5 / Max: 3444 Min: 3208 / Avg: 3323.43 / Max: 3442
Darmstadt Automotive Parallel Heterogeneous Suite DAPHNE is the Darmstadt Automotive Parallel HeterogeNEous Benchmark Suite with OpenCL / CUDA / OpenMP test cases for these automotive benchmarks for evaluating programming models in context to vehicle autonomous driving capabilities. Learn more via the OpenBenchmarking.org test page.
Result
OpenBenchmarking.org Test Cases Per Minute, More Is Better Darmstadt Automotive Parallel Heterogeneous Suite Backend: OpenMP - Kernel: Points2Image EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 6K 12K 18K 24K 30K SE +/- 130.62, N = 3 SE +/- 251.88, N = 3 SE +/- 162.08, N = 13 SE +/- 278.67, N = 4 SE +/- 228.79, N = 5 SE +/- 303.68, N = 3 SE +/- 233.41, N = 5 SE +/- 300.22, N = 3 SE +/- 149.83, N = 11 SE +/- 208.12, N = 5 SE +/- 203.19, N = 6 SE +/- 189.69, N = 6 SE +/- 296.05, N = 4 SE +/- 205.94, N = 13 23230.19 23807.67 22574.80 22339.85 21653.91 21272.04 20967.48 21442.00 20634.20 20036.19 19915.00 19062.92 27135.63 24205.54 1. (CXX) g++ options: -O3 -std=c++11 -fopenmp
Test Cases Per Minute Per Watt
OpenBenchmarking.org Test Cases Per Minute Per Watt, More Is Better Darmstadt Automotive Parallel Heterogeneous Suite Backend: OpenMP - Kernel: Points2Image EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 110 220 330 440 550 531.57 527.48 475.56 405.87 372.78 356.46 261.72 365.15 278.09 242.20 231.24 211.71 446.35 283.96
Result Confidence
OpenBenchmarking.org Test Cases Per Minute, More Is Better Darmstadt Automotive Parallel Heterogeneous Suite Backend: OpenMP - Kernel: Points2Image EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 5K 10K 15K 20K 25K Min: 22989.39 / Avg: 23230.19 / Max: 23438.32 Min: 23305.32 / Avg: 23807.67 / Max: 24091.45 Min: 20715.3 / Avg: 22574.8 / Max: 23030.24 Min: 21516.1 / Avg: 22339.85 / Max: 22741.4 Min: 20776.27 / Avg: 21653.91 / Max: 22118.67 Min: 20665.78 / Avg: 21272.04 / Max: 21606.83 Min: 20100.44 / Avg: 20967.48 / Max: 21472.74 Min: 20857.09 / Avg: 21442 / Max: 21851.95 Min: 19629.33 / Avg: 20634.2 / Max: 21282.63 Min: 19216.66 / Avg: 20036.19 / Max: 20355.61 Min: 18959.86 / Avg: 19915 / Max: 20292.89 Min: 18118.9 / Avg: 19062.92 / Max: 19320.87 Min: 26266.6 / Avg: 27135.63 / Max: 27598.01 Min: 22569.97 / Avg: 24205.54 / Max: 25313.47 1. (CXX) g++ options: -O3 -std=c++11 -fopenmp
Result
OpenBenchmarking.org ms, Fewer Is Better NCNN 20201218 Target: CPU - Model: resnet18 EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 4 8 12 16 20 SE +/- 0.01, N = 3 SE +/- 0.16, N = 3 SE +/- 0.23, N = 3 SE +/- 0.02, N = 3 SE +/- 0.02, N = 3 SE +/- 0.22, N = 3 SE +/- 0.03, N = 11 SE +/- 0.09, N = 3 SE +/- 0.09, N = 3 SE +/- 0.50, N = 12 SE +/- 0.08, N = 9 SE +/- 0.13, N = 9 SE +/- 0.06, N = 3 SE +/- 0.02, N = 3 14.14 14.50 14.52 12.02 12.53 13.17 13.09 13.01 14.95 15.35 16.19 16.80 11.88 15.83 MIN: 14.02 / MAX: 14.84 MIN: 14.03 / MAX: 30.23 MIN: 14.04 / MAX: 90.85 MIN: 11.87 / MAX: 12.25 MIN: 12.29 / MAX: 14.54 MIN: 12.72 / MAX: 15.99 MIN: 12.54 / MAX: 15.91 MIN: 12.71 / MAX: 16.73 MIN: 14.44 / MAX: 17.51 MIN: 13.83 / MAX: 1062.41 MIN: 14.96 / MAX: 24.1 MIN: 15.34 / MAX: 148.17 MIN: 11.62 / MAX: 12.46 MIN: 15.56 / MAX: 17.09 1. (CXX) g++ options: -O3 -rdynamic -lgomp -lpthread
Result Confidence
OpenBenchmarking.org ms, Fewer Is Better NCNN 20201218 Target: CPU - Model: resnet18 EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 4 8 12 16 20 Min: 14.12 / Avg: 14.14 / Max: 14.15 Min: 14.19 / Avg: 14.5 / Max: 14.66 Min: 14.26 / Avg: 14.52 / Max: 14.98 Min: 11.98 / Avg: 12.02 / Max: 12.05 Min: 12.49 / Avg: 12.53 / Max: 12.57 Min: 12.85 / Avg: 13.17 / Max: 13.59 Min: 12.94 / Avg: 13.09 / Max: 13.29 Min: 12.88 / Avg: 13.01 / Max: 13.19 Min: 14.77 / Avg: 14.95 / Max: 15.05 Min: 14.54 / Avg: 15.35 / Max: 20.77 Min: 15.8 / Avg: 16.19 / Max: 16.66 Min: 16.19 / Avg: 16.8 / Max: 17.25 Min: 11.76 / Avg: 11.88 / Max: 11.97 Min: 15.79 / Avg: 15.83 / Max: 15.87 1. (CXX) g++ options: -O3 -rdynamic -lgomp -lpthread
AI Benchmark Alpha AI Benchmark Alpha is a Python library for evaluating artificial intelligence (AI) performance on diverse hardware platforms and relies upon the TensorFlow machine learning library. Learn more via the OpenBenchmarking.org test page.
OpenBenchmarking.org Score, More Is Better AI Benchmark Alpha 0.1.2 Device Training Score EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 300 600 900 1200 1500 1094 1307 1384 1459 1546 1488 1475 1534 1348 1403 1219 1124 1173 1159
Monte Carlo Simulations of Ionised Nebulae Mocassin is the Monte Carlo Simulations of Ionised Nebulae. MOCASSIN is a fully 3D or 2D photoionisation and dust radiative transfer code which employs a Monte Carlo approach to the transfer of radiation through media of arbitrary geometry and density distribution. Learn more via the OpenBenchmarking.org test page.
Ngspice Ngspice is an open-source SPICE circuit simulator. Ngspice was originally based on the Berkeley SPICE electronic circuit simulator. Ngspice supports basic threading using OpenMP. This test profile is making use of the ISCAS 85 benchmark circuits. Learn more via the OpenBenchmarking.org test page.
Result
OpenBenchmarking.org Seconds, Fewer Is Better Ngspice 34 Circuit: C2670 EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 50 100 150 200 250 SE +/- 2.54, N = 3 SE +/- 1.59, N = 3 SE +/- 1.23, N = 3 SE +/- 1.93, N = 5 SE +/- 1.85, N = 3 SE +/- 1.90, N = 3 SE +/- 1.89, N = 3 SE +/- 1.33, N = 3 SE +/- 1.88, N = 4 SE +/- 1.05, N = 3 SE +/- 2.33, N = 9 211.49 174.20 183.22 173.90 175.85 165.66 170.22 172.37 177.62 158.79 151.46 1. (CC) gcc options: -O0 -fopenmp -lm -lstdc++ -lfftw3 -lXaw -lXmu -lXt -lXext -lX11 -lSM -lICE
Result Confidence
OpenBenchmarking.org Seconds, Fewer Is Better Ngspice 34 Circuit: C2670 EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 40 80 120 160 200 Min: 206.5 / Avg: 211.49 / Max: 214.78 Min: 171.02 / Avg: 174.2 / Max: 175.94 Min: 181.83 / Avg: 183.22 / Max: 185.67 Min: 168.11 / Avg: 173.89 / Max: 179.12 Min: 172.42 / Avg: 175.85 / Max: 178.76 Min: 162.62 / Avg: 165.66 / Max: 169.15 Min: 168.07 / Avg: 170.22 / Max: 173.98 Min: 170.3 / Avg: 172.37 / Max: 174.84 Min: 172.48 / Avg: 177.62 / Max: 181.39 Min: 157.45 / Avg: 158.79 / Max: 160.86 Min: 142 / Avg: 151.46 / Max: 162.3 1. (CC) gcc options: -O0 -fopenmp -lm -lstdc++ -lfftw3 -lXaw -lXmu -lXt -lXext -lX11 -lSM -lICE
Mobile Neural Network MNN is the Mobile Neural Network as a highly efficient, lightweight deep learning framework developed by Alibaba. Learn more via the OpenBenchmarking.org test page.
Result
OpenBenchmarking.org ms, Fewer Is Better Mobile Neural Network 1.1.1 Model: SqueezeNetV1.0 EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 3 6 9 12 15 SE +/- 0.071, N = 11 SE +/- 0.115, N = 4 SE +/- 0.027, N = 3 SE +/- 0.061, N = 15 SE +/- 0.114, N = 3 SE +/- 0.048, N = 3 SE +/- 0.016, N = 3 SE +/- 0.252, N = 15 SE +/- 0.271, N = 15 SE +/- 0.003, N = 3 SE +/- 0.018, N = 3 SE +/- 0.014, N = 3 SE +/- 0.062, N = 14 SE +/- 0.064, N = 3 9.650 9.768 9.610 9.504 8.978 7.493 7.338 7.625 8.142 7.479 7.542 8.375 9.357 10.209 MIN: 9.16 / MAX: 25.96 MIN: 9.3 / MAX: 12.44 MIN: 9.28 / MAX: 25.71 MIN: 9.01 / MAX: 25.56 MIN: 8.7 / MAX: 10.42 MIN: 7.29 / MAX: 9.78 MIN: 7.23 / MAX: 7.87 MIN: 7.08 / MAX: 14.04 MIN: 7.43 / MAX: 13.26 MIN: 7.34 / MAX: 8.04 MIN: 7.38 / MAX: 8.01 MIN: 8.25 / MAX: 8.55 MIN: 8.98 / MAX: 23.95 MIN: 10.06 / MAX: 11.23 1. (CXX) g++ options: -std=c++11 -O3 -fvisibility=hidden -fomit-frame-pointer -fstrict-aliasing -ffunction-sections -fdata-sections -ffast-math -fno-rtti -fno-exceptions -rdynamic -pthread -ldl
Result Confidence
OpenBenchmarking.org ms, Fewer Is Better Mobile Neural Network 1.1.1 Model: SqueezeNetV1.0 EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 3 6 9 12 15 Min: 9.3 / Avg: 9.65 / Max: 10.14 Min: 9.49 / Avg: 9.77 / Max: 10.05 Min: 9.58 / Avg: 9.61 / Max: 9.66 Min: 9.26 / Avg: 9.5 / Max: 10.27 Min: 8.84 / Avg: 8.98 / Max: 9.2 Min: 7.44 / Avg: 7.49 / Max: 7.59 Min: 7.32 / Avg: 7.34 / Max: 7.37 Min: 7.17 / Avg: 7.63 / Max: 10.86 Min: 7.63 / Avg: 8.14 / Max: 11.51 Min: 7.47 / Avg: 7.48 / Max: 7.48 Min: 7.51 / Avg: 7.54 / Max: 7.56 Min: 8.35 / Avg: 8.37 / Max: 8.4 Min: 9.16 / Avg: 9.36 / Max: 10 Min: 10.14 / Avg: 10.21 / Max: 10.34 1. (CXX) g++ options: -std=c++11 -O3 -fvisibility=hidden -fomit-frame-pointer -fstrict-aliasing -ffunction-sections -fdata-sections -ffast-math -fno-rtti -fno-exceptions -rdynamic -pthread -ldl
RawTherapee RawTherapee is a cross-platform, open-source multi-threaded RAW image processing program. Learn more via the OpenBenchmarking.org test page.
Result
OpenBenchmarking.org Seconds, Fewer Is Better RawTherapee Total Benchmark Time EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 16 32 48 64 80 SE +/- 0.02, N = 3 SE +/- 0.05, N = 3 SE +/- 0.59, N = 3 SE +/- 0.01, N = 3 SE +/- 0.04, N = 3 SE +/- 0.03, N = 3 SE +/- 0.06, N = 3 SE +/- 0.04, N = 3 SE +/- 0.08, N = 3 SE +/- 0.01, N = 3 SE +/- 0.04, N = 3 SE +/- 0.08, N = 3 SE +/- 0.12, N = 3 72.47 62.76 61.54 58.51 53.93 52.74 54.77 52.13 54.49 55.04 56.03 62.24 53.15 1. RawTherapee, version 5.8, command line.
Result Confidence
OpenBenchmarking.org Seconds, Fewer Is Better RawTherapee Total Benchmark Time EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 14 28 42 56 70 Min: 72.44 / Avg: 72.47 / Max: 72.51 Min: 62.66 / Avg: 62.76 / Max: 62.82 Min: 60.92 / Avg: 61.54 / Max: 62.73 Min: 58.49 / Avg: 58.51 / Max: 58.52 Min: 53.88 / Avg: 53.93 / Max: 54 Min: 52.69 / Avg: 52.74 / Max: 52.79 Min: 54.71 / Avg: 54.77 / Max: 54.89 Min: 52.04 / Avg: 52.12 / Max: 52.19 Min: 54.34 / Avg: 54.49 / Max: 54.59 Min: 55.03 / Avg: 55.04 / Max: 55.06 Min: 55.95 / Avg: 56.03 / Max: 56.09 Min: 62.13 / Avg: 62.24 / Max: 62.4 Min: 52.9 / Avg: 53.15 / Max: 53.28 1. RawTherapee, version 5.8, command line.
ASTC Encoder ASTC Encoder (astcenc) is for the Adaptive Scalable Texture Compression (ASTC) format commonly used with OpenGL, OpenGL ES, and Vulkan graphics APIs. This test profile does a coding test of both compression/decompression. Learn more via the OpenBenchmarking.org test page.
Result
OpenBenchmarking.org Seconds, Fewer Is Better ASTC Encoder 2.0 Preset: Fast EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 2 4 6 8 10 SE +/- 0.01, N = 6 SE +/- 0.01, N = 6 SE +/- 0.00, N = 6 SE +/- 0.01, N = 6 SE +/- 0.00, N = 7 SE +/- 0.01, N = 7 SE +/- 0.01, N = 7 SE +/- 0.01, N = 7 SE +/- 0.01, N = 7 SE +/- 0.00, N = 7 SE +/- 0.01, N = 7 SE +/- 0.01, N = 7 SE +/- 0.01, N = 7 7.65 6.97 6.68 6.47 6.06 5.93 6.05 5.83 5.89 5.83 5.76 6.28 5.51 1. (CXX) g++ options: -std=c++14 -fvisibility=hidden -O3 -flto -mfpmath=sse -mavx2 -mpopcnt -lpthread
Result Confidence
OpenBenchmarking.org Seconds, Fewer Is Better ASTC Encoder 2.0 Preset: Fast EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 3 6 9 12 15 Min: 7.6 / Avg: 7.65 / Max: 7.69 Min: 6.93 / Avg: 6.97 / Max: 7.01 Min: 6.66 / Avg: 6.68 / Max: 6.69 Min: 6.45 / Avg: 6.47 / Max: 6.5 Min: 6.04 / Avg: 6.06 / Max: 6.07 Min: 5.92 / Avg: 5.93 / Max: 5.96 Min: 6.01 / Avg: 6.05 / Max: 6.07 Min: 5.81 / Avg: 5.83 / Max: 5.86 Min: 5.87 / Avg: 5.89 / Max: 5.91 Min: 5.82 / Avg: 5.83 / Max: 5.84 Min: 5.75 / Avg: 5.76 / Max: 5.8 Min: 6.24 / Avg: 6.28 / Max: 6.31 Min: 5.49 / Avg: 5.51 / Max: 5.54 1. (CXX) g++ options: -std=c++14 -fvisibility=hidden -O3 -flto -mfpmath=sse -mavx2 -mpopcnt -lpthread
Timed GDB GNU Debugger Compilation This test times how long it takes to build the GNU Debugger (GDB) in a default configuration. Learn more via the OpenBenchmarking.org test page.
Result
OpenBenchmarking.org Seconds, Fewer Is Better Timed GDB GNU Debugger Compilation 9.1 Time To Compile EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 30 60 90 120 150 SE +/- 0.11, N = 3 SE +/- 0.06, N = 3 SE +/- 0.05, N = 3 SE +/- 0.09, N = 3 SE +/- 0.03, N = 3 SE +/- 0.03, N = 3 SE +/- 0.11, N = 3 SE +/- 0.07, N = 3 SE +/- 0.01, N = 3 SE +/- 0.01, N = 3 SE +/- 0.04, N = 3 SE +/- 0.07, N = 3 SE +/- 0.08, N = 3 SE +/- 0.08, N = 3 114.83 99.22 94.48 92.26 86.97 85.96 88.42 84.83 86.95 87.21 87.02 86.37 94.01 82.92
Result Confidence
OpenBenchmarking.org Seconds, Fewer Is Better Timed GDB GNU Debugger Compilation 9.1 Time To Compile EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 20 40 60 80 100 Min: 114.63 / Avg: 114.83 / Max: 115 Min: 99.11 / Avg: 99.22 / Max: 99.3 Min: 94.41 / Avg: 94.48 / Max: 94.59 Min: 92.07 / Avg: 92.26 / Max: 92.37 Min: 86.94 / Avg: 86.97 / Max: 87.03 Min: 85.93 / Avg: 85.96 / Max: 86.02 Min: 88.21 / Avg: 88.42 / Max: 88.6 Min: 84.74 / Avg: 84.83 / Max: 84.97 Min: 86.95 / Avg: 86.95 / Max: 86.96 Min: 87.2 / Avg: 87.21 / Max: 87.22 Min: 86.98 / Avg: 87.02 / Max: 87.09 Min: 86.23 / Avg: 86.37 / Max: 86.48 Min: 93.84 / Avg: 94.01 / Max: 94.13 Min: 82.8 / Avg: 82.92 / Max: 83.07
Quantum ESPRESSO Quantum ESPRESSO is an integrated suite of Open-Source computer codes for electronic-structure calculations and materials modeling at the nanoscale. It is based on density-functional theory, plane waves, and pseudopotentials. Learn more via the OpenBenchmarking.org test page.
Result
OpenBenchmarking.org Seconds, Fewer Is Better Quantum ESPRESSO 6.7 Input: AUSURF112 EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 400 800 1200 1600 2000 SE +/- 0.83, N = 3 SE +/- 1.18, N = 3 SE +/- 4.40, N = 3 SE +/- 5.19, N = 3 SE +/- 1.29, N = 3 SE +/- 5.50, N = 3 SE +/- 6.34, N = 3 SE +/- 3.48, N = 3 SE +/- 16.58, N = 4 SE +/- 22.87, N = 9 SE +/- 1.64, N = 3 SE +/- 1.52, N = 3 SE +/- 0.33, N = 3 SE +/- 11.50, N = 3 1656.88 1520.43 1456.82 1403.52 1342.14 1386.78 1403.87 1317.27 1329.90 1372.73 1216.50 1208.31 1356.26 1357.30 1. (F9X) gfortran options: -lopenblas -lFoX_dom -lFoX_sax -lFoX_wxml -lFoX_common -lFoX_utils -lFoX_fsys -lfftw3 -pthread -lmpi_usempif08 -lmpi_mpifh -lmpi
Result Confidence
OpenBenchmarking.org Seconds, Fewer Is Better Quantum ESPRESSO 6.7 Input: AUSURF112 EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 300 600 900 1200 1500 Min: 1655.62 / Avg: 1656.88 / Max: 1658.44 Min: 1518.1 / Avg: 1520.43 / Max: 1521.97 Min: 1450.92 / Avg: 1456.82 / Max: 1465.43 Min: 1394.1 / Avg: 1403.52 / Max: 1411.99 Min: 1339.87 / Avg: 1342.14 / Max: 1344.32 Min: 1377.07 / Avg: 1386.78 / Max: 1396.11 Min: 1396.5 / Avg: 1403.87 / Max: 1416.5 Min: 1313.6 / Avg: 1317.27 / Max: 1324.22 Min: 1306.89 / Avg: 1329.9 / Max: 1377.55 Min: 1251.31 / Avg: 1372.73 / Max: 1438.64 Min: 1214.11 / Avg: 1216.5 / Max: 1219.63 Min: 1205.82 / Avg: 1208.31 / Max: 1211.05 Min: 1355.84 / Avg: 1356.26 / Max: 1356.92 Min: 1338.99 / Avg: 1357.3 / Max: 1378.5 1. (F9X) gfortran options: -lopenblas -lFoX_dom -lFoX_sax -lFoX_wxml -lFoX_common -lFoX_utils -lFoX_fsys -lfftw3 -pthread -lmpi_usempif08 -lmpi_mpifh -lmpi
Result
OpenBenchmarking.org ms, Fewer Is Better NCNN 20201218 Target: CPU - Model: alexnet EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 3 6 9 12 15 SE +/- 0.02, N = 3 SE +/- 0.02, N = 3 SE +/- 0.08, N = 3 SE +/- 0.01, N = 2 SE +/- 0.01, N = 3 SE +/- 0.16, N = 3 SE +/- 0.06, N = 11 SE +/- 0.16, N = 3 SE +/- 0.32, N = 3 SE +/- 0.07, N = 12 SE +/- 0.08, N = 9 SE +/- 0.05, N = 9 SE +/- 0.00, N = 3 SE +/- 0.14, N = 3 9.86 9.86 10.16 7.44 7.80 8.55 7.81 8.28 9.49 8.56 8.81 9.01 7.60 9.87 MIN: 9.77 / MAX: 25.65 MIN: 9.77 / MAX: 10.66 MIN: 9.88 / MAX: 21.62 MIN: 7.34 / MAX: 8.53 MIN: 7.66 / MAX: 9.41 MIN: 8.18 / MAX: 10.72 MIN: 7.55 / MAX: 10.47 MIN: 8 / MAX: 10.85 MIN: 8.54 / MAX: 13.63 MIN: 8.22 / MAX: 24.11 MIN: 8.44 / MAX: 32.96 MIN: 8.61 / MAX: 17.39 MIN: 7.51 / MAX: 8.13 MIN: 9.45 / MAX: 10.5 1. (CXX) g++ options: -O3 -rdynamic -lgomp -lpthread
Result Confidence
OpenBenchmarking.org ms, Fewer Is Better NCNN 20201218 Target: CPU - Model: alexnet EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 3 6 9 12 15 Min: 9.84 / Avg: 9.86 / Max: 9.9 Min: 9.82 / Avg: 9.86 / Max: 9.89 Min: 10.05 / Avg: 10.16 / Max: 10.31 Min: 7.43 / Avg: 7.44 / Max: 7.45 Min: 7.78 / Avg: 7.8 / Max: 7.82 Min: 8.38 / Avg: 8.55 / Max: 8.86 Min: 7.65 / Avg: 7.81 / Max: 8.24 Min: 8.12 / Avg: 8.28 / Max: 8.6 Min: 8.86 / Avg: 9.49 / Max: 9.82 Min: 8.41 / Avg: 8.56 / Max: 9.07 Min: 8.55 / Avg: 8.81 / Max: 9.42 Min: 8.88 / Avg: 9.01 / Max: 9.38 Min: 7.6 / Avg: 7.6 / Max: 7.61 Min: 9.7 / Avg: 9.87 / Max: 10.15 1. (CXX) g++ options: -O3 -rdynamic -lgomp -lpthread
Caffe This is a benchmark of the Caffe deep learning framework and currently supports the AlexNet and Googlenet model and execution on both CPUs and NVIDIA GPUs. Learn more via the OpenBenchmarking.org test page.
Result
OpenBenchmarking.org Milli-Seconds, Fewer Is Better Caffe 2020-02-13 Model: AlexNet - Acceleration: CPU - Iterations: 200 EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 40K 80K 120K 160K 200K SE +/- 139.37, N = 3 SE +/- 272.29, N = 3 SE +/- 76.96, N = 3 SE +/- 37.21, N = 3 SE +/- 92.46, N = 3 SE +/- 187.42, N = 3 SE +/- 106.86, N = 3 SE +/- 120.93, N = 3 SE +/- 1549.72, N = 7 SE +/- 114.49, N = 3 SE +/- 146.69, N = 3 SE +/- 182.06, N = 3 SE +/- 101.93, N = 3 SE +/- 1333.26, N = 3 151559 154871 155763 152539 154693 168728 172508 162544 171885 173812 127699 128965 140558 151327 1. (CXX) g++ options: -fPIC -O3 -rdynamic -lglog -lgflags -lprotobuf -lpthread -lsz -lz -ldl -lm -llmdb -lopenblas
Result Confidence
OpenBenchmarking.org Milli-Seconds, Fewer Is Better Caffe 2020-02-13 Model: AlexNet - Acceleration: CPU - Iterations: 200 EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 30K 60K 90K 120K 150K Min: 151334 / Avg: 151559 / Max: 151814 Min: 154328 / Avg: 154871.33 / Max: 155175 Min: 155611 / Avg: 155763 / Max: 155860 Min: 152490 / Avg: 152539 / Max: 152612 Min: 154545 / Avg: 154693 / Max: 154863 Min: 168512 / Avg: 168727.67 / Max: 169101 Min: 172364 / Avg: 172508.33 / Max: 172717 Min: 162302 / Avg: 162543.67 / Max: 162673 Min: 162598 / Avg: 171885 / Max: 173740 Min: 173597 / Avg: 173811.67 / Max: 173988 Min: 127449 / Avg: 127699.33 / Max: 127957 Min: 128622 / Avg: 128965.33 / Max: 129242 Min: 140379 / Avg: 140558 / Max: 140732 Min: 149779 / Avg: 151326.67 / Max: 153981 1. (CXX) g++ options: -fPIC -O3 -rdynamic -lglog -lgflags -lprotobuf -lpthread -lsz -lz -ldl -lm -llmdb -lopenblas
Mobile Neural Network MNN is the Mobile Neural Network as a highly efficient, lightweight deep learning framework developed by Alibaba. Learn more via the OpenBenchmarking.org test page.
Result
OpenBenchmarking.org ms, Fewer Is Better Mobile Neural Network 1.1.1 Model: inception-v3 EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 10 20 30 40 50 SE +/- 0.12, N = 11 SE +/- 0.09, N = 4 SE +/- 0.09, N = 3 SE +/- 0.09, N = 15 SE +/- 0.70, N = 3 SE +/- 0.14, N = 3 SE +/- 0.06, N = 3 SE +/- 0.05, N = 15 SE +/- 0.05, N = 15 SE +/- 0.12, N = 3 SE +/- 0.01, N = 3 SE +/- 0.04, N = 3 SE +/- 0.02, N = 14 SE +/- 0.27, N = 3 38.33 38.62 43.13 41.12 36.88 32.92 32.47 31.87 35.47 32.86 33.58 38.00 34.91 43.36 MIN: 37.06 / MAX: 55.19 MIN: 38.09 / MAX: 52.97 MIN: 42.07 / MAX: 59.48 MIN: 39.63 / MAX: 81.35 MIN: 35.1 / MAX: 40.26 MIN: 32.02 / MAX: 35.9 MIN: 32.03 / MAX: 34.7 MIN: 30.79 / MAX: 34.77 MIN: 34.49 / MAX: 38.11 MIN: 32.05 / MAX: 34.89 MIN: 32.98 / MAX: 34.68 MIN: 36.26 / MAX: 38.93 MIN: 33.81 / MAX: 50.1 MIN: 40.47 / MAX: 57.18 1. (CXX) g++ options: -std=c++11 -O3 -fvisibility=hidden -fomit-frame-pointer -fstrict-aliasing -ffunction-sections -fdata-sections -ffast-math -fno-rtti -fno-exceptions -rdynamic -pthread -ldl
Result Confidence
OpenBenchmarking.org ms, Fewer Is Better Mobile Neural Network 1.1.1 Model: inception-v3 EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 9 18 27 36 45 Min: 37.94 / Avg: 38.33 / Max: 39.34 Min: 38.45 / Avg: 38.62 / Max: 38.79 Min: 43 / Avg: 43.13 / Max: 43.3 Min: 40.41 / Avg: 41.12 / Max: 41.65 Min: 35.66 / Avg: 36.88 / Max: 38.08 Min: 32.64 / Avg: 32.92 / Max: 33.11 Min: 32.35 / Avg: 32.47 / Max: 32.57 Min: 31.52 / Avg: 31.87 / Max: 32.13 Min: 34.98 / Avg: 35.47 / Max: 35.68 Min: 32.62 / Avg: 32.86 / Max: 33.02 Min: 33.57 / Avg: 33.58 / Max: 33.59 Min: 37.92 / Avg: 38 / Max: 38.08 Min: 34.79 / Avg: 34.91 / Max: 35.08 Min: 42.82 / Avg: 43.36 / Max: 43.65 1. (CXX) g++ options: -std=c++11 -O3 -fvisibility=hidden -fomit-frame-pointer -fstrict-aliasing -ffunction-sections -fdata-sections -ffast-math -fno-rtti -fno-exceptions -rdynamic -pthread -ldl
ONNX Runtime ONNX Runtime is developed by Microsoft and partners as a open-source, cross-platform, high performance machine learning inferencing and training accelerator. This test profile runs the ONNX Runtime with various models available from the ONNX Zoo. Learn more via the OpenBenchmarking.org test page.
Result
OpenBenchmarking.org Inferences Per Minute, More Is Better ONNX Runtime 1.6 Model: fcn-resnet101-11 - Device: OpenMP CPU EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 20 40 60 80 100 SE +/- 0.00, N = 3 SE +/- 0.17, N = 3 SE +/- 0.29, N = 3 SE +/- 0.67, N = 3 SE +/- 0.29, N = 3 SE +/- 0.53, N = 12 SE +/- 0.67, N = 3 SE +/- 0.58, N = 3 SE +/- 1.04, N = 3 SE +/- 0.17, N = 3 SE +/- 0.33, N = 3 SE +/- 0.44, N = 3 SE +/- 0.67, N = 3 SE +/- 0.60, N = 3 59 70 77 69 72 64 79 69 79 80 79 74 59 69 1. (CXX) g++ options: -fopenmp -ffunction-sections -fdata-sections -O3 -ldl -lrt
Inferences Per Minute Per Watt
OpenBenchmarking.org Inferences Per Minute Per Watt, More Is Better ONNX Runtime 1.6 Model: fcn-resnet101-11 - Device: OpenMP CPU EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 0.1845 0.369 0.5535 0.738 0.9225 0.68 0.76 0.82 0.66 0.61 0.58 0.55 0.60 0.67 0.58 0.55 0.57 0.46 0.39
Result Confidence
OpenBenchmarking.org Inferences Per Minute, More Is Better ONNX Runtime 1.6 Model: fcn-resnet101-11 - Device: OpenMP CPU EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 15 30 45 60 75 Min: 58.5 / Avg: 58.5 / Max: 58.5 Min: 69.5 / Avg: 69.83 / Max: 70 Min: 76.5 / Avg: 77 / Max: 77.5 Min: 68 / Avg: 69.33 / Max: 70 Min: 71 / Avg: 71.5 / Max: 72 Min: 61 / Avg: 64 / Max: 67.5 Min: 78.5 / Avg: 79.17 / Max: 80.5 Min: 68 / Avg: 69 / Max: 70 Min: 77 / Avg: 79 / Max: 80.5 Min: 80 / Avg: 80.17 / Max: 80.5 Min: 78.5 / Avg: 79.17 / Max: 79.5 Min: 73.5 / Avg: 74.33 / Max: 75 Min: 58 / Avg: 59.33 / Max: 60 Min: 68 / Avg: 69.17 / Max: 70 1. (CXX) g++ options: -fopenmp -ffunction-sections -fdata-sections -O3 -ldl -lrt
C-Blosc A simple, compressed, fast and persistent data store library for C. Learn more via the OpenBenchmarking.org test page.
Result
OpenBenchmarking.org MB/s, More Is Better C-Blosc 2.0 Beta 5 Compressor: blosclz EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 2K 4K 6K 8K 10K SE +/- 13.17, N = 3 SE +/- 6.54, N = 3 SE +/- 21.69, N = 3 SE +/- 5.79, N = 3 SE +/- 4.79, N = 3 SE +/- 6.00, N = 3 SE +/- 8.53, N = 3 SE +/- 0.44, N = 3 SE +/- 22.60, N = 3 SE +/- 9.12, N = 3 SE +/- 18.47, N = 3 SE +/- 20.77, N = 3 SE +/- 15.51, N = 3 SE +/- 27.57, N = 3 9386.8 9442.9 9400.7 10476.8 10178.3 9808.0 10253.3 9878.0 9155.0 9301.0 8328.2 8372.7 11206.8 10910.1 1. (CXX) g++ options: -rdynamic
MB/s Per Watt
OpenBenchmarking.org MB/s Per Watt, More Is Better C-Blosc 2.0 Beta 5 Compressor: blosclz EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 40 80 120 160 200 182.90 173.90 165.18 160.12 145.89 135.67 106.55 138.76 104.37 93.88 83.21 77.37 165.32 109.47
Result Confidence
OpenBenchmarking.org MB/s, More Is Better C-Blosc 2.0 Beta 5 Compressor: blosclz EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 2K 4K 6K 8K 10K Min: 9360.9 / Avg: 9386.83 / Max: 9403.8 Min: 9434.1 / Avg: 9442.93 / Max: 9455.7 Min: 9370.8 / Avg: 9400.73 / Max: 9442.9 Min: 10468.4 / Avg: 10476.8 / Max: 10487.9 Min: 10170 / Avg: 10178.27 / Max: 10186.6 Min: 9796 / Avg: 9808 / Max: 9814.1 Min: 10242.8 / Avg: 10253.3 / Max: 10270.2 Min: 9877.3 / Avg: 9878 / Max: 9878.8 Min: 9132 / Avg: 9155 / Max: 9200.2 Min: 9282.8 / Avg: 9301 / Max: 9311.2 Min: 8294.6 / Avg: 8328.2 / Max: 8358.3 Min: 8331.9 / Avg: 8372.7 / Max: 8399.9 Min: 11190.3 / Avg: 11206.8 / Max: 11237.8 Min: 10869.2 / Avg: 10910.13 / Max: 10962.6 1. (CXX) g++ options: -rdynamic
ONNX Runtime ONNX Runtime is developed by Microsoft and partners as a open-source, cross-platform, high performance machine learning inferencing and training accelerator. This test profile runs the ONNX Runtime with various models available from the ONNX Zoo. Learn more via the OpenBenchmarking.org test page.
Result
OpenBenchmarking.org Inferences Per Minute, More Is Better ONNX Runtime 1.6 Model: bertsquad-10 - Device: OpenMP CPU EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 110 220 330 440 550 SE +/- 0.50, N = 3 SE +/- 1.26, N = 3 SE +/- 0.29, N = 3 SE +/- 5.01, N = 3 SE +/- 4.15, N = 9 SE +/- 4.69, N = 12 SE +/- 0.44, N = 3 SE +/- 1.15, N = 3 SE +/- 0.60, N = 3 SE +/- 3.97, N = 3 SE +/- 6.16, N = 12 SE +/- 7.16, N = 12 SE +/- 0.50, N = 3 SE +/- 6.13, N = 12 409 403 400 456 500 459 466 475 440 431 395 390 480 372 1. (CXX) g++ options: -fopenmp -ffunction-sections -fdata-sections -O3 -ldl -lrt
Inferences Per Minute Per Watt
OpenBenchmarking.org Inferences Per Minute Per Watt, More Is Better ONNX Runtime 1.6 Model: bertsquad-10 - Device: OpenMP CPU EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 1.179 2.358 3.537 4.716 5.895 5.24 4.79 4.71 4.50 4.25 3.86 3.27 4.08 3.22 2.84 2.50 2.39 4.10 2.50
Result Confidence
OpenBenchmarking.org Inferences Per Minute, More Is Better ONNX Runtime 1.6 Model: bertsquad-10 - Device: OpenMP CPU EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 90 180 270 360 450 Min: 408 / Avg: 409 / Max: 409.5 Min: 401.5 / Avg: 403 / Max: 405.5 Min: 399.5 / Avg: 400 / Max: 400.5 Min: 450.5 / Avg: 456 / Max: 466 Min: 468 / Avg: 500.22 / Max: 507 Min: 425.5 / Avg: 459.13 / Max: 469.5 Min: 465.5 / Avg: 466.33 / Max: 467 Min: 472.5 / Avg: 474.5 / Max: 476.5 Min: 439.5 / Avg: 440.33 / Max: 441.5 Min: 424.5 / Avg: 430.5 / Max: 438 Min: 343.5 / Avg: 395 / Max: 412.5 Min: 335.5 / Avg: 389.54 / Max: 410.5 Min: 479.5 / Avg: 480 / Max: 481 Min: 329.5 / Avg: 371.92 / Max: 403.5 1. (CXX) g++ options: -fopenmp -ffunction-sections -fdata-sections -O3 -ldl -lrt
Result
OpenBenchmarking.org Inferences Per Minute, More Is Better ONNX Runtime 1.6 Model: super-resolution-10 - Device: OpenMP CPU EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 1100 2200 3300 4400 5500 SE +/- 3.69, N = 3 SE +/- 16.48, N = 3 SE +/- 24.57, N = 3 SE +/- 73.62, N = 12 SE +/- 71.97, N = 12 SE +/- 62.74, N = 3 SE +/- 35.49, N = 11 SE +/- 67.46, N = 11 SE +/- 27.98, N = 3 SE +/- 52.31, N = 12 SE +/- 95.52, N = 12 SE +/- 84.35, N = 9 SE +/- 5.63, N = 3 SE +/- 88.35, N = 12 3941 3943 4044 4522 4946 4755 4864 4986 4642 4506 4175 4087 4518 5212 1. (CXX) g++ options: -fopenmp -ffunction-sections -fdata-sections -O3 -ldl -lrt
Inferences Per Minute Per Watt
OpenBenchmarking.org Inferences Per Minute Per Watt, More Is Better ONNX Runtime 1.6 Model: super-resolution-10 - Device: OpenMP CPU EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 11 22 33 44 55 47.91 44.61 45.86 43.67 39.90 38.41 32.78 40.89 33.35 28.36 25.67 25.73 36.02 28.68
Result Confidence
OpenBenchmarking.org Inferences Per Minute, More Is Better ONNX Runtime 1.6 Model: super-resolution-10 - Device: OpenMP CPU EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 900 1800 2700 3600 4500 Min: 3934 / Avg: 3941 / Max: 3946.5 Min: 3922 / Avg: 3943 / Max: 3975.5 Min: 3996 / Avg: 4043.83 / Max: 4077.5 Min: 4171 / Avg: 4521.92 / Max: 5107 Min: 4494.5 / Avg: 4946.25 / Max: 5164.5 Min: 4633.5 / Avg: 4754.67 / Max: 4843.5 Min: 4539 / Avg: 4864.36 / Max: 4940.5 Min: 4318 / Avg: 4986.05 / Max: 5084 Min: 4586 / Avg: 4641.67 / Max: 4674.5 Min: 4219.5 / Avg: 4506.42 / Max: 4722 Min: 3788 / Avg: 4174.71 / Max: 4608.5 Min: 3791.5 / Avg: 4086.5 / Max: 4435 Min: 4508 / Avg: 4517.67 / Max: 4527.5 Min: 4665 / Avg: 5211.92 / Max: 5596 1. (CXX) g++ options: -fopenmp -ffunction-sections -fdata-sections -O3 -ldl -lrt
Nebular Empirical Analysis Tool NEAT is the Nebular Empirical Analysis Tool for empirical analysis of ionised nebulae, with uncertainty propagation. Learn more via the OpenBenchmarking.org test page.
Result
OpenBenchmarking.org Seconds, Fewer Is Better Nebular Empirical Analysis Tool 2020-02-29 EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 5 10 15 20 25 SE +/- 0.02, N = 3 SE +/- 0.01, N = 3 SE +/- 0.01, N = 3 SE +/- 0.01, N = 3 SE +/- 0.01, N = 3 SE +/- 0.03, N = 4 SE +/- 0.00, N = 3 SE +/- 0.01, N = 4 SE +/- 0.08, N = 3 SE +/- 0.16, N = 3 SE +/- 0.05, N = 3 SE +/- 0.15, N = 3 SE +/- 0.01, N = 3 SE +/- 0.01, N = 4 21.35 18.10 17.39 17.75 16.92 16.55 17.21 16.37 16.67 17.03 16.89 17.37 17.44 16.20 1. (F9X) gfortran options: -cpp -ffree-line-length-0 -Jsource/ -fopenmp -O3 -fno-backtrace
Result Confidence
OpenBenchmarking.org Seconds, Fewer Is Better Nebular Empirical Analysis Tool 2020-02-29 EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 5 10 15 20 25 Min: 21.31 / Avg: 21.35 / Max: 21.39 Min: 18.08 / Avg: 18.1 / Max: 18.11 Min: 17.38 / Avg: 17.39 / Max: 17.4 Min: 17.73 / Avg: 17.75 / Max: 17.77 Min: 16.91 / Avg: 16.92 / Max: 16.93 Min: 16.49 / Avg: 16.55 / Max: 16.65 Min: 17.21 / Avg: 17.21 / Max: 17.22 Min: 16.34 / Avg: 16.37 / Max: 16.39 Min: 16.52 / Avg: 16.67 / Max: 16.78 Min: 16.72 / Avg: 17.03 / Max: 17.24 Min: 16.79 / Avg: 16.89 / Max: 16.96 Min: 17.08 / Avg: 17.37 / Max: 17.52 Min: 17.42 / Avg: 17.43 / Max: 17.46 Min: 16.19 / Avg: 16.2 / Max: 16.23 1. (F9X) gfortran options: -cpp -ffree-line-length-0 -Jsource/ -fopenmp -O3 -fno-backtrace
Basis Universal Basis Universal is a GPU texture codoec. This test times how long it takes to convert sRGB PNGs into Basis Univeral assets with various settings. Learn more via the OpenBenchmarking.org test page.
Result
OpenBenchmarking.org Seconds, Fewer Is Better Basis Universal 1.12 Settings: ETC1S EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 14 28 42 56 70 SE +/- 0.13, N = 3 SE +/- 0.04, N = 3 SE +/- 0.01, N = 3 SE +/- 0.04, N = 3 SE +/- 0.01, N = 3 SE +/- 0.07, N = 3 SE +/- 0.05, N = 3 SE +/- 0.05, N = 3 SE +/- 0.02, N = 3 SE +/- 0.03, N = 3 SE +/- 0.06, N = 3 SE +/- 0.23, N = 3 SE +/- 0.03, N = 3 64.83 60.10 58.64 57.18 55.14 54.57 55.59 53.93 54.98 54.82 54.10 53.65 49.34 1. (CXX) g++ options: -std=c++11 -fvisibility=hidden -fPIC -fno-strict-aliasing -O3 -rdynamic -lm -lpthread
Result Confidence
OpenBenchmarking.org Seconds, Fewer Is Better Basis Universal 1.12 Settings: ETC1S EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 13 26 39 52 65 Min: 64.68 / Avg: 64.83 / Max: 65.09 Min: 60.03 / Avg: 60.1 / Max: 60.17 Min: 58.62 / Avg: 58.64 / Max: 58.66 Min: 57.13 / Avg: 57.18 / Max: 57.25 Min: 55.12 / Avg: 55.14 / Max: 55.16 Min: 54.42 / Avg: 54.57 / Max: 54.65 Min: 55.5 / Avg: 55.59 / Max: 55.67 Min: 53.83 / Avg: 53.93 / Max: 54.01 Min: 54.94 / Avg: 54.98 / Max: 55.01 Min: 54.77 / Avg: 54.82 / Max: 54.86 Min: 54.02 / Avg: 54.1 / Max: 54.23 Min: 53.23 / Avg: 53.65 / Max: 54.01 Min: 49.28 / Avg: 49.34 / Max: 49.38 1. (CXX) g++ options: -std=c++11 -fvisibility=hidden -fPIC -fno-strict-aliasing -O3 -rdynamic -lm -lpthread
Result
OpenBenchmarking.org Seconds, Fewer Is Better Basis Universal 1.12 Settings: UASTC Level 0 EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 3 6 9 12 15 SE +/- 0.005, N = 5 SE +/- 0.002, N = 5 SE +/- 0.007, N = 5 SE +/- 0.005, N = 5 SE +/- 0.009, N = 6 SE +/- 0.002, N = 6 SE +/- 0.003, N = 5 SE +/- 0.005, N = 6 SE +/- 0.003, N = 6 SE +/- 0.002, N = 6 SE +/- 0.006, N = 6 SE +/- 0.002, N = 6 SE +/- 0.005, N = 6 9.756 9.190 8.923 8.660 8.267 8.149 8.357 8.038 8.198 8.132 8.095 8.077 7.453 1. (CXX) g++ options: -std=c++11 -fvisibility=hidden -fPIC -fno-strict-aliasing -O3 -rdynamic -lm -lpthread
Result Confidence
OpenBenchmarking.org Seconds, Fewer Is Better Basis Universal 1.12 Settings: UASTC Level 0 EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 3 6 9 12 15 Min: 9.74 / Avg: 9.76 / Max: 9.77 Min: 9.18 / Avg: 9.19 / Max: 9.19 Min: 8.9 / Avg: 8.92 / Max: 8.94 Min: 8.65 / Avg: 8.66 / Max: 8.67 Min: 8.24 / Avg: 8.27 / Max: 8.3 Min: 8.14 / Avg: 8.15 / Max: 8.16 Min: 8.35 / Avg: 8.36 / Max: 8.37 Min: 8.02 / Avg: 8.04 / Max: 8.05 Min: 8.19 / Avg: 8.2 / Max: 8.21 Min: 8.13 / Avg: 8.13 / Max: 8.14 Min: 8.06 / Avg: 8.09 / Max: 8.11 Min: 8.07 / Avg: 8.08 / Max: 8.08 Min: 7.44 / Avg: 7.45 / Max: 7.48 1. (CXX) g++ options: -std=c++11 -fvisibility=hidden -fPIC -fno-strict-aliasing -O3 -rdynamic -lm -lpthread
Caffe This is a benchmark of the Caffe deep learning framework and currently supports the AlexNet and Googlenet model and execution on both CPUs and NVIDIA GPUs. Learn more via the OpenBenchmarking.org test page.
Result
OpenBenchmarking.org Milli-Seconds, Fewer Is Better Caffe 2020-02-13 Model: GoogleNet - Acceleration: CPU - Iterations: 200 EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 90K 180K 270K 360K 450K SE +/- 533.40, N = 3 SE +/- 226.68, N = 3 SE +/- 456.29, N = 3 SE +/- 60.14, N = 3 SE +/- 338.07, N = 3 SE +/- 440.86, N = 3 SE +/- 422.64, N = 3 SE +/- 147.16, N = 3 SE +/- 18239.03, N = 9 SE +/- 10886.13, N = 9 SE +/- 1226.45, N = 3 SE +/- 730.51, N = 3 SE +/- 95.91, N = 3 SE +/- 1699.46, N = 3 369027 378367 388699 387173 391015 427967 441978 411681 399610 429875 345626 347484 340168 382020 1. (CXX) g++ options: -fPIC -O3 -rdynamic -lglog -lgflags -lprotobuf -lpthread -lsz -lz -ldl -lm -llmdb -lopenblas
Result Confidence
OpenBenchmarking.org Milli-Seconds, Fewer Is Better Caffe 2020-02-13 Model: GoogleNet - Acceleration: CPU - Iterations: 200 EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 80K 160K 240K 320K 400K Min: 367965 / Avg: 369027.33 / Max: 369643 Min: 378044 / Avg: 378367 / Max: 378804 Min: 387821 / Avg: 388699.33 / Max: 389353 Min: 387058 / Avg: 387173 / Max: 387261 Min: 390425 / Avg: 391015.33 / Max: 391596 Min: 427345 / Avg: 427966.67 / Max: 428819 Min: 441242 / Avg: 441977.67 / Max: 442706 Min: 411435 / Avg: 411681.33 / Max: 411944 Min: 331340 / Avg: 399610.44 / Max: 446964 Min: 364614 / Avg: 429875.11 / Max: 446994 Min: 344068 / Avg: 345626.33 / Max: 348046 Min: 346044 / Avg: 347483.67 / Max: 348419 Min: 339980 / Avg: 340168 / Max: 340295 Min: 379249 / Avg: 382019.67 / Max: 385110 1. (CXX) g++ options: -fPIC -O3 -rdynamic -lglog -lgflags -lprotobuf -lpthread -lsz -lz -ldl -lm -llmdb -lopenblas
Timed Apache Compilation This test times how long it takes to build the Apache HTTPD web server. Learn more via the OpenBenchmarking.org test page.
Result
OpenBenchmarking.org Seconds, Fewer Is Better Timed Apache Compilation 2.4.41 Time To Compile EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 7 14 21 28 35 SE +/- 0.02, N = 3 SE +/- 0.01, N = 3 SE +/- 0.02, N = 3 SE +/- 0.03, N = 3 SE +/- 0.02, N = 3 SE +/- 0.02, N = 3 SE +/- 0.02, N = 3 SE +/- 0.02, N = 3 SE +/- 0.02, N = 3 SE +/- 0.01, N = 3 SE +/- 0.02, N = 3 SE +/- 0.01, N = 3 SE +/- 0.02, N = 3 SE +/- 0.02, N = 3 28.08 26.02 25.65 25.02 24.53 24.43 25.02 24.20 24.89 24.93 24.92 24.56 23.00 21.62
Result Confidence
OpenBenchmarking.org Seconds, Fewer Is Better Timed Apache Compilation 2.4.41 Time To Compile EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 6 12 18 24 30 Min: 28.05 / Avg: 28.08 / Max: 28.12 Min: 26.01 / Avg: 26.02 / Max: 26.03 Min: 25.6 / Avg: 25.65 / Max: 25.68 Min: 24.97 / Avg: 25.02 / Max: 25.06 Min: 24.51 / Avg: 24.53 / Max: 24.56 Min: 24.41 / Avg: 24.43 / Max: 24.46 Min: 25 / Avg: 25.02 / Max: 25.06 Min: 24.17 / Avg: 24.2 / Max: 24.23 Min: 24.85 / Avg: 24.89 / Max: 24.92 Min: 24.92 / Avg: 24.93 / Max: 24.95 Min: 24.89 / Avg: 24.92 / Max: 24.95 Min: 24.54 / Avg: 24.56 / Max: 24.58 Min: 22.98 / Avg: 23 / Max: 23.04 Min: 21.59 / Avg: 21.62 / Max: 21.66
FFTW FFTW is a C subroutine library for computing the discrete Fourier transform (DFT) in one or more dimensions. Learn more via the OpenBenchmarking.org test page.
Result
OpenBenchmarking.org Mflops, More Is Better FFTW 3.3.6 Build: Float + SSE - Size: 2D FFT Size 4096 EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 4K 8K 12K 16K 20K SE +/- 181.85, N = 3 SE +/- 167.66, N = 3 SE +/- 49.84, N = 3 SE +/- 28.18, N = 3 SE +/- 31.25, N = 3 SE +/- 33.50, N = 3 SE +/- 135.81, N = 9 SE +/- 37.78, N = 3 SE +/- 159.60, N = 7 SE +/- 142.34, N = 3 SE +/- 32.36, N = 3 SE +/- 52.30, N = 3 SE +/- 233.09, N = 3 SE +/- 146.33, N = 3 14713 16820 17559 17600 17644 17664 17308 18047 17090 17609 17681 17793 19036 19037 1. (CC) gcc options: -pthread -O3 -fomit-frame-pointer -mtune=native -malign-double -fstrict-aliasing -fno-schedule-insns -ffast-math -lm
Mflops Per Watt
OpenBenchmarking.org Mflops Per Watt, More Is Better FFTW 3.3.6 Build: Float + SSE - Size: 2D FFT Size 4096 EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 90 180 270 360 450 338.94 387.92 395.06 337.27 344.76 339.99 239.28 350.90 277.86 257.05 246.91 241.00 332.96 250.92
Result Confidence
OpenBenchmarking.org Mflops, More Is Better FFTW 3.3.6 Build: Float + SSE - Size: 2D FFT Size 4096 EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 3K 6K 9K 12K 15K Min: 14527 / Avg: 14713.33 / Max: 15077 Min: 16499 / Avg: 16820.33 / Max: 17064 Min: 17469 / Avg: 17559.33 / Max: 17641 Min: 17559 / Avg: 17600 / Max: 17654 Min: 17597 / Avg: 17643.67 / Max: 17703 Min: 17611 / Avg: 17664 / Max: 17726 Min: 16389 / Avg: 17308.33 / Max: 17615 Min: 18004 / Avg: 18046.67 / Max: 18122 Min: 16499 / Avg: 17090.14 / Max: 17664 Min: 17324 / Avg: 17608.67 / Max: 17754 Min: 17626 / Avg: 17680.67 / Max: 17738 Min: 17693 / Avg: 17792.67 / Max: 17870 Min: 18580 / Avg: 19036.33 / Max: 19347 Min: 18745 / Avg: 19037 / Max: 19200 1. (CC) gcc options: -pthread -O3 -fomit-frame-pointer -mtune=native -malign-double -fstrict-aliasing -fno-schedule-insns -ffast-math -lm
Timed MAFFT Alignment This test performs an alignment of 100 pyruvate decarboxylase sequences. Learn more via the OpenBenchmarking.org test page.
Result
OpenBenchmarking.org Seconds, Fewer Is Better Timed MAFFT Alignment 7.471 Multiple Sequence Alignment - LSU RNA EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 3 6 9 12 15 SE +/- 0.035, N = 5 SE +/- 0.023, N = 5 SE +/- 0.028, N = 5 SE +/- 0.004, N = 5 SE +/- 0.027, N = 5 SE +/- 0.030, N = 5 SE +/- 0.021, N = 5 SE +/- 0.014, N = 5 SE +/- 0.033, N = 5 SE +/- 0.037, N = 5 SE +/- 0.024, N = 5 SE +/- 0.027, N = 5 SE +/- 0.030, N = 5 SE +/- 0.037, N = 5 11.112 10.236 10.221 9.892 9.725 9.735 9.938 9.602 9.925 10.040 9.989 10.097 8.598 8.868 1. (CC) gcc options: -std=c99 -O3 -lm -lpthread
Result Confidence
OpenBenchmarking.org Seconds, Fewer Is Better Timed MAFFT Alignment 7.471 Multiple Sequence Alignment - LSU RNA EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 3 6 9 12 15 Min: 11.04 / Avg: 11.11 / Max: 11.22 Min: 10.16 / Avg: 10.24 / Max: 10.3 Min: 10.15 / Avg: 10.22 / Max: 10.32 Min: 9.88 / Avg: 9.89 / Max: 9.9 Min: 9.65 / Avg: 9.73 / Max: 9.8 Min: 9.66 / Avg: 9.74 / Max: 9.84 Min: 9.89 / Avg: 9.94 / Max: 10.01 Min: 9.57 / Avg: 9.6 / Max: 9.64 Min: 9.82 / Avg: 9.92 / Max: 10 Min: 9.91 / Avg: 10.04 / Max: 10.12 Min: 9.92 / Avg: 9.99 / Max: 10.06 Min: 10.02 / Avg: 10.1 / Max: 10.18 Min: 8.55 / Avg: 8.6 / Max: 8.69 Min: 8.78 / Avg: 8.87 / Max: 8.95 1. (CC) gcc options: -std=c99 -O3 -lm -lpthread
NCNN NCNN is a high performance neural network inference framework optimized for mobile and other platforms developed by Tencent. Learn more via the OpenBenchmarking.org test page.
Result
OpenBenchmarking.org ms, Fewer Is Better NCNN 20201218 Target: CPU - Model: yolov4-tiny EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 8 16 24 32 40 SE +/- 0.50, N = 3 SE +/- 0.61, N = 3 SE +/- 0.45, N = 3 SE +/- 0.17, N = 3 SE +/- 0.02, N = 3 SE +/- 0.33, N = 3 SE +/- 0.17, N = 11 SE +/- 0.04, N = 3 SE +/- 0.10, N = 3 SE +/- 0.06, N = 12 SE +/- 0.12, N = 9 SE +/- 0.21, N = 9 SE +/- 0.29, N = 3 SE +/- 0.28, N = 3 29.67 29.23 29.78 27.87 27.78 29.11 29.66 28.27 31.61 30.63 34.15 35.12 27.61 35.38 MIN: 28.72 / MAX: 42.97 MIN: 28.35 / MAX: 32.28 MIN: 28.36 / MAX: 108.17 MIN: 27.31 / MAX: 41.48 MIN: 27.43 / MAX: 29.51 MIN: 28.33 / MAX: 32.38 MIN: 28.65 / MAX: 167.51 MIN: 27.87 / MAX: 31.14 MIN: 30.9 / MAX: 36.86 MIN: 29.81 / MAX: 126.09 MIN: 32.54 / MAX: 132.52 MIN: 33.13 / MAX: 169.41 MIN: 26.76 / MAX: 28.5 MIN: 34.22 / MAX: 37.33 1. (CXX) g++ options: -O3 -rdynamic -lgomp -lpthread
Result Confidence
OpenBenchmarking.org ms, Fewer Is Better NCNN 20201218 Target: CPU - Model: yolov4-tiny EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 8 16 24 32 40 Min: 29 / Avg: 29.67 / Max: 30.66 Min: 28.56 / Avg: 29.23 / Max: 30.45 Min: 28.88 / Avg: 29.78 / Max: 30.25 Min: 27.62 / Avg: 27.87 / Max: 28.19 Min: 27.74 / Avg: 27.78 / Max: 27.82 Min: 28.7 / Avg: 29.11 / Max: 29.76 Min: 29.28 / Avg: 29.66 / Max: 31.16 Min: 28.2 / Avg: 28.27 / Max: 28.34 Min: 31.41 / Avg: 31.61 / Max: 31.75 Min: 30.33 / Avg: 30.63 / Max: 30.98 Min: 33.31 / Avg: 34.15 / Max: 34.59 Min: 33.91 / Avg: 35.12 / Max: 35.94 Min: 27.05 / Avg: 27.61 / Max: 28 Min: 34.83 / Avg: 35.38 / Max: 35.68 1. (CXX) g++ options: -O3 -rdynamic -lgomp -lpthread
InfluxDB This is a benchmark of the InfluxDB open-source time-series database optimized for fast, high-availability storage for IoT and other use-cases. The InfluxDB test profile makes use of InfluxDB Inch for facilitating the benchmarks. Learn more via the OpenBenchmarking.org test page.
Result
OpenBenchmarking.org val/sec, More Is Better InfluxDB 1.8.2 Concurrent Streams: 64 - Batch Size: 10000 - Tags: 2,5000,1 - Points Per Series: 10000 EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 300K 600K 900K 1200K 1500K SE +/- 1442.60, N = 3 SE +/- 1242.45, N = 3 SE +/- 1061.91, N = 3 SE +/- 1121.87, N = 3 SE +/- 2008.07, N = 3 SE +/- 702.94, N = 3 SE +/- 759.90, N = 3 SE +/- 295.02, N = 3 SE +/- 686.09, N = 3 SE +/- 1733.41, N = 3 SE +/- 762.66, N = 3 SE +/- 628.66, N = 3 SE +/- 1176.92, N = 3 SE +/- 2686.24, N = 3 1113861.3 1185857.8 1211354.3 1249264.6 1290897.8 1303437.6 1281490.5 1206497.8 1288738.6 1295588.8 1294664.5 1308517.2 1279851.8 1438050.4
val/sec Per Watt
OpenBenchmarking.org val/sec Per Watt, More Is Better InfluxDB 1.8.2 Concurrent Streams: 64 - Batch Size: 10000 - Tags: 2,5000,1 - Points Per Series: 10000 EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 4K 8K 12K 16K 20K 19958.05 19817.67 19723.37 18467.75 17743.64 17835.71 13818.71 17199.25 15448.09 13661.39 13662.86 12919.70 16288.24 13202.43
Result Confidence
OpenBenchmarking.org val/sec, More Is Better InfluxDB 1.8.2 Concurrent Streams: 64 - Batch Size: 10000 - Tags: 2,5000,1 - Points Per Series: 10000 EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 200K 400K 600K 800K 1000K Min: 1110976.3 / Avg: 1113861.27 / Max: 1115334.9 Min: 1183868.7 / Avg: 1185857.83 / Max: 1188142.2 Min: 1209909.6 / Avg: 1211354.27 / Max: 1213424.8 Min: 1247865.2 / Avg: 1249264.6 / Max: 1251483.2 Min: 1287374.1 / Avg: 1290897.83 / Max: 1294328.4 Min: 1302037.7 / Avg: 1303437.6 / Max: 1304249.7 Min: 1279979.8 / Avg: 1281490.47 / Max: 1282389.9 Min: 1205942.3 / Avg: 1206497.83 / Max: 1206947.8 Min: 1287797.7 / Avg: 1288738.57 / Max: 1290074 Min: 1293258.5 / Avg: 1295588.83 / Max: 1298976.9 Min: 1293775.5 / Avg: 1294664.5 / Max: 1296182.4 Min: 1307504.2 / Avg: 1308517.23 / Max: 1309668.7 Min: 1277678.1 / Avg: 1279851.77 / Max: 1281720.8 Min: 1433192.9 / Avg: 1438050.37 / Max: 1442466.9
Numpy Benchmark This is a test to obtain the general Numpy performance. Learn more via the OpenBenchmarking.org test page.
Result
OpenBenchmarking.org Score, More Is Better Numpy Benchmark EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 80 160 240 320 400 SE +/- 0.53, N = 3 SE +/- 0.30, N = 3 SE +/- 0.76, N = 3 SE +/- 1.35, N = 3 SE +/- 0.30, N = 3 SE +/- 0.31, N = 3 SE +/- 0.48, N = 3 SE +/- 0.40, N = 3 SE +/- 0.35, N = 3 SE +/- 0.24, N = 3 SE +/- 0.41, N = 3 SE +/- 0.70, N = 3 SE +/- 0.65, N = 3 SE +/- 0.20, N = 3 270.83 298.27 296.96 301.28 307.47 309.10 303.33 311.97 303.45 303.75 303.21 306.50 345.36 348.66
Score Per Watt
OpenBenchmarking.org Score Per Watt, More Is Better Numpy Benchmark EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 2 4 6 8 10 6.25 6.82 6.72 5.85 5.98 5.96 4.23 6.05 4.97 4.46 4.22 4.18 6.03 4.56
Result Confidence
OpenBenchmarking.org Score, More Is Better Numpy Benchmark EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 60 120 180 240 300 Min: 269.87 / Avg: 270.83 / Max: 271.69 Min: 297.91 / Avg: 298.27 / Max: 298.86 Min: 295.48 / Avg: 296.96 / Max: 298.01 Min: 298.67 / Avg: 301.28 / Max: 303.16 Min: 307 / Avg: 307.47 / Max: 308.03 Min: 308.57 / Avg: 309.1 / Max: 309.64 Min: 302.7 / Avg: 303.33 / Max: 304.28 Min: 311.24 / Avg: 311.97 / Max: 312.62 Min: 302.78 / Avg: 303.45 / Max: 303.96 Min: 303.29 / Avg: 303.75 / Max: 304.08 Min: 302.77 / Avg: 303.21 / Max: 304.03 Min: 305.69 / Avg: 306.5 / Max: 307.9 Min: 344.12 / Avg: 345.36 / Max: 346.34 Min: 348.4 / Avg: 348.66 / Max: 349.06
Apache CouchDB This is a bulk insertion benchmark of Apache CouchDB. CouchDB is a document-oriented NoSQL database implemented in Erlang. Learn more via the OpenBenchmarking.org test page.
Result
OpenBenchmarking.org Seconds, Fewer Is Better Apache CouchDB 3.1.1 Bulk Size: 100 - Inserts: 1000 - Rounds: 24 EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 20 40 60 80 100 SE +/- 0.41, N = 3 SE +/- 1.02, N = 4 SE +/- 0.89, N = 3 SE +/- 0.51, N = 3 SE +/- 0.52, N = 3 SE +/- 1.14, N = 3 SE +/- 0.64, N = 3 SE +/- 0.45, N = 3 SE +/- 0.35, N = 3 SE +/- 0.03, N = 3 SE +/- 0.34, N = 3 SE +/- 0.55, N = 3 SE +/- 0.48, N = 3 SE +/- 0.45, N = 3 107.01 92.35 87.94 89.43 86.68 86.23 91.32 86.57 92.59 91.51 97.30 97.95 93.79 83.28 1. (CXX) g++ options: -std=c++14 -lmozjs-68 -lm -lerl_interface -lei -fPIC -MMD
Result Confidence
OpenBenchmarking.org Seconds, Fewer Is Better Apache CouchDB 3.1.1 Bulk Size: 100 - Inserts: 1000 - Rounds: 24 EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 20 40 60 80 100 Min: 106.25 / Avg: 107.01 / Max: 107.66 Min: 90.47 / Avg: 92.35 / Max: 94.9 Min: 86.34 / Avg: 87.94 / Max: 89.41 Min: 88.41 / Avg: 89.43 / Max: 89.96 Min: 85.65 / Avg: 86.68 / Max: 87.25 Min: 84.36 / Avg: 86.23 / Max: 88.29 Min: 90.24 / Avg: 91.31 / Max: 92.46 Min: 86.01 / Avg: 86.57 / Max: 87.47 Min: 91.9 / Avg: 92.59 / Max: 93.05 Min: 91.47 / Avg: 91.51 / Max: 91.55 Min: 96.62 / Avg: 97.29 / Max: 97.72 Min: 96.92 / Avg: 97.95 / Max: 98.78 Min: 92.83 / Avg: 93.79 / Max: 94.31 Min: 82.43 / Avg: 83.28 / Max: 83.97 1. (CXX) g++ options: -std=c++14 -lmozjs-68 -lm -lerl_interface -lei -fPIC -MMD
DaCapo Benchmark This test runs the DaCapo Benchmarks written in Java and intended to test system/CPU performance. Learn more via the OpenBenchmarking.org test page.
Result
OpenBenchmarking.org msec, Fewer Is Better DaCapo Benchmark 9.12-MR1 Java Test: Jython EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 1200 2400 3600 4800 6000 SE +/- 49.86, N = 6 SE +/- 17.45, N = 6 SE +/- 22.94, N = 6 SE +/- 20.02, N = 6 SE +/- 17.40, N = 6 SE +/- 12.59, N = 6 SE +/- 21.30, N = 6 SE +/- 17.79, N = 6 SE +/- 9.85, N = 6 SE +/- 12.22, N = 6 SE +/- 22.61, N = 6 SE +/- 22.07, N = 7 SE +/- 11.37, N = 7 5580 5353 5280 5145 5053 4916 5070 4935 5112 5021 5012 4544 4375
Result Confidence
OpenBenchmarking.org msec, Fewer Is Better DaCapo Benchmark 9.12-MR1 Java Test: Jython EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 1000 2000 3000 4000 5000 Min: 5502 / Avg: 5579.5 / Max: 5827 Min: 5275 / Avg: 5352.5 / Max: 5392 Min: 5219 / Avg: 5279.5 / Max: 5358 Min: 5069 / Avg: 5145.33 / Max: 5205 Min: 5000 / Avg: 5053.33 / Max: 5104 Min: 4883 / Avg: 4916 / Max: 4959 Min: 5014 / Avg: 5070.17 / Max: 5141 Min: 4891 / Avg: 4934.83 / Max: 4996 Min: 5077 / Avg: 5112 / Max: 5138 Min: 4981 / Avg: 5020.83 / Max: 5072 Min: 4957 / Avg: 5011.67 / Max: 5119 Min: 4475 / Avg: 4544.29 / Max: 4659 Min: 4328 / Avg: 4374.57 / Max: 4420
WebP Image Encode This is a test of Google's libwebp with the cwebp image encode utility and using a sample 6000x4000 pixel JPEG image as the input. Learn more via the OpenBenchmarking.org test page.
Result
OpenBenchmarking.org Encode Time - Seconds, Fewer Is Better WebP Image Encode 1.1 Encode Settings: Quality 100, Lossless EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 5 10 15 20 25 SE +/- 0.03, N = 3 SE +/- 0.15, N = 3 SE +/- 0.20, N = 3 SE +/- 0.20, N = 3 SE +/- 0.09, N = 3 SE +/- 0.13, N = 3 SE +/- 0.09, N = 3 SE +/- 0.17, N = 3 SE +/- 0.09, N = 3 SE +/- 0.06, N = 3 SE +/- 0.09, N = 3 SE +/- 0.10, N = 3 SE +/- 0.10, N = 3 SE +/- 0.14, N = 3 22.45 21.27 21.38 20.87 20.50 20.29 20.86 20.10 20.85 20.86 20.90 20.39 17.70 17.67 1. (CC) gcc options: -fvisibility=hidden -O2 -pthread -lm -ljpeg -lpng16 -ltiff
Result Confidence
OpenBenchmarking.org Encode Time - Seconds, Fewer Is Better WebP Image Encode 1.1 Encode Settings: Quality 100, Lossless EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 5 10 15 20 25 Min: 22.41 / Avg: 22.45 / Max: 22.5 Min: 21.11 / Avg: 21.27 / Max: 21.58 Min: 21.02 / Avg: 21.38 / Max: 21.69 Min: 20.48 / Avg: 20.87 / Max: 21.12 Min: 20.34 / Avg: 20.5 / Max: 20.64 Min: 20.1 / Avg: 20.29 / Max: 20.55 Min: 20.71 / Avg: 20.86 / Max: 21.01 Min: 19.77 / Avg: 20.1 / Max: 20.29 Min: 20.67 / Avg: 20.85 / Max: 20.97 Min: 20.76 / Avg: 20.86 / Max: 20.97 Min: 20.76 / Avg: 20.9 / Max: 21.07 Min: 20.19 / Avg: 20.39 / Max: 20.52 Min: 17.51 / Avg: 17.7 / Max: 17.84 Min: 17.4 / Avg: 17.67 / Max: 17.81 1. (CC) gcc options: -fvisibility=hidden -O2 -pthread -lm -ljpeg -lpng16 -ltiff
PyPerformance PyPerformance is the reference Python performance benchmark suite. Learn more via the OpenBenchmarking.org test page.
Result
OpenBenchmarking.org Milliseconds, Fewer Is Better PyPerformance 1.0.0 Benchmark: python_startup EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 3 6 9 12 15 SE +/- 0.00, N = 3 SE +/- 0.00, N = 3 SE +/- 0.00, N = 3 SE +/- 0.00, N = 3 SE +/- 0.00, N = 3 SE +/- 0.00, N = 3 SE +/- 0.00, N = 3 SE +/- 0.00, N = 3 SE +/- 0.01, N = 3 SE +/- 0.01, N = 3 SE +/- 0.00, N = 3 SE +/- 0.00, N = 3 SE +/- 0.00, N = 3 SE +/- 0.00, N = 3 9.49 9.06 9.13 8.82 8.72 8.62 8.79 8.57 8.83 8.84 8.80 8.71 7.47 7.54
Result Confidence
OpenBenchmarking.org Milliseconds, Fewer Is Better PyPerformance 1.0.0 Benchmark: python_startup EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 3 6 9 12 15 Min: 9.49 / Avg: 9.49 / Max: 9.49 Min: 9.05 / Avg: 9.06 / Max: 9.06 Min: 9.12 / Avg: 9.13 / Max: 9.13 Min: 8.81 / Avg: 8.82 / Max: 8.82 Min: 8.72 / Avg: 8.72 / Max: 8.73 Min: 8.61 / Avg: 8.62 / Max: 8.62 Min: 8.78 / Avg: 8.79 / Max: 8.79 Min: 8.57 / Avg: 8.57 / Max: 8.57 Min: 8.81 / Avg: 8.83 / Max: 8.84 Min: 8.83 / Avg: 8.84 / Max: 8.85 Min: 8.8 / Avg: 8.8 / Max: 8.8 Min: 8.71 / Avg: 8.71 / Max: 8.71 Min: 7.47 / Avg: 7.47 / Max: 7.48 Min: 7.54 / Avg: 7.54 / Max: 7.55
WebP Image Encode This is a test of Google's libwebp with the cwebp image encode utility and using a sample 6000x4000 pixel JPEG image as the input. Learn more via the OpenBenchmarking.org test page.
Result
OpenBenchmarking.org Encode Time - Seconds, Fewer Is Better WebP Image Encode 1.1 Encode Settings: Quality 100, Lossless, Highest Compression EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 10 20 30 40 50 SE +/- 0.08, N = 3 SE +/- 0.06, N = 3 SE +/- 0.08, N = 3 SE +/- 0.07, N = 3 SE +/- 0.18, N = 3 SE +/- 0.04, N = 3 SE +/- 0.04, N = 3 SE +/- 0.02, N = 3 SE +/- 0.09, N = 3 SE +/- 0.09, N = 3 SE +/- 0.12, N = 3 SE +/- 0.01, N = 3 SE +/- 0.02, N = 3 SE +/- 0.07, N = 3 46.30 44.27 44.37 42.88 42.30 42.31 42.90 41.66 42.86 42.96 43.14 42.29 36.49 36.44 1. (CC) gcc options: -fvisibility=hidden -O2 -pthread -lm -ljpeg -lpng16 -ltiff
Result Confidence
OpenBenchmarking.org Encode Time - Seconds, Fewer Is Better WebP Image Encode 1.1 Encode Settings: Quality 100, Lossless, Highest Compression EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 9 18 27 36 45 Min: 46.14 / Avg: 46.3 / Max: 46.42 Min: 44.18 / Avg: 44.27 / Max: 44.39 Min: 44.26 / Avg: 44.37 / Max: 44.53 Min: 42.75 / Avg: 42.88 / Max: 42.95 Min: 42.03 / Avg: 42.3 / Max: 42.64 Min: 42.23 / Avg: 42.31 / Max: 42.35 Min: 42.83 / Avg: 42.9 / Max: 42.94 Min: 41.62 / Avg: 41.66 / Max: 41.7 Min: 42.71 / Avg: 42.86 / Max: 43.03 Min: 42.78 / Avg: 42.96 / Max: 43.08 Min: 43 / Avg: 43.13 / Max: 43.38 Min: 42.26 / Avg: 42.29 / Max: 42.3 Min: 36.45 / Avg: 36.49 / Max: 36.52 Min: 36.33 / Avg: 36.44 / Max: 36.56 1. (CC) gcc options: -fvisibility=hidden -O2 -pthread -lm -ljpeg -lpng16 -ltiff
AOM AV1 This is a simple test of the AOMedia AV1 encoder run on the CPU with a sample video file. Learn more via the OpenBenchmarking.org test page.
Result
OpenBenchmarking.org Frames Per Second, More Is Better AOM AV1 2.0 Encoder Mode: Speed 4 Two-Pass EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 0.5648 1.1296 1.6944 2.2592 2.824 SE +/- 0.00, N = 3 SE +/- 0.01, N = 3 SE +/- 0.01, N = 3 SE +/- 0.00, N = 3 SE +/- 0.00, N = 3 SE +/- 0.00, N = 3 SE +/- 0.00, N = 3 SE +/- 0.01, N = 3 SE +/- 0.00, N = 3 SE +/- 0.00, N = 3 SE +/- 0.00, N = 3 SE +/- 0.00, N = 3 SE +/- 0.01, N = 3 SE +/- 0.00, N = 3 1.98 2.05 2.08 2.14 2.19 2.20 2.15 2.22 2.16 2.12 2.16 2.17 2.38 2.51 1. (CXX) g++ options: -O3 -std=c++11 -U_FORTIFY_SOURCE -lm -lpthread
Frames Per Second Per Watt
OpenBenchmarking.org Frames Per Second Per Watt, More Is Better AOM AV1 2.0 Encoder Mode: Speed 4 Two-Pass EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 0.009 0.018 0.027 0.036 0.045 0.04 0.04 0.04 0.04 0.04 0.04 0.03 0.04 0.03 0.03 0.03 0.03 0.04 0.03
Result Confidence
OpenBenchmarking.org Frames Per Second, More Is Better AOM AV1 2.0 Encoder Mode: Speed 4 Two-Pass EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 2 4 6 8 10 Min: 1.97 / Avg: 1.98 / Max: 1.98 Min: 2.04 / Avg: 2.05 / Max: 2.06 Min: 2.07 / Avg: 2.08 / Max: 2.09 Min: 2.14 / Avg: 2.14 / Max: 2.15 Min: 2.19 / Avg: 2.19 / Max: 2.19 Min: 2.2 / Avg: 2.2 / Max: 2.2 Min: 2.14 / Avg: 2.15 / Max: 2.15 Min: 2.21 / Avg: 2.22 / Max: 2.23 Min: 2.15 / Avg: 2.16 / Max: 2.16 Min: 2.12 / Avg: 2.12 / Max: 2.13 Min: 2.15 / Avg: 2.16 / Max: 2.16 Min: 2.17 / Avg: 2.17 / Max: 2.17 Min: 2.37 / Avg: 2.38 / Max: 2.39 Min: 2.5 / Avg: 2.51 / Max: 2.51 1. (CXX) g++ options: -O3 -std=c++11 -U_FORTIFY_SOURCE -lm -lpthread
Result
OpenBenchmarking.org Frames Per Second, More Is Better AOM AV1 2.0 Encoder Mode: Speed 6 Two-Pass EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 0.8775 1.755 2.6325 3.51 4.3875 SE +/- 0.01, N = 3 SE +/- 0.01, N = 3 SE +/- 0.02, N = 3 SE +/- 0.01, N = 3 SE +/- 0.00, N = 3 SE +/- 0.01, N = 3 SE +/- 0.00, N = 3 SE +/- 0.00, N = 3 SE +/- 0.00, N = 3 SE +/- 0.01, N = 3 SE +/- 0.00, N = 3 SE +/- 0.00, N = 3 SE +/- 0.00, N = 3 SE +/- 0.01, N = 3 3.08 3.19 3.23 3.36 3.42 3.42 3.37 3.48 3.37 3.33 3.36 3.38 3.73 3.90 1. (CXX) g++ options: -O3 -std=c++11 -U_FORTIFY_SOURCE -lm -lpthread
Frames Per Second Per Watt
OpenBenchmarking.org Frames Per Second Per Watt, More Is Better AOM AV1 2.0 Encoder Mode: Speed 6 Two-Pass EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 0.0158 0.0316 0.0474 0.0632 0.079 0.07 0.07 0.07 0.06 0.06 0.06 0.05 0.06 0.05 0.05 0.05 0.04 0.06 0.05
Result Confidence
OpenBenchmarking.org Frames Per Second, More Is Better AOM AV1 2.0 Encoder Mode: Speed 6 Two-Pass EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 2 4 6 8 10 Min: 3.07 / Avg: 3.08 / Max: 3.1 Min: 3.18 / Avg: 3.19 / Max: 3.21 Min: 3.21 / Avg: 3.23 / Max: 3.27 Min: 3.33 / Avg: 3.36 / Max: 3.37 Min: 3.42 / Avg: 3.42 / Max: 3.43 Min: 3.41 / Avg: 3.42 / Max: 3.43 Min: 3.36 / Avg: 3.37 / Max: 3.37 Min: 3.48 / Avg: 3.48 / Max: 3.48 Min: 3.37 / Avg: 3.37 / Max: 3.38 Min: 3.32 / Avg: 3.33 / Max: 3.35 Min: 3.36 / Avg: 3.36 / Max: 3.36 Min: 3.38 / Avg: 3.38 / Max: 3.39 Min: 3.73 / Avg: 3.73 / Max: 3.74 Min: 3.89 / Avg: 3.9 / Max: 3.91 1. (CXX) g++ options: -O3 -std=c++11 -U_FORTIFY_SOURCE -lm -lpthread
JPEG XL The JPEG XL Image Coding System is designed to provide next-generation JPEG image capabilities with JPEG XL offering better image quality and compression over legacy JPEG. This test profile is currently focused on the multi-threaded JPEG XL image encode performance. Learn more via the OpenBenchmarking.org test page.
AOM AV1 This is a simple test of the AOMedia AV1 encoder run on the CPU with a sample video file. Learn more via the OpenBenchmarking.org test page.
Result
OpenBenchmarking.org Frames Per Second, More Is Better AOM AV1 2.0 Encoder Mode: Speed 6 Realtime EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 5 10 15 20 25 SE +/- 0.05, N = 3 SE +/- 0.05, N = 3 SE +/- 0.07, N = 3 SE +/- 0.16, N = 3 SE +/- 0.07, N = 3 SE +/- 0.04, N = 3 SE +/- 0.03, N = 3 SE +/- 0.02, N = 3 SE +/- 0.02, N = 3 SE +/- 0.02, N = 3 SE +/- 0.01, N = 3 SE +/- 0.01, N = 3 SE +/- 0.03, N = 3 SE +/- 0.02, N = 3 17.30 17.83 18.92 19.11 19.88 19.97 19.51 20.19 19.63 19.48 19.59 19.84 20.22 21.76 1. (CXX) g++ options: -O3 -std=c++11 -U_FORTIFY_SOURCE -lm -lpthread
Frames Per Second Per Watt
OpenBenchmarking.org Frames Per Second Per Watt, More Is Better AOM AV1 2.0 Encoder Mode: Speed 6 Realtime EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 0.072 0.144 0.216 0.288 0.36 0.31 0.31 0.32 0.29 0.29 0.30 0.23 0.30 0.26 0.23 0.23 0.22 0.26 0.21
Result Confidence
OpenBenchmarking.org Frames Per Second, More Is Better AOM AV1 2.0 Encoder Mode: Speed 6 Realtime EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 5 10 15 20 25 Min: 17.21 / Avg: 17.3 / Max: 17.37 Min: 17.77 / Avg: 17.83 / Max: 17.92 Min: 18.8 / Avg: 18.92 / Max: 19.03 Min: 18.83 / Avg: 19.11 / Max: 19.38 Min: 19.75 / Avg: 19.88 / Max: 19.97 Min: 19.9 / Avg: 19.97 / Max: 20.03 Min: 19.46 / Avg: 19.51 / Max: 19.57 Min: 20.17 / Avg: 20.19 / Max: 20.22 Min: 19.61 / Avg: 19.63 / Max: 19.66 Min: 19.45 / Avg: 19.48 / Max: 19.52 Min: 19.58 / Avg: 19.59 / Max: 19.6 Min: 19.82 / Avg: 19.84 / Max: 19.86 Min: 20.16 / Avg: 20.22 / Max: 20.28 Min: 21.73 / Avg: 21.76 / Max: 21.79 1. (CXX) g++ options: -O3 -std=c++11 -U_FORTIFY_SOURCE -lm -lpthread
Timed Eigen Compilation This test times how long it takes to build all Eigen examples. The Eigen examples are compiled serially. Eigen is a C++ template library for linear algebra. Learn more via the OpenBenchmarking.org test page.
Result
OpenBenchmarking.org Seconds, Fewer Is Better Timed Eigen Compilation 3.3.9 Time To Compile EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 20 40 60 80 100 SE +/- 0.03, N = 3 SE +/- 0.04, N = 3 SE +/- 0.02, N = 3 SE +/- 0.03, N = 3 SE +/- 0.05, N = 3 SE +/- 0.01, N = 3 SE +/- 0.00, N = 3 SE +/- 0.03, N = 3 SE +/- 0.01, N = 3 SE +/- 0.03, N = 3 SE +/- 0.02, N = 3 SE +/- 0.05, N = 3 SE +/- 0.02, N = 3 SE +/- 0.02, N = 3 103.98 99.84 99.92 97.20 94.84 95.81 97.37 94.97 97.22 97.99 97.55 96.09 83.50 83.02
Result Confidence
OpenBenchmarking.org Seconds, Fewer Is Better Timed Eigen Compilation 3.3.9 Time To Compile EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 20 40 60 80 100 Min: 103.94 / Avg: 103.98 / Max: 104.04 Min: 99.78 / Avg: 99.84 / Max: 99.91 Min: 99.9 / Avg: 99.92 / Max: 99.96 Min: 97.15 / Avg: 97.2 / Max: 97.27 Min: 94.73 / Avg: 94.83 / Max: 94.91 Min: 95.78 / Avg: 95.81 / Max: 95.83 Min: 97.37 / Avg: 97.37 / Max: 97.38 Min: 94.92 / Avg: 94.97 / Max: 95.02 Min: 97.2 / Avg: 97.22 / Max: 97.24 Min: 97.94 / Avg: 97.99 / Max: 98.06 Min: 97.52 / Avg: 97.55 / Max: 97.6 Min: 96 / Avg: 96.09 / Max: 96.18 Min: 83.48 / Avg: 83.5 / Max: 83.55 Min: 82.99 / Avg: 83.02 / Max: 83.06
Darmstadt Automotive Parallel Heterogeneous Suite DAPHNE is the Darmstadt Automotive Parallel HeterogeNEous Benchmark Suite with OpenCL / CUDA / OpenMP test cases for these automotive benchmarks for evaluating programming models in context to vehicle autonomous driving capabilities. Learn more via the OpenBenchmarking.org test page.
Result
OpenBenchmarking.org Test Cases Per Minute, More Is Better Darmstadt Automotive Parallel Heterogeneous Suite Backend: OpenMP - Kernel: NDT Mapping EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 200 400 600 800 1000 SE +/- 1.85, N = 3 SE +/- 3.25, N = 3 SE +/- 3.07, N = 3 SE +/- 1.97, N = 3 SE +/- 2.49, N = 3 SE +/- 3.41, N = 3 SE +/- 1.89, N = 3 SE +/- 3.23, N = 3 SE +/- 3.34, N = 3 SE +/- 1.66, N = 3 SE +/- 7.17, N = 3 SE +/- 3.26, N = 3 SE +/- 2.91, N = 3 SE +/- 5.28, N = 3 861.07 864.62 858.54 898.21 899.45 898.84 895.33 908.46 895.52 903.30 897.59 861.35 967.37 773.86 1. (CXX) g++ options: -O3 -std=c++11 -fopenmp
Test Cases Per Minute Per Watt
OpenBenchmarking.org Test Cases Per Minute Per Watt, More Is Better Darmstadt Automotive Parallel Heterogeneous Suite Backend: OpenMP - Kernel: NDT Mapping EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 5 10 15 20 25 19.69 19.36 18.48 16.79 16.53 16.03 11.94 16.61 13.37 12.13 11.61 10.75 16.68 9.53
Result Confidence
OpenBenchmarking.org Test Cases Per Minute, More Is Better Darmstadt Automotive Parallel Heterogeneous Suite Backend: OpenMP - Kernel: NDT Mapping EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 200 400 600 800 1000 Min: 857.36 / Avg: 861.07 / Max: 863.04 Min: 858.29 / Avg: 864.62 / Max: 869.06 Min: 852.55 / Avg: 858.54 / Max: 862.73 Min: 894.42 / Avg: 898.21 / Max: 901.07 Min: 895.16 / Avg: 899.45 / Max: 903.77 Min: 892.02 / Avg: 898.84 / Max: 902.4 Min: 892.13 / Avg: 895.33 / Max: 898.66 Min: 902.91 / Avg: 908.46 / Max: 914.1 Min: 888.84 / Avg: 895.52 / Max: 899.09 Min: 900.01 / Avg: 903.3 / Max: 905.33 Min: 885.88 / Avg: 897.59 / Max: 910.61 Min: 854.83 / Avg: 861.35 / Max: 864.7 Min: 961.58 / Avg: 967.37 / Max: 970.7 Min: 763.33 / Avg: 773.86 / Max: 779.83 1. (CXX) g++ options: -O3 -std=c++11 -fopenmp
librsvg RSVG/librsvg is an SVG vector graphics library. This test profile times how long it takes to complete various operations by rsvg-convert. Learn more via the OpenBenchmarking.org test page.
Result
OpenBenchmarking.org Seconds, Fewer Is Better librsvg Operation: SVG Files To PNG EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 6 12 18 24 30 SE +/- 0.04, N = 3 SE +/- 0.09, N = 3 SE +/- 0.04, N = 3 SE +/- 0.07, N = 3 SE +/- 0.09, N = 3 SE +/- 0.06, N = 3 SE +/- 0.06, N = 3 SE +/- 0.07, N = 3 SE +/- 0.05, N = 3 SE +/- 0.06, N = 3 SE +/- 0.03, N = 3 SE +/- 0.04, N = 3 SE +/- 0.05, N = 3 25.02 24.09 24.46 23.78 23.66 23.65 24.09 23.35 24.53 24.73 24.34 20.03 20.48 1. rsvg-convert version 2.48.9
Result Confidence
OpenBenchmarking.org Seconds, Fewer Is Better librsvg Operation: SVG Files To PNG EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 6 12 18 24 30 Min: 24.97 / Avg: 25.02 / Max: 25.1 Min: 23.94 / Avg: 24.09 / Max: 24.24 Min: 24.41 / Avg: 24.46 / Max: 24.53 Min: 23.65 / Avg: 23.78 / Max: 23.89 Min: 23.49 / Avg: 23.66 / Max: 23.78 Min: 23.57 / Avg: 23.65 / Max: 23.77 Min: 24 / Avg: 24.09 / Max: 24.2 Min: 23.26 / Avg: 23.35 / Max: 23.49 Min: 24.43 / Avg: 24.53 / Max: 24.6 Min: 24.63 / Avg: 24.73 / Max: 24.84 Min: 24.29 / Avg: 24.34 / Max: 24.4 Min: 19.96 / Avg: 20.03 / Max: 20.1 Min: 20.42 / Avg: 20.48 / Max: 20.58 1. rsvg-convert version 2.48.9
simdjson This is a benchmark of SIMDJSON, a high performance JSON parser. SIMDJSON aims to be the fastest JSON parser and is used by projects like Microsoft FishStore, Yandex ClickHouse, Shopify, and others. Learn more via the OpenBenchmarking.org test page.
Result
OpenBenchmarking.org GB/s, More Is Better simdjson 0.7.1 Throughput Test: PartialTweets EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 0.1395 0.279 0.4185 0.558 0.6975 SE +/- 0.01, N = 3 SE +/- 0.01, N = 3 SE +/- 0.01, N = 3 SE +/- 0.00, N = 3 SE +/- 0.00, N = 3 SE +/- 0.00, N = 3 SE +/- 0.00, N = 3 SE +/- 0.01, N = 3 SE +/- 0.00, N = 3 SE +/- 0.00, N = 3 SE +/- 0.00, N = 3 SE +/- 0.00, N = 3 SE +/- 0.00, N = 3 SE +/- 0.00, N = 3 0.50 0.50 0.50 0.52 0.53 0.52 0.51 0.53 0.52 0.52 0.52 0.52 0.62 0.61 1. (CXX) g++ options: -O3 -pthread
GB/s Per Watt
OpenBenchmarking.org GB/s Per Watt, More Is Better simdjson 0.7.1 Throughput Test: PartialTweets EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 0.0023 0.0046 0.0069 0.0092 0.0115 0.01 0.01 0.01 0.01 0.01 0.01 0.01 0.01 0.01 0.01 0.01 0.01 0.01 0.01
Result Confidence
OpenBenchmarking.org GB/s, More Is Better simdjson 0.7.1 Throughput Test: PartialTweets EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 2 4 6 8 10 Min: 0.49 / Avg: 0.5 / Max: 0.51 Min: 0.49 / Avg: 0.5 / Max: 0.51 Min: 0.49 / Avg: 0.5 / Max: 0.51 Min: 0.52 / Avg: 0.52 / Max: 0.52 Min: 0.52 / Avg: 0.53 / Max: 0.53 Min: 0.52 / Avg: 0.52 / Max: 0.53 Min: 0.51 / Avg: 0.51 / Max: 0.52 Min: 0.52 / Avg: 0.53 / Max: 0.54 Min: 0.51 / Avg: 0.52 / Max: 0.52 Min: 0.51 / Avg: 0.52 / Max: 0.52 Min: 0.51 / Avg: 0.52 / Max: 0.52 Min: 0.52 / Avg: 0.52 / Max: 0.53 Min: 0.62 / Avg: 0.62 / Max: 0.62 Min: 0.61 / Avg: 0.61 / Max: 0.62 1. (CXX) g++ options: -O3 -pthread
PyPerformance PyPerformance is the reference Python performance benchmark suite. Learn more via the OpenBenchmarking.org test page.
Result
OpenBenchmarking.org Milliseconds, Fewer Is Better PyPerformance 1.0.0 Benchmark: pathlib EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 5 10 15 20 25 SE +/- 0.00, N = 3 SE +/- 0.03, N = 3 SE +/- 0.03, N = 3 SE +/- 0.03, N = 3 SE +/- 0.03, N = 3 SE +/- 0.00, N = 3 SE +/- 0.03, N = 3 SE +/- 0.03, N = 3 SE +/- 0.00, N = 3 SE +/- 0.00, N = 3 SE +/- 0.03, N = 3 SE +/- 0.00, N = 3 SE +/- 0.00, N = 3 SE +/- 0.00, N = 3 21.1 21.0 21.3 20.4 20.2 19.9 20.4 19.9 20.5 20.5 20.5 20.2 17.2 17.5
Result Confidence
OpenBenchmarking.org Milliseconds, Fewer Is Better PyPerformance 1.0.0 Benchmark: pathlib EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 5 10 15 20 25 Min: 21.1 / Avg: 21.1 / Max: 21.1 Min: 20.9 / Avg: 20.97 / Max: 21 Min: 21.2 / Avg: 21.27 / Max: 21.3 Min: 20.4 / Avg: 20.43 / Max: 20.5 Min: 20.2 / Avg: 20.23 / Max: 20.3 Min: 19.9 / Avg: 19.9 / Max: 19.9 Min: 20.4 / Avg: 20.43 / Max: 20.5 Min: 19.8 / Avg: 19.87 / Max: 19.9 Min: 20.5 / Avg: 20.5 / Max: 20.5 Min: 20.5 / Avg: 20.5 / Max: 20.5 Min: 20.5 / Avg: 20.53 / Max: 20.6 Min: 20.2 / Avg: 20.2 / Max: 20.2 Min: 17.2 / Avg: 17.2 / Max: 17.2 Min: 17.5 / Avg: 17.5 / Max: 17.5
Crafty This is a performance test of Crafty, an advanced open-source chess engine. Learn more via the OpenBenchmarking.org test page.
Result
OpenBenchmarking.org Nodes Per Second, More Is Better Crafty 25.2 Elapsed Time EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 2M 4M 6M 8M 10M SE +/- 8448.82, N = 3 SE +/- 4235.69, N = 3 SE +/- 18409.69, N = 3 SE +/- 16881.14, N = 3 SE +/- 5954.89, N = 3 SE +/- 2921.91, N = 3 SE +/- 8887.25, N = 3 SE +/- 15198.80, N = 3 SE +/- 15133.11, N = 3 SE +/- 6430.53, N = 3 SE +/- 4763.31, N = 3 SE +/- 9056.97, N = 3 SE +/- 3201.01, N = 3 6414609 6551351 6547690 6787692 6880760 6804305 6545211 6983945 6674881 6753902 6899948 7939883 7940047 1. (CC) gcc options: -pthread -lstdc++ -fprofile-use -lm
Nodes Per Second Per Watt
OpenBenchmarking.org Nodes Per Second Per Watt, More Is Better Crafty 25.2 Elapsed Time EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 30K 60K 90K 120K 150K 158031.23 159454.66 156016.10 139072.47 142769.17 139718.79 97701.58 144587.96 116329.09 100655.93 99938.47 150336.84 114628.80
Result Confidence
OpenBenchmarking.org Nodes Per Second, More Is Better Crafty 25.2 Elapsed Time EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 1.4M 2.8M 4.2M 5.6M 7M Min: 6399116 / Avg: 6414609 / Max: 6428197 Min: 6543694 / Avg: 6551351.33 / Max: 6558318 Min: 6524614 / Avg: 6547690 / Max: 6584075 Min: 6763111 / Avg: 6787691.67 / Max: 6820026 Min: 6872751 / Avg: 6880759.67 / Max: 6892398 Min: 6798906 / Avg: 6804305.33 / Max: 6808941 Min: 6532471 / Avg: 6545211 / Max: 6562315 Min: 6962515 / Avg: 6983944.67 / Max: 7013330 Min: 6646698 / Avg: 6674880.67 / Max: 6698529 Min: 6743220 / Avg: 6753902.33 / Max: 6765446 Min: 6892591 / Avg: 6899948 / Max: 6908868 Min: 7924088 / Avg: 7939883 / Max: 7955460 Min: 7934298 / Avg: 7940047 / Max: 7945361 1. (CC) gcc options: -pthread -lstdc++ -fprofile-use -lm
simdjson This is a benchmark of SIMDJSON, a high performance JSON parser. SIMDJSON aims to be the fastest JSON parser and is used by projects like Microsoft FishStore, Yandex ClickHouse, Shopify, and others. Learn more via the OpenBenchmarking.org test page.
Result
OpenBenchmarking.org GB/s, More Is Better simdjson 0.7.1 Throughput Test: DistinctUserID EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 0.1418 0.2836 0.4254 0.5672 0.709 SE +/- 0.00, N = 3 SE +/- 0.00, N = 3 SE +/- 0.00, N = 3 SE +/- 0.00, N = 3 SE +/- 0.00, N = 3 SE +/- 0.00, N = 3 SE +/- 0.00, N = 3 SE +/- 0.00, N = 3 SE +/- 0.00, N = 3 SE +/- 0.00, N = 3 SE +/- 0.00, N = 3 SE +/- 0.00, N = 3 SE +/- 0.00, N = 3 SE +/- 0.01, N = 3 0.52 0.51 0.51 0.53 0.53 0.53 0.52 0.54 0.52 0.52 0.53 0.54 0.63 0.62 1. (CXX) g++ options: -O3 -pthread
GB/s Per Watt
OpenBenchmarking.org GB/s Per Watt, More Is Better simdjson 0.7.1 Throughput Test: DistinctUserID EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 0.0023 0.0046 0.0069 0.0092 0.0115 0.01 0.01 0.01 0.01 0.01 0.01 0.01 0.01 0.01 0.01 0.01 0.01 0.01 0.01
Result Confidence
OpenBenchmarking.org GB/s, More Is Better simdjson 0.7.1 Throughput Test: DistinctUserID EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 2 4 6 8 10 Min: 0.51 / Avg: 0.52 / Max: 0.52 Min: 0.51 / Avg: 0.51 / Max: 0.52 Min: 0.51 / Avg: 0.51 / Max: 0.52 Min: 0.53 / Avg: 0.53 / Max: 0.53 Min: 0.53 / Avg: 0.53 / Max: 0.54 Min: 0.53 / Avg: 0.53 / Max: 0.54 Min: 0.52 / Avg: 0.52 / Max: 0.53 Min: 0.54 / Avg: 0.54 / Max: 0.55 Min: 0.52 / Avg: 0.52 / Max: 0.53 Min: 0.52 / Avg: 0.52 / Max: 0.53 Min: 0.52 / Avg: 0.53 / Max: 0.53 Min: 0.53 / Avg: 0.54 / Max: 0.54 Min: 0.62 / Avg: 0.63 / Max: 0.63 Min: 0.61 / Avg: 0.62 / Max: 0.63 1. (CXX) g++ options: -O3 -pthread
LZ4 Compression This test measures the time needed to compress/decompress a sample file (an Ubuntu ISO) using LZ4 compression. Learn more via the OpenBenchmarking.org test page.
Result
OpenBenchmarking.org MB/s, More Is Better LZ4 Compression 1.9.3 Compression Level: 9 - Compression Speed EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 12 24 36 48 60 SE +/- 0.44, N = 5 SE +/- 0.61, N = 3 SE +/- 0.13, N = 3 SE +/- 0.42, N = 3 SE +/- 0.34, N = 3 SE +/- 0.39, N = 3 SE +/- 0.02, N = 3 SE +/- 0.28, N = 3 SE +/- 0.48, N = 5 SE +/- 0.42, N = 3 SE +/- 0.30, N = 14 SE +/- 0.36, N = 15 SE +/- 0.42, N = 3 43.17 42.94 42.25 43.98 45.09 44.68 43.69 45.13 44.49 44.80 44.54 51.95 52.02 1. (CC) gcc options: -O3
Result Confidence
OpenBenchmarking.org MB/s, More Is Better LZ4 Compression 1.9.3 Compression Level: 9 - Compression Speed EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 10 20 30 40 50 Min: 42.2 / Avg: 43.17 / Max: 44.21 Min: 42.28 / Avg: 42.94 / Max: 44.16 Min: 42.11 / Avg: 42.25 / Max: 42.52 Min: 43.51 / Avg: 43.98 / Max: 44.82 Min: 44.42 / Avg: 45.09 / Max: 45.46 Min: 44.24 / Avg: 44.68 / Max: 45.45 Min: 43.65 / Avg: 43.69 / Max: 43.71 Min: 44.77 / Avg: 45.13 / Max: 45.69 Min: 43.45 / Avg: 44.49 / Max: 45.67 Min: 44.34 / Avg: 44.8 / Max: 45.63 Min: 42.74 / Avg: 44.54 / Max: 46.27 Min: 49.68 / Avg: 51.95 / Max: 54.03 Min: 51.53 / Avg: 52.02 / Max: 52.86 1. (CC) gcc options: -O3
Radiance Benchmark This is a benchmark of NREL Radiance, a synthetic imaging system that is open-source and developed by the Lawrence Berkeley National Laboratory in California. Learn more via the OpenBenchmarking.org test page.
OpenBenchmarking.org Seconds, Fewer Is Better Radiance Benchmark 5.0 Test: SMP Parallel EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 50 100 150 200 250 226.64 223.38 224.52 218.14 217.55 215.16 217.33 214.26 217.90 218.42 219.26 214.77 184.74 184.49
Minion Minion is an open-source constraint solver that is designed to be very scalable. This test profile uses Minion's integrated benchmarking problems to solve. Learn more via the OpenBenchmarking.org test page.
Result
OpenBenchmarking.org Seconds, Fewer Is Better Minion 1.8 Benchmark: Graceful EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 12 24 36 48 60 SE +/- 0.06, N = 3 SE +/- 0.12, N = 3 SE +/- 0.08, N = 3 SE +/- 0.02, N = 3 SE +/- 0.00, N = 3 SE +/- 0.12, N = 3 SE +/- 0.06, N = 3 SE +/- 0.06, N = 3 SE +/- 0.11, N = 3 SE +/- 0.06, N = 3 SE +/- 0.07, N = 3 SE +/- 0.04, N = 3 SE +/- 0.07, N = 3 SE +/- 0.06, N = 3 55.08 54.63 54.76 52.93 52.30 52.34 53.18 51.62 53.29 53.20 53.07 52.35 44.92 44.84 1. (CXX) g++ options: -std=gnu++11 -O3 -fomit-frame-pointer -rdynamic
Result Confidence
OpenBenchmarking.org Seconds, Fewer Is Better Minion 1.8 Benchmark: Graceful EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 11 22 33 44 55 Min: 54.97 / Avg: 55.08 / Max: 55.19 Min: 54.4 / Avg: 54.63 / Max: 54.76 Min: 54.61 / Avg: 54.76 / Max: 54.89 Min: 52.9 / Avg: 52.93 / Max: 52.97 Min: 52.29 / Avg: 52.3 / Max: 52.3 Min: 52.19 / Avg: 52.34 / Max: 52.57 Min: 53.07 / Avg: 53.18 / Max: 53.26 Min: 51.51 / Avg: 51.62 / Max: 51.69 Min: 53.08 / Avg: 53.29 / Max: 53.44 Min: 53.13 / Avg: 53.2 / Max: 53.31 Min: 52.97 / Avg: 53.07 / Max: 53.19 Min: 52.3 / Avg: 52.35 / Max: 52.43 Min: 44.81 / Avg: 44.92 / Max: 45.04 Min: 44.76 / Avg: 44.84 / Max: 44.96 1. (CXX) g++ options: -std=gnu++11 -O3 -fomit-frame-pointer -rdynamic
Dolfyn Dolfyn is a Computational Fluid Dynamics (CFD) code of modern numerical simulation techniques. The Dolfyn test profile measures the execution time of the bundled computational fluid dynamics demos that are bundled with Dolfyn. Learn more via the OpenBenchmarking.org test page.
Result
OpenBenchmarking.org Seconds, Fewer Is Better Dolfyn 0.527 Computational Fluid Dynamics EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 5 10 15 20 25 SE +/- 0.03, N = 3 SE +/- 0.01, N = 3 SE +/- 0.05, N = 3 SE +/- 0.07, N = 3 SE +/- 0.01, N = 3 SE +/- 0.00, N = 3 SE +/- 0.04, N = 3 SE +/- 0.02, N = 3 SE +/- 0.01, N = 3 SE +/- 0.01, N = 3 SE +/- 0.01, N = 3 SE +/- 0.02, N = 3 SE +/- 0.02, N = 3 SE +/- 0.04, N = 3 21.55 21.39 21.42 20.79 20.48 20.69 20.79 20.11 20.81 20.74 20.78 20.56 17.56 17.60
Result Confidence
OpenBenchmarking.org Seconds, Fewer Is Better Dolfyn 0.527 Computational Fluid Dynamics EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 5 10 15 20 25 Min: 21.5 / Avg: 21.55 / Max: 21.61 Min: 21.37 / Avg: 21.39 / Max: 21.42 Min: 21.35 / Avg: 21.42 / Max: 21.51 Min: 20.67 / Avg: 20.79 / Max: 20.9 Min: 20.46 / Avg: 20.48 / Max: 20.5 Min: 20.68 / Avg: 20.69 / Max: 20.7 Min: 20.71 / Avg: 20.79 / Max: 20.84 Min: 20.1 / Avg: 20.11 / Max: 20.15 Min: 20.79 / Avg: 20.81 / Max: 20.83 Min: 20.73 / Avg: 20.74 / Max: 20.77 Min: 20.77 / Avg: 20.78 / Max: 20.8 Min: 20.54 / Avg: 20.56 / Max: 20.59 Min: 17.53 / Avg: 17.56 / Max: 17.6 Min: 17.53 / Avg: 17.6 / Max: 17.67
Gcrypt Library Libgcrypt is a general purpose cryptographic library developed as part of the GnuPG project. This is a benchmark of libgcrypt's integrated benchmark and is measuring the time to run the benchmark command with a cipher/mac/hash repetition count set for 50 times as simple, high level look at the overall crypto performance of the system under test. Learn more via the OpenBenchmarking.org test page.
Result
OpenBenchmarking.org Seconds, Fewer Is Better Gcrypt Library 1.9 EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 60 120 180 240 300 SE +/- 0.64, N = 3 SE +/- 0.37, N = 3 SE +/- 0.34, N = 3 SE +/- 0.38, N = 3 SE +/- 1.43, N = 3 SE +/- 1.03, N = 3 SE +/- 0.48, N = 3 SE +/- 0.52, N = 3 SE +/- 0.57, N = 3 SE +/- 1.00, N = 3 SE +/- 0.81, N = 3 SE +/- 0.70, N = 3 SE +/- 0.09, N = 3 SE +/- 0.11, N = 3 273.02 273.20 274.30 268.68 262.91 262.12 264.68 257.57 264.99 265.92 265.19 261.45 223.71 223.75 1. (CC) gcc options: -O2 -fvisibility=hidden
Result Confidence
OpenBenchmarking.org Seconds, Fewer Is Better Gcrypt Library 1.9 EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 50 100 150 200 250 Min: 271.81 / Avg: 273.02 / Max: 274.01 Min: 272.5 / Avg: 273.19 / Max: 273.74 Min: 273.81 / Avg: 274.3 / Max: 274.96 Min: 267.92 / Avg: 268.68 / Max: 269.11 Min: 261.48 / Avg: 262.91 / Max: 265.77 Min: 260.44 / Avg: 262.12 / Max: 264 Min: 263.89 / Avg: 264.68 / Max: 265.54 Min: 256.94 / Avg: 257.57 / Max: 258.61 Min: 264.26 / Avg: 264.98 / Max: 266.12 Min: 264.29 / Avg: 265.92 / Max: 267.74 Min: 263.73 / Avg: 265.19 / Max: 266.52 Min: 260.68 / Avg: 261.45 / Max: 262.85 Min: 223.61 / Avg: 223.71 / Max: 223.89 Min: 223.6 / Avg: 223.75 / Max: 223.97 1. (CC) gcc options: -O2 -fvisibility=hidden
Scikit-Learn Scikit-learn is a Python module for machine learning Learn more via the OpenBenchmarking.org test page.
Result
OpenBenchmarking.org Seconds, Fewer Is Better Scikit-Learn 0.22.1 EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 3 6 9 12 15 SE +/- 0.168, N = 15 SE +/- 0.007, N = 5 SE +/- 0.010, N = 5 SE +/- 0.012, N = 5 SE +/- 0.006, N = 5 SE +/- 0.003, N = 5 SE +/- 0.004, N = 5 SE +/- 0.158, N = 15 SE +/- 0.009, N = 5 SE +/- 0.016, N = 5 SE +/- 0.006, N = 5 SE +/- 0.051, N = 5 SE +/- 0.004, N = 5 SE +/- 0.031, N = 5 11.327 10.746 10.539 10.281 10.154 10.083 10.325 10.074 10.358 10.337 10.130 10.131 9.293 9.240
Result Confidence
OpenBenchmarking.org Seconds, Fewer Is Better Scikit-Learn 0.22.1 EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 3 6 9 12 15 Min: 11.13 / Avg: 11.33 / Max: 13.67 Min: 10.72 / Avg: 10.75 / Max: 10.76 Min: 10.52 / Avg: 10.54 / Max: 10.57 Min: 10.25 / Avg: 10.28 / Max: 10.32 Min: 10.13 / Avg: 10.15 / Max: 10.17 Min: 10.08 / Avg: 10.08 / Max: 10.09 Min: 10.32 / Avg: 10.33 / Max: 10.34 Min: 9.88 / Avg: 10.07 / Max: 12.28 Min: 10.34 / Avg: 10.36 / Max: 10.39 Min: 10.28 / Avg: 10.34 / Max: 10.37 Min: 10.11 / Avg: 10.13 / Max: 10.14 Min: 10.04 / Avg: 10.13 / Max: 10.33 Min: 9.28 / Avg: 9.29 / Max: 9.3 Min: 9.14 / Avg: 9.24 / Max: 9.33
simdjson This is a benchmark of SIMDJSON, a high performance JSON parser. SIMDJSON aims to be the fastest JSON parser and is used by projects like Microsoft FishStore, Yandex ClickHouse, Shopify, and others. Learn more via the OpenBenchmarking.org test page.
Result
OpenBenchmarking.org GB/s, More Is Better simdjson 0.7.1 Throughput Test: LargeRandom EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 0.0855 0.171 0.2565 0.342 0.4275 SE +/- 0.00, N = 3 SE +/- 0.00, N = 3 SE +/- 0.00, N = 3 SE +/- 0.00, N = 3 SE +/- 0.00, N = 3 SE +/- 0.00, N = 3 SE +/- 0.00, N = 3 SE +/- 0.00, N = 3 SE +/- 0.00, N = 3 SE +/- 0.00, N = 3 SE +/- 0.00, N = 3 SE +/- 0.00, N = 3 SE +/- 0.00, N = 3 SE +/- 0.00, N = 3 0.31 0.32 0.32 0.33 0.33 0.33 0.32 0.33 0.32 0.32 0.32 0.33 0.38 0.38 1. (CXX) g++ options: -O3 -pthread
GB/s Per Watt
OpenBenchmarking.org GB/s Per Watt, More Is Better simdjson 0.7.1 Throughput Test: LargeRandom EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 0.0023 0.0046 0.0069 0.0092 0.0115 0.01 0.01 0.01 0.01 0.01 0.01 0.01 0.01 0.01 0.01
Result Confidence
OpenBenchmarking.org GB/s, More Is Better simdjson 0.7.1 Throughput Test: LargeRandom EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 1 2 3 4 5 Min: 0.31 / Avg: 0.31 / Max: 0.31 Min: 0.31 / Avg: 0.32 / Max: 0.32 Min: 0.31 / Avg: 0.32 / Max: 0.32 Min: 0.32 / Avg: 0.33 / Max: 0.33 Min: 0.33 / Avg: 0.33 / Max: 0.33 Min: 0.33 / Avg: 0.33 / Max: 0.33 Min: 0.32 / Avg: 0.32 / Max: 0.32 Min: 0.33 / Avg: 0.33 / Max: 0.34 Min: 0.32 / Avg: 0.32 / Max: 0.33 Min: 0.32 / Avg: 0.32 / Max: 0.33 Min: 0.32 / Avg: 0.32 / Max: 0.33 Min: 0.33 / Avg: 0.33 / Max: 0.33 Min: 0.38 / Avg: 0.38 / Max: 0.39 Min: 0.38 / Avg: 0.38 / Max: 0.38 1. (CXX) g++ options: -O3 -pthread
SQLite Speedtest This is a benchmark of SQLite's speedtest1 benchmark program with an increased problem size of 1,000. Learn more via the OpenBenchmarking.org test page.
Result
OpenBenchmarking.org Seconds, Fewer Is Better SQLite Speedtest 3.30 Timed Time - Size 1,000 EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 20 40 60 80 100 SE +/- 0.25, N = 3 SE +/- 0.06, N = 3 SE +/- 0.18, N = 3 SE +/- 0.05, N = 3 SE +/- 0.54, N = 3 SE +/- 0.36, N = 3 SE +/- 0.27, N = 3 SE +/- 0.19, N = 3 SE +/- 0.06, N = 3 SE +/- 0.11, N = 3 SE +/- 0.11, N = 3 SE +/- 0.04, N = 3 SE +/- 0.06, N = 3 SE +/- 0.10, N = 3 81.51 80.19 80.05 77.74 75.91 77.19 78.07 76.16 78.26 78.23 77.94 77.61 67.30 66.52 1. (CC) gcc options: -O2 -ldl -lz -lpthread
Result Confidence
OpenBenchmarking.org Seconds, Fewer Is Better SQLite Speedtest 3.30 Timed Time - Size 1,000 EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 16 32 48 64 80 Min: 81.25 / Avg: 81.51 / Max: 82.01 Min: 80.11 / Avg: 80.19 / Max: 80.3 Min: 79.76 / Avg: 80.05 / Max: 80.38 Min: 77.69 / Avg: 77.74 / Max: 77.85 Min: 74.83 / Avg: 75.9 / Max: 76.53 Min: 76.8 / Avg: 77.18 / Max: 77.9 Min: 77.69 / Avg: 78.06 / Max: 78.59 Min: 75.89 / Avg: 76.16 / Max: 76.52 Min: 78.14 / Avg: 78.26 / Max: 78.37 Min: 78.09 / Avg: 78.23 / Max: 78.45 Min: 77.74 / Avg: 77.94 / Max: 78.1 Min: 77.55 / Avg: 77.61 / Max: 77.67 Min: 67.2 / Avg: 67.3 / Max: 67.4 Min: 66.35 / Avg: 66.52 / Max: 66.7 1. (CC) gcc options: -O2 -ldl -lz -lpthread
WebP Image Encode This is a test of Google's libwebp with the cwebp image encode utility and using a sample 6000x4000 pixel JPEG image as the input. Learn more via the OpenBenchmarking.org test page.
Result
OpenBenchmarking.org Encode Time - Seconds, Fewer Is Better WebP Image Encode 1.1 Encode Settings: Quality 100, Highest Compression EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 3 6 9 12 15 SE +/- 0.004, N = 5 SE +/- 0.009, N = 5 SE +/- 0.025, N = 5 SE +/- 0.009, N = 5 SE +/- 0.014, N = 5 SE +/- 0.025, N = 5 SE +/- 0.005, N = 5 SE +/- 0.004, N = 5 SE +/- 0.001, N = 5 SE +/- 0.009, N = 5 SE +/- 0.025, N = 5 SE +/- 0.005, N = 5 SE +/- 0.010, N = 6 SE +/- 0.003, N = 6 9.414 9.419 9.481 9.151 9.014 9.014 9.140 8.861 9.126 9.145 9.154 9.003 7.745 7.739 1. (CC) gcc options: -fvisibility=hidden -O2 -pthread -lm -ljpeg -lpng16 -ltiff
Result Confidence
OpenBenchmarking.org Encode Time - Seconds, Fewer Is Better WebP Image Encode 1.1 Encode Settings: Quality 100, Highest Compression EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 3 6 9 12 15 Min: 9.4 / Avg: 9.41 / Max: 9.42 Min: 9.41 / Avg: 9.42 / Max: 9.46 Min: 9.43 / Avg: 9.48 / Max: 9.58 Min: 9.12 / Avg: 9.15 / Max: 9.17 Min: 8.99 / Avg: 9.01 / Max: 9.06 Min: 8.98 / Avg: 9.01 / Max: 9.12 Min: 9.13 / Avg: 9.14 / Max: 9.15 Min: 8.85 / Avg: 8.86 / Max: 8.87 Min: 9.12 / Avg: 9.13 / Max: 9.13 Min: 9.13 / Avg: 9.14 / Max: 9.17 Min: 9.12 / Avg: 9.15 / Max: 9.25 Min: 8.99 / Avg: 9 / Max: 9.02 Min: 7.72 / Avg: 7.74 / Max: 7.79 Min: 7.73 / Avg: 7.74 / Max: 7.75 1. (CC) gcc options: -fvisibility=hidden -O2 -pthread -lm -ljpeg -lpng16 -ltiff
TNN TNN is an open-source deep learning reasoning framework developed by Tencent. Learn more via the OpenBenchmarking.org test page.
Result
OpenBenchmarking.org ms, Fewer Is Better TNN 0.2.3 Target: CPU - Model: MobileNet v2 EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 80 160 240 320 400 SE +/- 0.14, N = 3 SE +/- 0.22, N = 3 SE +/- 0.21, N = 3 SE +/- 0.94, N = 3 SE +/- 0.03, N = 3 SE +/- 0.72, N = 3 SE +/- 0.88, N = 3 SE +/- 0.10, N = 3 SE +/- 0.46, N = 3 SE +/- 0.40, N = 3 SE +/- 0.29, N = 3 SE +/- 0.62, N = 3 SE +/- 0.35, N = 3 SE +/- 0.41, N = 3 347.18 347.77 350.76 339.05 336.66 336.89 344.25 333.28 344.33 341.93 342.47 333.30 286.43 288.47 MIN: 343.85 / MAX: 356.42 MIN: 345.44 / MAX: 366.04 MIN: 346.27 / MAX: 363.67 MIN: 335.68 / MAX: 355.89 MIN: 333.97 / MAX: 348.51 MIN: 332.6 / MAX: 347.08 MIN: 339.59 / MAX: 367.05 MIN: 329.87 / MAX: 349.8 MIN: 340.96 / MAX: 358.42 MIN: 337.09 / MAX: 359.76 MIN: 338.7 / MAX: 360.58 MIN: 330.49 / MAX: 343.73 MIN: 283.81 / MAX: 294.29 MIN: 285.34 / MAX: 304.15 1. (CXX) g++ options: -fopenmp -pthread -fvisibility=hidden -O3 -rdynamic -ldl
Result Confidence
OpenBenchmarking.org ms, Fewer Is Better TNN 0.2.3 Target: CPU - Model: MobileNet v2 EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 60 120 180 240 300 Min: 347.01 / Avg: 347.18 / Max: 347.46 Min: 347.4 / Avg: 347.77 / Max: 348.16 Min: 350.35 / Avg: 350.76 / Max: 351.03 Min: 337.77 / Avg: 339.05 / Max: 340.89 Min: 336.61 / Avg: 336.66 / Max: 336.68 Min: 335.5 / Avg: 336.89 / Max: 337.88 Min: 342.92 / Avg: 344.25 / Max: 345.93 Min: 333.14 / Avg: 333.28 / Max: 333.46 Min: 343.4 / Avg: 344.33 / Max: 344.79 Min: 341.17 / Avg: 341.93 / Max: 342.54 Min: 342 / Avg: 342.47 / Max: 343.01 Min: 332.62 / Avg: 333.3 / Max: 334.54 Min: 285.73 / Avg: 286.43 / Max: 286.81 Min: 287.8 / Avg: 288.47 / Max: 289.23 1. (CXX) g++ options: -fopenmp -pthread -fvisibility=hidden -O3 -rdynamic -ldl
Crypto++ Crypto++ is a C++ class library of cryptographic algorithms. Learn more via the OpenBenchmarking.org test page.
Result
OpenBenchmarking.org MiB/second, More Is Better Crypto++ 8.2 Test: Integer + Elliptic Curve Public Key Algorithms EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 1000 2000 3000 4000 5000 SE +/- 5.48, N = 3 SE +/- 1.24, N = 3 SE +/- 2.72, N = 3 SE +/- 1.09, N = 3 SE +/- 2.96, N = 3 SE +/- 4.11, N = 3 SE +/- 3.97, N = 3 SE +/- 5.67, N = 3 SE +/- 2.54, N = 3 SE +/- 3.12, N = 3 SE +/- 2.07, N = 3 SE +/- 5.35, N = 3 SE +/- 2.49, N = 3 SE +/- 3.14, N = 3 3949.44 3965.03 3949.00 4086.08 4151.29 4139.98 4089.12 4207.91 4085.53 4072.76 4091.78 4152.60 4835.02 4834.05 1. (CXX) g++ options: -g2 -O3 -fPIC -pthread -pipe
MiB/second Per Watt
OpenBenchmarking.org MiB/second Per Watt, More Is Better Crypto++ 8.2 Test: Integer + Elliptic Curve Public Key Algorithms EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 20 40 60 80 100 94.07 93.36 91.59 81.20 82.69 81.90 57.18 83.94 68.50 61.08 58.12 57.63 87.24 64.14
Result Confidence
OpenBenchmarking.org MiB/second, More Is Better Crypto++ 8.2 Test: Integer + Elliptic Curve Public Key Algorithms EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 800 1600 2400 3200 4000 Min: 3939.83 / Avg: 3949.44 / Max: 3958.81 Min: 3963.31 / Avg: 3965.03 / Max: 3967.43 Min: 3943.6 / Avg: 3949 / Max: 3952.3 Min: 4084.12 / Avg: 4086.08 / Max: 4087.91 Min: 4145.43 / Avg: 4151.29 / Max: 4154.96 Min: 4132.23 / Avg: 4139.98 / Max: 4146.24 Min: 4081.58 / Avg: 4089.12 / Max: 4095.03 Min: 4199.27 / Avg: 4207.91 / Max: 4218.6 Min: 4080.99 / Avg: 4085.53 / Max: 4089.76 Min: 4068.43 / Avg: 4072.76 / Max: 4078.81 Min: 4087.91 / Avg: 4091.78 / Max: 4095.01 Min: 4142.26 / Avg: 4152.6 / Max: 4160.14 Min: 4830.71 / Avg: 4835.02 / Max: 4839.34 Min: 4828.11 / Avg: 4834.05 / Max: 4838.82 1. (CXX) g++ options: -g2 -O3 -fPIC -pthread -pipe
PyBench This test profile reports the total time of the different average timed test results from PyBench. PyBench reports average test times for different functions such as BuiltinFunctionCalls and NestedForLoops, with this total result providing a rough estimate as to Python's average performance on a given system. This test profile runs PyBench each time for 20 rounds. Learn more via the OpenBenchmarking.org test page.
Result
OpenBenchmarking.org Milliseconds, Fewer Is Better PyBench 2018-02-16 Total For Average Test Times EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 300 600 900 1200 1500 SE +/- 9.68, N = 3 SE +/- 8.01, N = 3 SE +/- 1.86, N = 3 SE +/- 1.20, N = 3 SE +/- 10.82, N = 3 SE +/- 7.33, N = 3 SE +/- 1.20, N = 3 SE +/- 9.35, N = 3 SE +/- 7.55, N = 3 SE +/- 9.54, N = 3 SE +/- 6.84, N = 3 SE +/- 8.33, N = 3 SE +/- 5.46, N = 3 1213 1208 1221 1172 1159 1173 1180 1137 1178 1184 1184 1166 998 999
Result Confidence
OpenBenchmarking.org Milliseconds, Fewer Is Better PyBench 2018-02-16 Total For Average Test Times EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 200 400 600 800 1000 Min: 1202 / Avg: 1212.67 / Max: 1232 Min: 1209 / Avg: 1220.67 / Max: 1236 Min: 1168 / Avg: 1171.67 / Max: 1174 Min: 1157 / Avg: 1159.33 / Max: 1161 Min: 1152 / Avg: 1173 / Max: 1188 Min: 1173 / Avg: 1180.33 / Max: 1195 Min: 1135 / Avg: 1137.33 / Max: 1139 Min: 1168 / Avg: 1178.33 / Max: 1197 Min: 1175 / Avg: 1184 / Max: 1199 Min: 1165 / Avg: 1184 / Max: 1195 Min: 1159 / Avg: 1166.33 / Max: 1180 Min: 990 / Avg: 998.33 / Max: 1015 Min: 992 / Avg: 999.33 / Max: 1010
Crypto++ Crypto++ is a C++ class library of cryptographic algorithms. Learn more via the OpenBenchmarking.org test page.
Result
OpenBenchmarking.org MiB/second, More Is Better Crypto++ 8.2 Test: Keyed Algorithms EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 140 280 420 560 700 SE +/- 0.59, N = 3 SE +/- 0.07, N = 3 SE +/- 0.21, N = 3 SE +/- 0.13, N = 3 SE +/- 0.56, N = 3 SE +/- 0.31, N = 3 SE +/- 0.27, N = 3 SE +/- 0.77, N = 3 SE +/- 0.13, N = 3 SE +/- 0.31, N = 3 SE +/- 0.63, N = 3 SE +/- 0.06, N = 3 SE +/- 0.29, N = 3 SE +/- 0.14, N = 3 513.65 514.85 513.60 530.36 538.09 539.17 531.14 546.72 530.80 529.60 529.62 539.45 627.44 628.21 1. (CXX) g++ options: -g2 -O3 -fPIC -pthread -pipe
MiB/second Per Watt
OpenBenchmarking.org MiB/second Per Watt, More Is Better Crypto++ 8.2 Test: Keyed Algorithms EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 3 6 9 12 15 12.39 12.28 12.03 10.63 10.84 10.78 7.57 11.01 9.00 7.98 7.58 7.54 11.44 8.43
Result Confidence
OpenBenchmarking.org MiB/second, More Is Better Crypto++ 8.2 Test: Keyed Algorithms EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 110 220 330 440 550 Min: 512.6 / Avg: 513.65 / Max: 514.65 Min: 514.7 / Avg: 514.85 / Max: 514.94 Min: 513.18 / Avg: 513.6 / Max: 513.82 Min: 530.22 / Avg: 530.36 / Max: 530.61 Min: 537.38 / Avg: 538.09 / Max: 539.19 Min: 538.79 / Avg: 539.17 / Max: 539.79 Min: 530.69 / Avg: 531.14 / Max: 531.61 Min: 545.3 / Avg: 546.72 / Max: 547.95 Min: 530.54 / Avg: 530.8 / Max: 530.93 Min: 528.99 / Avg: 529.6 / Max: 530.03 Min: 528.75 / Avg: 529.62 / Max: 530.84 Min: 539.37 / Avg: 539.45 / Max: 539.56 Min: 627.02 / Avg: 627.44 / Max: 627.99 Min: 628.01 / Avg: 628.21 / Max: 628.49 1. (CXX) g++ options: -g2 -O3 -fPIC -pthread -pipe
FinanceBench FinanceBench is a collection of financial program benchmarks with support for benchmarking on the GPU via OpenCL and CPU benchmarking with OpenMP. The FinanceBench test cases are focused on Black-Sholes-Merton Process with Analytic European Option engine, QMC (Sobol) Monte-Carlo method (Equity Option Example), Bonds Fixed-rate bond with flat forward curve, and Repo Securities repurchase agreement. FinanceBench was originally written by the Cavazos Lab at University of Delaware. Learn more via the OpenBenchmarking.org test page.
Result
OpenBenchmarking.org ms, Fewer Is Better FinanceBench 2016-07-25 Benchmark: Repo OpenMP EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 11K 22K 33K 44K 55K SE +/- 275.73, N = 3 SE +/- 108.67, N = 3 SE +/- 109.50, N = 3 SE +/- 383.79, N = 3 SE +/- 17.38, N = 3 SE +/- 71.59, N = 3 SE +/- 133.22, N = 3 SE +/- 84.26, N = 3 SE +/- 241.95, N = 3 SE +/- 71.36, N = 3 SE +/- 45.54, N = 3 SE +/- 107.65, N = 3 SE +/- 174.69, N = 3 53237.68 52936.98 52977.60 51629.10 50474.70 50609.04 51428.89 50076.27 51630.50 51437.79 51015.87 43548.63 43527.28 1. (CXX) g++ options: -O3 -march=native -fopenmp
Result Confidence
OpenBenchmarking.org ms, Fewer Is Better FinanceBench 2016-07-25 Benchmark: Repo OpenMP EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 9K 18K 27K 36K 45K Min: 52860.58 / Avg: 53237.68 / Max: 53774.7 Min: 52784.59 / Avg: 52936.98 / Max: 53147.39 Min: 52852.14 / Avg: 52977.6 / Max: 53195.79 Min: 51241.3 / Avg: 51629.1 / Max: 52396.66 Min: 50450.23 / Avg: 50474.7 / Max: 50508.32 Min: 50528.84 / Avg: 50609.04 / Max: 50751.85 Min: 51271.63 / Avg: 51428.89 / Max: 51693.79 Min: 49985.34 / Avg: 50076.27 / Max: 50244.61 Min: 51347.45 / Avg: 51630.5 / Max: 52111.92 Min: 51363.7 / Avg: 51437.79 / Max: 51580.48 Min: 50939.99 / Avg: 51015.87 / Max: 51097.43 Min: 43343.38 / Avg: 43548.63 / Max: 43707.56 Min: 43324.05 / Avg: 43527.28 / Max: 43875.02 1. (CXX) g++ options: -O3 -march=native -fopenmp
Minion Minion is an open-source constraint solver that is designed to be very scalable. This test profile uses Minion's integrated benchmarking problems to solve. Learn more via the OpenBenchmarking.org test page.
Result
OpenBenchmarking.org Seconds, Fewer Is Better Minion 1.8 Benchmark: Quasigroup EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 30 60 90 120 150 SE +/- 0.50, N = 3 SE +/- 0.38, N = 3 SE +/- 0.80, N = 3 SE +/- 0.37, N = 3 SE +/- 0.44, N = 3 SE +/- 0.46, N = 3 SE +/- 0.37, N = 3 SE +/- 0.55, N = 3 SE +/- 0.31, N = 3 SE +/- 0.18, N = 3 SE +/- 0.28, N = 3 SE +/- 0.49, N = 3 SE +/- 0.39, N = 3 SE +/- 0.12, N = 3 140.53 140.43 140.13 136.52 133.73 133.23 135.33 132.23 136.07 135.09 135.90 134.93 114.95 114.91 1. (CXX) g++ options: -std=gnu++11 -O3 -fomit-frame-pointer -rdynamic
Result Confidence
OpenBenchmarking.org Seconds, Fewer Is Better Minion 1.8 Benchmark: Quasigroup EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 30 60 90 120 150 Min: 139.78 / Avg: 140.53 / Max: 141.47 Min: 139.94 / Avg: 140.43 / Max: 141.19 Min: 138.59 / Avg: 140.13 / Max: 141.26 Min: 135.79 / Avg: 136.52 / Max: 136.95 Min: 133.03 / Avg: 133.73 / Max: 134.55 Min: 132.34 / Avg: 133.23 / Max: 133.85 Min: 134.6 / Avg: 135.33 / Max: 135.75 Min: 131.17 / Avg: 132.23 / Max: 133 Min: 135.55 / Avg: 136.07 / Max: 136.63 Min: 134.86 / Avg: 135.09 / Max: 135.44 Min: 135.39 / Avg: 135.9 / Max: 136.37 Min: 133.97 / Avg: 134.93 / Max: 135.63 Min: 114.45 / Avg: 114.95 / Max: 115.72 Min: 114.67 / Avg: 114.91 / Max: 115.06 1. (CXX) g++ options: -std=gnu++11 -O3 -fomit-frame-pointer -rdynamic
Botan Botan is a cross-platform open-source C++ crypto library that supports most all publicly known cryptographic algorithms. Learn more via the OpenBenchmarking.org test page.
Result
OpenBenchmarking.org MiB/s, More Is Better Botan 2.13.0 Test: Blowfish EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 90 180 270 360 450 SE +/- 0.13, N = 3 SE +/- 0.16, N = 3 SE +/- 0.25, N = 3 SE +/- 0.15, N = 3 SE +/- 0.40, N = 3 SE +/- 0.14, N = 3 SE +/- 0.13, N = 3 SE +/- 0.10, N = 3 SE +/- 0.10, N = 3 SE +/- 0.20, N = 3 SE +/- 0.16, N = 3 SE +/- 0.16, N = 3 SE +/- 0.15, N = 3 SE +/- 0.07, N = 3 352.29 352.07 351.14 362.20 368.38 368.69 363.10 374.52 363.50 361.80 362.99 368.93 429.41 429.14 1. (CXX) g++ options: -fstack-protector -m64 -pthread -lbotan-2 -ldl -lrt
MiB/s Per Watt
OpenBenchmarking.org MiB/s Per Watt, More Is Better Botan 2.13.0 Test: Blowfish EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 3 6 9 12 15 8.96 8.88 8.62 7.70 7.92 7.85 5.52 8.01 6.50 5.83 5.51 5.49 8.25 6.21
Result Confidence
OpenBenchmarking.org MiB/s, More Is Better Botan 2.13.0 Test: Blowfish EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 80 160 240 320 400 Min: 352.1 / Avg: 352.29 / Max: 352.53 Min: 351.75 / Avg: 352.07 / Max: 352.26 Min: 350.66 / Avg: 351.14 / Max: 351.45 Min: 362.03 / Avg: 362.2 / Max: 362.49 Min: 367.96 / Avg: 368.38 / Max: 369.17 Min: 368.54 / Avg: 368.69 / Max: 368.97 Min: 362.85 / Avg: 363.1 / Max: 363.25 Min: 374.32 / Avg: 374.52 / Max: 374.67 Min: 363.36 / Avg: 363.5 / Max: 363.69 Min: 361.43 / Avg: 361.8 / Max: 362.1 Min: 362.68 / Avg: 362.99 / Max: 363.15 Min: 368.71 / Avg: 368.93 / Max: 369.25 Min: 429.18 / Avg: 429.41 / Max: 429.7 Min: 429.06 / Avg: 429.14 / Max: 429.27 1. (CXX) g++ options: -fstack-protector -m64 -pthread -lbotan-2 -ldl -lrt
Minion Minion is an open-source constraint solver that is designed to be very scalable. This test profile uses Minion's integrated benchmarking problems to solve. Learn more via the OpenBenchmarking.org test page.
Result
OpenBenchmarking.org Seconds, Fewer Is Better Minion 1.8 Benchmark: Solitaire EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 20 40 60 80 100 SE +/- 0.13, N = 3 SE +/- 0.19, N = 3 SE +/- 0.33, N = 3 SE +/- 0.11, N = 3 SE +/- 0.10, N = 3 SE +/- 0.02, N = 3 SE +/- 0.17, N = 3 SE +/- 0.07, N = 3 SE +/- 0.09, N = 3 SE +/- 0.32, N = 3 SE +/- 0.07, N = 3 SE +/- 0.14, N = 3 SE +/- 0.23, N = 3 SE +/- 0.11, N = 3 82.84 81.97 82.15 80.33 79.03 79.00 79.85 77.80 80.15 79.72 80.12 79.39 67.80 67.74 1. (CXX) g++ options: -std=gnu++11 -O3 -fomit-frame-pointer -rdynamic
Result Confidence
OpenBenchmarking.org Seconds, Fewer Is Better Minion 1.8 Benchmark: Solitaire EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 16 32 48 64 80 Min: 82.61 / Avg: 82.84 / Max: 83.06 Min: 81.59 / Avg: 81.97 / Max: 82.16 Min: 81.53 / Avg: 82.15 / Max: 82.68 Min: 80.18 / Avg: 80.33 / Max: 80.55 Min: 78.84 / Avg: 79.03 / Max: 79.18 Min: 78.98 / Avg: 79 / Max: 79.03 Min: 79.51 / Avg: 79.85 / Max: 80.03 Min: 77.68 / Avg: 77.8 / Max: 77.93 Min: 80.03 / Avg: 80.15 / Max: 80.32 Min: 79.1 / Avg: 79.72 / Max: 80.13 Min: 80.05 / Avg: 80.12 / Max: 80.26 Min: 79.2 / Avg: 79.39 / Max: 79.66 Min: 67.36 / Avg: 67.8 / Max: 68.07 Min: 67.63 / Avg: 67.74 / Max: 67.95 1. (CXX) g++ options: -std=gnu++11 -O3 -fomit-frame-pointer -rdynamic
Hierarchical INTegration This test runs the U.S. Department of Energy's Ames Laboratory Hierarchical INTegration (HINT) benchmark. Learn more via the OpenBenchmarking.org test page.
Result
OpenBenchmarking.org QUIPs, More Is Better Hierarchical INTegration 1.0 Test: FLOAT EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 70M 140M 210M 280M 350M SE +/- 333820.85, N = 3 SE +/- 380619.49, N = 3 SE +/- 38644.36, N = 3 SE +/- 206566.86, N = 3 SE +/- 465752.47, N = 3 SE +/- 131222.60, N = 3 SE +/- 12833.10, N = 3 SE +/- 40543.01, N = 3 SE +/- 234513.76, N = 3 SE +/- 136985.64, N = 3 SE +/- 320354.97, N = 3 SE +/- 60046.42, N = 3 SE +/- 33906.80, N = 3 284332324.15 284710986.66 283588722.34 292597759.78 297827555.09 297816529.28 293437386.11 302406827.18 293216264.80 293169027.15 297478250.43 346733990.00 346505619.64 1. (CC) gcc options: -O3 -march=native -lm
QUIPs Per Watt
OpenBenchmarking.org QUIPs Per Watt, More Is Better Hierarchical INTegration 1.0 Test: FLOAT EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 1.5M 3M 4.5M 6M 7.5M 6962207.10 6892716.30 6710210.44 5937216.36 6095028.20 6028009.87 4210427.87 6161220.61 5029503.05 4208867.42 4189997.27 6400547.89 4710525.85
Result Confidence
OpenBenchmarking.org QUIPs, More Is Better Hierarchical INTegration 1.0 Test: FLOAT EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 60M 120M 180M 240M 300M Min: 283664869.62 / Avg: 284332324.15 / Max: 284679741.15 Min: 284060087.32 / Avg: 284710986.66 / Max: 285378285.89 Min: 283512887.38 / Avg: 283588722.34 / Max: 283639560.88 Min: 292233343.29 / Avg: 292597759.78 / Max: 292948520.88 Min: 297325728.53 / Avg: 297827555.09 / Max: 298758103.32 Min: 297554997.89 / Avg: 297816529.28 / Max: 297966245.2 Min: 293416576.95 / Avg: 293437386.11 / Max: 293460802.19 Min: 302325902.16 / Avg: 302406827.18 / Max: 302451712.79 Min: 292759126.74 / Avg: 293216264.8 / Max: 293535711.28 Min: 292897063.96 / Avg: 293169027.15 / Max: 293333683.01 Min: 296837585.98 / Avg: 297478250.43 / Max: 297805193.98 Min: 346619184.22 / Avg: 346733990 / Max: 346821912.43 Min: 346439918.8 / Avg: 346505619.64 / Max: 346553015.3 1. (CC) gcc options: -O3 -march=native -lm
Botan Botan is a cross-platform open-source C++ crypto library that supports most all publicly known cryptographic algorithms. Learn more via the OpenBenchmarking.org test page.
Result
OpenBenchmarking.org MiB/s, More Is Better Botan 2.13.0 Test: Twofish EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 80 160 240 320 400 SE +/- 0.10, N = 3 SE +/- 0.07, N = 3 SE +/- 0.10, N = 3 SE +/- 0.11, N = 3 SE +/- 0.18, N = 3 SE +/- 0.04, N = 3 SE +/- 0.03, N = 3 SE +/- 0.37, N = 3 SE +/- 0.05, N = 3 SE +/- 0.05, N = 3 SE +/- 0.08, N = 3 SE +/- 0.04, N = 3 SE +/- 0.08, N = 3 SE +/- 0.04, N = 3 288.70 288.62 287.93 297.65 302.12 302.25 297.71 306.62 297.10 296.91 297.81 302.14 351.99 351.63 1. (CXX) g++ options: -fstack-protector -m64 -pthread -lbotan-2 -ldl -lrt
MiB/s Per Watt
OpenBenchmarking.org MiB/s Per Watt, More Is Better Botan 2.13.0 Test: Twofish EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 2 4 6 8 10 7.37 7.30 7.11 6.28 6.50 6.42 4.57 6.60 5.41 4.77 4.53 4.50 6.82 5.10
Result Confidence
OpenBenchmarking.org MiB/s, More Is Better Botan 2.13.0 Test: Twofish EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 60 120 180 240 300 Min: 288.49 / Avg: 288.7 / Max: 288.83 Min: 288.49 / Avg: 288.62 / Max: 288.69 Min: 287.77 / Avg: 287.93 / Max: 288.1 Min: 297.5 / Avg: 297.65 / Max: 297.86 Min: 301.76 / Avg: 302.12 / Max: 302.35 Min: 302.19 / Avg: 302.25 / Max: 302.32 Min: 297.66 / Avg: 297.7 / Max: 297.77 Min: 305.88 / Avg: 306.62 / Max: 307 Min: 297.02 / Avg: 297.1 / Max: 297.2 Min: 296.81 / Avg: 296.91 / Max: 296.96 Min: 297.64 / Avg: 297.81 / Max: 297.92 Min: 302.1 / Avg: 302.14 / Max: 302.21 Min: 351.85 / Avg: 351.99 / Max: 352.11 Min: 351.56 / Avg: 351.63 / Max: 351.71 1. (CXX) g++ options: -fstack-protector -m64 -pthread -lbotan-2 -ldl -lrt
Google SynthMark SynthMark is a cross platform tool for benchmarking CPU performance under a variety of real-time audio workloads. It uses a polyphonic synthesizer model to provide standardized tests for latency, jitter and computational throughput. Learn more via the OpenBenchmarking.org test page.
Result
OpenBenchmarking.org Voices, More Is Better Google SynthMark 20201109 Test: VoiceMark_100 EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 160 320 480 640 800 SE +/- 0.27, N = 3 SE +/- 0.12, N = 3 SE +/- 0.36, N = 3 SE +/- 0.13, N = 3 SE +/- 0.32, N = 3 SE +/- 0.11, N = 3 SE +/- 0.46, N = 3 SE +/- 0.70, N = 3 SE +/- 0.70, N = 3 SE +/- 0.57, N = 3 SE +/- 0.57, N = 3 SE +/- 0.17, N = 3 SE +/- 0.59, N = 3 608.61 608.05 605.83 627.74 636.43 637.38 627.06 645.87 626.57 624.73 635.92 740.58 739.72 1. (CXX) g++ options: -lm -lpthread -std=c++11 -Ofast
Voices Per Watt
OpenBenchmarking.org Voices Per Watt, More Is Better Google SynthMark 20201109 Test: VoiceMark_100 EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 4 8 12 16 20 15.47 15.33 14.84 13.11 13.61 13.51 9.49 13.83 11.25 9.48 9.49 14.59 10.89
Result Confidence
OpenBenchmarking.org Voices, More Is Better Google SynthMark 20201109 Test: VoiceMark_100 EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 130 260 390 520 650 Min: 608.15 / Avg: 608.61 / Max: 609.07 Min: 607.84 / Avg: 608.05 / Max: 608.27 Min: 605.12 / Avg: 605.82 / Max: 606.33 Min: 627.49 / Avg: 627.74 / Max: 627.91 Min: 635.86 / Avg: 636.43 / Max: 636.98 Min: 637.17 / Avg: 637.38 / Max: 637.55 Min: 626.15 / Avg: 627.06 / Max: 627.62 Min: 644.48 / Avg: 645.87 / Max: 646.66 Min: 625.29 / Avg: 626.57 / Max: 627.72 Min: 623.79 / Avg: 624.73 / Max: 625.77 Min: 634.78 / Avg: 635.92 / Max: 636.53 Min: 740.39 / Avg: 740.58 / Max: 740.92 Min: 738.56 / Avg: 739.72 / Max: 740.43 1. (CXX) g++ options: -lm -lpthread -std=c++11 -Ofast
FFTW FFTW is a C subroutine library for computing the discrete Fourier transform (DFT) in one or more dimensions. Learn more via the OpenBenchmarking.org test page.
Result
OpenBenchmarking.org Mflops, More Is Better FFTW 3.3.6 Build: Float + SSE - Size: 1D FFT Size 4096 EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 11K 22K 33K 44K 55K SE +/- 369.07, N = 6 SE +/- 304.76, N = 6 SE +/- 244.70, N = 6 SE +/- 385.00, N = 7 SE +/- 343.41, N = 6 SE +/- 288.40, N = 6 SE +/- 312.60, N = 6 SE +/- 307.98, N = 6 SE +/- 152.42, N = 6 SE +/- 392.71, N = 6 SE +/- 399.17, N = 6 SE +/- 126.64, N = 6 SE +/- 204.79, N = 6 SE +/- 131.48, N = 6 41704 41912 42375 42761 43414 43903 43275 43936 43404 42836 42730 44328 50675 50969 1. (CC) gcc options: -pthread -O3 -fomit-frame-pointer -mtune=native -malign-double -fstrict-aliasing -fno-schedule-insns -ffast-math -lm
Mflops Per Watt
OpenBenchmarking.org Mflops Per Watt, More Is Better FFTW 3.3.6 Build: Float + SSE - Size: 1D FFT Size 4096 EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 200 400 600 800 1000 1123.76 1109.61 1101.31 963.62 988.44 984.98 709.62 1000.27 820.23 736.70 683.14 696.81 1037.75 775.34
Result Confidence
OpenBenchmarking.org Mflops, More Is Better FFTW 3.3.6 Build: Float + SSE - Size: 1D FFT Size 4096 EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 9K 18K 27K 36K 45K Min: 40672 / Avg: 41703.5 / Max: 42890 Min: 40544 / Avg: 41912 / Max: 42672 Min: 41289 / Avg: 42374.5 / Max: 42923 Min: 40864 / Avg: 42761.14 / Max: 44031 Min: 42288 / Avg: 43414 / Max: 44416 Min: 42938 / Avg: 43902.83 / Max: 44700 Min: 41954 / Avg: 43274.83 / Max: 44008 Min: 43041 / Avg: 43936.17 / Max: 44903 Min: 42872 / Avg: 43404.33 / Max: 43831 Min: 41412 / Avg: 42836.17 / Max: 44004 Min: 40860 / Avg: 42729.67 / Max: 43619 Min: 43820 / Avg: 44328.17 / Max: 44688 Min: 49987 / Avg: 50674.5 / Max: 51435 Min: 50577 / Avg: 50968.83 / Max: 51456 1. (CC) gcc options: -pthread -O3 -fomit-frame-pointer -mtune=native -malign-double -fstrict-aliasing -fno-schedule-insns -ffast-math -lm
PyPerformance PyPerformance is the reference Python performance benchmark suite. Learn more via the OpenBenchmarking.org test page.
Result
OpenBenchmarking.org Milliseconds, Fewer Is Better PyPerformance 1.0.0 Benchmark: django_template EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 13 26 39 52 65 SE +/- 0.40, N = 3 SE +/- 0.15, N = 3 SE +/- 0.27, N = 3 SE +/- 0.44, N = 3 SE +/- 0.03, N = 3 SE +/- 0.37, N = 3 SE +/- 0.26, N = 3 SE +/- 0.22, N = 3 SE +/- 0.52, N = 3 SE +/- 0.37, N = 3 SE +/- 0.19, N = 3 SE +/- 0.09, N = 3 SE +/- 0.45, N = 3 SE +/- 0.23, N = 3 59.5 60.0 59.1 57.6 57.2 56.9 58.3 56.7 58.1 58.4 58.6 57.5 49.1 50.4
Result Confidence
OpenBenchmarking.org Milliseconds, Fewer Is Better PyPerformance 1.0.0 Benchmark: django_template EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 12 24 36 48 60 Min: 58.7 / Avg: 59.5 / Max: 59.9 Min: 59.8 / Avg: 60.03 / Max: 60.3 Min: 58.6 / Avg: 59.13 / Max: 59.4 Min: 56.8 / Avg: 57.63 / Max: 58.3 Min: 57.2 / Avg: 57.23 / Max: 57.3 Min: 56.2 / Avg: 56.93 / Max: 57.4 Min: 57.8 / Avg: 58.27 / Max: 58.7 Min: 56.4 / Avg: 56.67 / Max: 57.1 Min: 57.2 / Avg: 58.1 / Max: 59 Min: 57.9 / Avg: 58.37 / Max: 59.1 Min: 58.2 / Avg: 58.57 / Max: 58.8 Min: 57.3 / Avg: 57.47 / Max: 57.6 Min: 48.2 / Avg: 49.07 / Max: 49.7 Min: 50.2 / Avg: 50.43 / Max: 50.9
FinanceBench FinanceBench is a collection of financial program benchmarks with support for benchmarking on the GPU via OpenCL and CPU benchmarking with OpenMP. The FinanceBench test cases are focused on Black-Sholes-Merton Process with Analytic European Option engine, QMC (Sobol) Monte-Carlo method (Equity Option Example), Bonds Fixed-rate bond with flat forward curve, and Repo Securities repurchase agreement. FinanceBench was originally written by the Cavazos Lab at University of Delaware. Learn more via the OpenBenchmarking.org test page.
Result
OpenBenchmarking.org ms, Fewer Is Better FinanceBench 2016-07-25 Benchmark: Bonds OpenMP EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 20K 40K 60K 80K 100K SE +/- 200.17, N = 3 SE +/- 203.38, N = 3 SE +/- 402.31, N = 3 SE +/- 461.99, N = 3 SE +/- 397.99, N = 3 SE +/- 294.03, N = 3 SE +/- 287.97, N = 3 SE +/- 26.41, N = 3 SE +/- 75.52, N = 3 SE +/- 966.88, N = 3 SE +/- 232.73, N = 3 SE +/- 185.79, N = 3 SE +/- 395.61, N = 3 92426.49 92387.25 92896.62 89863.26 88634.31 88487.57 90157.28 86946.61 90310.90 90672.45 88553.78 76027.98 76410.11 1. (CXX) g++ options: -O3 -march=native -fopenmp
Result Confidence
OpenBenchmarking.org ms, Fewer Is Better FinanceBench 2016-07-25 Benchmark: Bonds OpenMP EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 16K 32K 48K 64K 80K Min: 92207.57 / Avg: 92426.49 / Max: 92826.23 Min: 92154.74 / Avg: 92387.25 / Max: 92792.54 Min: 92266.52 / Avg: 92896.62 / Max: 93645.02 Min: 89400.2 / Avg: 89863.26 / Max: 90787.24 Min: 88093.03 / Avg: 88634.31 / Max: 89410.36 Min: 88176.03 / Avg: 88487.57 / Max: 89075.27 Min: 89581.38 / Avg: 90157.28 / Max: 90451.57 Min: 86896.07 / Avg: 86946.61 / Max: 86985.19 Min: 90159.87 / Avg: 90310.9 / Max: 90387.48 Min: 89694.92 / Avg: 90672.45 / Max: 92606.17 Min: 88306.55 / Avg: 88553.78 / Max: 89018.95 Min: 75656.88 / Avg: 76027.98 / Max: 76230.05 Min: 75619.2 / Avg: 76410.11 / Max: 76824.91 1. (CXX) g++ options: -O3 -march=native -fopenmp
LZ4 Compression This test measures the time needed to compress/decompress a sample file (an Ubuntu ISO) using LZ4 compression. Learn more via the OpenBenchmarking.org test page.
Result
OpenBenchmarking.org MB/s, More Is Better LZ4 Compression 1.9.3 Compression Level: 3 - Compression Speed EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 12 24 36 48 60 SE +/- 0.43, N = 3 SE +/- 0.15, N = 3 SE +/- 0.15, N = 3 SE +/- 0.53, N = 3 SE +/- 0.55, N = 4 SE +/- 0.29, N = 3 SE +/- 0.37, N = 3 SE +/- 0.04, N = 3 SE +/- 0.65, N = 3 SE +/- 0.31, N = 3 SE +/- 0.42, N = 7 SE +/- 0.35, N = 3 SE +/- 0.01, N = 3 44.93 43.23 44.38 44.53 45.98 45.77 44.69 45.90 45.38 45.19 45.69 52.79 52.82 1. (CC) gcc options: -O3
Result Confidence
OpenBenchmarking.org MB/s, More Is Better LZ4 Compression 1.9.3 Compression Level: 3 - Compression Speed EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 11 22 33 44 55 Min: 44.07 / Avg: 44.93 / Max: 45.44 Min: 42.93 / Avg: 43.23 / Max: 43.4 Min: 44.15 / Avg: 44.38 / Max: 44.66 Min: 44 / Avg: 44.53 / Max: 45.58 Min: 45.35 / Avg: 45.98 / Max: 47.62 Min: 45.44 / Avg: 45.77 / Max: 46.36 Min: 44.12 / Avg: 44.69 / Max: 45.37 Min: 45.84 / Avg: 45.9 / Max: 45.97 Min: 44.32 / Avg: 45.38 / Max: 46.55 Min: 44.56 / Avg: 45.19 / Max: 45.52 Min: 44.72 / Avg: 45.69 / Max: 47.44 Min: 52.36 / Avg: 52.79 / Max: 53.48 Min: 52.79 / Avg: 52.82 / Max: 52.84 1. (CC) gcc options: -O3
Swet Swet is a synthetic CPU/RAM benchmark, includes multi-processor test cases. Learn more via the OpenBenchmarking.org test page.
Result
OpenBenchmarking.org Operations Per Second, More Is Better Swet 1.5.16 Average EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 150M 300M 450M 600M 750M SE +/- 6957648.38, N = 3 SE +/- 2920022.24, N = 3 SE +/- 5177314.46, N = 3 SE +/- 3828695.03, N = 3 SE +/- 2164773.96, N = 3 SE +/- 4052005.46, N = 3 SE +/- 1400113.05, N = 3 SE +/- 8506660.76, N = 3 SE +/- 807930.96, N = 3 SE +/- 5706451.14, N = 3 SE +/- 2469610.76, N = 3 SE +/- 2325206.90, N = 3 SE +/- 2209414.80, N = 3 561816772 581194588 571825580 598589228 600065572 597361197 582684333 612218425 605644364 602203842 602434885 686395419 685188810 1. (CC) gcc options: -lm -lpthread -lcurses -lrt
Operations Per Second Per Watt
OpenBenchmarking.org Operations Per Second Per Watt, More Is Better Swet 1.5.16 Average EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 3M 6M 9M 12M 15M 14546659.15 14898341.79 14256393.92 12821906.80 13079157.08 12873172.87 9008595.44 13255560.12 11032151.74 9228207.39 9098672.56 13794532.24 10268451.78
Result Confidence
OpenBenchmarking.org Operations Per Second, More Is Better Swet 1.5.16 Average EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 120M 240M 360M 480M 600M Min: 547924209 / Avg: 561816771.67 / Max: 569451631 Min: 575619977 / Avg: 581194588 / Max: 585489333 Min: 566389680 / Avg: 571825580.33 / Max: 582175830 Min: 593041731 / Avg: 598589227.67 / Max: 605934155 Min: 595836568 / Avg: 600065571.67 / Max: 602983432 Min: 589487365 / Avg: 597361197.33 / Max: 602958932 Min: 579892857 / Avg: 582684332.67 / Max: 584271636 Min: 596416785 / Avg: 612218425.33 / Max: 625580102 Min: 604227306 / Avg: 605644364.33 / Max: 607025364 Min: 590802604 / Avg: 602203842.33 / Max: 608351202 Min: 597611652 / Avg: 602434885.33 / Max: 605768048 Min: 682854921 / Avg: 686395419.33 / Max: 690776878 Min: 680933266 / Avg: 685188809.67 / Max: 688347262 1. (CC) gcc options: -lm -lpthread -lcurses -lrt
Botan Botan is a cross-platform open-source C++ crypto library that supports most all publicly known cryptographic algorithms. Learn more via the OpenBenchmarking.org test page.
Result
OpenBenchmarking.org MiB/s, More Is Better Botan 2.13.0 Test: CAST-256 EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 30 60 90 120 150 SE +/- 0.04, N = 3 SE +/- 0.06, N = 3 SE +/- 0.09, N = 3 SE +/- 0.28, N = 3 SE +/- 0.03, N = 3 SE +/- 0.05, N = 3 SE +/- 0.04, N = 3 SE +/- 0.02, N = 3 SE +/- 0.02, N = 3 SE +/- 0.11, N = 3 SE +/- 0.09, N = 3 SE +/- 0.01, N = 3 SE +/- 0.02, N = 3 SE +/- 0.04, N = 3 114.59 114.69 114.47 117.88 119.99 120.06 118.29 121.92 118.32 117.99 118.23 120.00 139.83 139.71 1. (CXX) g++ options: -fstack-protector -m64 -pthread -lbotan-2 -ldl -lrt
MiB/s Per Watt
OpenBenchmarking.org MiB/s Per Watt, More Is Better Botan 2.13.0 Test: CAST-256 EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 0.675 1.35 2.025 2.7 3.375 3.00 2.98 2.88 2.56 2.65 2.61 1.83 2.67 2.16 1.93 1.82 1.83 2.83 2.09
Result Confidence
OpenBenchmarking.org MiB/s, More Is Better Botan 2.13.0 Test: CAST-256 EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 30 60 90 120 150 Min: 114.51 / Avg: 114.59 / Max: 114.64 Min: 114.63 / Avg: 114.69 / Max: 114.8 Min: 114.34 / Avg: 114.47 / Max: 114.63 Min: 117.32 / Avg: 117.88 / Max: 118.21 Min: 119.95 / Avg: 119.99 / Max: 120.04 Min: 119.97 / Avg: 120.06 / Max: 120.12 Min: 118.22 / Avg: 118.29 / Max: 118.36 Min: 121.89 / Avg: 121.92 / Max: 121.94 Min: 118.29 / Avg: 118.32 / Max: 118.36 Min: 117.81 / Avg: 117.99 / Max: 118.19 Min: 118.06 / Avg: 118.23 / Max: 118.33 Min: 119.99 / Avg: 119.99 / Max: 120.01 Min: 139.8 / Avg: 139.83 / Max: 139.86 Min: 139.63 / Avg: 139.71 / Max: 139.74 1. (CXX) g++ options: -fstack-protector -m64 -pthread -lbotan-2 -ldl -lrt
Result
OpenBenchmarking.org MiB/s, More Is Better Botan 2.13.0 Test: KASUMI EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 20 40 60 80 100 SE +/- 0.02, N = 3 SE +/- 0.01, N = 3 SE +/- 0.07, N = 3 SE +/- 0.01, N = 3 SE +/- 0.05, N = 3 SE +/- 0.01, N = 3 SE +/- 0.06, N = 3 SE +/- 0.02, N = 3 SE +/- 0.00, N = 3 SE +/- 0.05, N = 3 SE +/- 0.00, N = 3 SE +/- 0.03, N = 3 SE +/- 0.00, N = 3 SE +/- 0.02, N = 3 74.27 74.21 74.06 76.51 77.57 77.69 76.53 78.88 76.58 76.22 76.55 77.70 90.46 90.42 1. (CXX) g++ options: -fstack-protector -m64 -pthread -lbotan-2 -ldl -lrt
MiB/s Per Watt
OpenBenchmarking.org MiB/s Per Watt, More Is Better Botan 2.13.0 Test: KASUMI EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 0.4365 0.873 1.3095 1.746 2.1825 1.94 1.92 1.86 1.66 1.70 1.69 1.18 1.73 1.40 1.25 1.18 1.18 1.82 1.33
Result Confidence
OpenBenchmarking.org MiB/s, More Is Better Botan 2.13.0 Test: KASUMI EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 20 40 60 80 100 Min: 74.23 / Avg: 74.27 / Max: 74.29 Min: 74.18 / Avg: 74.21 / Max: 74.22 Min: 73.98 / Avg: 74.06 / Max: 74.21 Min: 76.49 / Avg: 76.51 / Max: 76.52 Min: 77.5 / Avg: 77.57 / Max: 77.66 Min: 77.68 / Avg: 77.69 / Max: 77.7 Min: 76.42 / Avg: 76.53 / Max: 76.6 Min: 78.84 / Avg: 78.88 / Max: 78.91 Min: 76.57 / Avg: 76.57 / Max: 76.58 Min: 76.12 / Avg: 76.22 / Max: 76.31 Min: 76.54 / Avg: 76.55 / Max: 76.55 Min: 77.66 / Avg: 77.7 / Max: 77.77 Min: 90.45 / Avg: 90.46 / Max: 90.47 Min: 90.37 / Avg: 90.42 / Max: 90.45 1. (CXX) g++ options: -fstack-protector -m64 -pthread -lbotan-2 -ldl -lrt
Radiance Benchmark This is a benchmark of NREL Radiance, a synthetic imaging system that is open-source and developed by the Lawrence Berkeley National Laboratory in California. Learn more via the OpenBenchmarking.org test page.
OpenBenchmarking.org Seconds, Fewer Is Better Radiance Benchmark 5.0 Test: Serial EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 160 320 480 640 800 748.59 746.72 746.18 724.99 714.24 721.79 724.56 705.16 727.34 725.23 723.32 713.56 613.55 612.89
eSpeak-NG Speech Engine This test times how long it takes the eSpeak speech synthesizer to read Project Gutenberg's The Outline of Science and output to a WAV file. This test profile is now tracking the eSpeak-NG version of eSpeak. Learn more via the OpenBenchmarking.org test page.
Result
OpenBenchmarking.org Seconds, Fewer Is Better eSpeak-NG Speech Engine 20200907 Text-To-Speech Synthesis EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 9 18 27 36 45 SE +/- 0.11, N = 4 SE +/- 0.08, N = 4 SE +/- 0.10, N = 4 SE +/- 0.12, N = 4 SE +/- 0.07, N = 4 SE +/- 0.08, N = 4 SE +/- 0.07, N = 4 SE +/- 0.04, N = 4 SE +/- 0.11, N = 4 SE +/- 0.06, N = 4 SE +/- 0.09, N = 4 SE +/- 0.12, N = 4 SE +/- 0.07, N = 4 SE +/- 0.08, N = 4 37.40 37.40 37.55 36.36 35.69 35.73 36.24 35.27 36.40 36.28 36.20 35.93 30.84 30.75 1. (CC) gcc options: -O2 -std=c99
Result Confidence
OpenBenchmarking.org Seconds, Fewer Is Better eSpeak-NG Speech Engine 20200907 Text-To-Speech Synthesis EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 8 16 24 32 40 Min: 37.13 / Avg: 37.4 / Max: 37.65 Min: 37.26 / Avg: 37.4 / Max: 37.61 Min: 37.36 / Avg: 37.55 / Max: 37.83 Min: 36.06 / Avg: 36.36 / Max: 36.65 Min: 35.55 / Avg: 35.69 / Max: 35.87 Min: 35.5 / Avg: 35.73 / Max: 35.85 Min: 36.12 / Avg: 36.24 / Max: 36.4 Min: 35.16 / Avg: 35.27 / Max: 35.37 Min: 36.11 / Avg: 36.4 / Max: 36.59 Min: 36.17 / Avg: 36.28 / Max: 36.45 Min: 35.97 / Avg: 36.2 / Max: 36.42 Min: 35.63 / Avg: 35.93 / Max: 36.21 Min: 30.64 / Avg: 30.84 / Max: 30.96 Min: 30.52 / Avg: 30.75 / Max: 30.86 1. (CC) gcc options: -O2 -std=c99
Perl Benchmarks Perl benchmark suite that can be used to compare the relative speed of different versions of perl. Learn more via the OpenBenchmarking.org test page.
Result
OpenBenchmarking.org Seconds, Fewer Is Better Perl Benchmarks Test: Pod2html EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 0.0352 0.0704 0.1056 0.1408 0.176 SE +/- 0.00101629, N = 3 SE +/- 0.00070595, N = 3 SE +/- 0.00047942, N = 3 SE +/- 0.00104595, N = 3 SE +/- 0.00052181, N = 3 SE +/- 0.00050264, N = 3 SE +/- 0.00097851, N = 3 SE +/- 0.00010921, N = 3 SE +/- 0.00076232, N = 3 SE +/- 0.00113052, N = 3 SE +/- 0.00009609, N = 3 SE +/- 0.00022828, N = 3 SE +/- 0.00007037, N = 3 SE +/- 0.00013172, N = 3 0.15653208 0.15457890 0.15341705 0.14978489 0.14573597 0.14859273 0.14988293 0.14850812 0.15124976 0.14868253 0.14976795 0.14954339 0.12819545 0.12924285
Result Confidence
OpenBenchmarking.org Seconds, Fewer Is Better Perl Benchmarks Test: Pod2html EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 1 2 3 4 5 Min: 0.16 / Avg: 0.16 / Max: 0.16 Min: 0.15 / Avg: 0.15 / Max: 0.16 Min: 0.15 / Avg: 0.15 / Max: 0.15 Min: 0.15 / Avg: 0.15 / Max: 0.15 Min: 0.14 / Avg: 0.15 / Max: 0.15 Min: 0.15 / Avg: 0.15 / Max: 0.15 Min: 0.15 / Avg: 0.15 / Max: 0.15 Min: 0.15 / Avg: 0.15 / Max: 0.15 Min: 0.15 / Avg: 0.15 / Max: 0.15 Min: 0.15 / Avg: 0.15 / Max: 0.15 Min: 0.15 / Avg: 0.15 / Max: 0.15 Min: 0.15 / Avg: 0.15 / Max: 0.15 Min: 0.13 / Avg: 0.13 / Max: 0.13 Min: 0.13 / Avg: 0.13 / Max: 0.13
Botan Botan is a cross-platform open-source C++ crypto library that supports most all publicly known cryptographic algorithms. Learn more via the OpenBenchmarking.org test page.
Result
OpenBenchmarking.org MiB/s, More Is Better Botan 2.13.0 Test: AES-256 EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 1100 2200 3300 4400 5500 SE +/- 13.87, N = 3 SE +/- 7.02, N = 3 SE +/- 0.80, N = 3 SE +/- 0.26, N = 3 SE +/- 0.83, N = 3 SE +/- 3.31, N = 3 SE +/- 1.33, N = 3 SE +/- 2.98, N = 3 SE +/- 3.88, N = 3 SE +/- 3.58, N = 3 SE +/- 0.85, N = 3 SE +/- 1.00, N = 3 SE +/- 1.69, N = 3 SE +/- 1.30, N = 3 4311.06 4290.85 4293.87 4430.72 4487.90 4497.77 4429.47 4561.19 4421.41 4425.92 4429.19 4499.50 5238.76 5226.75 1. (CXX) g++ options: -fstack-protector -m64 -pthread -lbotan-2 -ldl -lrt
MiB/s Per Watt
OpenBenchmarking.org MiB/s Per Watt, More Is Better Botan 2.13.0 Test: AES-256 EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 20 40 60 80 100 109.56 108.21 105.14 94.08 96.36 95.12 67.57 97.57 79.86 70.28 67.17 66.83 101.50 76.11
Result Confidence
OpenBenchmarking.org MiB/s, More Is Better Botan 2.13.0 Test: AES-256 EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 900 1800 2700 3600 4500 Min: 4293.42 / Avg: 4311.06 / Max: 4338.43 Min: 4276.91 / Avg: 4290.85 / Max: 4299.27 Min: 4292.82 / Avg: 4293.87 / Max: 4295.45 Min: 4430.21 / Avg: 4430.72 / Max: 4431.05 Min: 4486.88 / Avg: 4487.9 / Max: 4489.54 Min: 4492.53 / Avg: 4497.77 / Max: 4503.89 Min: 4426.94 / Avg: 4429.47 / Max: 4431.46 Min: 4555.36 / Avg: 4561.19 / Max: 4565.19 Min: 4413.66 / Avg: 4421.41 / Max: 4425.33 Min: 4421.28 / Avg: 4425.91 / Max: 4432.96 Min: 4427.63 / Avg: 4429.19 / Max: 4430.55 Min: 4497.86 / Avg: 4499.5 / Max: 4501.3 Min: 5235.4 / Avg: 5238.76 / Max: 5240.69 Min: 5224.38 / Avg: 5226.75 / Max: 5228.88 1. (CXX) g++ options: -fstack-protector -m64 -pthread -lbotan-2 -ldl -lrt
Etcpak Etcpack is the self-proclaimed "fastest ETC compressor on the planet" with focused on providing open-source, very fast ETC and S3 texture compression support. Learn more via the OpenBenchmarking.org test page.
Result
OpenBenchmarking.org Mpx/s, More Is Better Etcpak 0.7 Configuration: ETC2 EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 40 80 120 160 200 SE +/- 0.02, N = 3 SE +/- 0.02, N = 3 SE +/- 0.09, N = 3 SE +/- 0.03, N = 3 SE +/- 0.10, N = 3 SE +/- 0.00, N = 3 SE +/- 0.08, N = 3 SE +/- 0.11, N = 3 SE +/- 0.03, N = 3 SE +/- 0.02, N = 3 SE +/- 0.01, N = 3 SE +/- 0.01, N = 3 SE +/- 0.03, N = 3 131.18 131.15 130.88 135.18 137.09 137.34 135.01 139.25 135.14 135.24 137.28 159.79 159.60 1. (CXX) g++ options: -O3 -march=native -std=c++11 -lpthread
Mpx/s Per Watt
OpenBenchmarking.org Mpx/s Per Watt, More Is Better Etcpak 0.7 Configuration: ETC2 EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 0.7358 1.4716 2.2074 2.9432 3.679 3.27 3.24 3.16 2.79 2.87 2.86 2.02 2.91 2.39 2.00 2.00 3.07 2.29
Result Confidence
OpenBenchmarking.org Mpx/s, More Is Better Etcpak 0.7 Configuration: ETC2 EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 30 60 90 120 150 Min: 131.16 / Avg: 131.18 / Max: 131.22 Min: 131.11 / Avg: 131.15 / Max: 131.19 Min: 130.77 / Avg: 130.88 / Max: 131.05 Min: 135.12 / Avg: 135.18 / Max: 135.24 Min: 136.98 / Avg: 137.09 / Max: 137.3 Min: 137.34 / Avg: 137.34 / Max: 137.35 Min: 134.91 / Avg: 135.01 / Max: 135.17 Min: 139.03 / Avg: 139.25 / Max: 139.39 Min: 135.11 / Avg: 135.14 / Max: 135.2 Min: 135.2 / Avg: 135.23 / Max: 135.25 Min: 137.26 / Avg: 137.28 / Max: 137.3 Min: 159.77 / Avg: 159.79 / Max: 159.8 Min: 159.56 / Avg: 159.6 / Max: 159.65 1. (CXX) g++ options: -O3 -march=native -std=c++11 -lpthread
libjpeg-turbo tjbench tjbench is a JPEG decompression/compression benchmark part of libjpeg-turbo. Learn more via the OpenBenchmarking.org test page.
Result
OpenBenchmarking.org Megapixels/sec, More Is Better libjpeg-turbo tjbench 2.0.2 Test: Decompression Throughput EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 40 80 120 160 200 SE +/- 0.03, N = 7 SE +/- 0.26, N = 7 SE +/- 0.10, N = 7 SE +/- 0.04, N = 7 SE +/- 0.44, N = 7 SE +/- 0.05, N = 7 SE +/- 0.07, N = 7 SE +/- 0.07, N = 7 SE +/- 0.02, N = 7 SE +/- 0.03, N = 7 SE +/- 0.04, N = 7 SE +/- 0.04, N = 7 SE +/- 0.02, N = 7 SE +/- 0.04, N = 7 162.56 162.37 162.07 167.63 169.70 170.11 167.52 172.55 167.61 167.57 167.62 169.54 197.77 197.79 1. (CC) gcc options: -O3 -rdynamic
Megapixels/sec Per Watt
OpenBenchmarking.org Megapixels/sec Per Watt, More Is Better libjpeg-turbo tjbench 2.0.2 Test: Decompression Throughput EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 1.0148 2.0296 3.0444 4.0592 5.074 4.51 4.45 4.30 3.87 3.95 3.96 2.85 4.03 3.31 2.88 2.80 2.78 4.25 3.16
Result Confidence
OpenBenchmarking.org Megapixels/sec, More Is Better libjpeg-turbo tjbench 2.0.2 Test: Decompression Throughput EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 40 80 120 160 200 Min: 162.5 / Avg: 162.56 / Max: 162.7 Min: 160.82 / Avg: 162.37 / Max: 162.74 Min: 161.84 / Avg: 162.07 / Max: 162.46 Min: 167.45 / Avg: 167.63 / Max: 167.79 Min: 167.04 / Avg: 169.7 / Max: 170.26 Min: 169.86 / Avg: 170.11 / Max: 170.26 Min: 167.15 / Avg: 167.52 / Max: 167.68 Min: 172.16 / Avg: 172.55 / Max: 172.69 Min: 167.49 / Avg: 167.61 / Max: 167.66 Min: 167.44 / Avg: 167.57 / Max: 167.69 Min: 167.5 / Avg: 167.62 / Max: 167.77 Min: 169.39 / Avg: 169.54 / Max: 169.69 Min: 197.66 / Avg: 197.77 / Max: 197.86 Min: 197.62 / Avg: 197.79 / Max: 197.87 1. (CC) gcc options: -O3 -rdynamic
Etcpak Etcpack is the self-proclaimed "fastest ETC compressor on the planet" with focused on providing open-source, very fast ETC and S3 texture compression support. Learn more via the OpenBenchmarking.org test page.
Result
OpenBenchmarking.org Mpx/s, More Is Better Etcpak 0.7 Configuration: ETC1 EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 60 120 180 240 300 SE +/- 0.14, N = 3 SE +/- 0.03, N = 3 SE +/- 0.21, N = 3 SE +/- 0.08, N = 3 SE +/- 0.16, N = 3 SE +/- 0.11, N = 3 SE +/- 0.10, N = 3 SE +/- 0.18, N = 3 SE +/- 0.00, N = 3 SE +/- 0.16, N = 3 SE +/- 0.12, N = 3 SE +/- 0.19, N = 3 SE +/- 0.18, N = 3 223.03 222.62 222.36 229.56 233.39 233.51 229.73 236.91 229.46 229.86 233.35 271.32 271.07 1. (CXX) g++ options: -O3 -march=native -std=c++11 -lpthread
Mpx/s Per Watt
OpenBenchmarking.org Mpx/s Per Watt, More Is Better Etcpak 0.7 Configuration: ETC1 EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 1.2713 2.5426 3.8139 5.0852 6.3565 5.65 5.60 5.44 4.81 4.94 4.95 3.48 5.04 4.14 3.46 3.48 5.29 3.89
Result Confidence
OpenBenchmarking.org Mpx/s, More Is Better Etcpak 0.7 Configuration: ETC1 EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 50 100 150 200 250 Min: 222.74 / Avg: 223.03 / Max: 223.2 Min: 222.56 / Avg: 222.62 / Max: 222.66 Min: 221.94 / Avg: 222.36 / Max: 222.64 Min: 229.4 / Avg: 229.56 / Max: 229.64 Min: 233.07 / Avg: 233.39 / Max: 233.6 Min: 233.3 / Avg: 233.51 / Max: 233.66 Min: 229.59 / Avg: 229.73 / Max: 229.93 Min: 236.57 / Avg: 236.91 / Max: 237.18 Min: 229.45 / Avg: 229.46 / Max: 229.47 Min: 229.54 / Avg: 229.86 / Max: 230.03 Min: 233.22 / Avg: 233.35 / Max: 233.6 Min: 271.12 / Avg: 271.32 / Max: 271.69 Min: 270.72 / Avg: 271.07 / Max: 271.3 1. (CXX) g++ options: -O3 -march=native -std=c++11 -lpthread
AOBench AOBench is a lightweight ambient occlusion renderer, written in C. The test profile is using a size of 2048 x 2048. Learn more via the OpenBenchmarking.org test page.
Result
OpenBenchmarking.org Seconds, Fewer Is Better AOBench Size: 2048 x 2048 - Total Time EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 10 20 30 40 50 SE +/- 0.01, N = 3 SE +/- 0.05, N = 3 SE +/- 0.02, N = 3 SE +/- 0.18, N = 3 SE +/- 0.00, N = 3 SE +/- 0.02, N = 3 SE +/- 0.01, N = 3 SE +/- 0.01, N = 3 SE +/- 0.01, N = 3 SE +/- 0.01, N = 3 SE +/- 0.02, N = 3 SE +/- 0.51, N = 3 SE +/- 0.02, N = 3 SE +/- 0.02, N = 3 42.44 42.48 42.44 40.98 40.59 40.53 41.19 39.92 41.17 41.17 41.26 41.15 34.84 34.81 1. (CC) gcc options: -lm -O3
Result Confidence
OpenBenchmarking.org Seconds, Fewer Is Better AOBench Size: 2048 x 2048 - Total Time EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 9 18 27 36 45 Min: 42.43 / Avg: 42.44 / Max: 42.45 Min: 42.42 / Avg: 42.48 / Max: 42.58 Min: 42.4 / Avg: 42.43 / Max: 42.45 Min: 40.63 / Avg: 40.98 / Max: 41.17 Min: 40.58 / Avg: 40.59 / Max: 40.6 Min: 40.51 / Avg: 40.53 / Max: 40.58 Min: 41.18 / Avg: 41.19 / Max: 41.2 Min: 39.91 / Avg: 39.92 / Max: 39.94 Min: 41.14 / Avg: 41.16 / Max: 41.18 Min: 41.14 / Avg: 41.17 / Max: 41.18 Min: 41.23 / Avg: 41.26 / Max: 41.3 Min: 40.64 / Avg: 41.15 / Max: 42.18 Min: 34.8 / Avg: 34.83 / Max: 34.87 Min: 34.79 / Avg: 34.81 / Max: 34.85 1. (CC) gcc options: -lm -O3
Etcpak Etcpack is the self-proclaimed "fastest ETC compressor on the planet" with focused on providing open-source, very fast ETC and S3 texture compression support. Learn more via the OpenBenchmarking.org test page.
Result
OpenBenchmarking.org Mpx/s, More Is Better Etcpak 0.7 Configuration: ETC1 + Dithering EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 60 120 180 240 300 SE +/- 0.09, N = 3 SE +/- 0.08, N = 3 SE +/- 0.12, N = 3 SE +/- 0.04, N = 3 SE +/- 0.02, N = 3 SE +/- 0.07, N = 3 SE +/- 0.08, N = 3 SE +/- 0.05, N = 3 SE +/- 0.01, N = 3 SE +/- 0.07, N = 3 SE +/- 0.08, N = 3 SE +/- 0.01, N = 3 SE +/- 0.04, N = 3 210.93 211.03 210.72 217.50 220.71 220.76 216.79 223.49 217.50 217.45 220.80 257.01 256.42 1. (CXX) g++ options: -O3 -march=native -std=c++11 -lpthread
Mpx/s Per Watt
OpenBenchmarking.org Mpx/s Per Watt, More Is Better Etcpak 0.7 Configuration: ETC1 + Dithering EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 1.2038 2.4076 3.6114 4.8152 6.019 5.35 5.28 5.14 4.57 4.70 4.65 3.32 4.78 3.92 3.28 3.28 5.05 3.74
Result Confidence
OpenBenchmarking.org Mpx/s, More Is Better Etcpak 0.7 Configuration: ETC1 + Dithering EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 50 100 150 200 250 Min: 210.74 / Avg: 210.93 / Max: 211.03 Min: 210.87 / Avg: 211.03 / Max: 211.13 Min: 210.52 / Avg: 210.72 / Max: 210.94 Min: 217.45 / Avg: 217.5 / Max: 217.57 Min: 220.68 / Avg: 220.71 / Max: 220.76 Min: 220.68 / Avg: 220.76 / Max: 220.9 Min: 216.67 / Avg: 216.79 / Max: 216.93 Min: 223.43 / Avg: 223.49 / Max: 223.58 Min: 217.48 / Avg: 217.5 / Max: 217.52 Min: 217.36 / Avg: 217.45 / Max: 217.6 Min: 220.64 / Avg: 220.8 / Max: 220.91 Min: 257 / Avg: 257.01 / Max: 257.02 Min: 256.36 / Avg: 256.42 / Max: 256.5 1. (CXX) g++ options: -O3 -march=native -std=c++11 -lpthread
TSCP This is a performance test of TSCP, Tom Kerrigan's Simple Chess Program, which has a built-in performance benchmark. Learn more via the OpenBenchmarking.org test page.
Result
OpenBenchmarking.org Nodes Per Second, More Is Better TSCP 1.81 AI Chess Performance EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 300K 600K 900K 1200K 1500K SE +/- 504.67, N = 11 SE +/- 863.61, N = 11 SE +/- 1355.09, N = 11 SE +/- 609.53, N = 11 SE +/- 1181.68, N = 11 SE +/- 1366.07, N = 11 SE +/- 986.25, N = 11 SE +/- 372.53, N = 12 SE +/- 587.46, N = 11 SE +/- 1511.23, N = 11 SE +/- 658.02, N = 11 SE +/- 1531.45, N = 12 SE +/- 791.31, N = 12 969371 969066 968149 997133 1013320 1014342 999442 1030295 997461 997809 1015858 1180682 1178140 1. (CC) gcc options: -O3 -march=native
Nodes Per Second Per Watt
OpenBenchmarking.org Nodes Per Second Per Watt, More Is Better TSCP 1.81 AI Chess Performance EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 7K 14K 21K 28K 35K 30915.01 30478.57 29161.11 26682.94 27950.92 27717.32 20016.67 28093.43 23213.22 19457.25 19805.30 31397.39 23615.12
Result Confidence
OpenBenchmarking.org Nodes Per Second, More Is Better TSCP 1.81 AI Chess Performance EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 200K 400K 600K 800K 1000K Min: 966277 / Avg: 969371.36 / Max: 971389 Min: 961218 / Avg: 969066.36 / Max: 971389 Min: 956211 / Avg: 968148.55 / Max: 971389 Min: 994184 / Avg: 997132.73 / Max: 999597 Min: 1003238 / Avg: 1013319.55 / Max: 1016195 Min: 1001414 / Avg: 1014342.27 / Max: 1018073 Min: 990607 / Avg: 999441.64 / Max: 1003238 Min: 1029491 / Avg: 1030294.92 / Max: 1033354 Min: 994184 / Avg: 997460.73 / Max: 999597 Min: 987057 / Avg: 997809 / Max: 1001414 Min: 1010601 / Avg: 1015858.45 / Max: 1018073 Min: 1166902 / Avg: 1180681.92 / Max: 1187021 Min: 1174366 / Avg: 1178140.42 / Max: 1181927 1. (CC) gcc options: -O3 -march=native
QuantLib QuantLib is an open-source library/framework around quantitative finance for modeling, trading and risk management scenarios. QuantLib is written in C++ with Boost and its built-in benchmark used reports the QuantLib Benchmark Index benchmark score. Learn more via the OpenBenchmarking.org test page.
Result
OpenBenchmarking.org MFLOPS, More Is Better QuantLib 1.21 EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 500 1000 1500 2000 2500 SE +/- 10.95, N = 3 SE +/- 12.91, N = 3 SE +/- 8.78, N = 3 SE +/- 10.13, N = 3 SE +/- 12.22, N = 3 SE +/- 9.97, N = 3 SE +/- 10.26, N = 3 SE +/- 11.83, N = 3 SE +/- 13.45, N = 3 SE +/- 10.12, N = 3 SE +/- 11.47, N = 3 SE +/- 13.33, N = 3 SE +/- 10.66, N = 3 1892.0 1893.2 1887.0 1952.5 1977.3 1984.5 1922.3 2016.4 1945.3 1955.3 1970.1 2285.2 2300.7 1. (CXX) g++ options: -O3 -march=native -rdynamic
MFLOPS Per Watt
OpenBenchmarking.org MFLOPS Per Watt, More Is Better QuantLib 1.21 EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 10 20 30 40 50 46.01 45.42 44.47 39.68 40.44 40.27 28.32 41.04 33.75 28.49 28.04 42.47 31.99
Result Confidence
OpenBenchmarking.org MFLOPS, More Is Better QuantLib 1.21 EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 400 800 1200 1600 2000 Min: 1870.4 / Avg: 1892 / Max: 1905.9 Min: 1867.5 / Avg: 1893.2 / Max: 1908.2 Min: 1869.4 / Avg: 1886.97 / Max: 1895.9 Min: 1932.3 / Avg: 1952.53 / Max: 1963.6 Min: 1953.5 / Avg: 1977.33 / Max: 1993.9 Min: 1964.7 / Avg: 1984.5 / Max: 1996.4 Min: 1902.5 / Avg: 1922.27 / Max: 1936.9 Min: 1993.3 / Avg: 2016.43 / Max: 2032.3 Min: 1918.7 / Avg: 1945.33 / Max: 1961.9 Min: 1935.1 / Avg: 1955.3 / Max: 1966.5 Min: 1947.7 / Avg: 1970.13 / Max: 1985.5 Min: 2258.5 / Avg: 2285.17 / Max: 2298.8 Min: 2279.8 / Avg: 2300.73 / Max: 2314.7 1. (CXX) g++ options: -O3 -march=native -rdynamic
TNN TNN is an open-source deep learning reasoning framework developed by Tencent. Learn more via the OpenBenchmarking.org test page.
Result
OpenBenchmarking.org ms, Fewer Is Better TNN 0.2.3 Target: CPU - Model: SqueezeNet v1.1 EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 70 140 210 280 350 SE +/- 0.77, N = 3 SE +/- 0.11, N = 3 SE +/- 1.44, N = 3 SE +/- 0.82, N = 3 SE +/- 0.19, N = 3 SE +/- 0.71, N = 3 SE +/- 0.26, N = 3 SE +/- 0.29, N = 3 SE +/- 1.22, N = 3 SE +/- 1.03, N = 3 SE +/- 0.83, N = 3 SE +/- 0.80, N = 3 SE +/- 0.36, N = 3 SE +/- 0.12, N = 3 327.99 328.36 328.64 318.37 314.31 312.89 318.58 308.94 318.67 318.67 317.55 313.01 269.64 269.92 MIN: 325.21 / MAX: 329.77 MIN: 325.02 / MAX: 339.93 MIN: 325.19 / MAX: 342.8 MIN: 315.66 / MAX: 323.53 MIN: 311.3 / MAX: 317.52 MIN: 310.9 / MAX: 315.08 MIN: 315.09 / MAX: 320.21 MIN: 306.29 / MAX: 322.41 MIN: 315.63 / MAX: 323.01 MIN: 315.68 / MAX: 321.91 MIN: 315.59 / MAX: 319.4 MIN: 310.72 / MAX: 314.66 MIN: 267.19 / MAX: 279.76 MIN: 267.18 / MAX: 272.47 1. (CXX) g++ options: -fopenmp -pthread -fvisibility=hidden -O3 -rdynamic -ldl
Result Confidence
OpenBenchmarking.org ms, Fewer Is Better TNN 0.2.3 Target: CPU - Model: SqueezeNet v1.1 EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 60 120 180 240 300 Min: 326.49 / Avg: 327.99 / Max: 329.05 Min: 328.14 / Avg: 328.36 / Max: 328.49 Min: 325.78 / Avg: 328.64 / Max: 330.41 Min: 317.19 / Avg: 318.37 / Max: 319.96 Min: 313.92 / Avg: 314.31 / Max: 314.52 Min: 311.52 / Avg: 312.89 / Max: 313.94 Min: 318.08 / Avg: 318.58 / Max: 318.92 Min: 308.42 / Avg: 308.94 / Max: 309.44 Min: 316.23 / Avg: 318.67 / Max: 320.01 Min: 316.65 / Avg: 318.67 / Max: 319.98 Min: 316.01 / Avg: 317.55 / Max: 318.87 Min: 311.43 / Avg: 313.01 / Max: 313.95 Min: 269.01 / Avg: 269.64 / Max: 270.25 Min: 269.68 / Avg: 269.92 / Max: 270.07 1. (CXX) g++ options: -fopenmp -pthread -fvisibility=hidden -O3 -rdynamic -ldl
Perl Benchmarks Perl benchmark suite that can be used to compare the relative speed of different versions of perl. Learn more via the OpenBenchmarking.org test page.
Result
OpenBenchmarking.org Seconds, Fewer Is Better Perl Benchmarks Test: Interpreter EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 0.0002 0.0004 0.0006 0.0008 0.001 SE +/- 0.00000737, N = 3 SE +/- 0.00001257, N = 3 SE +/- 0.00000497, N = 3 SE +/- 0.00000413, N = 3 SE +/- 0.00000962, N = 3 SE +/- 0.00000724, N = 3 SE +/- 0.00000252, N = 3 SE +/- 0.00000879, N = 3 SE +/- 0.00000921, N = 3 SE +/- 0.00000264, N = 3 SE +/- 0.00000365, N = 3 SE +/- 0.00000621, N = 3 SE +/- 0.00001015, N = 3 SE +/- 0.00000483, N = 3 0.00100608 0.00098074 0.00099210 0.00095478 0.00095586 0.00096082 0.00096753 0.00095485 0.00096153 0.00096579 0.00097455 0.00097084 0.00083563 0.00082570
Result Confidence
OpenBenchmarking.org Seconds, Fewer Is Better Perl Benchmarks Test: Interpreter EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 1 2 3 4 5 Min: 0 / Avg: 0 / Max: 0 Min: 0 / Avg: 0 / Max: 0 Min: 0 / Avg: 0 / Max: 0 Min: 0 / Avg: 0 / Max: 0 Min: 0 / Avg: 0 / Max: 0 Min: 0 / Avg: 0 / Max: 0 Min: 0 / Avg: 0 / Max: 0 Min: 0 / Avg: 0 / Max: 0 Min: 0 / Avg: 0 / Max: 0 Min: 0 / Avg: 0 / Max: 0 Min: 0 / Avg: 0 / Max: 0 Min: 0 / Avg: 0 / Max: 0 Min: 0 / Avg: 0 / Max: 0 Min: 0 / Avg: 0 / Max: 0
Montage Astronomical Image Mosaic Engine Montage is an open-source astronomical image mosaic engine. This BSD-licensed astronomy software is developed by the California Institute of Technology, Pasadena. Learn more via the OpenBenchmarking.org test page.
Result
OpenBenchmarking.org Seconds, Fewer Is Better Montage Astronomical Image Mosaic Engine 6.0 Mosaic of M17, K band, 1.5 deg x 1.5 deg EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 20 40 60 80 100 SE +/- 0.16, N = 3 SE +/- 0.04, N = 3 SE +/- 0.12, N = 3 SE +/- 0.09, N = 3 SE +/- 0.09, N = 3 SE +/- 0.17, N = 3 SE +/- 0.08, N = 3 SE +/- 0.31, N = 3 SE +/- 0.28, N = 3 SE +/- 0.19, N = 3 SE +/- 0.12, N = 3 SE +/- 0.11, N = 3 SE +/- 0.05, N = 3 SE +/- 0.14, N = 3 98.41 98.31 98.24 95.45 93.92 93.86 95.48 92.77 95.53 95.39 95.56 94.76 80.85 80.94 1. (CC) gcc options: -std=gnu99 -lcfitsio -lm -O2
Result Confidence
OpenBenchmarking.org Seconds, Fewer Is Better Montage Astronomical Image Mosaic Engine 6.0 Mosaic of M17, K band, 1.5 deg x 1.5 deg EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 20 40 60 80 100 Min: 98.12 / Avg: 98.41 / Max: 98.67 Min: 98.25 / Avg: 98.31 / Max: 98.39 Min: 98.08 / Avg: 98.24 / Max: 98.48 Min: 95.27 / Avg: 95.45 / Max: 95.58 Min: 93.8 / Avg: 93.92 / Max: 94.11 Min: 93.53 / Avg: 93.86 / Max: 94.1 Min: 95.35 / Avg: 95.48 / Max: 95.62 Min: 92.29 / Avg: 92.77 / Max: 93.36 Min: 95.11 / Avg: 95.53 / Max: 96.06 Min: 95.12 / Avg: 95.39 / Max: 95.75 Min: 95.43 / Avg: 95.56 / Max: 95.8 Min: 94.65 / Avg: 94.76 / Max: 94.97 Min: 80.76 / Avg: 80.85 / Max: 80.91 Min: 80.67 / Avg: 80.94 / Max: 81.13 1. (CC) gcc options: -std=gnu99 -lcfitsio -lm -O2
WebP Image Encode This is a test of Google's libwebp with the cwebp image encode utility and using a sample 6000x4000 pixel JPEG image as the input. Learn more via the OpenBenchmarking.org test page.
Result
OpenBenchmarking.org Encode Time - Seconds, Fewer Is Better WebP Image Encode 1.1 Encode Settings: Quality 100 EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 0.6833 1.3666 2.0499 2.7332 3.4165 SE +/- 0.002, N = 9 SE +/- 0.001, N = 9 SE +/- 0.002, N = 9 SE +/- 0.002, N = 9 SE +/- 0.002, N = 9 SE +/- 0.003, N = 9 SE +/- 0.001, N = 9 SE +/- 0.001, N = 9 SE +/- 0.002, N = 9 SE +/- 0.003, N = 9 SE +/- 0.003, N = 9 SE +/- 0.003, N = 9 SE +/- 0.001, N = 10 SE +/- 0.002, N = 10 3.035 3.029 3.037 2.945 2.901 2.899 2.945 2.858 2.945 2.952 2.946 2.905 2.495 2.500 1. (CC) gcc options: -fvisibility=hidden -O2 -pthread -lm -ljpeg -lpng16 -ltiff
Result Confidence
OpenBenchmarking.org Encode Time - Seconds, Fewer Is Better WebP Image Encode 1.1 Encode Settings: Quality 100 EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 2 4 6 8 10 Min: 3.03 / Avg: 3.04 / Max: 3.05 Min: 3.02 / Avg: 3.03 / Max: 3.03 Min: 3.03 / Avg: 3.04 / Max: 3.05 Min: 2.94 / Avg: 2.94 / Max: 2.95 Min: 2.89 / Avg: 2.9 / Max: 2.91 Min: 2.89 / Avg: 2.9 / Max: 2.92 Min: 2.94 / Avg: 2.94 / Max: 2.95 Min: 2.85 / Avg: 2.86 / Max: 2.87 Min: 2.94 / Avg: 2.94 / Max: 2.95 Min: 2.94 / Avg: 2.95 / Max: 2.97 Min: 2.94 / Avg: 2.95 / Max: 2.97 Min: 2.89 / Avg: 2.9 / Max: 2.92 Min: 2.49 / Avg: 2.49 / Max: 2.5 Min: 2.49 / Avg: 2.5 / Max: 2.51 1. (CC) gcc options: -fvisibility=hidden -O2 -pthread -lm -ljpeg -lpng16 -ltiff
Himeno Benchmark The Himeno benchmark is a linear solver of pressure Poisson using a point-Jacobi method. Learn more via the OpenBenchmarking.org test page.
Result
OpenBenchmarking.org MFLOPS, More Is Better Himeno Benchmark 3.0 Poisson Pressure Solver EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 900 1800 2700 3600 4500 SE +/- 25.83, N = 3 SE +/- 37.21, N = 3 SE +/- 17.87, N = 3 SE +/- 46.66, N = 4 SE +/- 37.84, N = 3 SE +/- 43.10, N = 4 SE +/- 42.46, N = 3 SE +/- 9.42, N = 3 SE +/- 31.29, N = 9 SE +/- 44.49, N = 4 SE +/- 47.38, N = 4 SE +/- 36.48, N = 3 SE +/- 33.69, N = 3 SE +/- 38.21, N = 3 3589.93 3634.17 3756.96 3792.81 3765.85 3853.50 3830.20 3988.94 3793.17 3816.08 3837.56 3762.49 4336.41 4367.12 1. (CC) gcc options: -O3 -mavx2
MFLOPS Per Watt
OpenBenchmarking.org MFLOPS Per Watt, More Is Better Himeno Benchmark 3.0 Poisson Pressure Solver EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 20 40 60 80 100 83.09 82.98 84.36 73.24 73.50 75.05 53.96 77.43 62.42 56.78 53.85 51.62 75.95 57.55
Result Confidence
OpenBenchmarking.org MFLOPS, More Is Better Himeno Benchmark 3.0 Poisson Pressure Solver EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 800 1600 2400 3200 4000 Min: 3541.75 / Avg: 3589.93 / Max: 3630.15 Min: 3590.61 / Avg: 3634.17 / Max: 3708.22 Min: 3721.38 / Avg: 3756.96 / Max: 3777.75 Min: 3699.39 / Avg: 3792.81 / Max: 3917.69 Min: 3719.42 / Avg: 3765.85 / Max: 3840.83 Min: 3731.7 / Avg: 3853.5 / Max: 3929.87 Min: 3768.21 / Avg: 3830.2 / Max: 3911.46 Min: 3976.02 / Avg: 3988.94 / Max: 4007.28 Min: 3632 / Avg: 3793.17 / Max: 3925.79 Min: 3692 / Avg: 3816.08 / Max: 3902.55 Min: 3701.86 / Avg: 3837.56 / Max: 3910.17 Min: 3718.35 / Avg: 3762.49 / Max: 3834.86 Min: 4277.41 / Avg: 4336.41 / Max: 4394.1 Min: 4297.85 / Avg: 4367.12 / Max: 4429.7 1. (CC) gcc options: -O3 -mavx2
PHPBench PHPBench is a benchmark suite for PHP. It performs a large number of simple tests in order to bench various aspects of the PHP interpreter. PHPBench can be used to compare hardware, operating systems, PHP versions, PHP accelerators and caches, compiler options, etc. Learn more via the OpenBenchmarking.org test page.
Result
OpenBenchmarking.org Score, More Is Better PHPBench 0.8.1 PHP Benchmark Suite EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 130K 260K 390K 520K 650K SE +/- 569.07, N = 3 SE +/- 2157.92, N = 3 SE +/- 973.54, N = 3 SE +/- 957.34, N = 3 SE +/- 4035.67, N = 3 SE +/- 948.15, N = 3 SE +/- 4131.15, N = 3 SE +/- 741.11, N = 3 SE +/- 142.64, N = 3 SE +/- 215.70, N = 3 SE +/- 1174.39, N = 3 SE +/- 1921.47, N = 3 SE +/- 7086.33, N = 3 SE +/- 1476.72, N = 3 511906 513356 511228 524189 542521 531740 532957 539060 523575 521572 524751 529609 621672 614039
Score Per Watt
OpenBenchmarking.org Score Per Watt, More Is Better PHPBench 0.8.1 PHP Benchmark Suite EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 3K 6K 9K 12K 15K 12522.00 12418.02 12087.81 10676.05 11170.88 10842.61 7829.14 11143.99 9050.74 8074.56 7697.43 7643.25 11604.83 8583.59
Result Confidence
OpenBenchmarking.org Score, More Is Better PHPBench 0.8.1 PHP Benchmark Suite EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 110K 220K 330K 440K 550K Min: 511300 / Avg: 511905.67 / Max: 513043 Min: 510924 / Avg: 513356.33 / Max: 517660 Min: 510027 / Avg: 511228.33 / Max: 513156 Min: 522517 / Avg: 524188.67 / Max: 525833 Min: 534521 / Avg: 542520.67 / Max: 547450 Min: 530354 / Avg: 531740.33 / Max: 533554 Min: 524902 / Avg: 532956.67 / Max: 538578 Min: 538010 / Avg: 539060 / Max: 540491 Min: 523393 / Avg: 523574.67 / Max: 523856 Min: 521324 / Avg: 521572.33 / Max: 522002 Min: 523197 / Avg: 524750.67 / Max: 527053 Min: 525962 / Avg: 529608.67 / Max: 532482 Min: 613060 / Avg: 621672 / Max: 635726 Min: 611253 / Avg: 614039 / Max: 616281
GnuPG This test times how long it takes to encrypt a sample file using GnuPG. Learn more via the OpenBenchmarking.org test page.
Result
OpenBenchmarking.org Seconds, Fewer Is Better GnuPG 2.2.27 2.7GB Sample File Encryption EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 20 40 60 80 100 SE +/- 0.53, N = 3 SE +/- 0.94, N = 3 SE +/- 0.25, N = 3 SE +/- 0.95, N = 3 SE +/- 0.84, N = 3 SE +/- 0.75, N = 3 SE +/- 0.48, N = 3 SE +/- 0.30, N = 3 SE +/- 0.71, N = 3 SE +/- 0.80, N = 3 SE +/- 0.88, N = 3 SE +/- 0.76, N = 3 SE +/- 0.36, N = 3 SE +/- 0.29, N = 3 88.44 88.44 89.68 85.82 84.43 85.02 85.79 83.90 86.37 86.36 85.73 85.24 73.75 73.85 1. (CC) gcc options: -O2
Result Confidence
OpenBenchmarking.org Seconds, Fewer Is Better GnuPG 2.2.27 2.7GB Sample File Encryption EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 20 40 60 80 100 Min: 87.54 / Avg: 88.44 / Max: 89.39 Min: 87.5 / Avg: 88.44 / Max: 90.31 Min: 89.26 / Avg: 89.68 / Max: 90.12 Min: 84.82 / Avg: 85.82 / Max: 87.72 Min: 83.56 / Avg: 84.43 / Max: 86.11 Min: 83.6 / Avg: 85.02 / Max: 86.12 Min: 85.06 / Avg: 85.79 / Max: 86.69 Min: 83.3 / Avg: 83.9 / Max: 84.23 Min: 85.07 / Avg: 86.37 / Max: 87.5 Min: 84.87 / Avg: 86.36 / Max: 87.6 Min: 84.82 / Avg: 85.73 / Max: 87.48 Min: 83.83 / Avg: 85.24 / Max: 86.45 Min: 73.34 / Avg: 73.75 / Max: 74.47 Min: 73.37 / Avg: 73.85 / Max: 74.37 1. (CC) gcc options: -O2
Darmstadt Automotive Parallel Heterogeneous Suite DAPHNE is the Darmstadt Automotive Parallel HeterogeNEous Benchmark Suite with OpenCL / CUDA / OpenMP test cases for these automotive benchmarks for evaluating programming models in context to vehicle autonomous driving capabilities. Learn more via the OpenBenchmarking.org test page.
Result
OpenBenchmarking.org Test Cases Per Minute, More Is Better Darmstadt Automotive Parallel Heterogeneous Suite Backend: OpenMP - Kernel: Euclidean Cluster EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 200 400 600 800 1000 SE +/- 0.40, N = 3 SE +/- 0.49, N = 3 SE +/- 1.22, N = 3 SE +/- 0.19, N = 3 SE +/- 0.40, N = 3 SE +/- 0.42, N = 3 SE +/- 0.79, N = 3 SE +/- 0.71, N = 3 SE +/- 0.82, N = 3 SE +/- 1.18, N = 3 SE +/- 0.53, N = 3 SE +/- 1.46, N = 3 SE +/- 1.50, N = 3 SE +/- 0.51, N = 3 876.45 919.01 928.43 943.29 962.88 974.40 949.15 983.45 956.82 963.00 966.04 954.20 1039.60 1062.32 1. (CXX) g++ options: -O3 -std=c++11 -fopenmp
Test Cases Per Minute Per Watt
OpenBenchmarking.org Test Cases Per Minute Per Watt, More Is Better Darmstadt Automotive Parallel Heterogeneous Suite Backend: OpenMP - Kernel: Euclidean Cluster EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 5 10 15 20 25 18.67 18.67 18.12 16.01 15.18 15.04 11.25 15.32 12.12 10.78 10.48 9.72 16.03 11.43
Result Confidence
OpenBenchmarking.org Test Cases Per Minute, More Is Better Darmstadt Automotive Parallel Heterogeneous Suite Backend: OpenMP - Kernel: Euclidean Cluster EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 200 400 600 800 1000 Min: 876.05 / Avg: 876.45 / Max: 877.26 Min: 918.04 / Avg: 919.01 / Max: 919.66 Min: 926.64 / Avg: 928.43 / Max: 930.77 Min: 942.97 / Avg: 943.29 / Max: 943.63 Min: 962.13 / Avg: 962.88 / Max: 963.5 Min: 973.64 / Avg: 974.4 / Max: 975.08 Min: 947.85 / Avg: 949.15 / Max: 950.57 Min: 982.72 / Avg: 983.45 / Max: 984.87 Min: 955.86 / Avg: 956.82 / Max: 958.45 Min: 961.75 / Avg: 963 / Max: 965.37 Min: 965.08 / Avg: 966.04 / Max: 966.9 Min: 951.37 / Avg: 954.2 / Max: 956.21 Min: 1037.63 / Avg: 1039.6 / Max: 1042.55 Min: 1061.29 / Avg: 1062.32 / Max: 1062.84 1. (CXX) g++ options: -O3 -std=c++11 -fopenmp
InfluxDB This is a benchmark of the InfluxDB open-source time-series database optimized for fast, high-availability storage for IoT and other use-cases. The InfluxDB test profile makes use of InfluxDB Inch for facilitating the benchmarks. Learn more via the OpenBenchmarking.org test page.
Result
OpenBenchmarking.org val/sec, More Is Better InfluxDB 1.8.2 Concurrent Streams: 4 - Batch Size: 10000 - Tags: 2,5000,1 - Points Per Series: 10000 EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 300K 600K 900K 1200K 1500K SE +/- 1045.78, N = 3 SE +/- 1165.03, N = 3 SE +/- 1258.02, N = 3 SE +/- 842.53, N = 3 SE +/- 607.09, N = 3 SE +/- 1998.87, N = 3 SE +/- 2350.83, N = 3 SE +/- 577.19, N = 3 SE +/- 2507.53, N = 3 SE +/- 472.72, N = 3 SE +/- 2041.67, N = 3 SE +/- 1936.89, N = 3 SE +/- 2229.96, N = 3 SE +/- 771.81, N = 3 1041996.8 1143360.5 1172021.1 1188387.2 1248284.1 1262530.4 1197778.9 1162690.9 1208480.8 1215056.1 1209698.0 1212918.2 1155871.8 1247037.6
val/sec Per Watt
OpenBenchmarking.org val/sec Per Watt, More Is Better InfluxDB 1.8.2 Concurrent Streams: 4 - Batch Size: 10000 - Tags: 2,5000,1 - Points Per Series: 10000 EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 4K 8K 12K 16K 20K 19005.43 19247.10 19191.04 17671.85 17298.69 17421.85 12972.75 16668.21 14523.73 12867.29 12804.70 12097.16 15038.78 11716.29
Result Confidence
OpenBenchmarking.org val/sec, More Is Better InfluxDB 1.8.2 Concurrent Streams: 4 - Batch Size: 10000 - Tags: 2,5000,1 - Points Per Series: 10000 EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 200K 400K 600K 800K 1000K Min: 1040104.9 / Avg: 1041996.77 / Max: 1043715.1 Min: 1141134.6 / Avg: 1143360.47 / Max: 1145070.1 Min: 1169540.4 / Avg: 1172021.13 / Max: 1173625.2 Min: 1187003 / Avg: 1188387.17 / Max: 1189911.5 Min: 1247624.2 / Avg: 1248284.1 / Max: 1249496.7 Min: 1259246.9 / Avg: 1262530.43 / Max: 1266147.1 Min: 1194820.8 / Avg: 1197778.87 / Max: 1202422.8 Min: 1161606.1 / Avg: 1162690.93 / Max: 1163575.1 Min: 1203466.2 / Avg: 1208480.8 / Max: 1211047.5 Min: 1214294.3 / Avg: 1215056.1 / Max: 1215921.9 Min: 1206399.7 / Avg: 1209698.03 / Max: 1213431.9 Min: 1209097.9 / Avg: 1212918.2 / Max: 1215383.9 Min: 1152601.1 / Avg: 1155871.8 / Max: 1160133 Min: 1245534.1 / Avg: 1247037.63 / Max: 1248092.1
Etcpak Etcpack is the self-proclaimed "fastest ETC compressor on the planet" with focused on providing open-source, very fast ETC and S3 texture compression support. Learn more via the OpenBenchmarking.org test page.
Result
OpenBenchmarking.org Mpx/s, More Is Better Etcpak 0.7 Configuration: DXT1 EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 300 600 900 1200 1500 SE +/- 1.98, N = 7 SE +/- 1.94, N = 7 SE +/- 2.23, N = 7 SE +/- 1.74, N = 7 SE +/- 1.99, N = 7 SE +/- 1.96, N = 7 SE +/- 2.27, N = 7 SE +/- 1.94, N = 7 SE +/- 1.97, N = 7 SE +/- 2.20, N = 7 SE +/- 1.34, N = 7 SE +/- 0.24, N = 8 SE +/- 2.05, N = 8 976.59 978.85 975.22 1007.95 1018.97 1022.48 1006.92 1035.23 1008.24 1007.22 1019.21 1179.30 1179.02 1. (CXX) g++ options: -O3 -march=native -std=c++11 -lpthread
Mpx/s Per Watt
OpenBenchmarking.org Mpx/s Per Watt, More Is Better Etcpak 0.7 Configuration: DXT1 EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 6 12 18 24 30 27.45 27.10 26.39 23.75 24.45 24.28 17.36 24.75 20.49 17.06 17.07 26.64 19.82
Result Confidence
OpenBenchmarking.org Mpx/s, More Is Better Etcpak 0.7 Configuration: DXT1 EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 200 400 600 800 1000 Min: 970.13 / Avg: 976.59 / Max: 981.11 Min: 972.88 / Avg: 978.85 / Max: 983.32 Min: 970.09 / Avg: 975.22 / Max: 983.12 Min: 1001.21 / Avg: 1007.95 / Max: 1011.76 Min: 1012.27 / Avg: 1018.97 / Max: 1026.96 Min: 1017.68 / Avg: 1022.48 / Max: 1028.23 Min: 999.92 / Avg: 1006.92 / Max: 1013.6 Min: 1031.59 / Avg: 1035.22 / Max: 1042.84 Min: 1002.46 / Avg: 1008.24 / Max: 1013.3 Min: 1002.3 / Avg: 1007.22 / Max: 1013.81 Min: 1017.42 / Avg: 1019.21 / Max: 1027.18 Min: 1178.67 / Avg: 1179.3 / Max: 1180.64 Min: 1173.37 / Avg: 1179.02 / Max: 1186.77 1. (CXX) g++ options: -O3 -march=native -std=c++11 -lpthread
JPEG XL Decoding The JPEG XL Image Coding System is designed to provide next-generation JPEG image capabilities with JPEG XL offering better image quality and compression over legacy JPEG. This test profile is suited for JPEG XL decode performance testing to PNG output file, the pts/jpexl test is for encode performance. Learn more via the OpenBenchmarking.org test page.
rav1e Xiph rav1e is a Rust-written AV1 video encoder. Learn more via the OpenBenchmarking.org test page.
Result
OpenBenchmarking.org Frames Per Second, More Is Better rav1e 0.4 Speed: 10 EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 0.767 1.534 2.301 3.068 3.835 SE +/- 0.006, N = 3 SE +/- 0.008, N = 3 SE +/- 0.008, N = 3 SE +/- 0.009, N = 3 SE +/- 0.004, N = 3 SE +/- 0.005, N = 3 SE +/- 0.006, N = 3 SE +/- 0.009, N = 3 SE +/- 0.005, N = 3 SE +/- 0.008, N = 3 SE +/- 0.009, N = 3 SE +/- 0.009, N = 3 SE +/- 0.010, N = 3 SE +/- 0.017, N = 3 2.822 2.861 2.838 2.926 2.967 2.929 2.937 3.004 2.929 2.894 2.926 2.970 3.409 3.365
Frames Per Second Per Watt
OpenBenchmarking.org Frames Per Second Per Watt, More Is Better rav1e 0.4 Speed: 10 EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 0.0135 0.027 0.0405 0.054 0.0675 0.06 0.06 0.06 0.05 0.06 0.05 0.04 0.06 0.05 0.04 0.04 0.04 0.06 0.04
Result Confidence
OpenBenchmarking.org Frames Per Second, More Is Better rav1e 0.4 Speed: 10 EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 2 4 6 8 10 Min: 2.81 / Avg: 2.82 / Max: 2.83 Min: 2.85 / Avg: 2.86 / Max: 2.87 Min: 2.82 / Avg: 2.84 / Max: 2.85 Min: 2.92 / Avg: 2.93 / Max: 2.94 Min: 2.96 / Avg: 2.97 / Max: 2.97 Min: 2.92 / Avg: 2.93 / Max: 2.94 Min: 2.93 / Avg: 2.94 / Max: 2.94 Min: 2.99 / Avg: 3 / Max: 3.02 Min: 2.92 / Avg: 2.93 / Max: 2.94 Min: 2.88 / Avg: 2.89 / Max: 2.9 Min: 2.91 / Avg: 2.93 / Max: 2.94 Min: 2.95 / Avg: 2.97 / Max: 2.98 Min: 3.39 / Avg: 3.41 / Max: 3.42 Min: 3.35 / Avg: 3.36 / Max: 3.4
Result
OpenBenchmarking.org Frames Per Second, More Is Better rav1e 0.4 Speed: 6 EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 0.3499 0.6998 1.0497 1.3996 1.7495 SE +/- 0.001, N = 3 SE +/- 0.002, N = 3 SE +/- 0.002, N = 3 SE +/- 0.000, N = 3 SE +/- 0.001, N = 3 SE +/- 0.002, N = 3 SE +/- 0.000, N = 3 SE +/- 0.002, N = 3 SE +/- 0.001, N = 3 SE +/- 0.003, N = 3 SE +/- 0.001, N = 3 SE +/- 0.001, N = 3 SE +/- 0.001, N = 3 SE +/- 0.001, N = 3 1.289 1.296 1.293 1.329 1.351 1.338 1.336 1.368 1.331 1.320 1.333 1.342 1.555 1.542
Frames Per Second Per Watt
OpenBenchmarking.org Frames Per Second Per Watt, More Is Better rav1e 0.4 Speed: 6 EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 0.0068 0.0136 0.0204 0.0272 0.034 0.03 0.03 0.03 0.02 0.02 0.02 0.02 0.02 0.02 0.02 0.02 0.02 0.02 0.02
Result Confidence
OpenBenchmarking.org Frames Per Second, More Is Better rav1e 0.4 Speed: 6 EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 2 4 6 8 10 Min: 1.29 / Avg: 1.29 / Max: 1.29 Min: 1.29 / Avg: 1.3 / Max: 1.3 Min: 1.29 / Avg: 1.29 / Max: 1.3 Min: 1.33 / Avg: 1.33 / Max: 1.33 Min: 1.35 / Avg: 1.35 / Max: 1.35 Min: 1.33 / Avg: 1.34 / Max: 1.34 Min: 1.34 / Avg: 1.34 / Max: 1.34 Min: 1.36 / Avg: 1.37 / Max: 1.37 Min: 1.33 / Avg: 1.33 / Max: 1.33 Min: 1.32 / Avg: 1.32 / Max: 1.32 Min: 1.33 / Avg: 1.33 / Max: 1.34 Min: 1.34 / Avg: 1.34 / Max: 1.34 Min: 1.55 / Avg: 1.55 / Max: 1.56 Min: 1.54 / Avg: 1.54 / Max: 1.54
Result
OpenBenchmarking.org Frames Per Second, More Is Better rav1e 0.4 Speed: 5 EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 0.2619 0.5238 0.7857 1.0476 1.3095 SE +/- 0.001, N = 3 SE +/- 0.001, N = 3 SE +/- 0.000, N = 3 SE +/- 0.001, N = 3 SE +/- 0.001, N = 3 SE +/- 0.001, N = 3 SE +/- 0.001, N = 3 SE +/- 0.003, N = 3 SE +/- 0.003, N = 3 SE +/- 0.001, N = 3 SE +/- 0.001, N = 3 SE +/- 0.001, N = 3 SE +/- 0.001, N = 3 SE +/- 0.001, N = 3 0.965 0.972 0.969 0.997 1.009 1.006 0.999 1.024 0.992 0.989 0.993 1.005 1.164 1.156
Frames Per Second Per Watt
OpenBenchmarking.org Frames Per Second Per Watt, More Is Better rav1e 0.4 Speed: 5 EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 0.0045 0.009 0.0135 0.018 0.0225 0.02 0.02 0.02 0.02 0.02 0.02 0.01 0.02 0.02 0.01 0.01 0.01 0.02 0.01
Result Confidence
OpenBenchmarking.org Frames Per Second, More Is Better rav1e 0.4 Speed: 5 EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 2 4 6 8 10 Min: 0.96 / Avg: 0.96 / Max: 0.97 Min: 0.97 / Avg: 0.97 / Max: 0.97 Min: 0.97 / Avg: 0.97 / Max: 0.97 Min: 0.99 / Avg: 1 / Max: 1 Min: 1.01 / Avg: 1.01 / Max: 1.01 Min: 1 / Avg: 1.01 / Max: 1.01 Min: 1 / Avg: 1 / Max: 1 Min: 1.02 / Avg: 1.02 / Max: 1.03 Min: 0.99 / Avg: 0.99 / Max: 1 Min: 0.99 / Avg: 0.99 / Max: 0.99 Min: 0.99 / Avg: 0.99 / Max: 0.99 Min: 1 / Avg: 1.01 / Max: 1.01 Min: 1.16 / Avg: 1.16 / Max: 1.17 Min: 1.15 / Avg: 1.16 / Max: 1.16
Crypto++ Crypto++ is a C++ class library of cryptographic algorithms. Learn more via the OpenBenchmarking.org test page.
Result
OpenBenchmarking.org MiB/second, More Is Better Crypto++ 8.2 Test: Unkeyed Algorithms EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 70 140 210 280 350 SE +/- 0.14, N = 3 SE +/- 0.17, N = 3 SE +/- 0.25, N = 3 SE +/- 0.12, N = 3 SE +/- 0.11, N = 3 SE +/- 0.11, N = 3 SE +/- 0.11, N = 3 SE +/- 0.11, N = 3 SE +/- 0.10, N = 3 SE +/- 0.93, N = 3 SE +/- 0.18, N = 3 SE +/- 0.01, N = 3 SE +/- 0.04, N = 3 SE +/- 0.17, N = 3 286.19 286.18 285.25 294.44 298.49 298.71 294.27 302.93 293.88 292.60 293.81 298.73 343.61 342.93 1. (CXX) g++ options: -g2 -O3 -fPIC -pthread -pipe
MiB/second Per Watt
OpenBenchmarking.org MiB/second Per Watt, More Is Better Crypto++ 8.2 Test: Unkeyed Algorithms EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 2 4 6 8 10 7.09 7.01 6.83 5.98 6.18 6.13 4.26 6.26 5.14 4.52 4.31 4.29 6.50 4.76
Result Confidence
OpenBenchmarking.org MiB/second, More Is Better Crypto++ 8.2 Test: Unkeyed Algorithms EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 60 120 180 240 300 Min: 285.95 / Avg: 286.19 / Max: 286.43 Min: 286.01 / Avg: 286.18 / Max: 286.52 Min: 284.78 / Avg: 285.25 / Max: 285.61 Min: 294.21 / Avg: 294.44 / Max: 294.59 Min: 298.33 / Avg: 298.49 / Max: 298.7 Min: 298.57 / Avg: 298.71 / Max: 298.93 Min: 294.13 / Avg: 294.27 / Max: 294.49 Min: 302.75 / Avg: 302.93 / Max: 303.14 Min: 293.7 / Avg: 293.88 / Max: 294.04 Min: 290.74 / Avg: 292.6 / Max: 293.53 Min: 293.61 / Avg: 293.81 / Max: 294.16 Min: 298.7 / Avg: 298.73 / Max: 298.75 Min: 343.56 / Avg: 343.61 / Max: 343.68 Min: 342.6 / Avg: 342.93 / Max: 343.11 1. (CXX) g++ options: -g2 -O3 -fPIC -pthread -pipe
simdjson This is a benchmark of SIMDJSON, a high performance JSON parser. SIMDJSON aims to be the fastest JSON parser and is used by projects like Microsoft FishStore, Yandex ClickHouse, Shopify, and others. Learn more via the OpenBenchmarking.org test page.
Result
OpenBenchmarking.org GB/s, More Is Better simdjson 0.7.1 Throughput Test: Kostya EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 0.1193 0.2386 0.3579 0.4772 0.5965 SE +/- 0.00, N = 3 SE +/- 0.00, N = 3 SE +/- 0.00, N = 3 SE +/- 0.00, N = 3 SE +/- 0.00, N = 3 SE +/- 0.00, N = 3 SE +/- 0.00, N = 3 SE +/- 0.00, N = 3 SE +/- 0.00, N = 3 SE +/- 0.00, N = 3 SE +/- 0.00, N = 3 SE +/- 0.00, N = 3 SE +/- 0.00, N = 3 SE +/- 0.00, N = 3 0.44 0.44 0.44 0.45 0.46 0.46 0.45 0.46 0.45 0.45 0.45 0.46 0.53 0.53 1. (CXX) g++ options: -O3 -pthread
GB/s Per Watt
OpenBenchmarking.org GB/s Per Watt, More Is Better simdjson 0.7.1 Throughput Test: Kostya EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 0.0023 0.0046 0.0069 0.0092 0.0115 0.01 0.01 0.01 0.01 0.01 0.01 0.01 0.01 0.01 0.01 0.01 0.01 0.01 0.01
Result Confidence
OpenBenchmarking.org GB/s, More Is Better simdjson 0.7.1 Throughput Test: Kostya EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 2 4 6 8 10 Min: 0.43 / Avg: 0.44 / Max: 0.44 Min: 0.44 / Avg: 0.44 / Max: 0.44 Min: 0.44 / Avg: 0.44 / Max: 0.44 Min: 0.45 / Avg: 0.45 / Max: 0.45 Min: 0.46 / Avg: 0.46 / Max: 0.46 Min: 0.46 / Avg: 0.46 / Max: 0.46 Min: 0.45 / Avg: 0.45 / Max: 0.45 Min: 0.46 / Avg: 0.46 / Max: 0.46 Min: 0.45 / Avg: 0.45 / Max: 0.45 Min: 0.45 / Avg: 0.45 / Max: 0.45 Min: 0.45 / Avg: 0.45 / Max: 0.45 Min: 0.46 / Avg: 0.46 / Max: 0.46 Min: 0.53 / Avg: 0.53 / Max: 0.53 Min: 0.53 / Avg: 0.53 / Max: 0.53 1. (CXX) g++ options: -O3 -pthread
ECP-CANDLE The CANDLE benchmark codes implement deep learning architectures relevant to problems in cancer. These architectures address problems at different biological scales, specifically problems at the molecular, cellular and population scales. Learn more via the OpenBenchmarking.org test page.
OpenBenchmarking.org Seconds, Fewer Is Better ECP-CANDLE 0.3 Benchmark: P1B2 EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 10 20 30 40 50 44.49 43.38 42.78 41.15 41.33 41.04 41.52 40.89 41.91 41.85 42.35 43.16 36.98 40.55
Rodinia Rodinia is a suite focused upon accelerating compute-intensive applications with accelerators. CUDA, OpenMP, and OpenCL parallel models are supported by the included applications. This profile utilizes select OpenCL, NVIDIA CUDA and OpenMP test binaries at the moment. Learn more via the OpenBenchmarking.org test page.
Result
OpenBenchmarking.org Seconds, Fewer Is Better Rodinia 3.1 Test: OpenMP HotSpot3D EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 20 40 60 80 100 SE +/- 1.23, N = 5 SE +/- 0.54, N = 3 SE +/- 0.58, N = 3 SE +/- 0.56, N = 3 SE +/- 0.65, N = 3 SE +/- 0.50, N = 3 SE +/- 0.36, N = 3 SE +/- 0.18, N = 3 SE +/- 0.05, N = 3 SE +/- 0.98, N = 3 SE +/- 0.11, N = 3 SE +/- 0.46, N = 3 SE +/- 0.07, N = 3 SE +/- 0.58, N = 3 110.50 109.60 108.86 106.77 105.28 105.24 107.48 103.80 108.25 107.70 107.88 106.58 93.08 92.08 1. (CXX) g++ options: -O2 -lOpenCL
Result Confidence
OpenBenchmarking.org Seconds, Fewer Is Better Rodinia 3.1 Test: OpenMP HotSpot3D EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 20 40 60 80 100 Min: 108.22 / Avg: 110.5 / Max: 115.08 Min: 108.57 / Avg: 109.6 / Max: 110.38 Min: 108.23 / Avg: 108.86 / Max: 110.01 Min: 106.14 / Avg: 106.77 / Max: 107.88 Min: 104.57 / Avg: 105.28 / Max: 106.58 Min: 104.53 / Avg: 105.24 / Max: 106.2 Min: 106.77 / Avg: 107.48 / Max: 107.96 Min: 103.43 / Avg: 103.8 / Max: 104 Min: 108.18 / Avg: 108.25 / Max: 108.34 Min: 105.86 / Avg: 107.7 / Max: 109.21 Min: 107.69 / Avg: 107.88 / Max: 108.06 Min: 105.66 / Avg: 106.58 / Max: 107.16 Min: 92.93 / Avg: 93.08 / Max: 93.17 Min: 91.23 / Avg: 92.08 / Max: 93.18 1. (CXX) g++ options: -O2 -lOpenCL
JPEG XL The JPEG XL Image Coding System is designed to provide next-generation JPEG image capabilities with JPEG XL offering better image quality and compression over legacy JPEG. This test profile is currently focused on the multi-threaded JPEG XL image encode performance. Learn more via the OpenBenchmarking.org test page.
DaCapo Benchmark This test runs the DaCapo Benchmarks written in Java and intended to test system/CPU performance. Learn more via the OpenBenchmarking.org test page.
Result
OpenBenchmarking.org msec, Fewer Is Better DaCapo Benchmark 9.12-MR1 Java Test: Tradebeans EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 1000 2000 3000 4000 5000 SE +/- 22.80, N = 5 SE +/- 33.20, N = 5 SE +/- 32.99, N = 5 SE +/- 20.03, N = 5 SE +/- 9.28, N = 5 SE +/- 28.80, N = 5 SE +/- 15.90, N = 5 SE +/- 12.58, N = 5 SE +/- 22.36, N = 5 SE +/- 25.14, N = 5 SE +/- 33.26, N = 5 SE +/- 35.92, N = 5 SE +/- 35.77, N = 5 3894 3971 3881 4138 3993 3912 4303 3886 4218 4457 4407 3724 4085
Result Confidence
OpenBenchmarking.org msec, Fewer Is Better DaCapo Benchmark 9.12-MR1 Java Test: Tradebeans EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 800 1600 2400 3200 4000 Min: 3832 / Avg: 3893.8 / Max: 3948 Min: 3886 / Avg: 3970.6 / Max: 4055 Min: 3765 / Avg: 3881.4 / Max: 3963 Min: 4074 / Avg: 4138.2 / Max: 4180 Min: 3975 / Avg: 3993.2 / Max: 4028 Min: 3827 / Avg: 3912.2 / Max: 3971 Min: 4246 / Avg: 4302.6 / Max: 4341 Min: 3845 / Avg: 3886.4 / Max: 3916 Min: 4158 / Avg: 4217.6 / Max: 4273 Min: 4392 / Avg: 4456.8 / Max: 4536 Min: 4330 / Avg: 4406.6 / Max: 4494 Min: 3653 / Avg: 3723.6 / Max: 3860 Min: 3969 / Avg: 4084.8 / Max: 4158
JPEG XL Decoding The JPEG XL Image Coding System is designed to provide next-generation JPEG image capabilities with JPEG XL offering better image quality and compression over legacy JPEG. This test profile is suited for JPEG XL decode performance testing to PNG output file, the pts/jpexl test is for encode performance. Learn more via the OpenBenchmarking.org test page.
Redis Redis is an open-source in-memory data structure store, used as a database, cache, and message broker. Learn more via the OpenBenchmarking.org test page.
Result
OpenBenchmarking.org Requests Per Second, More Is Better Redis 6.0.9 Test: GET EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 400K 800K 1200K 1600K 2000K SE +/- 18495.33, N = 15 SE +/- 12289.67, N = 3 SE +/- 14367.89, N = 15 SE +/- 13583.32, N = 6 SE +/- 13170.58, N = 15 SE +/- 18437.40, N = 3 SE +/- 21214.43, N = 3 SE +/- 13573.21, N = 15 SE +/- 8071.25, N = 3 SE +/- 11135.64, N = 15 SE +/- 13883.40, N = 3 SE +/- 18256.32, N = 3 SE +/- 19118.80, N = 4 SE +/- 17849.12, N = 5 1421564.35 1372468.88 1414840.41 1438157.73 1466557.03 1419600.13 1481804.00 1508082.41 1450496.71 1437534.23 1417246.67 1482738.92 1601070.50 1635794.57 1. (CXX) g++ options: -MM -MT -g3 -fvisibility=hidden -O3
Requests Per Second Per Watt
OpenBenchmarking.org Requests Per Second Per Watt, More Is Better Redis 6.0.9 Test: GET EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 9K 18K 27K 36K 45K 42939.75 40587.49 39449.14 36649.44 39042.93 35995.93 27229.69 38176.82 31741.99 27083.65 25840.00 27989.20 37914.84 29783.14
Result Confidence
OpenBenchmarking.org Requests Per Second, More Is Better Redis 6.0.9 Test: GET EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 300K 600K 900K 1200K 1500K Min: 1340662.25 / Avg: 1421564.35 / Max: 1628409.75 Min: 1350621.38 / Avg: 1372468.88 / Max: 1393145.75 Min: 1349900.62 / Avg: 1414840.41 / Max: 1535877.12 Min: 1387351.75 / Avg: 1438157.73 / Max: 1487252.88 Min: 1388893.38 / Avg: 1466557.03 / Max: 1567157.5 Min: 1387942.88 / Avg: 1419600.13 / Max: 1451804.88 Min: 1456461.38 / Avg: 1481804 / Max: 1523945.12 Min: 1433897.38 / Avg: 1508082.41 / Max: 1604899.38 Min: 1439056 / Avg: 1450496.71 / Max: 1466079.5 Min: 1363529.88 / Avg: 1437534.23 / Max: 1507163.75 Min: 1397042.75 / Avg: 1417246.67 / Max: 1443844 Min: 1456664.25 / Avg: 1482738.92 / Max: 1517911.38 Min: 1561051.5 / Avg: 1601070.5 / Max: 1650709.75 Min: 1586048 / Avg: 1635794.57 / Max: 1671133.62 1. (CXX) g++ options: -MM -MT -g3 -fvisibility=hidden -O3
Tinymembench This benchmark tests the system memory (RAM) performance. Learn more via the OpenBenchmarking.org test page.
Result
OpenBenchmarking.org MB/s, More Is Better Tinymembench 2018-05-28 Standard Memset EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 4K 8K 12K 16K 20K SE +/- 21.61, N = 3 SE +/- 37.39, N = 3 SE +/- 18.80, N = 3 SE +/- 20.90, N = 3 SE +/- 46.42, N = 3 SE +/- 13.93, N = 3 SE +/- 27.08, N = 3 SE +/- 39.21, N = 3 SE +/- 217.68, N = 3 SE +/- 52.61, N = 3 SE +/- 217.98, N = 3 SE +/- 28.30, N = 3 SE +/- 39.37, N = 3 14571.7 14776.4 14921.3 14820.3 14961.4 15097.1 14786.9 15872.0 16494.4 15640.1 17329.8 16357.2 15585.7 1. (CC) gcc options: -O2 -lm
MB/s Per Watt
OpenBenchmarking.org MB/s Per Watt, More Is Better Tinymembench 2018-05-28 Standard Memset EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 70 140 210 280 350 332.00 334.79 333.88 279.72 284.81 289.31 202.28 303.95 268.71 215.62 236.78 286.11 209.76
Result Confidence
OpenBenchmarking.org MB/s, More Is Better Tinymembench 2018-05-28 Standard Memset EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 3K 6K 9K 12K 15K Min: 14546.4 / Avg: 14571.7 / Max: 14614.7 Min: 14704.8 / Avg: 14776.4 / Max: 14830.9 Min: 14884.6 / Avg: 14921.27 / Max: 14946.8 Min: 14781.5 / Avg: 14820.27 / Max: 14853.2 Min: 14876.5 / Avg: 14961.37 / Max: 15036.4 Min: 15074.8 / Avg: 15097.07 / Max: 15122.7 Min: 14734.2 / Avg: 14786.93 / Max: 14824 Min: 15794.6 / Avg: 15872.03 / Max: 15921.5 Min: 16092.5 / Avg: 16494.43 / Max: 16840.3 Min: 15534.9 / Avg: 15640.1 / Max: 15694.5 Min: 16900.6 / Avg: 17329.83 / Max: 17610.5 Min: 16301.7 / Avg: 16357.2 / Max: 16394.6 Min: 15512.6 / Avg: 15585.7 / Max: 15647.6 1. (CC) gcc options: -O2 -lm
LibRaw LibRaw is a RAW image decoder for digital camera photos. This test profile runs LibRaw's post-processing benchmark. Learn more via the OpenBenchmarking.org test page.
Result
OpenBenchmarking.org Mpix/sec, More Is Better LibRaw 0.20 Post-Processing Benchmark EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 9 18 27 36 45 SE +/- 0.02, N = 3 SE +/- 0.05, N = 3 SE +/- 0.10, N = 3 SE +/- 0.02, N = 3 SE +/- 0.07, N = 3 SE +/- 0.09, N = 3 SE +/- 0.07, N = 3 SE +/- 0.05, N = 3 SE +/- 0.23, N = 3 SE +/- 0.17, N = 3 SE +/- 0.09, N = 3 SE +/- 0.01, N = 3 SE +/- 0.03, N = 3 32.48 33.12 33.08 33.71 34.03 34.11 33.06 34.38 33.64 34.01 34.50 38.59 38.01 1. (CXX) g++ options: -O2 -fopenmp -ljpeg -lz -lm
Mpix/sec Per Watt
OpenBenchmarking.org Mpix/sec Per Watt, More Is Better LibRaw 0.20 Post-Processing Benchmark EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 0.1395 0.279 0.4185 0.558 0.6975 0.62 0.62 0.61 0.55 0.55 0.55 0.41 0.55 0.47 0.41 0.40 0.53 0.40
Result Confidence
OpenBenchmarking.org Mpix/sec, More Is Better LibRaw 0.20 Post-Processing Benchmark EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 8 16 24 32 40 Min: 32.44 / Avg: 32.48 / Max: 32.51 Min: 33.04 / Avg: 33.12 / Max: 33.21 Min: 32.96 / Avg: 33.08 / Max: 33.27 Min: 33.67 / Avg: 33.71 / Max: 33.74 Min: 33.89 / Avg: 34.03 / Max: 34.12 Min: 33.96 / Avg: 34.11 / Max: 34.27 Min: 32.93 / Avg: 33.06 / Max: 33.13 Min: 34.31 / Avg: 34.38 / Max: 34.48 Min: 33.2 / Avg: 33.64 / Max: 34 Min: 33.71 / Avg: 34.01 / Max: 34.31 Min: 34.32 / Avg: 34.5 / Max: 34.63 Min: 38.57 / Avg: 38.59 / Max: 38.62 Min: 37.96 / Avg: 38.01 / Max: 38.06 1. (CXX) g++ options: -O2 -fopenmp -ljpeg -lz -lm
ONNX Runtime ONNX Runtime is developed by Microsoft and partners as a open-source, cross-platform, high performance machine learning inferencing and training accelerator. This test profile runs the ONNX Runtime with various models available from the ONNX Zoo. Learn more via the OpenBenchmarking.org test page.
Result
OpenBenchmarking.org Inferences Per Minute, More Is Better ONNX Runtime 1.6 Model: yolov4 - Device: OpenMP CPU EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 60 120 180 240 300 SE +/- 0.60, N = 3 SE +/- 0.29, N = 3 SE +/- 0.33, N = 3 SE +/- 0.29, N = 3 SE +/- 0.17, N = 3 SE +/- 0.88, N = 3 SE +/- 0.17, N = 3 SE +/- 0.67, N = 3 SE +/- 0.50, N = 3 SE +/- 1.01, N = 3 SE +/- 0.93, N = 3 SE +/- 1.30, N = 3 SE +/- 1.00, N = 3 243 259 267 277 280 277 271 285 264 263 243 240 262 248 1. (CXX) g++ options: -fopenmp -ffunction-sections -fdata-sections -O3 -ldl -lrt
Inferences Per Minute Per Watt
OpenBenchmarking.org Inferences Per Minute Per Watt, More Is Better ONNX Runtime 1.6 Model: yolov4 - Device: OpenMP CPU EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 0.7695 1.539 2.3085 3.078 3.8475 3.42 3.26 3.28 2.95 2.60 2.49 1.98 2.57 2.01 1.75 1.58 1.55 2.55 1.71
Result Confidence
OpenBenchmarking.org Inferences Per Minute, More Is Better ONNX Runtime 1.6 Model: yolov4 - Device: OpenMP CPU EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 50 100 150 200 250 Min: 242.5 / Avg: 243.33 / Max: 244.5 Min: 258.5 / Avg: 259 / Max: 259.5 Min: 266.5 / Avg: 267.17 / Max: 267.5 Min: 276.5 / Avg: 277 / Max: 277.5 Min: 279.5 / Avg: 279.67 / Max: 280 Min: 275.5 / Avg: 276.83 / Max: 278.5 Min: 270.5 / Avg: 270.67 / Max: 271 Min: 284.5 / Avg: 285.17 / Max: 286.5 Min: 263 / Avg: 263.5 / Max: 264.5 Min: 261 / Avg: 262.83 / Max: 264.5 Min: 242 / Avg: 243.17 / Max: 245 Min: 238 / Avg: 240.33 / Max: 242.5 Min: 260 / Avg: 262 / Max: 263 1. (CXX) g++ options: -fopenmp -ffunction-sections -fdata-sections -O3 -ldl -lrt
Redis Redis is an open-source in-memory data structure store, used as a database, cache, and message broker. Learn more via the OpenBenchmarking.org test page.
Result
OpenBenchmarking.org Requests Per Second, More Is Better Redis 6.0.9 Test: SET EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 300K 600K 900K 1200K 1500K SE +/- 11537.36, N = 4 SE +/- 17229.52, N = 15 SE +/- 15930.17, N = 3 SE +/- 12613.83, N = 5 SE +/- 4313.29, N = 3 SE +/- 14615.10, N = 4 SE +/- 15826.22, N = 15 SE +/- 15275.38, N = 3 SE +/- 14106.76, N = 3 SE +/- 16083.41, N = 14 SE +/- 18435.82, N = 15 SE +/- 22602.36, N = 12 SE +/- 13442.74, N = 3 SE +/- 8091.69, N = 3 1126925.50 1156241.74 1143594.63 1173570.00 1147451.38 1180459.91 1186674.32 1189270.87 1170719.46 1183717.45 1200527.31 1228831.79 1315900.46 1336546.21 1. (CXX) g++ options: -MM -MT -g3 -fvisibility=hidden -O3
Requests Per Second Per Watt
OpenBenchmarking.org Requests Per Second Per Watt, More Is Better Redis 6.0.9 Test: SET EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 7K 14K 21K 28K 35K 33238.20 33520.26 31275.55 29192.78 29418.44 29043.85 21182.66 29411.07 24980.53 21774.45 21301.37 22530.98 30367.37 23705.79
Result Confidence
OpenBenchmarking.org Requests Per Second, More Is Better Redis 6.0.9 Test: SET EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 200K 400K 600K 800K 1000K Min: 1105957.12 / Avg: 1126925.5 / Max: 1159285.88 Min: 1088613.12 / Avg: 1156241.74 / Max: 1310666.25 Min: 1112121 / Avg: 1143594.63 / Max: 1163617.38 Min: 1141950.88 / Avg: 1173570 / Max: 1208467 Min: 1143020.75 / Avg: 1147451.38 / Max: 1156076.88 Min: 1147582.38 / Avg: 1180459.91 / Max: 1209351.5 Min: 1117600.38 / Avg: 1186674.32 / Max: 1295341 Min: 1161717.5 / Avg: 1189270.87 / Max: 1214476.5 Min: 1151024 / Avg: 1170719.46 / Max: 1198062 Min: 1125387.38 / Avg: 1183717.45 / Max: 1363145 Min: 1107542.38 / Avg: 1200527.31 / Max: 1349007.38 Min: 1142730.12 / Avg: 1228831.79 / Max: 1378956.5 Min: 1289503 / Avg: 1315900.46 / Max: 1333515.38 Min: 1320510.25 / Avg: 1336546.21 / Max: 1346451.62 1. (CXX) g++ options: -MM -MT -g3 -fvisibility=hidden -O3
Result
OpenBenchmarking.org Requests Per Second, More Is Better Redis 6.0.9 Test: LPUSH EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 300K 600K 900K 1200K 1500K SE +/- 6585.32, N = 3 SE +/- 15424.51, N = 15 SE +/- 3774.33, N = 3 SE +/- 8436.86, N = 3 SE +/- 11072.90, N = 15 SE +/- 9569.43, N = 3 SE +/- 10288.34, N = 15 SE +/- 11205.82, N = 5 SE +/- 7701.66, N = 3 SE +/- 4227.00, N = 3 SE +/- 5890.12, N = 3 SE +/- 7054.62, N = 13 SE +/- 6374.74, N = 3 SE +/- 8000.25, N = 3 991962.08 1037523.56 997652.46 1030785.79 1045821.59 1045486.81 1059976.32 1067438.77 1013049.13 1018402.69 1039389.17 1031876.33 1174520.46 1174427.00 1. (CXX) g++ options: -MM -MT -g3 -fvisibility=hidden -O3
Requests Per Second Per Watt
OpenBenchmarking.org Requests Per Second Per Watt, More Is Better Redis 6.0.9 Test: LPUSH EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 6K 12K 18K 24K 30K 28993.77 29596.02 27079.37 25453.57 26554.24 25519.76 18680.49 26166.33 21454.67 18554.91 18391.09 18361.54 26954.89 20551.40
Result Confidence
OpenBenchmarking.org Requests Per Second, More Is Better Redis 6.0.9 Test: LPUSH EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 200K 400K 600K 800K 1000K Min: 978965.06 / Avg: 991962.08 / Max: 1000306.5 Min: 976187.38 / Avg: 1037523.56 / Max: 1152915 Min: 990504 / Avg: 997652.46 / Max: 1003327 Min: 1014202.06 / Avg: 1030785.79 / Max: 1041775.19 Min: 987478.25 / Avg: 1045821.59 / Max: 1105957.12 Min: 1029134.12 / Avg: 1045486.81 / Max: 1062275 Min: 1006359.25 / Avg: 1059976.32 / Max: 1149564.75 Min: 1044932.12 / Avg: 1067438.77 / Max: 1106467.75 Min: 1004120.12 / Avg: 1013049.13 / Max: 1028383.38 Min: 1013376.56 / Avg: 1018402.69 / Max: 1026802.69 Min: 1027854.88 / Avg: 1039389.17 / Max: 1047230.12 Min: 1004120.12 / Avg: 1031876.33 / Max: 1093254.62 Min: 1167284.62 / Avg: 1174520.46 / Max: 1187229.25 Min: 1165101.25 / Avg: 1174427 / Max: 1190349.75 1. (CXX) g++ options: -MM -MT -g3 -fvisibility=hidden -O3
Result
OpenBenchmarking.org Requests Per Second, More Is Better Redis 6.0.9 Test: SADD EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 300K 600K 900K 1200K 1500K SE +/- 8933.33, N = 3 SE +/- 13873.03, N = 3 SE +/- 16958.48, N = 15 SE +/- 8695.76, N = 3 SE +/- 20897.40, N = 15 SE +/- 16125.60, N = 15 SE +/- 3475.48, N = 3 SE +/- 17960.88, N = 3 SE +/- 17355.22, N = 15 SE +/- 16607.14, N = 15 SE +/- 12423.96, N = 3 SE +/- 13671.93, N = 15 SE +/- 11422.05, N = 10 SE +/- 8827.27, N = 3 1302498.71 1285763.37 1325778.66 1345235.04 1393300.08 1387616.13 1319402.58 1388206.16 1349388.24 1360852.66 1328786.50 1347163.14 1510395.93 1514902.30 1. (CXX) g++ options: -MM -MT -g3 -fvisibility=hidden -O3
Requests Per Second Per Watt
OpenBenchmarking.org Requests Per Second Per Watt, More Is Better Redis 6.0.9 Test: SADD EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 8K 16K 24K 32K 40K 39084.39 37338.23 36856.97 34516.59 36325.60 34715.91 23687.13 34766.37 29367.10 25475.97 24141.05 25016.28 35697.64 27216.48
Result Confidence
OpenBenchmarking.org Requests Per Second, More Is Better Redis 6.0.9 Test: SADD EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 300K 600K 900K 1200K 1500K Min: 1285520.5 / Avg: 1302498.71 / Max: 1315806.38 Min: 1260088.75 / Avg: 1285763.37 / Max: 1307710.75 Min: 1238091.38 / Avg: 1325778.66 / Max: 1481061.62 Min: 1327844.88 / Avg: 1345235.04 / Max: 1354117.75 Min: 1309088.62 / Avg: 1393300.08 / Max: 1560067.38 Min: 1293828.38 / Avg: 1387616.13 / Max: 1488321.5 Min: 1313197.62 / Avg: 1319402.58 / Max: 1325218.12 Min: 1357040.62 / Avg: 1388206.16 / Max: 1419258.62 Min: 1255650.38 / Avg: 1349388.24 / Max: 1542049.62 Min: 1297029.25 / Avg: 1360852.66 / Max: 1498136.88 Min: 1314595.5 / Avg: 1328786.5 / Max: 1353546.25 Min: 1270656.12 / Avg: 1347163.14 / Max: 1487873.75 Min: 1461584.38 / Avg: 1510395.93 / Max: 1591637.12 Min: 1500849.5 / Avg: 1514902.33 / Max: 1531183.5 1. (CXX) g++ options: -MM -MT -g3 -fvisibility=hidden -O3
JPEG XL The JPEG XL Image Coding System is designed to provide next-generation JPEG image capabilities with JPEG XL offering better image quality and compression over legacy JPEG. This test profile is currently focused on the multi-threaded JPEG XL image encode performance. Learn more via the OpenBenchmarking.org test page.
Hugin Hugin is an open-source, cross-platform panorama photo stitcher software package. This test profile times how long it takes to run the assistant and panorama photo stitching on a set of images. Learn more via the OpenBenchmarking.org test page.
Result
OpenBenchmarking.org Seconds, Fewer Is Better Hugin Panorama Photo Assistant + Stitching Time EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 13 26 39 52 65 SE +/- 0.80, N = 3 SE +/- 0.07, N = 3 SE +/- 0.50, N = 3 SE +/- 0.45, N = 3 SE +/- 0.41, N = 3 SE +/- 0.42, N = 3 SE +/- 0.36, N = 3 SE +/- 0.30, N = 3 SE +/- 0.28, N = 3 SE +/- 0.23, N = 3 SE +/- 0.32, N = 3 SE +/- 0.33, N = 3 SE +/- 0.24, N = 3 59.31 57.24 56.10 55.77 53.36 53.72 55.57 52.99 55.42 55.95 55.68 52.99 50.59
Result Confidence
OpenBenchmarking.org Seconds, Fewer Is Better Hugin Panorama Photo Assistant + Stitching Time EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 12 24 36 48 60 Min: 57.78 / Avg: 59.31 / Max: 60.47 Min: 57.12 / Avg: 57.24 / Max: 57.34 Min: 55.21 / Avg: 56.1 / Max: 56.93 Min: 54.93 / Avg: 55.77 / Max: 56.46 Min: 52.68 / Avg: 53.36 / Max: 54.09 Min: 52.98 / Avg: 53.72 / Max: 54.43 Min: 55.11 / Avg: 55.57 / Max: 56.28 Min: 52.43 / Avg: 52.99 / Max: 53.44 Min: 54.86 / Avg: 55.42 / Max: 55.71 Min: 55.51 / Avg: 55.95 / Max: 56.27 Min: 55.04 / Avg: 55.68 / Max: 56.12 Min: 52.38 / Avg: 52.99 / Max: 53.51 Min: 50.13 / Avg: 50.59 / Max: 50.91
KeyDB A benchmark of KeyDB as a multi-threaded fork of the Redis server. The KeyDB benchmark is conducted using memtier-benchmark. Learn more via the OpenBenchmarking.org test page.
Result
OpenBenchmarking.org Ops/sec, More Is Better KeyDB 6.0.16 EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 90K 180K 270K 360K 450K SE +/- 533.37, N = 3 SE +/- 1365.59, N = 3 SE +/- 1079.81, N = 3 SE +/- 639.41, N = 3 SE +/- 3460.73, N = 3 SE +/- 430.27, N = 3 SE +/- 2791.26, N = 3 SE +/- 3270.77, N = 3 SE +/- 5135.26, N = 3 SE +/- 4280.31, N = 3 SE +/- 4382.81, N = 3 SE +/- 4507.61, N = 3 SE +/- 183.84, N = 3 SE +/- 428.23, N = 3 399110.88 418080.47 420324.96 405905.78 415583.96 413354.59 404313.15 422944.46 394639.23 386824.54 376241.11 371448.21 424600.07 433091.73 1. (CXX) g++ options: -O2 -levent_openssl -levent -lcrypto -lssl -lpthread -lz -lpcre
Ops/sec Per Watt
OpenBenchmarking.org Ops/sec Per Watt, More Is Better KeyDB 6.0.16 EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 1600 3200 4800 6400 8000 7415.88 7232.18 7158.88 6206.07 5903.16 5856.34 4517.76 6102.85 4838.07 4228.11 4095.78 3833.65 5640.60 4143.95
Result Confidence
OpenBenchmarking.org Ops/sec, More Is Better KeyDB 6.0.16 EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 80K 160K 240K 320K 400K Min: 398044.81 / Avg: 399110.88 / Max: 399676.81 Min: 416043.78 / Avg: 418080.47 / Max: 420674.69 Min: 419061.55 / Avg: 420324.96 / Max: 422473.5 Min: 404993.42 / Avg: 405905.78 / Max: 407138 Min: 412054.17 / Avg: 415583.96 / Max: 422504.97 Min: 412498.94 / Avg: 413354.59 / Max: 413861.79 Min: 399536.5 / Avg: 404313.15 / Max: 409203.69 Min: 416505.35 / Avg: 422944.46 / Max: 427162.66 Min: 385396.59 / Avg: 394639.23 / Max: 403139.08 Min: 379984.9 / Avg: 386824.54 / Max: 394702.8 Min: 368183.94 / Avg: 376241.11 / Max: 383259.45 Min: 362545.96 / Avg: 371448.21 / Max: 377131.41 Min: 424252.48 / Avg: 424600.07 / Max: 424877.7 Min: 432304.57 / Avg: 433091.73 / Max: 433777.59 1. (CXX) g++ options: -O2 -levent_openssl -levent -lcrypto -lssl -lpthread -lz -lpcre
PlaidML This test profile uses PlaidML deep learning framework developed by Intel for offering up various benchmarks. Learn more via the OpenBenchmarking.org test page.
Result
OpenBenchmarking.org FPS, More Is Better PlaidML FP16: No - Mode: Inference - Network: ResNet 50 - Device: CPU EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 1.3478 2.6956 4.0434 5.3912 6.739 SE +/- 0.02, N = 3 SE +/- 0.04, N = 3 SE +/- 0.01, N = 3 SE +/- 0.01, N = 3 SE +/- 0.03, N = 3 SE +/- 0.01, N = 3 SE +/- 0.02, N = 3 SE +/- 0.01, N = 3 SE +/- 0.01, N = 3 SE +/- 0.01, N = 3 SE +/- 0.02, N = 3 SE +/- 0.01, N = 3 SE +/- 0.03, N = 3 SE +/- 0.05, N = 3 5.17 5.53 5.57 5.67 5.68 5.76 5.71 5.84 5.67 5.72 5.76 5.56 5.96 5.99
FPS Per Watt
OpenBenchmarking.org FPS Per Watt, More Is Better PlaidML FP16: No - Mode: Inference - Network: ResNet 50 - Device: CPU EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 0.0248 0.0496 0.0744 0.0992 0.124 0.10 0.11 0.11 0.09 0.09 0.09 0.07 0.10 0.08 0.07 0.07 0.06 0.09 0.07
Result Confidence
OpenBenchmarking.org FPS, More Is Better PlaidML FP16: No - Mode: Inference - Network: ResNet 50 - Device: CPU EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 2 4 6 8 10 Min: 5.14 / Avg: 5.17 / Max: 5.2 Min: 5.46 / Avg: 5.53 / Max: 5.61 Min: 5.55 / Avg: 5.57 / Max: 5.59 Min: 5.65 / Avg: 5.67 / Max: 5.68 Min: 5.62 / Avg: 5.68 / Max: 5.72 Min: 5.73 / Avg: 5.76 / Max: 5.78 Min: 5.68 / Avg: 5.71 / Max: 5.73 Min: 5.82 / Avg: 5.84 / Max: 5.86 Min: 5.64 / Avg: 5.67 / Max: 5.69 Min: 5.7 / Avg: 5.72 / Max: 5.73 Min: 5.73 / Avg: 5.76 / Max: 5.79 Min: 5.54 / Avg: 5.56 / Max: 5.58 Min: 5.9 / Avg: 5.96 / Max: 6.02 Min: 5.9 / Avg: 5.99 / Max: 6.05
AOM AV1 This is a simple test of the AOMedia AV1 encoder run on the CPU with a sample video file. Learn more via the OpenBenchmarking.org test page.
Result
OpenBenchmarking.org Frames Per Second, More Is Better AOM AV1 2.0 Encoder Mode: Speed 8 Realtime EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 8 16 24 32 40 SE +/- 0.03, N = 3 SE +/- 0.03, N = 3 SE +/- 0.04, N = 3 SE +/- 0.11, N = 3 SE +/- 0.07, N = 3 SE +/- 0.34, N = 5 SE +/- 0.03, N = 3 SE +/- 0.06, N = 3 SE +/- 0.02, N = 3 SE +/- 0.03, N = 3 SE +/- 0.00, N = 3 SE +/- 0.03, N = 3 SE +/- 0.06, N = 3 SE +/- 0.03, N = 3 31.08 31.63 32.03 32.62 32.99 32.86 32.35 33.51 32.60 32.31 32.54 32.78 35.48 35.56 1. (CXX) g++ options: -O3 -std=c++11 -U_FORTIFY_SOURCE -lm -lpthread
Frames Per Second Per Watt
OpenBenchmarking.org Frames Per Second Per Watt, More Is Better AOM AV1 2.0 Encoder Mode: Speed 8 Realtime EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 0.1508 0.3016 0.4524 0.6032 0.754 0.67 0.67 0.66 0.59 0.59 0.59 0.45 0.60 0.51 0.44 0.44 0.42 0.58 0.42
Result Confidence
OpenBenchmarking.org Frames Per Second, More Is Better AOM AV1 2.0 Encoder Mode: Speed 8 Realtime EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 8 16 24 32 40 Min: 31.04 / Avg: 31.08 / Max: 31.13 Min: 31.58 / Avg: 31.63 / Max: 31.69 Min: 31.98 / Avg: 32.03 / Max: 32.11 Min: 32.42 / Avg: 32.62 / Max: 32.79 Min: 32.85 / Avg: 32.99 / Max: 33.06 Min: 31.51 / Avg: 32.86 / Max: 33.21 Min: 32.3 / Avg: 32.35 / Max: 32.38 Min: 33.4 / Avg: 33.51 / Max: 33.6 Min: 32.57 / Avg: 32.6 / Max: 32.62 Min: 32.25 / Avg: 32.31 / Max: 32.36 Min: 32.54 / Avg: 32.54 / Max: 32.55 Min: 32.72 / Avg: 32.78 / Max: 32.82 Min: 35.37 / Avg: 35.48 / Max: 35.54 Min: 35.51 / Avg: 35.56 / Max: 35.62 1. (CXX) g++ options: -O3 -std=c++11 -U_FORTIFY_SOURCE -lm -lpthread
JPEG XL The JPEG XL Image Coding System is designed to provide next-generation JPEG image capabilities with JPEG XL offering better image quality and compression over legacy JPEG. This test profile is currently focused on the multi-threaded JPEG XL image encode performance. Learn more via the OpenBenchmarking.org test page.
WireGuard + Linux Networking Stack Stress Test This is a benchmark of the WireGuard secure VPN tunnel and Linux networking stack stress test. The test runs on the local host but does require root permissions to run. The way it works is it creates three namespaces. ns0 has a loopback device. ns1 and ns2 each have wireguard devices. Those two wireguard devices send traffic through the loopback device of ns0. The end result of this is that tests wind up testing encryption and decryption at the same time -- a pretty CPU and scheduler-heavy workflow. Learn more via the OpenBenchmarking.org test page.
Result
OpenBenchmarking.org Seconds, Fewer Is Better WireGuard + Linux Networking Stack Stress Test EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 70 140 210 280 350 SE +/- 0.07, N = 3 SE +/- 0.55, N = 3 SE +/- 0.25, N = 3 SE +/- 0.22, N = 3 SE +/- 1.52, N = 3 SE +/- 1.08, N = 3 SE +/- 0.79, N = 3 SE +/- 0.63, N = 3 SE +/- 0.75, N = 3 SE +/- 1.82, N = 3 SE +/- 1.60, N = 3 SE +/- 0.79, N = 3 SE +/- 0.12, N = 3 326.23 305.22 296.16 308.49 297.53 292.42 305.06 291.08 302.11 302.42 307.85 302.70 299.33
Result Confidence
OpenBenchmarking.org Seconds, Fewer Is Better WireGuard + Linux Networking Stack Stress Test EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 60 120 180 240 300 Min: 326.14 / Avg: 326.23 / Max: 326.37 Min: 304.14 / Avg: 305.22 / Max: 305.91 Min: 295.71 / Avg: 296.16 / Max: 296.59 Min: 308.17 / Avg: 308.49 / Max: 308.9 Min: 295.48 / Avg: 297.53 / Max: 300.5 Min: 291.12 / Avg: 292.42 / Max: 294.56 Min: 303.92 / Avg: 305.06 / Max: 306.58 Min: 290.32 / Avg: 291.08 / Max: 292.34 Min: 301.02 / Avg: 302.11 / Max: 303.55 Min: 299.36 / Avg: 302.42 / Max: 305.67 Min: 305.74 / Avg: 307.85 / Max: 310.98 Min: 301.87 / Avg: 302.7 / Max: 304.28 Min: 299.09 / Avg: 299.33 / Max: 299.49
ECP-CANDLE The CANDLE benchmark codes implement deep learning architectures relevant to problems in cancer. These architectures address problems at different biological scales, specifically problems at the molecular, cellular and population scales. Learn more via the OpenBenchmarking.org test page.
OpenBenchmarking.org Seconds, Fewer Is Better ECP-CANDLE 0.3 Benchmark: P3B2 EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 200 400 600 800 1000 783.24 748.54 736.22 763.80 749.67 755.01 783.25 739.71 788.52 792.74 789.56 817.66 775.67 785.07
DeepSpeech Mozilla DeepSpeech is a speech-to-text engine powered by TensorFlow for machine learning and derived from Baidu's Deep Speech research paper. This test profile times the speech-to-text process for a roughly three minute audio recording. Learn more via the OpenBenchmarking.org test page.
Result
OpenBenchmarking.org Seconds, Fewer Is Better DeepSpeech 0.6 Acceleration: CPU EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 20 40 60 80 100 SE +/- 0.15, N = 3 SE +/- 0.20, N = 3 SE +/- 0.07, N = 3 SE +/- 0.22, N = 3 SE +/- 0.20, N = 3 SE +/- 0.52, N = 3 SE +/- 0.09, N = 3 SE +/- 0.14, N = 3 SE +/- 0.13, N = 3 SE +/- 0.58, N = 3 SE +/- 0.10, N = 3 SE +/- 0.28, N = 3 SE +/- 0.14, N = 3 SE +/- 0.45, N = 3 72.99 73.79 74.99 73.17 72.68 72.21 71.56 72.13 70.72 70.17 70.67 70.11 69.51 71.67
Result Confidence
OpenBenchmarking.org Seconds, Fewer Is Better DeepSpeech 0.6 Acceleration: CPU EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 14 28 42 56 70 Min: 72.82 / Avg: 72.99 / Max: 73.3 Min: 73.4 / Avg: 73.79 / Max: 74.01 Min: 74.85 / Avg: 74.99 / Max: 75.07 Min: 72.74 / Avg: 73.17 / Max: 73.46 Min: 72.4 / Avg: 72.68 / Max: 73.08 Min: 71.26 / Avg: 72.21 / Max: 73.03 Min: 71.46 / Avg: 71.56 / Max: 71.73 Min: 71.89 / Avg: 72.13 / Max: 72.38 Min: 70.48 / Avg: 70.72 / Max: 70.91 Min: 69.04 / Avg: 70.17 / Max: 70.95 Min: 70.52 / Avg: 70.67 / Max: 70.87 Min: 69.57 / Avg: 70.11 / Max: 70.51 Min: 69.32 / Avg: 69.51 / Max: 69.77 Min: 70.79 / Avg: 71.67 / Max: 72.23
Tinymembench This benchmark tests the system memory (RAM) performance. Learn more via the OpenBenchmarking.org test page.
Result
OpenBenchmarking.org MB/s, More Is Better Tinymembench 2018-05-28 Standard Memcpy EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 2K 4K 6K 8K 10K SE +/- 2.95, N = 3 SE +/- 22.30, N = 3 SE +/- 7.90, N = 3 SE +/- 2.29, N = 3 SE +/- 19.03, N = 3 SE +/- 2.05, N = 3 SE +/- 2.22, N = 3 SE +/- 17.46, N = 3 SE +/- 35.12, N = 3 SE +/- 14.82, N = 3 SE +/- 44.65, N = 3 SE +/- 2.03, N = 3 SE +/- 1.52, N = 3 8805.9 8825.7 8850.6 8842.7 8902.8 8854.2 8829.9 8907.7 9087.1 8852.0 9314.0 9025.4 9055.1 1. (CC) gcc options: -O2 -lm
Result Confidence
OpenBenchmarking.org MB/s, More Is Better Tinymembench 2018-05-28 Standard Memcpy EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 1600 3200 4800 6400 8000 Min: 8800 / Avg: 8805.9 / Max: 8809 Min: 8781.6 / Avg: 8825.67 / Max: 8853.7 Min: 8835.2 / Avg: 8850.57 / Max: 8861.4 Min: 8838.4 / Avg: 8842.73 / Max: 8846.2 Min: 8864.9 / Avg: 8902.83 / Max: 8924.5 Min: 8851 / Avg: 8854.17 / Max: 8858 Min: 8825.5 / Avg: 8829.87 / Max: 8832.7 Min: 8873.4 / Avg: 8907.73 / Max: 8930.4 Min: 9051.6 / Avg: 9087.07 / Max: 9157.3 Min: 8829.6 / Avg: 8851.97 / Max: 8880 Min: 9224.8 / Avg: 9313.97 / Max: 9362.9 Min: 9023.3 / Avg: 9025.43 / Max: 9029.5 Min: 9052.3 / Avg: 9055.13 / Max: 9057.5 1. (CC) gcc options: -O2 -lm
LZ4 Compression This test measures the time needed to compress/decompress a sample file (an Ubuntu ISO) using LZ4 compression. Learn more via the OpenBenchmarking.org test page.
Result
OpenBenchmarking.org MB/s, More Is Better LZ4 Compression 1.9.3 Compression Level: 9 - Decompression Speed EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 2K 4K 6K 8K 10K SE +/- 28.32, N = 5 SE +/- 37.27, N = 3 SE +/- 51.98, N = 3 SE +/- 35.59, N = 3 SE +/- 36.49, N = 3 SE +/- 31.02, N = 3 SE +/- 51.28, N = 3 SE +/- 71.90, N = 3 SE +/- 28.28, N = 5 SE +/- 42.91, N = 3 SE +/- 25.22, N = 14 SE +/- 12.37, N = 15 SE +/- 33.96, N = 3 10057.8 10070.2 10110.9 10132.1 10256.3 10184.5 10188.6 10292.5 10156.5 10249.3 10219.5 10561.9 10068.5 1. (CC) gcc options: -O3
MB/s Per Watt
OpenBenchmarking.org MB/s Per Watt, More Is Better LZ4 Compression 1.9.3 Compression Level: 9 - Decompression Speed EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 50 100 150 200 250 234.32 231.30 228.69 197.87 201.08 197.68 142.36 201.45 166.46 144.64 139.63 183.94 134.54
Result Confidence
OpenBenchmarking.org MB/s, More Is Better LZ4 Compression 1.9.3 Compression Level: 9 - Decompression Speed EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 2K 4K 6K 8K 10K Min: 10025.8 / Avg: 10057.76 / Max: 10170.9 Min: 10010.8 / Avg: 10070.17 / Max: 10138.9 Min: 10010.1 / Avg: 10110.87 / Max: 10183.4 Min: 10093.6 / Avg: 10132.1 / Max: 10203.2 Min: 10188.2 / Avg: 10256.27 / Max: 10313.1 Min: 10134.8 / Avg: 10184.5 / Max: 10241.5 Min: 10089.5 / Avg: 10188.6 / Max: 10261 Min: 10179.5 / Avg: 10292.47 / Max: 10426 Min: 10088.8 / Avg: 10156.48 / Max: 10226.8 Min: 10163.9 / Avg: 10249.27 / Max: 10299.5 Min: 10124.1 / Avg: 10219.52 / Max: 10411.5 Min: 10508.8 / Avg: 10561.89 / Max: 10609.7 Min: 10031 / Avg: 10068.5 / Max: 10136.3 1. (CC) gcc options: -O3
Result
OpenBenchmarking.org MB/s, More Is Better LZ4 Compression 1.9.3 Compression Level: 3 - Decompression Speed EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 2K 4K 6K 8K 10K SE +/- 44.49, N = 3 SE +/- 29.05, N = 3 SE +/- 66.67, N = 3 SE +/- 93.14, N = 3 SE +/- 36.01, N = 4 SE +/- 14.46, N = 3 SE +/- 43.54, N = 3 SE +/- 29.33, N = 3 SE +/- 54.81, N = 3 SE +/- 44.06, N = 3 SE +/- 18.64, N = 7 SE +/- 34.53, N = 3 SE +/- 89.78, N = 3 10063.0 10101.0 10112.2 10172.7 10209.3 10232.8 10118.0 10222.4 10159.7 10170.7 10162.0 10567.2 10099.6 1. (CC) gcc options: -O3
MB/s Per Watt
OpenBenchmarking.org MB/s Per Watt, More Is Better LZ4 Compression 1.9.3 Compression Level: 3 - Decompression Speed EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 50 100 150 200 250 233.97 232.15 227.31 198.83 199.84 198.84 141.26 199.63 166.50 143.59 139.07 188.33 134.23
Result Confidence
OpenBenchmarking.org MB/s, More Is Better LZ4 Compression 1.9.3 Compression Level: 3 - Decompression Speed EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 2K 4K 6K 8K 10K Min: 10013.3 / Avg: 10063.03 / Max: 10151.8 Min: 10050 / Avg: 10101 / Max: 10150.6 Min: 9978.9 / Avg: 10112.23 / Max: 10180.1 Min: 10073 / Avg: 10172.67 / Max: 10358.8 Min: 10125 / Avg: 10209.25 / Max: 10270.7 Min: 10214 / Avg: 10232.77 / Max: 10261.2 Min: 10073.2 / Avg: 10118.03 / Max: 10205.1 Min: 10167.9 / Avg: 10222.43 / Max: 10268.4 Min: 10076.5 / Avg: 10159.67 / Max: 10263.1 Min: 10082.6 / Avg: 10170.7 / Max: 10215.9 Min: 10103.5 / Avg: 10162.01 / Max: 10237.8 Min: 10498.8 / Avg: 10567.23 / Max: 10609.5 Min: 9990.9 / Avg: 10099.57 / Max: 10277.7 1. (CC) gcc options: -O3
Result
OpenBenchmarking.org MB/s, More Is Better LZ4 Compression 1.9.3 Compression Level: 1 - Decompression Speed EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 2K 4K 6K 8K 10K SE +/- 37.22, N = 3 SE +/- 27.35, N = 3 SE +/- 7.93, N = 3 SE +/- 18.80, N = 3 SE +/- 43.01, N = 3 SE +/- 5.92, N = 3 SE +/- 41.47, N = 3 SE +/- 47.44, N = 3 SE +/- 23.29, N = 3 SE +/- 27.42, N = 3 SE +/- 36.93, N = 3 SE +/- 42.46, N = 3 SE +/- 24.26, N = 3 10936.6 10929.9 10898.3 11006.6 10951.0 10968.6 10931.6 10993.2 10920.5 10926.3 10996.1 11210.0 10701.3 1. (CC) gcc options: -O3
MB/s Per Watt
OpenBenchmarking.org MB/s Per Watt, More Is Better LZ4 Compression 1.9.3 Compression Level: 1 - Decompression Speed EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 50 100 150 200 250 237.48 234.75 227.91 201.84 202.51 200.00 146.91 202.37 172.19 147.64 142.24 189.50 139.96
Result Confidence
OpenBenchmarking.org MB/s, More Is Better LZ4 Compression 1.9.3 Compression Level: 1 - Decompression Speed EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 2K 4K 6K 8K 10K Min: 10862.2 / Avg: 10936.63 / Max: 10975.1 Min: 10878.3 / Avg: 10929.9 / Max: 10971.4 Min: 10885.6 / Avg: 10898.33 / Max: 10912.9 Min: 10976.1 / Avg: 11006.63 / Max: 11040.9 Min: 10899.4 / Avg: 10951 / Max: 11036.4 Min: 10961.1 / Avg: 10968.63 / Max: 10980.3 Min: 10851.3 / Avg: 10931.63 / Max: 10989.7 Min: 10916.9 / Avg: 10993.2 / Max: 11080.2 Min: 10874.2 / Avg: 10920.47 / Max: 10948.2 Min: 10874.5 / Avg: 10926.3 / Max: 10967.8 Min: 10957.3 / Avg: 10996.07 / Max: 11069.9 Min: 11129.3 / Avg: 11209.97 / Max: 11273.3 Min: 10654.2 / Avg: 10701.33 / Max: 10734.9 1. (CC) gcc options: -O3
MBW This is a basic/simple memory (RAM) bandwidth benchmark for memory copy operations. Learn more via the OpenBenchmarking.org test page.
Result
OpenBenchmarking.org MiB/s, More Is Better MBW 2018-09-08 Test: Memory Copy - Array Size: 8192 MiB EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 3K 6K 9K 12K 15K SE +/- 33.58, N = 3 SE +/- 85.10, N = 3 SE +/- 87.56, N = 3 SE +/- 60.36, N = 3 SE +/- 93.82, N = 3 SE +/- 83.23, N = 3 SE +/- 36.28, N = 3 SE +/- 24.53, N = 3 SE +/- 23.45, N = 3 SE +/- 2.47, N = 3 SE +/- 67.71, N = 3 SE +/- 4.94, N = 3 SE +/- 1.29, N = 3 15523.14 15482.71 15482.74 15480.29 15510.92 15621.64 15503.05 15641.09 15459.16 15616.90 15599.90 15666.70 14958.19 1. (CC) gcc options: -O3 -march=native
MiB/s Per Watt
OpenBenchmarking.org MiB/s Per Watt, More Is Better MBW 2018-09-08 Test: Memory Copy - Array Size: 8192 MiB EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 70 140 210 280 350 315.08 311.47 306.50 266.51 268.62 269.18 194.18 272.57 230.35 201.36 192.02 248.71 182.44
Result Confidence
OpenBenchmarking.org MiB/s, More Is Better MBW 2018-09-08 Test: Memory Copy - Array Size: 8192 MiB EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 3K 6K 9K 12K 15K Min: 15473.92 / Avg: 15523.14 / Max: 15587.31 Min: 15312.58 / Avg: 15482.71 / Max: 15571.59 Min: 15323.81 / Avg: 15482.73 / Max: 15625.9 Min: 15391.63 / Avg: 15480.29 / Max: 15595.56 Min: 15344.4 / Avg: 15510.92 / Max: 15669.08 Min: 15473.05 / Avg: 15621.64 / Max: 15760.91 Min: 15458.28 / Avg: 15503.05 / Max: 15574.89 Min: 15608.52 / Avg: 15641.09 / Max: 15689.15 Min: 15413.52 / Avg: 15459.16 / Max: 15491.31 Min: 15613.31 / Avg: 15616.9 / Max: 15621.62 Min: 15488.47 / Avg: 15599.9 / Max: 15722.26 Min: 15657.32 / Avg: 15666.7 / Max: 15674.1 Min: 14955.9 / Avg: 14958.19 / Max: 14960.35 1. (CC) gcc options: -O3 -march=native
LZ4 Compression This test measures the time needed to compress/decompress a sample file (an Ubuntu ISO) using LZ4 compression. Learn more via the OpenBenchmarking.org test page.
Result
OpenBenchmarking.org MB/s, More Is Better LZ4 Compression 1.9.3 Compression Level: 1 - Compression Speed EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 2K 4K 6K 8K 10K SE +/- 52.82, N = 3 SE +/- 18.11, N = 3 SE +/- 8.54, N = 3 SE +/- 29.02, N = 3 SE +/- 57.96, N = 3 SE +/- 5.54, N = 3 SE +/- 55.86, N = 3 SE +/- 14.87, N = 3 SE +/- 18.08, N = 3 SE +/- 19.08, N = 3 SE +/- 50.78, N = 3 SE +/- 52.96, N = 3 SE +/- 19.46, N = 3 9421.69 9365.44 9360.35 9428.77 9472.86 9464.00 9434.31 9468.59 9369.35 9376.86 9496.00 9802.81 9461.09 1. (CC) gcc options: -O3
Result Confidence
OpenBenchmarking.org MB/s, More Is Better LZ4 Compression 1.9.3 Compression Level: 1 - Compression Speed EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 2K 4K 6K 8K 10K Min: 9316.16 / Avg: 9421.69 / Max: 9478.74 Min: 9344.67 / Avg: 9365.44 / Max: 9401.53 Min: 9345.51 / Avg: 9360.35 / Max: 9375.08 Min: 9379.2 / Avg: 9428.77 / Max: 9479.71 Min: 9413.59 / Avg: 9472.86 / Max: 9588.77 Min: 9454.4 / Avg: 9464 / Max: 9473.6 Min: 9377.21 / Avg: 9434.31 / Max: 9546.03 Min: 9438.88 / Avg: 9468.59 / Max: 9484.45 Min: 9339.76 / Avg: 9369.35 / Max: 9402.14 Min: 9351.87 / Avg: 9376.86 / Max: 9414.33 Min: 9444.69 / Avg: 9496 / Max: 9597.56 Min: 9744.32 / Avg: 9802.81 / Max: 9908.52 Min: 9423.06 / Avg: 9461.09 / Max: 9487.27 1. (CC) gcc options: -O3
MBW This is a basic/simple memory (RAM) bandwidth benchmark for memory copy operations. Learn more via the OpenBenchmarking.org test page.
Result
OpenBenchmarking.org MiB/s, More Is Better MBW 2018-09-08 Test: Memory Copy, Fixed Block Size - Array Size: 8192 MiB EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 2K 4K 6K 8K 10K SE +/- 7.74, N = 3 SE +/- 6.09, N = 3 SE +/- 16.74, N = 3 SE +/- 19.18, N = 3 SE +/- 18.97, N = 3 SE +/- 16.71, N = 3 SE +/- 27.37, N = 3 SE +/- 2.76, N = 3 SE +/- 10.51, N = 3 SE +/- 4.98, N = 3 SE +/- 18.50, N = 3 SE +/- 5.81, N = 3 SE +/- 3.26, N = 3 8983.76 8970.77 8945.24 8995.85 9012.11 9078.88 8963.64 9117.75 9022.45 9073.57 9048.74 9215.24 8872.56 1. (CC) gcc options: -O3 -march=native
MiB/s Per Watt
OpenBenchmarking.org MiB/s Per Watt, More Is Better MBW 2018-09-08 Test: Memory Copy, Fixed Block Size - Array Size: 8192 MiB EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 40 80 120 160 200 185.90 183.37 179.48 154.41 159.14 158.03 112.76 160.00 134.77 117.41 111.88 149.02 108.64
Result Confidence
OpenBenchmarking.org MiB/s, More Is Better MBW 2018-09-08 Test: Memory Copy, Fixed Block Size - Array Size: 8192 MiB EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 1600 3200 4800 6400 8000 Min: 8971.61 / Avg: 8983.76 / Max: 8998.15 Min: 8960.57 / Avg: 8970.77 / Max: 8981.63 Min: 8912.98 / Avg: 8945.24 / Max: 8969.13 Min: 8971.17 / Avg: 8995.85 / Max: 9033.63 Min: 8974.68 / Avg: 9012.11 / Max: 9036.23 Min: 9045.61 / Avg: 9078.88 / Max: 9098.27 Min: 8910.42 / Avg: 8963.64 / Max: 9001.37 Min: 9112.63 / Avg: 9117.75 / Max: 9122.1 Min: 9010.61 / Avg: 9022.45 / Max: 9043.42 Min: 9065.01 / Avg: 9073.56 / Max: 9082.25 Min: 9023.71 / Avg: 9048.74 / Max: 9084.85 Min: 9203.97 / Avg: 9215.24 / Max: 9223.37 Min: 8866.67 / Avg: 8872.56 / Max: 8877.91 1. (CC) gcc options: -O3 -march=native
Result
OpenBenchmarking.org ms, Fewer Is Better NCNN 20201218 Target: CPU - Model: blazeface EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 3 6 9 12 15 SE +/- 0.02, N = 3 SE +/- 0.02, N = 3 SE +/- 0.04, N = 3 SE +/- 0.02, N = 3 SE +/- 0.01, N = 3 SE +/- 0.05, N = 3 SE +/- 0.05, N = 11 SE +/- 0.03, N = 3 SE +/- 0.67, N = 3 SE +/- 0.26, N = 12 SE +/- 0.37, N = 9 SE +/- 0.25, N = 9 SE +/- 0.03, N = 3 SE +/- 0.01, N = 3 3.49 3.54 3.74 3.72 4.21 4.60 4.95 4.61 6.57 6.80 8.68 9.32 3.30 3.82 MIN: 3.4 / MAX: 3.75 MIN: 3.43 / MAX: 3.74 MIN: 3.58 / MAX: 8.88 MIN: 3.58 / MAX: 5.16 MIN: 4.06 / MAX: 5.91 MIN: 4.38 / MAX: 6.31 MIN: 4.63 / MAX: 6.53 MIN: 4.45 / MAX: 4.81 MIN: 5.73 / MAX: 18.41 MIN: 5.67 / MAX: 11.73 MIN: 6.7 / MAX: 15.99 MIN: 7.36 / MAX: 18.28 MIN: 3.2 / MAX: 3.51 MIN: 3.72 / MAX: 4.1 1. (CXX) g++ options: -O3 -rdynamic -lgomp -lpthread
Result Confidence
OpenBenchmarking.org ms, Fewer Is Better NCNN 20201218 Target: CPU - Model: blazeface EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 3 6 9 12 15 Min: 3.46 / Avg: 3.49 / Max: 3.51 Min: 3.5 / Avg: 3.54 / Max: 3.58 Min: 3.67 / Avg: 3.74 / Max: 3.82 Min: 3.68 / Avg: 3.72 / Max: 3.75 Min: 4.19 / Avg: 4.21 / Max: 4.23 Min: 4.49 / Avg: 4.6 / Max: 4.66 Min: 4.75 / Avg: 4.95 / Max: 5.37 Min: 4.55 / Avg: 4.61 / Max: 4.67 Min: 5.85 / Avg: 6.57 / Max: 7.9 Min: 5.79 / Avg: 6.8 / Max: 8.57 Min: 6.85 / Avg: 8.68 / Max: 9.99 Min: 8.39 / Avg: 9.32 / Max: 10.48 Min: 3.26 / Avg: 3.3 / Max: 3.36 Min: 3.79 / Avg: 3.82 / Max: 3.83 1. (CXX) g++ options: -O3 -rdynamic -lgomp -lpthread
Result
OpenBenchmarking.org ms, Fewer Is Better NCNN 20201218 Target: CPU - Model: efficientnet-b0 EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 6 12 18 24 30 SE +/- 0.03, N = 3 SE +/- 0.04, N = 3 SE +/- 0.10, N = 3 SE +/- 0.08, N = 3 SE +/- 0.06, N = 3 SE +/- 0.07, N = 3 SE +/- 0.26, N = 11 SE +/- 0.11, N = 3 SE +/- 2.24, N = 3 SE +/- 0.75, N = 12 SE +/- 1.16, N = 9 SE +/- 0.85, N = 9 SE +/- 0.13, N = 3 SE +/- 0.17, N = 3 10.87 9.84 10.40 10.80 11.69 12.92 14.63 12.94 19.66 21.71 26.52 26.76 10.55 12.47 MIN: 10.68 / MAX: 11.57 MIN: 9.58 / MAX: 10.75 MIN: 9.83 / MAX: 20.38 MIN: 10.45 / MAX: 26 MIN: 11.36 / MAX: 14.13 MIN: 12.36 / MAX: 16.63 MIN: 13.29 / MAX: 20.58 MIN: 12.46 / MAX: 15.4 MIN: 15.98 / MAX: 32.16 MIN: 16.06 / MAX: 33.9 MIN: 18.34 / MAX: 159.39 MIN: 19.65 / MAX: 171.03 MIN: 10.24 / MAX: 69.96 MIN: 12.02 / MAX: 14.07 1. (CXX) g++ options: -O3 -rdynamic -lgomp -lpthread
Result Confidence
OpenBenchmarking.org ms, Fewer Is Better NCNN 20201218 Target: CPU - Model: efficientnet-b0 EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 6 12 18 24 30 Min: 10.82 / Avg: 10.87 / Max: 10.92 Min: 9.77 / Avg: 9.84 / Max: 9.88 Min: 10.24 / Avg: 10.4 / Max: 10.57 Min: 10.65 / Avg: 10.8 / Max: 10.94 Min: 11.58 / Avg: 11.69 / Max: 11.76 Min: 12.84 / Avg: 12.92 / Max: 13.06 Min: 13.74 / Avg: 14.63 / Max: 16.32 Min: 12.72 / Avg: 12.94 / Max: 13.1 Min: 17.26 / Avg: 19.66 / Max: 24.13 Min: 18.48 / Avg: 21.71 / Max: 26.84 Min: 20 / Avg: 26.52 / Max: 29.87 Min: 23.41 / Avg: 26.76 / Max: 31.76 Min: 10.38 / Avg: 10.55 / Max: 10.8 Min: 12.29 / Avg: 12.47 / Max: 12.8 1. (CXX) g++ options: -O3 -rdynamic -lgomp -lpthread
Result
OpenBenchmarking.org ms, Fewer Is Better NCNN 20201218 Target: CPU - Model: mnasnet EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 5 10 15 20 25 SE +/- 0.03, N = 3 SE +/- 0.02, N = 3 SE +/- 0.04, N = 3 SE +/- 0.06, N = 3 SE +/- 0.04, N = 2 SE +/- 0.05, N = 3 SE +/- 0.23, N = 11 SE +/- 0.37, N = 3 SE +/- 2.35, N = 3 SE +/- 0.94, N = 12 SE +/- 1.14, N = 9 SE +/- 0.77, N = 9 SE +/- 0.12, N = 3 SE +/- 0.31, N = 3 6.64 6.49 6.95 7.32 8.16 9.07 10.38 9.28 15.49 16.71 22.05 22.34 6.42 8.72 MIN: 6.54 / MAX: 7.23 MIN: 6.37 / MAX: 6.92 MIN: 6.71 / MAX: 14.84 MIN: 7.05 / MAX: 8.22 MIN: 7.75 / MAX: 9.91 MIN: 8.75 / MAX: 11.1 MIN: 9.3 / MAX: 16.29 MIN: 8.66 / MAX: 11.37 MIN: 11.65 / MAX: 28.64 MIN: 11.37 / MAX: 30.58 MIN: 13.54 / MAX: 37.68 MIN: 14.54 / MAX: 162.38 MIN: 6.09 / MAX: 7.09 MIN: 8.12 / MAX: 10.61 1. (CXX) g++ options: -O3 -rdynamic -lgomp -lpthread
Result Confidence
OpenBenchmarking.org ms, Fewer Is Better NCNN 20201218 Target: CPU - Model: mnasnet EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 5 10 15 20 25 Min: 6.59 / Avg: 6.64 / Max: 6.7 Min: 6.47 / Avg: 6.49 / Max: 6.52 Min: 6.9 / Avg: 6.95 / Max: 7.02 Min: 7.22 / Avg: 7.32 / Max: 7.41 Min: 8.12 / Avg: 8.16 / Max: 8.19 Min: 8.98 / Avg: 9.07 / Max: 9.14 Min: 9.65 / Avg: 10.38 / Max: 12.34 Min: 8.87 / Avg: 9.28 / Max: 10.01 Min: 12.98 / Avg: 15.49 / Max: 20.18 Min: 12.43 / Avg: 16.71 / Max: 22.78 Min: 14.87 / Avg: 22.05 / Max: 25.24 Min: 19.2 / Avg: 22.34 / Max: 26.98 Min: 6.18 / Avg: 6.42 / Max: 6.58 Min: 8.32 / Avg: 8.72 / Max: 9.32 1. (CXX) g++ options: -O3 -rdynamic -lgomp -lpthread
Result
OpenBenchmarking.org ms, Fewer Is Better NCNN 20201218 Target: CPU - Model: shufflenet-v2 EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 4 8 12 16 20 SE +/- 0.01, N = 3 SE +/- 0.03, N = 3 SE +/- 0.04, N = 3 SE +/- 0.04, N = 3 SE +/- 0.02, N = 3 SE +/- 0.04, N = 3 SE +/- 0.07, N = 11 SE +/- 0.07, N = 3 SE +/- 0.60, N = 3 SE +/- 0.42, N = 12 SE +/- 0.61, N = 9 SE +/- 0.35, N = 9 SE +/- 0.04, N = 3 SE +/- 0.36, N = 3 10.20 9.61 8.87 8.91 9.52 9.94 10.68 9.97 12.82 14.06 17.29 16.71 9.60 9.99 MIN: 10.07 / MAX: 10.8 MIN: 9.51 / MAX: 13.18 MIN: 8.52 / MAX: 34.05 MIN: 8.74 / MAX: 12.61 MIN: 9.28 / MAX: 10.99 MIN: 9.64 / MAX: 11.99 MIN: 10.17 / MAX: 154.31 MIN: 9.68 / MAX: 12.72 MIN: 12.07 / MAX: 17.58 MIN: 11.71 / MAX: 20.88 MIN: 13.68 / MAX: 128.19 MIN: 14.39 / MAX: 153.63 MIN: 9.43 / MAX: 10.04 MIN: 9.5 / MAX: 11.56 1. (CXX) g++ options: -O3 -rdynamic -lgomp -lpthread
Result Confidence
OpenBenchmarking.org ms, Fewer Is Better NCNN 20201218 Target: CPU - Model: shufflenet-v2 EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 4 8 12 16 20 Min: 10.18 / Avg: 10.2 / Max: 10.21 Min: 9.56 / Avg: 9.61 / Max: 9.65 Min: 8.8 / Avg: 8.87 / Max: 8.94 Min: 8.84 / Avg: 8.91 / Max: 8.99 Min: 9.47 / Avg: 9.52 / Max: 9.55 Min: 9.85 / Avg: 9.94 / Max: 9.98 Min: 10.49 / Avg: 10.68 / Max: 11.36 Min: 9.83 / Avg: 9.97 / Max: 10.05 Min: 12.17 / Avg: 12.82 / Max: 14.01 Min: 12.14 / Avg: 14.06 / Max: 16.52 Min: 13.79 / Avg: 17.29 / Max: 19.27 Min: 14.5 / Avg: 16.71 / Max: 17.77 Min: 9.56 / Avg: 9.6 / Max: 9.68 Min: 9.61 / Avg: 9.99 / Max: 10.71 1. (CXX) g++ options: -O3 -rdynamic -lgomp -lpthread
Result
OpenBenchmarking.org ms, Fewer Is Better NCNN 20201218 Target: CPU-v3-v3 - Model: mobilenet-v3 EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 5 10 15 20 25 SE +/- 0.02, N = 3 SE +/- 0.01, N = 3 SE +/- 0.02, N = 3 SE +/- 0.08, N = 3 SE +/- 0.04, N = 3 SE +/- 0.07, N = 3 SE +/- 0.18, N = 11 SE +/- 0.19, N = 3 SE +/- 1.69, N = 3 SE +/- 0.60, N = 12 SE +/- 1.03, N = 9 SE +/- 0.75, N = 9 SE +/- 0.02, N = 3 SE +/- 0.20, N = 3 6.72 6.54 6.94 7.31 8.13 9.11 10.51 9.20 14.21 15.94 20.29 20.70 6.58 8.74 MIN: 6.58 / MAX: 8.56 MIN: 6.36 / MAX: 10.78 MIN: 6.68 / MAX: 16.72 MIN: 7.02 / MAX: 19.94 MIN: 7.77 / MAX: 9.9 MIN: 8.69 / MAX: 12.94 MIN: 9.5 / MAX: 16.4 MIN: 8.74 / MAX: 13.15 MIN: 11.65 / MAX: 24.12 MIN: 11.89 / MAX: 108.3 MIN: 13.64 / MAX: 155.26 MIN: 14.71 / MAX: 286.24 MIN: 6.13 / MAX: 7.08 MIN: 8.27 / MAX: 12.35 1. (CXX) g++ options: -O3 -rdynamic -lgomp -lpthread
Result Confidence
OpenBenchmarking.org ms, Fewer Is Better NCNN 20201218 Target: CPU-v3-v3 - Model: mobilenet-v3 EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 5 10 15 20 25 Min: 6.68 / Avg: 6.72 / Max: 6.76 Min: 6.53 / Avg: 6.54 / Max: 6.55 Min: 6.9 / Avg: 6.94 / Max: 6.96 Min: 7.21 / Avg: 7.31 / Max: 7.46 Min: 8.05 / Avg: 8.13 / Max: 8.19 Min: 8.97 / Avg: 9.11 / Max: 9.18 Min: 9.94 / Avg: 10.51 / Max: 11.53 Min: 8.99 / Avg: 9.2 / Max: 9.58 Min: 12.47 / Avg: 14.21 / Max: 17.58 Min: 13.25 / Avg: 15.94 / Max: 19.97 Min: 14.9 / Avg: 20.29 / Max: 23.39 Min: 17.42 / Avg: 20.7 / Max: 24.59 Min: 6.55 / Avg: 6.58 / Max: 6.62 Min: 8.53 / Avg: 8.74 / Max: 9.13 1. (CXX) g++ options: -O3 -rdynamic -lgomp -lpthread
Result
OpenBenchmarking.org ms, Fewer Is Better NCNN 20201218 Target: CPU-v2-v2 - Model: mobilenet-v2 EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 6 12 18 24 30 SE +/- 0.02, N = 3 SE +/- 0.01, N = 3 SE +/- 0.01, N = 3 SE +/- 0.04, N = 3 SE +/- 0.04, N = 3 SE +/- 0.04, N = 3 SE +/- 0.22, N = 11 SE +/- 0.17, N = 3 SE +/- 2.17, N = 3 SE +/- 1.02, N = 12 SE +/- 1.26, N = 9 SE +/- 0.94, N = 9 SE +/- 0.03, N = 3 SE +/- 0.27, N = 3 7.61 7.32 7.88 7.85 8.41 10.07 11.55 10.15 16.05 17.78 23.01 22.98 7.13 10.11 MIN: 7.45 / MAX: 8.18 MIN: 7.06 / MAX: 11.87 MIN: 7.53 / MAX: 17.78 MIN: 7.44 / MAX: 11.79 MIN: 7.96 / MAX: 10.39 MIN: 9.55 / MAX: 13.68 MIN: 10.24 / MAX: 25.89 MIN: 9.54 / MAX: 14.14 MIN: 12.41 / MAX: 30.85 MIN: 12.27 / MAX: 35.04 MIN: 14.46 / MAX: 130.77 MIN: 15.37 / MAX: 193.31 MIN: 6.91 / MAX: 7.7 MIN: 9.12 / MAX: 13.81 1. (CXX) g++ options: -O3 -rdynamic -lgomp -lpthread
Result Confidence
OpenBenchmarking.org ms, Fewer Is Better NCNN 20201218 Target: CPU-v2-v2 - Model: mobilenet-v2 EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 5 10 15 20 25 Min: 7.59 / Avg: 7.61 / Max: 7.64 Min: 7.3 / Avg: 7.32 / Max: 7.34 Min: 7.86 / Avg: 7.88 / Max: 7.9 Min: 7.8 / Avg: 7.85 / Max: 7.92 Min: 8.33 / Avg: 8.41 / Max: 8.48 Min: 10 / Avg: 10.07 / Max: 10.13 Min: 10.7 / Avg: 11.55 / Max: 13.04 Min: 9.86 / Avg: 10.15 / Max: 10.44 Min: 13.72 / Avg: 16.05 / Max: 20.38 Min: 12.86 / Avg: 17.78 / Max: 24.89 Min: 16.68 / Avg: 23.01 / Max: 27.84 Min: 19.59 / Avg: 22.98 / Max: 29.47 Min: 7.08 / Avg: 7.13 / Max: 7.18 Min: 9.76 / Avg: 10.11 / Max: 10.65 1. (CXX) g++ options: -O3 -rdynamic -lgomp -lpthread
Stress-NG OpenBenchmarking.org Bogo Ops/s Per Watt, More Is Better Stress-NG 0.11.07 Test: CPU Cache EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 0.1553 0.3106 0.4659 0.6212 0.7765 0.63 0.50 0.55 0.54 0.62 0.66 0.58 0.69 0.63 0.53 0.50 0.38 0.47
Result
OpenBenchmarking.org Bogo Ops/s, More Is Better Stress-NG 0.11.07 Test: CPU Cache EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 12 24 36 48 60 SE +/- 0.49, N = 13 SE +/- 0.77, N = 12 SE +/- 0.37, N = 15 SE +/- 0.68, N = 15 SE +/- 0.69, N = 12 SE +/- 1.28, N = 12 SE +/- 1.06, N = 15 SE +/- 0.67, N = 3 SE +/- 0.96, N = 12 SE +/- 0.36, N = 3 SE +/- 0.81, N = 15 SE +/- 0.72, N = 15 SE +/- 1.23, N = 12 32.53 25.17 30.12 32.72 41.11 45.23 51.39 49.19 49.78 44.36 43.70 24.85 46.39 1. (CC) gcc options: -O2 -std=gnu99 -lm -laio -lbsd -lcrypt -lrt -lz -ldl -lpthread -lc
Bogo Ops/s Per Watt
OpenBenchmarking.org Bogo Ops/s Per Watt, More Is Better Stress-NG 0.11.07 Test: CPU Cache EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 0.1553 0.3106 0.4659 0.6212 0.7765 0.63 0.50 0.55 0.54 0.62 0.66 0.58 0.69 0.63 0.53 0.50 0.38 0.47
Result Confidence
OpenBenchmarking.org Bogo Ops/s, More Is Better Stress-NG 0.11.07 Test: CPU Cache EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 10 20 30 40 50 Min: 29.83 / Avg: 32.53 / Max: 36.16 Min: 20.46 / Avg: 25.17 / Max: 29.16 Min: 28.09 / Avg: 30.12 / Max: 33.69 Min: 28.49 / Avg: 32.72 / Max: 38.56 Min: 35.35 / Avg: 41.11 / Max: 44.78 Min: 35.87 / Avg: 45.23 / Max: 51.94 Min: 45.08 / Avg: 51.39 / Max: 61.54 Min: 48.23 / Avg: 49.19 / Max: 50.47 Min: 45.03 / Avg: 49.78 / Max: 56.32 Min: 43.65 / Avg: 44.36 / Max: 44.75 Min: 38.22 / Avg: 43.7 / Max: 48.67 Min: 20.06 / Avg: 24.85 / Max: 30.63 Min: 38.66 / Avg: 46.39 / Max: 52.29 1. (CC) gcc options: -O2 -std=gnu99 -lm -laio -lbsd -lcrypt -lrt -lz -ldl -lpthread -lc
BlogBench OpenBenchmarking.org Final Score Per Watt, More Is Better BlogBench 1.1 Test: Write EPYC 7302P EPYC 7702 200 400 600 800 1000 1143.48 984.94
Result
OpenBenchmarking.org Final Score, More Is Better BlogBench 1.1 Test: Write EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 10K 20K 30K 40K 50K SE +/- 510.12, N = 3 SE +/- 66.78, N = 3 SE +/- 361.51, N = 3 SE +/- 448.51, N = 3 SE +/- 1363.32, N = 3 SE +/- 1515.78, N = 3 SE +/- 1222.34, N = 3 SE +/- 1923.72, N = 3 SE +/- 2893.83, N = 3 SE +/- 2455.63, N = 3 SE +/- 249.84, N = 3 SE +/- 312.03, N = 3 SE +/- 648.32, N = 3 SE +/- 379.22, N = 3 21916 28663 33627 37026 42491 43733 39412 43408 41586 39319 45477 44434 27443 36834 1. (CC) gcc options: -O2 -pthread
Final Score Per Watt
OpenBenchmarking.org Final Score Per Watt, More Is Better BlogBench 1.1 Test: Write EPYC 7302P EPYC 7702 200 400 600 800 1000 1143.48 984.94
Result Confidence
OpenBenchmarking.org Final Score, More Is Better BlogBench 1.1 Test: Write EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 8K 16K 24K 32K 40K Min: 20947 / Avg: 21916 / Max: 22677 Min: 28551 / Avg: 28663 / Max: 28782 Min: 33112 / Avg: 33627 / Max: 34324 Min: 36148 / Avg: 37025.67 / Max: 37625 Min: 39807 / Avg: 42491 / Max: 44249 Min: 40707 / Avg: 43733 / Max: 45405 Min: 36967 / Avg: 39411.67 / Max: 40640 Min: 39566 / Avg: 43408.33 / Max: 45501 Min: 35861 / Avg: 41586 / Max: 45184 Min: 34451 / Avg: 39318.67 / Max: 42318 Min: 44984 / Avg: 45477 / Max: 45794 Min: 43811 / Avg: 44434.33 / Max: 44772 Min: 26499 / Avg: 27443.33 / Max: 28685 Min: 36386 / Avg: 36834 / Max: 37588 1. (CC) gcc options: -O2 -pthread
SVT-VP9 OpenBenchmarking.org Frames Per Second Per Watt, More Is Better SVT-VP9 0.1 Tuning: Visual Quality Optimized - Input: Bosphorus 1080p EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 1.1565 2.313 3.4695 4.626 5.7825 1.90 3.02 3.89 3.55 4.59 5.00 4.00 5.14 4.48 4.11 4.04 3.67 1.67 2.19
Result
OpenBenchmarking.org Frames Per Second, More Is Better SVT-VP9 0.1 Tuning: Visual Quality Optimized - Input: Bosphorus 1080p EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 80 160 240 320 400 SE +/- 0.51, N = 7 SE +/- 1.04, N = 9 SE +/- 1.82, N = 15 SE +/- 2.50, N = 15 SE +/- 5.48, N = 15 SE +/- 5.89, N = 15 SE +/- 5.85, N = 15 SE +/- 6.75, N = 15 SE +/- 6.16, N = 15 SE +/- 6.69, N = 15 SE +/- 5.77, N = 15 SE +/- 4.45, N = 15 SE +/- 0.53, N = 7 SE +/- 2.97, N = 15 107.11 184.83 229.82 242.24 319.05 334.18 325.84 350.63 336.24 346.63 332.56 305.10 124.35 230.31 1. (CC) gcc options: -O3 -fcommon -fPIE -fPIC -fvisibility=hidden -pie -rdynamic -lpthread -lrt -lm
Frames Per Second Per Watt
OpenBenchmarking.org Frames Per Second Per Watt, More Is Better SVT-VP9 0.1 Tuning: Visual Quality Optimized - Input: Bosphorus 1080p EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 1.1565 2.313 3.4695 4.626 5.7825 1.90 3.02 3.89 3.55 4.59 5.00 4.00 5.14 4.48 4.11 4.04 3.67 1.67 2.19
Result Confidence
OpenBenchmarking.org Frames Per Second, More Is Better SVT-VP9 0.1 Tuning: Visual Quality Optimized - Input: Bosphorus 1080p EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 60 120 180 240 300 Min: 104.11 / Avg: 107.11 / Max: 107.86 Min: 176.68 / Avg: 184.83 / Max: 187.03 Min: 204.43 / Avg: 229.82 / Max: 232.47 Min: 207.33 / Avg: 242.24 / Max: 245.7 Min: 242.72 / Avg: 319.05 / Max: 326.26 Min: 252.42 / Avg: 334.18 / Max: 348.23 Min: 244.6 / Avg: 325.84 / Max: 336.51 Min: 256.63 / Avg: 350.63 / Max: 362.54 Min: 250.31 / Avg: 336.24 / Max: 345.82 Min: 253.27 / Avg: 346.63 / Max: 357.36 Min: 253.16 / Avg: 332.56 / Max: 350.88 Min: 248.76 / Avg: 305.1 / Max: 317.63 Min: 121.26 / Avg: 124.35 / Max: 125.39 Min: 188.8 / Avg: 230.31 / Max: 234.56 1. (CC) gcc options: -O3 -fcommon -fPIE -fPIC -fvisibility=hidden -pie -rdynamic -lpthread -lrt -lm
Cpuminer-Opt OpenBenchmarking.org kH/s Per Watt, More Is Better Cpuminer-Opt 3.15.5 Algorithm: Deepcoin EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 120 240 360 480 600 140.99 201.02 255.88 224.80 318.51 441.39 286.60 438.65 474.77 432.56 565.67 562.57 128.88 175.98
Result
OpenBenchmarking.org kH/s, More Is Better Cpuminer-Opt 3.15.5 Algorithm: Deepcoin EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 10K 20K 30K 40K 50K SE +/- 0.23, N = 3 SE +/- 78.72, N = 3 SE +/- 407.34, N = 15 SE +/- 14.53, N = 3 SE +/- 94.04, N = 3 SE +/- 1900.37, N = 15 SE +/- 38.44, N = 3 SE +/- 991.42, N = 15 SE +/- 964.94, N = 15 SE +/- 1521.20, N = 15 SE +/- 1295.28, N = 15 SE +/- 2134.76, N = 15 SE +/- 73.09, N = 6 SE +/- 333.56, N = 15 6207.89 9361.06 12793.00 12697.00 19363.00 26546.00 23013.00 26493.00 33589.00 34363.00 45051.00 46113.00 7644.10 15338.00 1. (CXX) g++ options: -O2 -lcurl -lz -lpthread -lssl -lcrypto -lgmp
kH/s Per Watt
OpenBenchmarking.org kH/s Per Watt, More Is Better Cpuminer-Opt 3.15.5 Algorithm: Deepcoin EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 120 240 360 480 600 140.99 201.02 255.88 224.80 318.51 441.39 286.60 438.65 474.77 432.56 565.67 562.57 128.88 175.98
Result Confidence
OpenBenchmarking.org kH/s, More Is Better Cpuminer-Opt 3.15.5 Algorithm: Deepcoin EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 8K 16K 24K 32K 40K Min: 6207.47 / Avg: 6207.89 / Max: 6208.24 Min: 9269.8 / Avg: 9361.06 / Max: 9517.79 Min: 12330 / Avg: 12793.33 / Max: 18480 Min: 12670 / Avg: 12696.67 / Max: 12720 Min: 19250 / Avg: 19363.33 / Max: 19550 Min: 23580 / Avg: 26546 / Max: 44860 Min: 22940 / Avg: 23013.33 / Max: 23070 Min: 25310 / Avg: 26492.67 / Max: 40340 Min: 32160 / Avg: 33588.67 / Max: 46960 Min: 32480 / Avg: 34363.33 / Max: 55610 Min: 42590 / Avg: 45050.67 / Max: 63100 Min: 42730 / Avg: 46112.67 / Max: 75810 Min: 7535.18 / Avg: 7644.1 / Max: 7997.88 Min: 14690 / Avg: 15338 / Max: 19990 1. (CXX) g++ options: -O2 -lcurl -lz -lpthread -lssl -lcrypto -lgmp
OpenBenchmarking.org kH/s Per Watt, More Is Better Cpuminer-Opt 3.15.5 Algorithm: Garlicoin EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 20 40 60 80 100 31.40 41.66 52.46 45.58 62.91 86.48 63.17 89.06 97.57 88.03 105.24 101.85 27.22 33.55
Result
OpenBenchmarking.org kH/s, More Is Better Cpuminer-Opt 3.15.5 Algorithm: Garlicoin EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 2K 4K 6K 8K 10K SE +/- 24.63, N = 15 SE +/- 22.88, N = 15 SE +/- 46.80, N = 15 SE +/- 6.92, N = 3 SE +/- 8.85, N = 3 SE +/- 179.55, N = 12 SE +/- 135.96, N = 15 SE +/- 157.39, N = 15 SE +/- 49.30, N = 3 SE +/- 113.98, N = 14 SE +/- 72.85, N = 13 SE +/- 215.48, N = 14 SE +/- 8.24, N = 3 SE +/- 3.02, N = 3 1473.31 2192.82 2991.73 2965.29 4490.86 6104.27 5725.79 6242.21 7811.99 7961.64 9507.95 9581.06 1769.46 3522.44 1. (CXX) g++ options: -O2 -lcurl -lz -lpthread -lssl -lcrypto -lgmp
kH/s Per Watt
OpenBenchmarking.org kH/s Per Watt, More Is Better Cpuminer-Opt 3.15.5 Algorithm: Garlicoin EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 20 40 60 80 100 31.40 41.66 52.46 45.58 62.91 86.48 63.17 89.06 97.57 88.03 105.24 101.85 27.22 33.55
Result Confidence
OpenBenchmarking.org kH/s, More Is Better Cpuminer-Opt 3.15.5 Algorithm: Garlicoin EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 1700 3400 5100 6800 8500 Min: 1428.33 / Avg: 1473.31 / Max: 1776.69 Min: 2113.61 / Avg: 2192.82 / Max: 2419.18 Min: 2871.77 / Avg: 2991.73 / Max: 3335.77 Min: 2956.9 / Avg: 2965.29 / Max: 2979.02 Min: 4477.91 / Avg: 4490.86 / Max: 4507.79 Min: 5581 / Avg: 6104.27 / Max: 7538.77 Min: 5501.12 / Avg: 5725.79 / Max: 7108.86 Min: 5942.72 / Avg: 6242.21 / Max: 7690.85 Min: 7760.8 / Avg: 7811.99 / Max: 7910.57 Min: 7778.26 / Avg: 7961.64 / Max: 9440.93 Min: 9387.02 / Avg: 9507.95 / Max: 10330 Min: 9331.1 / Avg: 9581.06 / Max: 12370 Min: 1758.86 / Avg: 1769.46 / Max: 1785.69 Min: 3516.78 / Avg: 3522.44 / Max: 3527.08 1. (CXX) g++ options: -O2 -lcurl -lz -lpthread -lssl -lcrypto -lgmp
OpenBenchmarking.org kH/s Per Watt, More Is Better Cpuminer-Opt 3.15.5 Algorithm: x25x EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 3 6 9 12 15 3.24 3.88 4.95 4.46 7.07 7.53 5.88 7.25 8.88 7.80 9.95 9.94 2.72 2.99
Result
OpenBenchmarking.org kH/s, More Is Better Cpuminer-Opt 3.15.5 Algorithm: x25x EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 300 600 900 1200 1500 SE +/- 1.33, N = 3 SE +/- 0.69, N = 3 SE +/- 1.04, N = 3 SE +/- 0.74, N = 3 SE +/- 39.35, N = 15 SE +/- 37.08, N = 15 SE +/- 0.86, N = 3 SE +/- 2.23, N = 3 SE +/- 11.98, N = 15 SE +/- 1.46, N = 3 SE +/- 32.30, N = 15 SE +/- 29.63, N = 14 SE +/- 1.31, N = 3 SE +/- 1.25, N = 3 216.58 322.83 429.51 447.01 862.81 883.87 807.02 891.02 1139.38 1147.36 1398.77 1360.06 262.90 524.31 1. (CXX) g++ options: -O2 -lcurl -lz -lpthread -lssl -lcrypto -lgmp
kH/s Per Watt
OpenBenchmarking.org kH/s Per Watt, More Is Better Cpuminer-Opt 3.15.5 Algorithm: x25x EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 3 6 9 12 15 3.24 3.88 4.95 4.46 7.07 7.53 5.88 7.25 8.88 7.80 9.95 9.94 2.72 2.99
Result Confidence
OpenBenchmarking.org kH/s, More Is Better Cpuminer-Opt 3.15.5 Algorithm: x25x EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 200 400 600 800 1000 Min: 214.04 / Avg: 216.58 / Max: 218.55 Min: 321.57 / Avg: 322.83 / Max: 323.96 Min: 427.95 / Avg: 429.51 / Max: 431.48 Min: 445.61 / Avg: 447.01 / Max: 448.15 Min: 675.58 / Avg: 862.81 / Max: 1074.46 Min: 822.42 / Avg: 883.87 / Max: 1393.5 Min: 806.02 / Avg: 807.02 / Max: 808.73 Min: 887.85 / Avg: 891.02 / Max: 895.31 Min: 1114.29 / Avg: 1139.38 / Max: 1274.78 Min: 1144.44 / Avg: 1147.36 / Max: 1148.92 Min: 1361.4 / Avg: 1398.77 / Max: 1850.16 Min: 1313.18 / Avg: 1360.06 / Max: 1735.96 Min: 260.27 / Avg: 262.9 / Max: 264.3 Min: 521.85 / Avg: 524.31 / Max: 525.94 1. (CXX) g++ options: -O2 -lcurl -lz -lpthread -lssl -lcrypto -lgmp
Parboil The Parboil Benchmarks from the IMPACT Research Group at University of Illinois are a set of throughput computing applications for looking at computing architecture and compilers. Parboil test-cases support OpenMP, OpenCL, and CUDA multi-processing environments. However, at this time the test profile is just making use of the OpenMP and OpenCL test workloads. Learn more via the OpenBenchmarking.org test page.
Result
OpenBenchmarking.org Seconds, Fewer Is Better Parboil 2.5 Test: OpenMP Stencil EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 3 6 9 12 15 SE +/- 0.312883, N = 14 SE +/- 0.172857, N = 15 SE +/- 0.040723, N = 15 SE +/- 0.040278, N = 15 SE +/- 0.017882, N = 6 SE +/- 0.076520, N = 15 SE +/- 0.046959, N = 15 SE +/- 0.076268, N = 15 SE +/- 0.017804, N = 7 SE +/- 0.024850, N = 7 SE +/- 0.021316, N = 15 SE +/- 0.025502, N = 9 SE +/- 0.288514, N = 15 SE +/- 0.084885, N = 6 10.635023 7.631597 5.758925 4.176971 4.572591 4.246361 3.621507 4.395850 3.779568 3.194662 3.100122 3.086435 9.844102 8.683131 1. (CXX) g++ options: -lm -lpthread -lgomp -O3 -ffast-math -fopenmp
Result Confidence
OpenBenchmarking.org Seconds, Fewer Is Better Parboil 2.5 Test: OpenMP Stencil EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 3 6 9 12 15 Min: 6.84 / Avg: 10.64 / Max: 11.74 Min: 5.38 / Avg: 7.63 / Max: 8.15 Min: 5.51 / Avg: 5.76 / Max: 6.05 Min: 4 / Avg: 4.18 / Max: 4.54 Min: 4.53 / Avg: 4.57 / Max: 4.63 Min: 3.7 / Avg: 4.25 / Max: 4.54 Min: 3.4 / Avg: 3.62 / Max: 3.93 Min: 3.64 / Avg: 4.4 / Max: 4.73 Min: 3.72 / Avg: 3.78 / Max: 3.86 Min: 3.06 / Avg: 3.19 / Max: 3.27 Min: 2.98 / Avg: 3.1 / Max: 3.25 Min: 2.96 / Avg: 3.09 / Max: 3.21 Min: 6.2 / Avg: 9.84 / Max: 10.6 Min: 8.26 / Avg: 8.68 / Max: 8.8 1. (CXX) g++ options: -lm -lpthread -lgomp -O3 -ffast-math -fopenmp
Kripke OpenBenchmarking.org Throughput FoM Per Watt, More Is Better Kripke 1.2.4 EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 400K 800K 1200K 1600K 2000K 1349588.10 1508621.96 1357552.35 1638766.48 1932212.23 1575405.35 1673190.41 1635500.08 1673028.98 1663875.88 1604877.74 1423158.29 1163515.81 514628.71
Result
OpenBenchmarking.org Throughput FoM, More Is Better Kripke 1.2.4 EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 50M 100M 150M 200M 250M SE +/- 1075776.09, N = 4 SE +/- 1366026.89, N = 3 SE +/- 927929.45, N = 9 SE +/- 3144064.63, N = 15 SE +/- 481377.88, N = 4 SE +/- 2175939.87, N = 3 SE +/- 5452949.69, N = 15 SE +/- 3811837.38, N = 15 SE +/- 1883204.11, N = 15 SE +/- 5572341.62, N = 12 SE +/- 2208966.30, N = 15 SE +/- 2966178.44, N = 15 SE +/- 1036502.10, N = 15 SE +/- 574642.20, N = 15 100898758 121256433 112489722 162898387 209811150 176798867 216525133 187397007 211310307 230851783 215771227 199683960 129536920 71413394 1. (CXX) g++ options: -O3 -fopenmp
Throughput FoM Per Watt
OpenBenchmarking.org Throughput FoM Per Watt, More Is Better Kripke 1.2.4 EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 400K 800K 1200K 1600K 2000K 1349588.10 1508621.96 1357552.35 1638766.48 1932212.23 1575405.35 1673190.41 1635500.08 1673028.98 1663875.88 1604877.74 1423158.29 1163515.81 514628.71
Result Confidence
OpenBenchmarking.org Throughput FoM, More Is Better Kripke 1.2.4 EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7532 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 40M 80M 120M 160M 200M Min: 97675130 / Avg: 100898757.5 / Max: 102097200 Min: 119380500 / Avg: 121256433.33 / Max: 123914500 Min: 107412100 / Avg: 112489722.22 / Max: 117685700 Min: 148262800 / Avg: 162898386.67 / Max: 178935200 Min: 208902500 / Avg: 209811150 / Max: 211002600 Min: 172473100 / Avg: 176798866.67 / Max: 179374000 Min: 170848300 / Avg: 216525133.33 / Max: 232847700 Min: 160767700 / Avg: 187397006.67 / Max: 215708300 Min: 200163900 / Avg: 211310306.67 / Max: 221141000 Min: 196106600 / Avg: 230851783.33 / Max: 255760700 Min: 199388700 / Avg: 215771226.67 / Max: 228027900 Min: 179253900 / Avg: 199683960 / Max: 214308000 Min: 124322100 / Avg: 129536920 / Max: 133041300 Min: 68795100 / Avg: 71413394 / Max: 74273840 1. (CXX) g++ options: -O3 -fopenmp
EPYC 7702 Processor: AMD EPYC 7702 64-Core @ 2.00GHz (64 Cores / 128 Threads), Motherboard: ASRockRack EPYCD8 (P2.40 BIOS), Chipset: AMD Starship/Matisse, Memory: 8 x 16384 MB DDR4-3200MT/s 18ASF2G72PDZ-3G2E1, Disk: 3841GB Micron_9300_MTFDHAL3T8TDP, Graphics: llvmpipe, Monitor: VE228, Network: 2 x Intel I350
OS: Ubuntu 20.04, Kernel: 5.11.0-051100rc6daily20210201-generic (x86_64) 20210131, Desktop: GNOME Shell 3.36.4, Display Server: X Server 1.20.8, Display Driver: llvmpipe, OpenGL: 4.5 Mesa 20.2.6 (LLVM 11.0.0 256 bits), Compiler: GCC 9.3.0, File-System: ext4, Screen Resolution: 1920x1080
Kernel Notes: Transparent Huge Pages: madviseCompiler Notes: --build=x86_64-linux-gnu --disable-vtable-verify --disable-werror --enable-checking=release --enable-clocale=gnu --enable-default-pie --enable-gnu-unique-object --enable-languages=c,ada,c++,go,brig,d,fortran,objc,obj-c++,gm2 --enable-libstdcxx-debug --enable-libstdcxx-time=yes --enable-multiarch --enable-multilib --enable-nls --enable-objc-gc=auto --enable-offload-targets=nvptx-none=/build/gcc-9-HskZEa/gcc-9-9.3.0/debian/tmp-nvptx/usr,hsa --enable-plugin --enable-shared --enable-threads=posix --host=x86_64-linux-gnu --program-prefix=x86_64-linux-gnu- --target=x86_64-linux-gnu --with-abi=m64 --with-arch-32=i686 --with-default-libstdcxx-abi=new --with-gcc-major-version-only --with-multilib-list=m32,m64,mx32 --with-target-system-zlib=auto --with-tune=generic --without-cuda-driver -vDisk Notes: NONE / errors=remount-ro,relatime,rw / Block Size: 4096Processor Notes: Scaling Governor: acpi-cpufreq performance (Boost: Enabled) - CPU Microcode: 0x8301034Java Notes: OpenJDK Runtime Environment (build 11.0.9.1+1-Ubuntu-0ubuntu1.20.04)Python Notes: Python 3.8.5Security Notes: itlb_multihit: Not affected + l1tf: Not affected + mds: Not affected + meltdown: Not affected + spec_store_bypass: Mitigation of SSB disabled via prctl and seccomp + spectre_v1: Mitigation of usercopy/swapgs barriers and __user pointer sanitization + spectre_v2: Mitigation of Full AMD retpoline IBPB: conditional IBRS_FW STIBP: conditional RSB filling + srbds: Not affected + tsx_async_abort: Not affected
Testing initiated at 1 February 2021 14:42 by user root.
EPYC 7402P Processor: AMD EPYC 7402P 24-Core @ 2.80GHz (24 Cores / 48 Threads), Motherboard: ASRockRack EPYCD8 (P2.40 BIOS), Chipset: AMD Starship/Matisse, Memory: 8 x 16384 MB DDR4-3200MT/s 18ASF2G72PDZ-3G2E1, Disk: 3841GB Micron_9300_MTFDHAL3T8TDP, Graphics: llvmpipe, Monitor: VE228, Network: 2 x Intel I350
OS: Ubuntu 20.04, Kernel: 5.11.0-051100rc6daily20210201-generic (x86_64) 20210131, Desktop: GNOME Shell 3.36.4, Display Server: X Server 1.20.8, Display Driver: llvmpipe, OpenGL: 4.5 Mesa 20.2.6 (LLVM 11.0.0 256 bits), Compiler: GCC 9.3.0, File-System: ext4, Screen Resolution: 1920x1080
Kernel Notes: Transparent Huge Pages: madviseCompiler Notes: --build=x86_64-linux-gnu --disable-vtable-verify --disable-werror --enable-checking=release --enable-clocale=gnu --enable-default-pie --enable-gnu-unique-object --enable-languages=c,ada,c++,go,brig,d,fortran,objc,obj-c++,gm2 --enable-libstdcxx-debug --enable-libstdcxx-time=yes --enable-multiarch --enable-multilib --enable-nls --enable-objc-gc=auto --enable-offload-targets=nvptx-none=/build/gcc-9-HskZEa/gcc-9-9.3.0/debian/tmp-nvptx/usr,hsa --enable-plugin --enable-shared --enable-threads=posix --host=x86_64-linux-gnu --program-prefix=x86_64-linux-gnu- --target=x86_64-linux-gnu --with-abi=m64 --with-arch-32=i686 --with-default-libstdcxx-abi=new --with-gcc-major-version-only --with-multilib-list=m32,m64,mx32 --with-target-system-zlib=auto --with-tune=generic --without-cuda-driver -vDisk Notes: NONE / errors=remount-ro,relatime,rw / Block Size: 4096Processor Notes: Scaling Governor: acpi-cpufreq performance (Boost: Enabled) - CPU Microcode: 0x8301034Java Notes: OpenJDK Runtime Environment (build 11.0.9.1+1-Ubuntu-0ubuntu1.20.04)Python Notes: Python 3.8.5Security Notes: itlb_multihit: Not affected + l1tf: Not affected + mds: Not affected + meltdown: Not affected + spec_store_bypass: Mitigation of SSB disabled via prctl and seccomp + spectre_v1: Mitigation of usercopy/swapgs barriers and __user pointer sanitization + spectre_v2: Mitigation of Full AMD retpoline IBPB: conditional IBRS_FW STIBP: conditional RSB filling + srbds: Not affected + tsx_async_abort: Not affected
Testing initiated at 3 February 2021 10:08 by user root.
EPYC 7302P Processor: AMD EPYC 7302P 16-Core @ 3.00GHz (16 Cores / 32 Threads), Motherboard: ASRockRack EPYCD8 (P2.40 BIOS), Chipset: AMD Starship/Matisse, Memory: 8 x 16384 MB DDR4-3200MT/s 18ASF2G72PDZ-3G2E1, Disk: 3841GB Micron_9300_MTFDHAL3T8TDP, Graphics: llvmpipe, Monitor: VE228, Network: 2 x Intel I350
OS: Ubuntu 20.04, Kernel: 5.11.0-051100rc6daily20210201-generic (x86_64) 20210131, Desktop: GNOME Shell 3.36.4, Display Server: X Server 1.20.8, Display Driver: llvmpipe, OpenGL: 4.5 Mesa 20.2.6 (LLVM 11.0.0 256 bits), Compiler: GCC 9.3.0, File-System: ext4, Screen Resolution: 1920x1080
Kernel Notes: Transparent Huge Pages: madviseCompiler Notes: --build=x86_64-linux-gnu --disable-vtable-verify --disable-werror --enable-checking=release --enable-clocale=gnu --enable-default-pie --enable-gnu-unique-object --enable-languages=c,ada,c++,go,brig,d,fortran,objc,obj-c++,gm2 --enable-libstdcxx-debug --enable-libstdcxx-time=yes --enable-multiarch --enable-multilib --enable-nls --enable-objc-gc=auto --enable-offload-targets=nvptx-none=/build/gcc-9-HskZEa/gcc-9-9.3.0/debian/tmp-nvptx/usr,hsa --enable-plugin --enable-shared --enable-threads=posix --host=x86_64-linux-gnu --program-prefix=x86_64-linux-gnu- --target=x86_64-linux-gnu --with-abi=m64 --with-arch-32=i686 --with-default-libstdcxx-abi=new --with-gcc-major-version-only --with-multilib-list=m32,m64,mx32 --with-target-system-zlib=auto --with-tune=generic --without-cuda-driver -vDisk Notes: NONE / errors=remount-ro,relatime,rw / Block Size: 4096Processor Notes: Scaling Governor: acpi-cpufreq performance (Boost: Enabled) - CPU Microcode: 0x8301034Java Notes: OpenJDK Runtime Environment (build 11.0.9.1+1-Ubuntu-0ubuntu1.20.04)Python Notes: Python 3.8.5Security Notes: itlb_multihit: Not affected + l1tf: Not affected + mds: Not affected + meltdown: Not affected + spec_store_bypass: Mitigation of SSB disabled via prctl and seccomp + spectre_v1: Mitigation of usercopy/swapgs barriers and __user pointer sanitization + spectre_v2: Mitigation of Full AMD retpoline IBPB: conditional IBRS_FW STIBP: conditional RSB filling + srbds: Not affected + tsx_async_abort: Not affected
Testing initiated at 4 February 2021 15:16 by user root.
EPYC 7232P Processor: AMD EPYC 7232P 8-Core @ 3.10GHz (8 Cores / 16 Threads), Motherboard: ASRockRack EPYCD8 (P2.40 BIOS), Chipset: AMD Starship/Matisse, Memory: 8 x 16384 MB DDR4-3200MT/s 18ASF2G72PDZ-3G2E1, Disk: 3841GB Micron_9300_MTFDHAL3T8TDP, Graphics: llvmpipe, Monitor: VE228, Network: 2 x Intel I350
OS: Ubuntu 20.04, Kernel: 5.11.0-051100rc6daily20210201-generic (x86_64) 20210131, Desktop: GNOME Shell 3.36.4, Display Server: X Server 1.20.8, Display Driver: llvmpipe, OpenGL: 4.5 Mesa 20.2.6 (LLVM 11.0.0 256 bits), Compiler: GCC 9.3.0, File-System: ext4, Screen Resolution: 1920x1080
Kernel Notes: Transparent Huge Pages: madviseCompiler Notes: --build=x86_64-linux-gnu --disable-vtable-verify --disable-werror --enable-checking=release --enable-clocale=gnu --enable-default-pie --enable-gnu-unique-object --enable-languages=c,ada,c++,go,brig,d,fortran,objc,obj-c++,gm2 --enable-libstdcxx-debug --enable-libstdcxx-time=yes --enable-multiarch --enable-multilib --enable-nls --enable-objc-gc=auto --enable-offload-targets=nvptx-none=/build/gcc-9-HskZEa/gcc-9-9.3.0/debian/tmp-nvptx/usr,hsa --enable-plugin --enable-shared --enable-threads=posix --host=x86_64-linux-gnu --program-prefix=x86_64-linux-gnu- --target=x86_64-linux-gnu --with-abi=m64 --with-arch-32=i686 --with-default-libstdcxx-abi=new --with-gcc-major-version-only --with-multilib-list=m32,m64,mx32 --with-target-system-zlib=auto --with-tune=generic --without-cuda-driver -vDisk Notes: NONE / errors=remount-ro,relatime,rw / Block Size: 4096Processor Notes: Scaling Governor: acpi-cpufreq performance (Boost: Enabled) - CPU Microcode: 0x8301034Java Notes: OpenJDK Runtime Environment (build 11.0.9.1+1-Ubuntu-0ubuntu1.20.04)Python Notes: Python 3.8.5Security Notes: itlb_multihit: Not affected + l1tf: Not affected + mds: Not affected + meltdown: Not affected + spec_store_bypass: Mitigation of SSB disabled via prctl and seccomp + spectre_v1: Mitigation of usercopy/swapgs barriers and __user pointer sanitization + spectre_v2: Mitigation of Full AMD retpoline IBPB: conditional IBRS_FW STIBP: conditional RSB filling + srbds: Not affected + tsx_async_abort: Not affected
Testing initiated at 6 February 2021 05:20 by user root.
EPYC 7552 Processor: AMD EPYC 7552 48-Core @ 2.20GHz (48 Cores / 96 Threads), Motherboard: ASRockRack EPYCD8 (P2.40 BIOS), Chipset: AMD Starship/Matisse, Memory: 8 x 16384 MB DDR4-3200MT/s 18ASF2G72PDZ-3G2E1, Disk: 3841GB Micron_9300_MTFDHAL3T8TDP, Graphics: llvmpipe, Monitor: VE228, Network: 2 x Intel I350
OS: Ubuntu 20.04, Kernel: 5.11.0-051100rc6daily20210201-generic (x86_64) 20210131, Desktop: GNOME Shell 3.36.4, Display Server: X Server 1.20.8, Display Driver: llvmpipe, OpenGL: 4.5 Mesa 20.2.6 (LLVM 11.0.0 256 bits), Compiler: GCC 9.3.0, File-System: ext4, Screen Resolution: 1920x1080
Kernel Notes: Transparent Huge Pages: madviseCompiler Notes: --build=x86_64-linux-gnu --disable-vtable-verify --disable-werror --enable-checking=release --enable-clocale=gnu --enable-default-pie --enable-gnu-unique-object --enable-languages=c,ada,c++,go,brig,d,fortran,objc,obj-c++,gm2 --enable-libstdcxx-debug --enable-libstdcxx-time=yes --enable-multiarch --enable-multilib --enable-nls --enable-objc-gc=auto --enable-offload-targets=nvptx-none=/build/gcc-9-HskZEa/gcc-9-9.3.0/debian/tmp-nvptx/usr,hsa --enable-plugin --enable-shared --enable-threads=posix --host=x86_64-linux-gnu --program-prefix=x86_64-linux-gnu- --target=x86_64-linux-gnu --with-abi=m64 --with-arch-32=i686 --with-default-libstdcxx-abi=new --with-gcc-major-version-only --with-multilib-list=m32,m64,mx32 --with-target-system-zlib=auto --with-tune=generic --without-cuda-driver -vDisk Notes: NONE / errors=remount-ro,relatime,rw / Block Size: 4096Processor Notes: Scaling Governor: acpi-cpufreq performance (Boost: Enabled) - CPU Microcode: 0x8301034Java Notes: OpenJDK Runtime Environment (build 11.0.9.1+1-Ubuntu-0ubuntu1.20.04)Python Notes: Python 3.8.5Security Notes: itlb_multihit: Not affected + l1tf: Not affected + mds: Not affected + meltdown: Not affected + spec_store_bypass: Mitigation of SSB disabled via prctl and seccomp + spectre_v1: Mitigation of usercopy/swapgs barriers and __user pointer sanitization + spectre_v2: Mitigation of Full AMD retpoline IBPB: conditional IBRS_FW STIBP: conditional RSB filling + srbds: Not affected + tsx_async_abort: Not affected
Testing initiated at 7 February 2021 14:57 by user root.
EPYC 7272 Processor: AMD EPYC 7272 12-Core @ 2.90GHz (12 Cores / 24 Threads), Motherboard: ASRockRack EPYCD8 (P2.40 BIOS), Chipset: AMD Starship/Matisse, Memory: 8 x 16384 MB DDR4-3200MT/s 18ASF2G72PDZ-3G2E1, Disk: 3841GB Micron_9300_MTFDHAL3T8TDP, Graphics: llvmpipe, Monitor: VE228, Network: 2 x Intel I350
OS: Ubuntu 20.04, Kernel: 5.11.0-051100rc6daily20210201-generic (x86_64) 20210131, Desktop: GNOME Shell 3.36.4, Display Server: X Server 1.20.8, Display Driver: llvmpipe, OpenGL: 4.5 Mesa 20.2.6 (LLVM 11.0.0 256 bits), Compiler: GCC 9.3.0, File-System: ext4, Screen Resolution: 1920x1080
Kernel Notes: Transparent Huge Pages: madviseCompiler Notes: --build=x86_64-linux-gnu --disable-vtable-verify --disable-werror --enable-checking=release --enable-clocale=gnu --enable-default-pie --enable-gnu-unique-object --enable-languages=c,ada,c++,go,brig,d,fortran,objc,obj-c++,gm2 --enable-libstdcxx-debug --enable-libstdcxx-time=yes --enable-multiarch --enable-multilib --enable-nls --enable-objc-gc=auto --enable-offload-targets=nvptx-none=/build/gcc-9-HskZEa/gcc-9-9.3.0/debian/tmp-nvptx/usr,hsa --enable-plugin --enable-shared --enable-threads=posix --host=x86_64-linux-gnu --program-prefix=x86_64-linux-gnu- --target=x86_64-linux-gnu --with-abi=m64 --with-arch-32=i686 --with-default-libstdcxx-abi=new --with-gcc-major-version-only --with-multilib-list=m32,m64,mx32 --with-target-system-zlib=auto --with-tune=generic --without-cuda-driver -vDisk Notes: NONE / errors=remount-ro,relatime,rw / Block Size: 4096Processor Notes: Scaling Governor: acpi-cpufreq performance (Boost: Enabled) - CPU Microcode: 0x8301034Java Notes: OpenJDK Runtime Environment (build 11.0.9.1+1-Ubuntu-0ubuntu1.20.04)Python Notes: Python 3.8.5Security Notes: itlb_multihit: Not affected + l1tf: Not affected + mds: Not affected + meltdown: Not affected + spec_store_bypass: Mitigation of SSB disabled via prctl and seccomp + spectre_v1: Mitigation of usercopy/swapgs barriers and __user pointer sanitization + spectre_v2: Mitigation of Full AMD retpoline IBPB: conditional IBRS_FW STIBP: conditional RSB filling + srbds: Not affected + tsx_async_abort: Not affected
Testing initiated at 8 February 2021 18:51 by user root.
EPYC 7662 Processor: AMD EPYC 7662 64-Core @ 2.00GHz (64 Cores / 128 Threads), Motherboard: ASRockRack EPYCD8 (P2.40 BIOS), Chipset: AMD Starship/Matisse, Memory: 8 x 16384 MB DDR4-3200MT/s 18ASF2G72PDZ-3G2E1, Disk: 3841GB Micron_9300_MTFDHAL3T8TDP, Graphics: llvmpipe, Monitor: VE228, Network: 2 x Intel I350
OS: Ubuntu 20.04, Kernel: 5.11.0-051100rc6daily20210201-generic (x86_64) 20210131, Desktop: GNOME Shell 3.36.4, Display Server: X Server 1.20.8, Display Driver: llvmpipe, OpenGL: 4.5 Mesa 20.2.6 (LLVM 11.0.0 256 bits), Compiler: GCC 9.3.0, File-System: ext4, Screen Resolution: 1920x1080
Kernel Notes: Transparent Huge Pages: madviseCompiler Notes: --build=x86_64-linux-gnu --disable-vtable-verify --disable-werror --enable-checking=release --enable-clocale=gnu --enable-default-pie --enable-gnu-unique-object --enable-languages=c,ada,c++,go,brig,d,fortran,objc,obj-c++,gm2 --enable-libstdcxx-debug --enable-libstdcxx-time=yes --enable-multiarch --enable-multilib --enable-nls --enable-objc-gc=auto --enable-offload-targets=nvptx-none=/build/gcc-9-HskZEa/gcc-9-9.3.0/debian/tmp-nvptx/usr,hsa --enable-plugin --enable-shared --enable-threads=posix --host=x86_64-linux-gnu --program-prefix=x86_64-linux-gnu- --target=x86_64-linux-gnu --with-abi=m64 --with-arch-32=i686 --with-default-libstdcxx-abi=new --with-gcc-major-version-only --with-multilib-list=m32,m64,mx32 --with-target-system-zlib=auto --with-tune=generic --without-cuda-driver -vDisk Notes: NONE / errors=remount-ro,relatime,rw / Block Size: 4096Processor Notes: Scaling Governor: acpi-cpufreq performance (Boost: Enabled) - CPU Microcode: 0x8301034Java Notes: OpenJDK Runtime Environment (build 11.0.9.1+1-Ubuntu-0ubuntu1.20.04)Python Notes: Python 3.8.5Security Notes: itlb_multihit: Not affected + l1tf: Not affected + mds: Not affected + meltdown: Not affected + spec_store_bypass: Mitigation of SSB disabled via prctl and seccomp + spectre_v1: Mitigation of usercopy/swapgs barriers and __user pointer sanitization + spectre_v2: Mitigation of Full AMD retpoline IBPB: conditional IBRS_FW STIBP: conditional RSB filling + srbds: Not affected + tsx_async_abort: Not affected
Testing initiated at 10 February 2021 06:13 by user root.
EPYC 7502P Processor: AMD EPYC 7502P 32-Core @ 2.50GHz (32 Cores / 64 Threads), Motherboard: ASRockRack EPYCD8 (P2.40 BIOS), Chipset: AMD Starship/Matisse, Memory: 8 x 16384 MB DDR4-3200MT/s 18ASF2G72PDZ-3G2E1, Disk: 3841GB Micron_9300_MTFDHAL3T8TDP, Graphics: llvmpipe, Monitor: VE228, Network: 2 x Intel I350
OS: Ubuntu 20.04, Kernel: 5.11.0-051100rc6daily20210201-generic (x86_64) 20210131, Desktop: GNOME Shell 3.36.4, Display Server: X Server 1.20.8, OpenGL: 4.5 Mesa 20.2.6 (LLVM 11.0.0 256 bits), Compiler: GCC 9.3.0, File-System: ext4, Screen Resolution: 1920x1080
Kernel Notes: Transparent Huge Pages: madviseCompiler Notes: --build=x86_64-linux-gnu --disable-vtable-verify --disable-werror --enable-checking=release --enable-clocale=gnu --enable-default-pie --enable-gnu-unique-object --enable-languages=c,ada,c++,go,brig,d,fortran,objc,obj-c++,gm2 --enable-libstdcxx-debug --enable-libstdcxx-time=yes --enable-multiarch --enable-multilib --enable-nls --enable-objc-gc=auto --enable-offload-targets=nvptx-none=/build/gcc-9-HskZEa/gcc-9-9.3.0/debian/tmp-nvptx/usr,hsa --enable-plugin --enable-shared --enable-threads=posix --host=x86_64-linux-gnu --program-prefix=x86_64-linux-gnu- --target=x86_64-linux-gnu --with-abi=m64 --with-arch-32=i686 --with-default-libstdcxx-abi=new --with-gcc-major-version-only --with-multilib-list=m32,m64,mx32 --with-target-system-zlib=auto --with-tune=generic --without-cuda-driver -vDisk Notes: NONE / errors=remount-ro,relatime,rw / Block Size: 4096Processor Notes: Scaling Governor: acpi-cpufreq performance (Boost: Enabled) - CPU Microcode: 0x8301034Java Notes: OpenJDK Runtime Environment (build 11.0.10+9-Ubuntu-0ubuntu1.20.04)Python Notes: Python 3.8.5Security Notes: itlb_multihit: Not affected + l1tf: Not affected + mds: Not affected + meltdown: Not affected + spec_store_bypass: Mitigation of SSB disabled via prctl and seccomp + spectre_v1: Mitigation of usercopy/swapgs barriers and __user pointer sanitization + spectre_v2: Mitigation of Full AMD retpoline IBPB: conditional IBRS_FW STIBP: conditional RSB filling + srbds: Not affected + tsx_async_abort: Not affected
Testing initiated at 11 February 2021 11:19 by user root.
EPYC 7F52 Processor: AMD EPYC 7F52 16-Core @ 3.50GHz (16 Cores / 32 Threads), Motherboard: ASRockRack EPYCD8 (P2.40 BIOS), Chipset: AMD Starship/Matisse, Memory: 7 x 16384 MB DDR4-3200MT/s 18ASF2G72PDZ-3G2E1, Disk: 3841GB Micron_9300_MTFDHAL3T8TDP, Graphics: llvmpipe, Monitor: VE228, Network: 2 x Intel I350
OS: Ubuntu 20.04, Kernel: 5.11.0-051100rc6daily20210201-generic (x86_64) 20210131, Desktop: GNOME Shell 3.36.4, Display Server: X Server 1.20.8, OpenGL: 4.5 Mesa 20.2.6 (LLVM 11.0.0 256 bits), Compiler: GCC 9.3.0, File-System: ext4, Screen Resolution: 1920x1080
Kernel Notes: Transparent Huge Pages: madviseCompiler Notes: --build=x86_64-linux-gnu --disable-vtable-verify --disable-werror --enable-checking=release --enable-clocale=gnu --enable-default-pie --enable-gnu-unique-object --enable-languages=c,ada,c++,go,brig,d,fortran,objc,obj-c++,gm2 --enable-libstdcxx-debug --enable-libstdcxx-time=yes --enable-multiarch --enable-multilib --enable-nls --enable-objc-gc=auto --enable-offload-targets=nvptx-none=/build/gcc-9-HskZEa/gcc-9-9.3.0/debian/tmp-nvptx/usr,hsa --enable-plugin --enable-shared --enable-threads=posix --host=x86_64-linux-gnu --program-prefix=x86_64-linux-gnu- --target=x86_64-linux-gnu --with-abi=m64 --with-arch-32=i686 --with-default-libstdcxx-abi=new --with-gcc-major-version-only --with-multilib-list=m32,m64,mx32 --with-target-system-zlib=auto --with-tune=generic --without-cuda-driver -vDisk Notes: NONE / errors=remount-ro,relatime,rw / Block Size: 4096Processor Notes: Scaling Governor: acpi-cpufreq performance (Boost: Enabled) - CPU Microcode: 0x8301034Java Notes: OpenJDK Runtime Environment (build 11.0.10+9-Ubuntu-0ubuntu1.20.04)Python Notes: Python 3.8.5Security Notes: itlb_multihit: Not affected + l1tf: Not affected + mds: Not affected + meltdown: Not affected + spec_store_bypass: Mitigation of SSB disabled via prctl and seccomp + spectre_v1: Mitigation of usercopy/swapgs barriers and __user pointer sanitization + spectre_v2: Mitigation of Full AMD retpoline IBPB: conditional IBRS_FW STIBP: conditional RSB filling + srbds: Not affected + tsx_async_abort: Not affected
Testing initiated at 12 February 2021 15:29 by user root.
EPYC 7542 Processor: AMD EPYC 7542 32-Core @ 2.90GHz (32 Cores / 64 Threads), Motherboard: ASRockRack EPYCD8 (P2.40 BIOS), Chipset: AMD Starship/Matisse, Memory: 8 x 16384 MB DDR4-3200MT/s 18ASF2G72PDZ-3G2E1, Disk: 3841GB Micron_9300_MTFDHAL3T8TDP, Graphics: llvmpipe, Monitor: VE228, Network: 2 x Intel I350
OS: Ubuntu 20.04, Kernel: 5.11.0-051100rc6daily20210201-generic (x86_64) 20210131, Desktop: GNOME Shell 3.36.4, Display Server: X Server 1.20.8, OpenGL: 4.5 Mesa 20.2.6 (LLVM 11.0.0 256 bits), Compiler: GCC 9.3.0, File-System: ext4, Screen Resolution: 1920x1080
Kernel Notes: Transparent Huge Pages: madviseCompiler Notes: --build=x86_64-linux-gnu --disable-vtable-verify --disable-werror --enable-checking=release --enable-clocale=gnu --enable-default-pie --enable-gnu-unique-object --enable-languages=c,ada,c++,go,brig,d,fortran,objc,obj-c++,gm2 --enable-libstdcxx-debug --enable-libstdcxx-time=yes --enable-multiarch --enable-multilib --enable-nls --enable-objc-gc=auto --enable-offload-targets=nvptx-none=/build/gcc-9-HskZEa/gcc-9-9.3.0/debian/tmp-nvptx/usr,hsa --enable-plugin --enable-shared --enable-threads=posix --host=x86_64-linux-gnu --program-prefix=x86_64-linux-gnu- --target=x86_64-linux-gnu --with-abi=m64 --with-arch-32=i686 --with-default-libstdcxx-abi=new --with-gcc-major-version-only --with-multilib-list=m32,m64,mx32 --with-target-system-zlib=auto --with-tune=generic --without-cuda-driver -vDisk Notes: NONE / errors=remount-ro,relatime,rw / Block Size: 4096Processor Notes: Scaling Governor: acpi-cpufreq performance (Boost: Enabled) - CPU Microcode: 0x8301034Java Notes: OpenJDK Runtime Environment (build 11.0.10+9-Ubuntu-0ubuntu1.20.04)Python Notes: Python 3.8.5Security Notes: itlb_multihit: Not affected + l1tf: Not affected + mds: Not affected + meltdown: Not affected + spec_store_bypass: Mitigation of SSB disabled via prctl and seccomp + spectre_v1: Mitigation of usercopy/swapgs barriers and __user pointer sanitization + spectre_v2: Mitigation of Full AMD retpoline IBPB: conditional IBRS_FW STIBP: conditional RSB filling + srbds: Not affected + tsx_async_abort: Not affected
Testing initiated at 13 February 2021 20:39 by user root.
EPYC 7282 Processor: AMD EPYC 7282 16-Core @ 2.80GHz (16 Cores / 32 Threads), Motherboard: ASRockRack EPYCD8 (P2.40 BIOS), Chipset: AMD Starship/Matisse, Memory: 8 x 16384 MB DDR4-3200MT/s 18ASF2G72PDZ-3G2E1, Disk: 3841GB Micron_9300_MTFDHAL3T8TDP, Graphics: llvmpipe, Monitor: VE228, Network: 2 x Intel I350
OS: Ubuntu 20.04, Kernel: 5.11.0-051100rc6daily20210201-generic (x86_64) 20210131, Desktop: GNOME Shell 3.36.4, Display Server: X Server 1.20.8, OpenGL: 4.5 Mesa 20.2.6 (LLVM 11.0.0 256 bits), Compiler: GCC 9.3.0, File-System: ext4, Screen Resolution: 1920x1080
Kernel Notes: Transparent Huge Pages: madviseCompiler Notes: --build=x86_64-linux-gnu --disable-vtable-verify --disable-werror --enable-checking=release --enable-clocale=gnu --enable-default-pie --enable-gnu-unique-object --enable-languages=c,ada,c++,go,brig,d,fortran,objc,obj-c++,gm2 --enable-libstdcxx-debug --enable-libstdcxx-time=yes --enable-multiarch --enable-multilib --enable-nls --enable-objc-gc=auto --enable-offload-targets=nvptx-none=/build/gcc-9-HskZEa/gcc-9-9.3.0/debian/tmp-nvptx/usr,hsa --enable-plugin --enable-shared --enable-threads=posix --host=x86_64-linux-gnu --program-prefix=x86_64-linux-gnu- --target=x86_64-linux-gnu --with-abi=m64 --with-arch-32=i686 --with-default-libstdcxx-abi=new --with-gcc-major-version-only --with-multilib-list=m32,m64,mx32 --with-target-system-zlib=auto --with-tune=generic --without-cuda-driver -vDisk Notes: NONE / errors=remount-ro,relatime,rw / Block Size: 4096Processor Notes: Scaling Governor: acpi-cpufreq performance (Boost: Enabled) - CPU Microcode: 0x8301034Java Notes: OpenJDK Runtime Environment (build 11.0.10+9-Ubuntu-0ubuntu1.20.04)Python Notes: Python 3.8.5Security Notes: itlb_multihit: Not affected + l1tf: Not affected + mds: Not affected + meltdown: Not affected + spec_store_bypass: Mitigation of SSB disabled via prctl and seccomp + spectre_v1: Mitigation of usercopy/swapgs barriers and __user pointer sanitization + spectre_v2: Mitigation of Full AMD retpoline IBPB: conditional IBRS_FW STIBP: conditional RSB filling + srbds: Not affected + tsx_async_abort: Not affected
Testing initiated at 15 February 2021 05:59 by user root.
EPYC 7F32 Processor: AMD EPYC 7F32 8-Core @ 3.70GHz (8 Cores / 16 Threads), Motherboard: ASRockRack EPYCD8 (P2.40 BIOS), Chipset: AMD Starship/Matisse, Memory: 8 x 16384 MB DDR4-3200MT/s 18ASF2G72PDZ-3G2E1, Disk: 3841GB Micron_9300_MTFDHAL3T8TDP, Graphics: llvmpipe, Monitor: VE228, Network: 2 x Intel I350
OS: Ubuntu 20.04, Kernel: 5.11.0-051100rc6daily20210201-generic (x86_64) 20210131, Desktop: GNOME Shell 3.36.4, Display Server: X Server 1.20.8, OpenGL: 4.5 Mesa 20.2.6 (LLVM 11.0.0 256 bits), Compiler: GCC 9.3.0, File-System: ext4, Screen Resolution: 1920x1080
Kernel Notes: Transparent Huge Pages: madviseCompiler Notes: --build=x86_64-linux-gnu --disable-vtable-verify --disable-werror --enable-checking=release --enable-clocale=gnu --enable-default-pie --enable-gnu-unique-object --enable-languages=c,ada,c++,go,brig,d,fortran,objc,obj-c++,gm2 --enable-libstdcxx-debug --enable-libstdcxx-time=yes --enable-multiarch --enable-multilib --enable-nls --enable-objc-gc=auto --enable-offload-targets=nvptx-none=/build/gcc-9-HskZEa/gcc-9-9.3.0/debian/tmp-nvptx/usr,hsa --enable-plugin --enable-shared --enable-threads=posix --host=x86_64-linux-gnu --program-prefix=x86_64-linux-gnu- --target=x86_64-linux-gnu --with-abi=m64 --with-arch-32=i686 --with-default-libstdcxx-abi=new --with-gcc-major-version-only --with-multilib-list=m32,m64,mx32 --with-target-system-zlib=auto --with-tune=generic --without-cuda-driver -vDisk Notes: NONE / errors=remount-ro,relatime,rw / Block Size: 4096Processor Notes: Scaling Governor: acpi-cpufreq performance (Boost: Enabled) - CPU Microcode: 0x8301034Java Notes: OpenJDK Runtime Environment (build 11.0.10+9-Ubuntu-0ubuntu1.20.04)Python Notes: Python 3.8.5Security Notes: itlb_multihit: Not affected + l1tf: Not affected + mds: Not affected + meltdown: Not affected + spec_store_bypass: Mitigation of SSB disabled via prctl and seccomp + spectre_v1: Mitigation of usercopy/swapgs barriers and __user pointer sanitization + spectre_v2: Mitigation of Full AMD retpoline IBPB: conditional IBRS_FW STIBP: conditional RSB filling + srbds: Not affected + tsx_async_abort: Not affected
Testing initiated at 16 February 2021 12:26 by user root.
EPYC 7532 Processor: AMD EPYC 7532 32-Core @ 2.40GHz (32 Cores / 64 Threads), Motherboard: ASRockRack EPYCD8 (P2.40 BIOS), Chipset: AMD Starship/Matisse, Memory: 8 x 16384 MB DDR4-3200MT/s 18ASF2G72PDZ-3G2E1, Disk: 3841GB Micron_9300_MTFDHAL3T8TDP, Graphics: llvmpipe, Monitor: VE228, Network: 2 x Intel I350
OS: Ubuntu 20.04, Kernel: 5.11.0-051100rc6daily20210201-generic (x86_64) 20210131, Desktop: GNOME Shell 3.36.4, Display Server: X Server 1.20.8, OpenGL: 4.5 Mesa 20.2.6 (LLVM 11.0.0 256 bits), Compiler: GCC 9.3.0, File-System: ext4, Screen Resolution: 1920x1080
Kernel Notes: Transparent Huge Pages: madviseCompiler Notes: --build=x86_64-linux-gnu --disable-vtable-verify --disable-werror --enable-checking=release --enable-clocale=gnu --enable-default-pie --enable-gnu-unique-object --enable-languages=c,ada,c++,go,brig,d,fortran,objc,obj-c++,gm2 --enable-libstdcxx-debug --enable-libstdcxx-time=yes --enable-multiarch --enable-multilib --enable-nls --enable-objc-gc=auto --enable-offload-targets=nvptx-none=/build/gcc-9-HskZEa/gcc-9-9.3.0/debian/tmp-nvptx/usr,hsa --enable-plugin --enable-shared --enable-threads=posix --host=x86_64-linux-gnu --program-prefix=x86_64-linux-gnu- --target=x86_64-linux-gnu --with-abi=m64 --with-arch-32=i686 --with-default-libstdcxx-abi=new --with-gcc-major-version-only --with-multilib-list=m32,m64,mx32 --with-target-system-zlib=auto --with-tune=generic --without-cuda-driver -vDisk Notes: NONE / errors=remount-ro,relatime,rw / Block Size: 4096Processor Notes: Scaling Governor: acpi-cpufreq performance (Boost: Enabled) - CPU Microcode: 0x8301034Java Notes: OpenJDK Runtime Environment (build 11.0.10+9-Ubuntu-0ubuntu1.20.04)Python Notes: Python 3.8.5Security Notes: itlb_multihit: Not affected + l1tf: Not affected + mds: Not affected + meltdown: Not affected + spec_store_bypass: Mitigation of SSB disabled via prctl and seccomp + spectre_v1: Mitigation of usercopy/swapgs barriers and __user pointer sanitization + spectre_v2: Mitigation of Full AMD retpoline IBPB: conditional IBRS_FW STIBP: conditional RSB filling + srbds: Not affected + tsx_async_abort: Not affected
Testing initiated at 17 February 2021 20:08 by user root.
EPYC 7642 Processor: AMD EPYC 7642 48-Core @ 2.30GHz (48 Cores / 96 Threads), Motherboard: ASRockRack EPYCD8 (P2.40 BIOS), Chipset: AMD Starship/Matisse, Memory: 8 x 16384 MB DDR4-3200MT/s 18ASF2G72PDZ-3G2E1, Disk: 3841GB Micron_9300_MTFDHAL3T8TDP, Graphics: llvmpipe, Monitor: VE228, Network: 2 x Intel I350
OS: Ubuntu 20.04, Kernel: 5.11.0-051100rc6daily20210201-generic (x86_64) 20210131, Desktop: GNOME Shell 3.36.4, Display Server: X Server 1.20.8, OpenGL: 4.5 Mesa 20.2.6 (LLVM 11.0.0 256 bits), Compiler: GCC 9.3.0, File-System: ext4, Screen Resolution: 1920x1080
Kernel Notes: Transparent Huge Pages: madviseCompiler Notes: --build=x86_64-linux-gnu --disable-vtable-verify --disable-werror --enable-checking=release --enable-clocale=gnu --enable-default-pie --enable-gnu-unique-object --enable-languages=c,ada,c++,go,brig,d,fortran,objc,obj-c++,gm2 --enable-libstdcxx-debug --enable-libstdcxx-time=yes --enable-multiarch --enable-multilib --enable-nls --enable-objc-gc=auto --enable-offload-targets=nvptx-none=/build/gcc-9-HskZEa/gcc-9-9.3.0/debian/tmp-nvptx/usr,hsa --enable-plugin --enable-shared --enable-threads=posix --host=x86_64-linux-gnu --program-prefix=x86_64-linux-gnu- --target=x86_64-linux-gnu --with-abi=m64 --with-arch-32=i686 --with-default-libstdcxx-abi=new --with-gcc-major-version-only --with-multilib-list=m32,m64,mx32 --with-target-system-zlib=auto --with-tune=generic --without-cuda-driver -vDisk Notes: NONE / errors=remount-ro,relatime,rw / Block Size: 4096Processor Notes: Scaling Governor: acpi-cpufreq performance (Boost: Enabled) - CPU Microcode: 0x8301034Java Notes: OpenJDK Runtime Environment (build 11.0.10+9-Ubuntu-0ubuntu1.20.04)Python Notes: Python 3.8.5Security Notes: itlb_multihit: Not affected + l1tf: Not affected + mds: Not affected + meltdown: Not affected + spec_store_bypass: Mitigation of SSB disabled via prctl and seccomp + spectre_v1: Mitigation of usercopy/swapgs barriers and __user pointer sanitization + spectre_v2: Mitigation of Full AMD retpoline IBPB: conditional IBRS_FW STIBP: conditional RSB filling + srbds: Not affected + tsx_async_abort: Not affected
Testing initiated at 19 February 2021 08:25 by user root.