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 7662 EPYC 7702 EPYC 7642 EPYC 7552 EPYC 7542 EPYC 7532 EPYC 7502P EPYC 7402P EPYC 7F52 EPYC 7302P EPYC 7282 EPYC 7272 EPYC 7F32 EPYC 7232P 140K 280K 420K 560K 700K SE +/- 5351.86, N = 13 SE +/- 12582.41, N = 12 SE +/- 9107.04, N = 12 SE +/- 6158.44, N = 12 SE +/- 2411.69, N = 3 SE +/- 2127.92, N = 3 SE +/- 4313.15, N = 3 SE +/- 3944.26, N = 15 SE +/- 335.77, N = 3 SE +/- 981.65, N = 3 SE +/- 1328.09, N = 3 SE +/- 728.58, N = 3 SE +/- 654.80, N = 15 SE +/- 611.43, N = 6 631038 605852 470502 468227 324420 317250 316350 210539 182403 151030 150287 105140 79365 63648 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 7662 EPYC 7702 EPYC 7552 EPYC 7642 EPYC 7542 EPYC 7502P EPYC 7532 EPYC 7402P EPYC 7282 EPYC 7302P EPYC 7272 EPYC 7F52 EPYC 7232P EPYC 7F32 2K 4K 6K 8K 10K 8559.50 8011.78 7328.52 6520.94 5932.59 5770.73 4208.20 3879.07 3270.93 2891.08 2410.51 2197.63 1483.87 1374.22
Result Confidence
OpenBenchmarking.org kH/s, More Is Better Cpuminer-Opt 3.15.5 Algorithm: Skeincoin EPYC 7662 EPYC 7702 EPYC 7642 EPYC 7552 EPYC 7542 EPYC 7532 EPYC 7502P EPYC 7402P EPYC 7F52 EPYC 7302P EPYC 7282 EPYC 7272 EPYC 7F32 EPYC 7232P 110K 220K 330K 440K 550K Min: 570830 / Avg: 631038.46 / Max: 649140 Min: 470320 / Avg: 605851.67 / Max: 630960 Min: 373060 / Avg: 470501.67 / Max: 494480 Min: 404270 / Avg: 468226.67 / Max: 483970 Min: 319750 / Avg: 324420 / Max: 327800 Min: 313810 / Avg: 317250 / Max: 321140 Min: 310740 / Avg: 316350 / Max: 324830 Min: 187570 / Avg: 210538.67 / Max: 242310 Min: 181900 / Avg: 182403.33 / Max: 183040 Min: 149150 / Avg: 151030 / Max: 152460 Min: 148430 / Avg: 150286.67 / Max: 152860 Min: 103990 / Avg: 105140 / Max: 106490 Min: 75330 / Avg: 79365.33 / Max: 84270 Min: 61790 / Avg: 63648.33 / Max: 66140 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 7662 EPYC 7702 EPYC 7552 EPYC 7542 EPYC 7502P EPYC 7532 EPYC 7402P EPYC 7F52 EPYC 7302P EPYC 7282 EPYC 7272 EPYC 7F32 EPYC 7232P 20K 40K 60K 80K 100K SE +/- 52.65, N = 5 SE +/- 97.15, N = 5 SE +/- 23.00, N = 5 SE +/- 20.39, N = 5 SE +/- 9.32, N = 5 SE +/- 7.32, N = 5 SE +/- 12.89, N = 5 SE +/- 7.33, N = 5 SE +/- 9.93, N = 5 SE +/- 10.65, N = 5 SE +/- 5.53, N = 5 SE +/- 2.64, N = 5 SE +/- 1.09, N = 5 108892.22 106421.95 80743.89 56066.79 56038.72 55254.66 42008.11 32649.36 27632.19 26778.62 20091.96 16323.92 13398.10 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 7662 EPYC 7702 EPYC 7552 EPYC 7542 EPYC 7502P EPYC 7402P EPYC 7532 EPYC 7282 EPYC 7302P EPYC 7272 EPYC 7F52 EPYC 7232P EPYC 7F32 200 400 600 800 1000 783.68 754.73 733.57 667.05 638.23 539.88 521.63 474.66 432.15 391.60 313.31 297.08 261.75
Result Confidence
OpenBenchmarking.org Events Per Second, More Is Better Sysbench 2018-07-28 Test: CPU EPYC 7662 EPYC 7702 EPYC 7552 EPYC 7542 EPYC 7502P EPYC 7532 EPYC 7402P EPYC 7F52 EPYC 7302P EPYC 7282 EPYC 7272 EPYC 7F32 EPYC 7232P 20K 40K 60K 80K 100K Min: 108721.1 / Avg: 108892.22 / Max: 109052.86 Min: 106076.46 / Avg: 106421.95 / Max: 106643.26 Min: 80668.55 / Avg: 80743.89 / Max: 80805.58 Min: 55989.07 / Avg: 56066.79 / Max: 56109.25 Min: 56017.18 / Avg: 56038.72 / Max: 56065.58 Min: 55238.42 / Avg: 55254.66 / Max: 55276.83 Min: 41974.26 / Avg: 42008.11 / Max: 42044 Min: 32621.61 / Avg: 32649.36 / Max: 32663.3 Min: 27594.22 / Avg: 27632.19 / Max: 27651.61 Min: 26746.06 / Avg: 26778.62 / Max: 26804.47 Min: 20074.61 / Avg: 20091.96 / Max: 20104.41 Min: 16316.25 / Avg: 16323.92 / Max: 16331.8 Min: 13395.23 / Avg: 13398.1 / Max: 13400.85 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 7662 EPYC 7702 EPYC 7552 EPYC 7542 EPYC 7502P EPYC 7532 EPYC 7402P EPYC 7F52 EPYC 7302P EPYC 7282 EPYC 7272 EPYC 7F32 EPYC 7232P 4K 8K 12K 16K 20K SE +/- 45.79, N = 3 SE +/- 24.42, N = 3 SE +/- 23.53, N = 3 SE +/- 39.53, N = 3 SE +/- 8.85, N = 3 SE +/- 14.79, N = 3 SE +/- 3.25, N = 3 SE +/- 1.01, N = 3 SE +/- 1.11, N = 3 SE +/- 4.51, N = 3 SE +/- 5.85, N = 3 SE +/- 4.39, N = 3 SE +/- 8.87, N = 3 20174.76 19926.61 15958.16 11234.60 11121.59 10901.47 8541.12 6629.06 5622.82 5463.45 4078.21 3306.39 2708.90 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 7662 EPYC 7702 EPYC 7552 EPYC 7502P EPYC 7542 EPYC 7532 EPYC 7402P EPYC 7282 EPYC 7302P EPYC 7272 EPYC 7232P EPYC 7F52 EPYC 7F32 30 60 90 120 150 125.49 119.94 108.92 96.72 94.22 82.69 79.28 75.08 68.61 61.95 48.74 47.44 41.61
Result Confidence
OpenBenchmarking.org Bogo Ops/s, More Is Better Stress-NG 0.11.07 Test: CPU Stress EPYC 7662 EPYC 7702 EPYC 7552 EPYC 7542 EPYC 7502P EPYC 7532 EPYC 7402P EPYC 7F52 EPYC 7302P EPYC 7282 EPYC 7272 EPYC 7F32 EPYC 7232P 3K 6K 9K 12K 15K Min: 20083.31 / Avg: 20174.76 / Max: 20224.79 Min: 19890.13 / Avg: 19926.61 / Max: 19972.98 Min: 15919.41 / Avg: 15958.16 / Max: 16000.66 Min: 11159.1 / Avg: 11234.6 / Max: 11292.66 Min: 11109.84 / Avg: 11121.59 / Max: 11138.93 Min: 10874.37 / Avg: 10901.47 / Max: 10925.3 Min: 8535.73 / Avg: 8541.12 / Max: 8546.95 Min: 6628.02 / Avg: 6629.06 / Max: 6631.08 Min: 5620.68 / Avg: 5622.82 / Max: 5624.41 Min: 5456.78 / Avg: 5463.45 / Max: 5472.04 Min: 4067.37 / Avg: 4078.21 / Max: 4087.43 Min: 3301.92 / Avg: 3306.39 / Max: 3315.16 Min: 2691.46 / Avg: 2708.9 / Max: 2720.48 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 7662 EPYC 7702 EPYC 7552 EPYC 7642 EPYC 7542 EPYC 7502P EPYC 7532 EPYC 7402P EPYC 7282 EPYC 7F52 EPYC 7302P EPYC 7272 EPYC 7F32 EPYC 7232P 6K 12K 18K 24K 30K SE +/- 46.32, N = 3 SE +/- 28.57, N = 3 SE +/- 55.79, N = 3 SE +/- 31.70, N = 3 SE +/- 85.72, N = 3 SE +/- 42.04, N = 3 SE +/- 22.86, N = 3 SE +/- 95.61, N = 3 SE +/- 50.79, N = 3 SE +/- 43.76, N = 3 SE +/- 21.57, N = 3 SE +/- 89.67, N = 3 SE +/- 52.69, N = 3 SE +/- 41.71, N = 15 28284.87 25067.04 23441.91 22986.05 19922.01 18612.54 16446.88 12800.59 10017.98 9663.43 9316.80 6689.95 4953.65 4012.40
Result Confidence
OpenBenchmarking.org FPS, More Is Better OpenVINO 2021.1 Model: Age Gender Recognition Retail 0013 FP16 - Device: CPU EPYC 7662 EPYC 7702 EPYC 7552 EPYC 7642 EPYC 7542 EPYC 7502P EPYC 7532 EPYC 7402P EPYC 7282 EPYC 7F52 EPYC 7302P EPYC 7272 EPYC 7F32 EPYC 7232P 5K 10K 15K 20K 25K Min: 28192.24 / Avg: 28284.87 / Max: 28331.27 Min: 25025.67 / Avg: 25067.04 / Max: 25121.85 Min: 23347.44 / Avg: 23441.91 / Max: 23540.57 Min: 22927.38 / Avg: 22986.05 / Max: 23036.21 Min: 19751.03 / Avg: 19922.01 / Max: 20018.47 Min: 18567.53 / Avg: 18612.54 / Max: 18696.54 Min: 16403.4 / Avg: 16446.88 / Max: 16480.83 Min: 12615.39 / Avg: 12800.59 / Max: 12934.43 Min: 9917.01 / Avg: 10017.98 / Max: 10078.03 Min: 9575.98 / Avg: 9663.43 / Max: 9710.01 Min: 9293.16 / Avg: 9316.8 / Max: 9359.87 Min: 6524.74 / Avg: 6689.95 / Max: 6832.97 Min: 4855.38 / Avg: 4953.65 / Max: 5035.74 Min: 3827.5 / Avg: 4012.4 / Max: 4339.41
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 7662 EPYC 7702 EPYC 7642 EPYC 7552 EPYC 7542 EPYC 7502P EPYC 7532 EPYC 7402P EPYC 7F52 EPYC 7302P EPYC 7282 EPYC 7272 EPYC 7F32 EPYC 7232P 900 1800 2700 3600 4500 SE +/- 9.36, N = 3 SE +/- 9.06, N = 3 SE +/- 8.46, N = 3 SE +/- 6.05, N = 3 SE +/- 5.63, N = 3 SE +/- 4.32, N = 3 SE +/- 1.11, N = 3 SE +/- 1.11, N = 3 SE +/- 0.05, N = 3 SE +/- 3.28, N = 3 SE +/- 1.25, N = 3 SE +/- 7.84, N = 3 SE +/- 0.03, N = 3 SE +/- 0.03, N = 3 4019.09 3989.79 3322.99 3292.84 2389.76 2380.27 2333.54 1813.29 1410.59 1190.48 1156.26 860.01 705.21 579.18 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 7662 EPYC 7702 EPYC 7552 EPYC 7642 EPYC 7542 EPYC 7502P EPYC 7532 EPYC 7402P EPYC 7282 EPYC 7302P EPYC 7272 EPYC 7232P EPYC 7F52 EPYC 7F32 6 12 18 24 30 24.18 23.49 20.64 18.05 17.20 16.63 14.32 14.01 13.47 12.24 11.07 9.24 8.30 7.56
Result Confidence
OpenBenchmarking.org Total Mop/s, More Is Better NAS Parallel Benchmarks 3.4 Test / Class: EP.D EPYC 7662 EPYC 7702 EPYC 7642 EPYC 7552 EPYC 7542 EPYC 7502P EPYC 7532 EPYC 7402P EPYC 7F52 EPYC 7302P EPYC 7282 EPYC 7272 EPYC 7F32 EPYC 7232P 700 1400 2100 2800 3500 Min: 4001.46 / Avg: 4019.09 / Max: 4033.33 Min: 3972.06 / Avg: 3989.79 / Max: 4001.86 Min: 3306.1 / Avg: 3322.99 / Max: 3332.1 Min: 3282.03 / Avg: 3292.84 / Max: 3302.95 Min: 2378.57 / Avg: 2389.76 / Max: 2396.35 Min: 2371.63 / Avg: 2380.27 / Max: 2384.67 Min: 2331.32 / Avg: 2333.54 / Max: 2334.74 Min: 1811.43 / Avg: 1813.29 / Max: 1815.27 Min: 1410.49 / Avg: 1410.59 / Max: 1410.66 Min: 1183.95 / Avg: 1190.48 / Max: 1194.25 Min: 1153.76 / Avg: 1156.26 / Max: 1157.7 Min: 844.33 / Avg: 860.01 / Max: 868.26 Min: 705.16 / Avg: 705.21 / Max: 705.27 Min: 579.13 / Avg: 579.18 / Max: 579.23 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 7662 EPYC 7702 EPYC 7552 EPYC 7642 EPYC 7542 EPYC 7502P EPYC 7532 EPYC 7402P EPYC 7282 EPYC 7F52 EPYC 7302P EPYC 7272 EPYC 7F32 EPYC 7232P 6K 12K 18K 24K 30K SE +/- 30.27, N = 3 SE +/- 48.27, N = 3 SE +/- 49.13, N = 3 SE +/- 4.60, N = 3 SE +/- 75.75, N = 3 SE +/- 60.57, N = 3 SE +/- 24.60, N = 3 SE +/- 157.24, N = 3 SE +/- 103.67, N = 4 SE +/- 47.83, N = 3 SE +/- 6.65, N = 3 SE +/- 21.76, N = 3 SE +/- 6.26, N = 3 SE +/- 46.05, N = 4 28316.50 25012.98 23559.17 22996.93 19958.41 18514.60 16443.73 13220.95 9884.62 9866.08 9314.82 6803.09 4984.35 4115.44
Result Confidence
OpenBenchmarking.org FPS, More Is Better OpenVINO 2021.1 Model: Age Gender Recognition Retail 0013 FP32 - Device: CPU EPYC 7662 EPYC 7702 EPYC 7552 EPYC 7642 EPYC 7542 EPYC 7502P EPYC 7532 EPYC 7402P EPYC 7282 EPYC 7F52 EPYC 7302P EPYC 7272 EPYC 7F32 EPYC 7232P 5K 10K 15K 20K 25K Min: 28279.61 / Avg: 28316.5 / Max: 28376.51 Min: 24963.18 / Avg: 25012.98 / Max: 25109.5 Min: 23467.34 / Avg: 23559.17 / Max: 23635.37 Min: 22990.44 / Avg: 22996.93 / Max: 23005.82 Min: 19820.95 / Avg: 19958.41 / Max: 20082.32 Min: 18416.86 / Avg: 18514.6 / Max: 18625.46 Min: 16395.26 / Avg: 16443.73 / Max: 16475.33 Min: 12906.62 / Avg: 13220.95 / Max: 13386.45 Min: 9618.02 / Avg: 9884.62 / Max: 10112.13 Min: 9816.8 / Avg: 9866.08 / Max: 9961.72 Min: 9307.85 / Avg: 9314.82 / Max: 9328.12 Min: 6767.48 / Avg: 6803.09 / Max: 6842.56 Min: 4971.91 / Avg: 4984.35 / Max: 4991.8 Min: 4003.8 / Avg: 4115.44 / Max: 4226.83
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 7662 EPYC 7702 EPYC 7642 EPYC 7552 EPYC 7542 EPYC 7502P EPYC 7532 EPYC 7402P EPYC 7F52 EPYC 7302P EPYC 7282 EPYC 7272 EPYC 7F32 EPYC 7232P 900 1800 2700 3600 4500 SE +/- 10.02, N = 10 SE +/- 13.78, N = 10 SE +/- 6.29, N = 9 SE +/- 9.01, N = 9 SE +/- 4.60, N = 8 SE +/- 3.24, N = 8 SE +/- 5.08, N = 8 SE +/- 1.48, N = 7 SE +/- 0.69, N = 6 SE +/- 0.45, N = 6 SE +/- 0.78, N = 6 SE +/- 0.17, N = 5 SE +/- 0.27, N = 4 SE +/- 0.60, N = 4 3967.28 3908.23 3310.34 3252.13 2375.48 2368.69 2318.44 1806.54 1407.62 1191.90 1155.88 867.81 704.69 578.12 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 7662 EPYC 7702 EPYC 7552 EPYC 7642 EPYC 7542 EPYC 7502P EPYC 7532 EPYC 7402P EPYC 7282 EPYC 7302P EPYC 7272 EPYC 7F52 EPYC 7232P EPYC 7F32 10 20 30 40 50 42.58 41.11 36.28 32.45 28.10 27.29 22.61 21.02 17.46 16.06 13.77 11.81 10.52 9.02
Result Confidence
OpenBenchmarking.org Total Mop/s, More Is Better NAS Parallel Benchmarks 3.4 Test / Class: EP.C EPYC 7662 EPYC 7702 EPYC 7642 EPYC 7552 EPYC 7542 EPYC 7502P EPYC 7532 EPYC 7402P EPYC 7F52 EPYC 7302P EPYC 7282 EPYC 7272 EPYC 7F32 EPYC 7232P 700 1400 2100 2800 3500 Min: 3922.41 / Avg: 3967.28 / Max: 4021.83 Min: 3840.34 / Avg: 3908.23 / Max: 3966.84 Min: 3286.05 / Avg: 3310.34 / Max: 3336.05 Min: 3210.93 / Avg: 3252.13 / Max: 3290.8 Min: 2361.46 / Avg: 2375.48 / Max: 2394.12 Min: 2349.79 / Avg: 2368.69 / Max: 2379.63 Min: 2296.55 / Avg: 2318.44 / Max: 2338.82 Min: 1799.65 / Avg: 1806.54 / Max: 1812.17 Min: 1404.92 / Avg: 1407.62 / Max: 1409.44 Min: 1190.44 / Avg: 1191.9 / Max: 1193.16 Min: 1152.71 / Avg: 1155.88 / Max: 1157.48 Min: 867.17 / Avg: 867.81 / Max: 868.12 Min: 703.93 / Avg: 704.69 / Max: 705.19 Min: 576.33 / Avg: 578.12 / Max: 578.84 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 7662 EPYC 7702 EPYC 7552 EPYC 7542 EPYC 7502P EPYC 7532 EPYC 7402P EPYC 7F52 EPYC 7302P EPYC 7282 EPYC 7272 EPYC 7F32 EPYC 7232P 90K 180K 270K 360K 450K SE +/- 137.59, N = 3 SE +/- 205.94, N = 3 SE +/- 189.45, N = 3 SE +/- 32.95, N = 3 SE +/- 66.32, N = 3 SE +/- 47.74, N = 3 SE +/- 100.32, N = 3 SE +/- 3.54, N = 3 SE +/- 3.30, N = 3 SE +/- 4.86, N = 3 SE +/- 1.61, N = 3 SE +/- 4.12, N = 3 SE +/- 4.97, N = 3 400773.38 397326.45 328019.70 241722.09 237596.66 232455.68 182716.39 142756.35 120826.81 117080.86 87851.58 71366.17 58583.38 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 7662 EPYC 7702 EPYC 7552 EPYC 7542 EPYC 7502P EPYC 7532 EPYC 7402P EPYC 7282 EPYC 7302P EPYC 7272 EPYC 7232P EPYC 7F52 EPYC 7F32 500 1000 1500 2000 2500 2387.46 2315.41 2071.71 1741.29 1705.78 1476.94 1407.24 1400.36 1278.65 1163.29 961.66 850.73 783.29
Result Confidence
OpenBenchmarking.org Bogo Ops/s, More Is Better Stress-NG 0.11.07 Test: Vector Math EPYC 7662 EPYC 7702 EPYC 7552 EPYC 7542 EPYC 7502P EPYC 7532 EPYC 7402P EPYC 7F52 EPYC 7302P EPYC 7282 EPYC 7272 EPYC 7F32 EPYC 7232P 70K 140K 210K 280K 350K Min: 400607.54 / Avg: 400773.38 / Max: 401046.47 Min: 397034.87 / Avg: 397326.45 / Max: 397724.18 Min: 327828.63 / Avg: 328019.7 / Max: 328398.59 Min: 241657.95 / Avg: 241722.09 / Max: 241767.28 Min: 237474.07 / Avg: 237596.66 / Max: 237701.83 Min: 232394.78 / Avg: 232455.68 / Max: 232549.81 Min: 182574.85 / Avg: 182716.39 / Max: 182910.32 Min: 142752.27 / Avg: 142756.35 / Max: 142763.4 Min: 120822.19 / Avg: 120826.81 / Max: 120833.2 Min: 117074.78 / Avg: 117080.86 / Max: 117090.47 Min: 87849.93 / Avg: 87851.58 / Max: 87854.8 Min: 71360.29 / Avg: 71366.17 / Max: 71374.11 Min: 58573.44 / Avg: 58583.38 / Max: 58588.42 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 7662 EPYC 7702 EPYC 7642 EPYC 7552 EPYC 7542 EPYC 7502P EPYC 7532 EPYC 7402P EPYC 7F52 EPYC 7302P EPYC 7282 EPYC 7272 EPYC 7F32 EPYC 7232P 16K 32K 48K 64K 80K SE +/- 4.67, N = 3 SE +/- 15.77, N = 3 SE +/- 3.00, N = 3 SE +/- 72.25, N = 3 SE +/- 17.06, N = 3 SE +/- 8.37, N = 3 SE +/- 9.84, N = 3 SE +/- 1.00, N = 3 SE +/- 3.33, N = 3 SE +/- 3.06, N = 3 SE +/- 12.17, N = 3 SE +/- 4.10, N = 3 SE +/- 1.67, N = 3 SE +/- 2.31, N = 3 73579 70033 61119 59963 44596 43703 42800 33755 26345 22314 21454 16224 13183 10825 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 7662 EPYC 7702 EPYC 7552 EPYC 7642 EPYC 7542 EPYC 7502P EPYC 7532 EPYC 7402P EPYC 7282 EPYC 7302P EPYC 7272 EPYC 7232P EPYC 7F52 EPYC 7F32 100 200 300 400 500 439.24 420.61 379.39 337.12 317.83 316.71 273.00 260.68 255.06 235.34 213.21 177.43 156.27 144.00
Result Confidence
OpenBenchmarking.org Real C/S, More Is Better John The Ripper 1.9.0-jumbo-1 Test: Blowfish EPYC 7662 EPYC 7702 EPYC 7642 EPYC 7552 EPYC 7542 EPYC 7502P EPYC 7532 EPYC 7402P EPYC 7F52 EPYC 7302P EPYC 7282 EPYC 7272 EPYC 7F32 EPYC 7232P 13K 26K 39K 52K 65K Min: 73574 / Avg: 73578.67 / Max: 73588 Min: 70003 / Avg: 70033.33 / Max: 70056 Min: 61113 / Avg: 61119 / Max: 61122 Min: 59835 / Avg: 59963.33 / Max: 60085 Min: 44563 / Avg: 44596 / Max: 44620 Min: 43689 / Avg: 43703.33 / Max: 43718 Min: 42782 / Avg: 42799.67 / Max: 42816 Min: 33753 / Avg: 33755 / Max: 33756 Min: 26342 / Avg: 26345.33 / Max: 26352 Min: 22310 / Avg: 22314 / Max: 22320 Min: 21436 / Avg: 21453.67 / Max: 21477 Min: 16216 / Avg: 16223.67 / Max: 16230 Min: 13181 / Avg: 13182.67 / Max: 13186 Min: 10821 / Avg: 10825 / Max: 10829 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 7662 EPYC 7702 EPYC 7642 EPYC 7552 EPYC 7542 EPYC 7502P EPYC 7532 EPYC 7402P EPYC 7302P EPYC 7282 EPYC 7F52 EPYC 7272 EPYC 7F32 EPYC 7232P 1.1228 2.2456 3.3684 4.4912 5.614 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 +/- 0.00, 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 4.99 4.92 4.21 4.17 3.23 3.03 2.97 2.45 1.65 1.59 1.48 1.22 0.95 0.76 MIN: 4.95 / MAX: 5.03 MIN: 4.88 / MAX: 4.95 MIN: 4.1 / MAX: 4.24 MIN: 4.12 / MAX: 4.18 MIN: 3.19 / MAX: 3.24 MIN: 2.99 / MAX: 3.04 MIN: 2.93 / MAX: 2.99 MIN: 2.43 / MAX: 2.46 MIN: 1.63 MIN: 1.58 / MAX: 1.6 MIN: 1.47 / MAX: 1.49 MIN: 1.21 MAX: 0.77
FPS Per Watt
OpenBenchmarking.org FPS Per Watt, More Is Better OSPray 1.8.5 Demo: San Miguel - Renderer: Path Tracer EPYC 7662 EPYC 7642 EPYC 7552 EPYC 7702 EPYC 7532 EPYC 7282 EPYC 7542 EPYC 7502P EPYC 7302P EPYC 7402P EPYC 7F32 EPYC 7F52 EPYC 7272 EPYC 7232P 0.009 0.018 0.027 0.036 0.045 0.04 0.03 0.03 0.03 0.02 0.02 0.02 0.02 0.02 0.02 0.01 0.01 0.01 0.01
Result Confidence
OpenBenchmarking.org FPS, More Is Better OSPray 1.8.5 Demo: San Miguel - Renderer: Path Tracer EPYC 7662 EPYC 7702 EPYC 7642 EPYC 7552 EPYC 7542 EPYC 7502P EPYC 7532 EPYC 7402P EPYC 7302P EPYC 7282 EPYC 7F52 EPYC 7272 EPYC 7F32 EPYC 7232P 2 4 6 8 10 Min: 4.98 / Avg: 4.99 / Max: 5 Min: 4.9 / Avg: 4.92 / Max: 4.93 Min: 4.2 / Avg: 4.21 / Max: 4.22 Min: 4.17 / Avg: 4.17 / Max: 4.17 Min: 3.23 / Avg: 3.23 / Max: 3.23 Min: 3.03 / Avg: 3.03 / Max: 3.03 Min: 2.97 / Avg: 2.97 / Max: 2.97 Min: 2.44 / Avg: 2.45 / Max: 2.45 Min: 1.65 / Avg: 1.65 / Max: 1.65 Min: 1.59 / Avg: 1.59 / Max: 1.59 Min: 1.48 / Avg: 1.48 / Max: 1.48 Min: 1.22 / Avg: 1.22 / Max: 1.22 Min: 0.95 / Avg: 0.95 / Max: 0.95 Min: 0.76 / Avg: 0.76 / Max: 0.76
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 7662 EPYC 7702 EPYC 7552 EPYC 7532 EPYC 7542 EPYC 7502P EPYC 7F52 EPYC 7402P EPYC 7302P EPYC 7282 EPYC 7272 EPYC 7F32 EPYC 7232P 10 20 30 40 50 SE +/- 0.054901, N = 6 SE +/- 0.058701, N = 6 SE +/- 0.095577, N = 5 SE +/- 0.014397, N = 5 SE +/- 0.043495, N = 4 SE +/- 0.026648, N = 4 SE +/- 0.007758, N = 4 SE +/- 0.019214, N = 3 SE +/- 0.036573, N = 3 SE +/- 0.019691, N = 3 SE +/- 0.292336, N = 3 SE +/- 0.037928, N = 3 SE +/- 0.039126, N = 3 6.995321 7.033982 8.988538 10.885760 14.164820 14.781570 16.139290 16.653750 21.951880 28.993920 33.808520 34.580030 45.154600 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 7662 EPYC 7702 EPYC 7552 EPYC 7532 EPYC 7542 EPYC 7502P EPYC 7F52 EPYC 7402P EPYC 7302P EPYC 7282 EPYC 7272 EPYC 7F32 EPYC 7232P 9 18 27 36 45 Min: 6.85 / Avg: 7 / Max: 7.2 Min: 6.86 / Avg: 7.03 / Max: 7.24 Min: 8.8 / Avg: 8.99 / Max: 9.33 Min: 10.85 / Avg: 10.89 / Max: 10.92 Min: 14.12 / Avg: 14.16 / Max: 14.3 Min: 14.73 / Avg: 14.78 / Max: 14.84 Min: 16.12 / Avg: 16.14 / Max: 16.16 Min: 16.63 / Avg: 16.65 / Max: 16.69 Min: 21.9 / Avg: 21.95 / Max: 22.02 Min: 28.96 / Avg: 28.99 / Max: 29.03 Min: 33.47 / Avg: 33.81 / Max: 34.39 Min: 34.52 / Avg: 34.58 / Max: 34.65 Min: 45.1 / Avg: 45.15 / Max: 45.23 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 7662 EPYC 7702 EPYC 7552 EPYC 7542 EPYC 7502P EPYC 7532 EPYC 7402P EPYC 7F52 EPYC 7302P EPYC 7282 EPYC 7272 EPYC 7F32 EPYC 7232P 3K 6K 9K 12K 15K SE +/- 2.16, N = 3 SE +/- 5.99, N = 3 SE +/- 6.05, N = 3 SE +/- 2.98, N = 3 SE +/- 6.32, N = 3 SE +/- 2.43, N = 3 SE +/- 0.38, N = 3 SE +/- 2.53, N = 3 SE +/- 5.77, N = 3 SE +/- 0.60, N = 3 SE +/- 0.42, N = 3 SE +/- 2.21, N = 3 SE +/- 0.98, N = 3 12091.56 11996.59 9992.15 7720.58 7273.71 7105.73 5847.70 4580.08 3871.57 3760.66 2821.19 2288.33 1878.74 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 7662 EPYC 7702 EPYC 7552 EPYC 7502P EPYC 7542 EPYC 7532 EPYC 7402P EPYC 7282 EPYC 7302P EPYC 7272 EPYC 7232P EPYC 7F52 EPYC 7F32 16 32 48 64 80 70.11 68.08 61.88 52.91 49.49 45.60 40.81 40.39 37.06 33.86 28.52 24.38 23.03
Result Confidence
OpenBenchmarking.org Bogo Ops/s, More Is Better Stress-NG 0.11.07 Test: Crypto EPYC 7662 EPYC 7702 EPYC 7552 EPYC 7542 EPYC 7502P EPYC 7532 EPYC 7402P EPYC 7F52 EPYC 7302P EPYC 7282 EPYC 7272 EPYC 7F32 EPYC 7232P 2K 4K 6K 8K 10K Min: 12087.35 / Avg: 12091.56 / Max: 12094.48 Min: 11984.94 / Avg: 11996.59 / Max: 12004.82 Min: 9980.12 / Avg: 9992.15 / Max: 9999.28 Min: 7715.51 / Avg: 7720.58 / Max: 7725.83 Min: 7261.15 / Avg: 7273.71 / Max: 7281.24 Min: 7100.89 / Avg: 7105.73 / Max: 7108.61 Min: 5846.99 / Avg: 5847.7 / Max: 5848.3 Min: 4577.39 / Avg: 4580.08 / Max: 4585.14 Min: 3864.76 / Avg: 3871.57 / Max: 3883.04 Min: 3759.79 / Avg: 3760.66 / Max: 3761.8 Min: 2820.54 / Avg: 2821.19 / Max: 2821.99 Min: 2285.96 / Avg: 2288.33 / Max: 2292.74 Min: 1877.16 / Avg: 1878.74 / Max: 1880.55 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 7662 EPYC 7702 EPYC 7642 EPYC 7532 EPYC 7552 EPYC 7F52 EPYC 7542 EPYC 7502P EPYC 7402P EPYC 7302P EPYC 7F32 EPYC 7282 EPYC 7272 EPYC 7232P 2 4 6 8 10 SE +/- 0.002146, N = 7 SE +/- 0.002719, N = 7 SE +/- 0.002747, N = 7 SE +/- 0.001701, N = 7 SE +/- 0.003838, N = 7 SE +/- 0.002179, N = 7 SE +/- 0.011195, N = 7 SE +/- 0.008223, N = 7 SE +/- 0.005689, N = 7 SE +/- 0.006442, N = 7 SE +/- 0.007190, N = 7 SE +/- 0.008434, N = 7 SE +/- 0.005350, N = 7 SE +/- 0.004801, N = 7 0.993732 1.078440 1.108050 1.483740 1.719670 2.001830 3.461740 3.462360 3.543470 3.706400 4.301300 5.864580 5.953480 6.376680 MIN: 1.28 MIN: 1.63 MIN: 1.91 MIN: 3.38 MIN: 3.38 MIN: 3.47 MIN: 3.6 MIN: 4.22 MIN: 5.63 MIN: 5.82 MIN: 6.27 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 7662 EPYC 7702 EPYC 7642 EPYC 7532 EPYC 7552 EPYC 7F52 EPYC 7542 EPYC 7502P EPYC 7402P EPYC 7302P EPYC 7F32 EPYC 7282 EPYC 7272 EPYC 7232P 3 6 9 12 15 Min: 0.99 / Avg: 0.99 / Max: 1 Min: 1.07 / Avg: 1.08 / Max: 1.09 Min: 1.1 / Avg: 1.11 / Max: 1.12 Min: 1.47 / Avg: 1.48 / Max: 1.49 Min: 1.7 / Avg: 1.72 / Max: 1.73 Min: 1.99 / Avg: 2 / Max: 2.01 Min: 3.44 / Avg: 3.46 / Max: 3.53 Min: 3.43 / Avg: 3.46 / Max: 3.5 Min: 3.52 / Avg: 3.54 / Max: 3.56 Min: 3.67 / Avg: 3.71 / Max: 3.73 Min: 4.26 / Avg: 4.3 / Max: 4.32 Min: 5.83 / Avg: 5.86 / Max: 5.9 Min: 5.94 / Avg: 5.95 / Max: 5.98 Min: 6.36 / Avg: 6.38 / Max: 6.4 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 7642 EPYC 7662 EPYC 7702 EPYC 7532 EPYC 7552 EPYC 7F52 EPYC 7402P EPYC 7502P EPYC 7542 EPYC 7302P EPYC 7F32 EPYC 7282 EPYC 7272 EPYC 7232P 5K 10K 15K 20K 25K SE +/- 197.00, N = 3 SE +/- 121.22, N = 3 SE +/- 112.07, N = 3 SE +/- 215.40, N = 3 SE +/- 61.33, N = 3 SE +/- 118.03, N = 3 SE +/- 63.07, N = 3 SE +/- 137.10, N = 3 SE +/- 162.55, N = 3 SE +/- 68.60, N = 3 SE +/- 74.25, N = 4 SE +/- 27.68, N = 3 SE +/- 48.79, N = 9 SE +/- 28.76, N = 3 21472.30 20993.10 20185.50 18311.70 16990.10 13692.30 12173.70 12067.30 11976.90 10427.20 6907.54 6587.57 6100.18 3350.22 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 7642 EPYC 7662 EPYC 7702 EPYC 7532 EPYC 7552 EPYC 7F52 EPYC 7402P EPYC 7502P EPYC 7542 EPYC 7302P EPYC 7F32 EPYC 7282 EPYC 7272 EPYC 7232P 4K 8K 12K 16K 20K 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: 18096.3 / Avg: 18311.7 / Max: 18742.5 Min: 16928.8 / Avg: 16990.13 / Max: 17112.8 Min: 13456.2 / Avg: 13692.27 / Max: 13810.3 Min: 12110.6 / Avg: 12173.67 / Max: 12299.8 Min: 11793.1 / Avg: 12067.3 / Max: 12204.4 Min: 11662 / Avg: 11976.87 / Max: 12204.4 Min: 10290 / Avg: 10427.2 / Max: 10495.8 Min: 6728.09 / Avg: 6907.54 / Max: 7091.77 Min: 6559.89 / Avg: 6587.57 / Max: 6642.93 Min: 5788.14 / Avg: 6100.18 / Max: 6247.52 Min: 3321.46 / Avg: 3350.22 / Max: 3407.74 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 7662 EPYC 7702 EPYC 7552 EPYC 7542 EPYC 7502P EPYC 7532 EPYC 7402P EPYC 7F52 EPYC 7302P EPYC 7282 EPYC 7272 EPYC 7F32 EPYC 7232P 400K 800K 1200K 1600K 2000K SE +/- 473.83, N = 3 SE +/- 1046.01, N = 3 SE +/- 10873.39, N = 3 SE +/- 1150.50, N = 3 SE +/- 609.31, N = 3 SE +/- 707.15, N = 3 SE +/- 1542.09, N = 3 SE +/- 1470.27, N = 3 SE +/- 1815.81, N = 3 SE +/- 538.09, N = 3 SE +/- 270.65, N = 3 SE +/- 818.34, N = 3 SE +/- 102.44, N = 3 1867023.46 1845888.80 1530338.79 1203386.72 1147733.95 1123555.30 902070.15 716393.88 603381.33 586659.10 440879.64 356570.41 293387.40 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 7662 EPYC 7702 EPYC 7552 EPYC 7502P EPYC 7542 EPYC 7532 EPYC 7402P EPYC 7282 EPYC 7302P EPYC 7272 EPYC 7232P EPYC 7F52 EPYC 7F32 3K 6K 9K 12K 15K 11942.55 11585.51 10306.40 8528.23 8324.83 7324.67 6564.90 6395.91 5810.65 5295.21 4345.65 3863.56 3489.81
Result Confidence
OpenBenchmarking.org Iterations/Sec, More Is Better Coremark 1.0 CoreMark Size 666 - Iterations Per Second EPYC 7662 EPYC 7702 EPYC 7552 EPYC 7542 EPYC 7502P EPYC 7532 EPYC 7402P EPYC 7F52 EPYC 7302P EPYC 7282 EPYC 7272 EPYC 7F32 EPYC 7232P 300K 600K 900K 1200K 1500K Min: 1866161.25 / Avg: 1867023.46 / Max: 1867795.13 Min: 1844712.66 / Avg: 1845888.8 / Max: 1847975.17 Min: 1517351.75 / Avg: 1530338.79 / Max: 1551938.41 Min: 1201201.2 / Avg: 1203386.72 / Max: 1205102.86 Min: 1146516.78 / Avg: 1147733.95 / Max: 1148394.04 Min: 1122462.4 / Avg: 1123555.3 / Max: 1124879.16 Min: 899666.14 / Avg: 902070.15 / Max: 904945.39 Min: 713469.52 / Avg: 716393.88 / Max: 718122.78 Min: 599995.31 / Avg: 603381.33 / Max: 606211.3 Min: 585752.04 / Avg: 586659.1 / Max: 587614.19 Min: 440356.87 / Avg: 440879.64 / Max: 441262.65 Min: 355244.72 / Avg: 356570.41 / Max: 358064.49 Min: 293258.49 / Avg: 293387.4 / Max: 293589.77 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 7662 EPYC 7702 EPYC 7642 EPYC 7532 EPYC 7552 EPYC 7F52 EPYC 7542 EPYC 7502P EPYC 7302P EPYC 7402P EPYC 7282 EPYC 7272 EPYC 7F32 EPYC 7232P 2 4 6 8 10 SE +/- 0.01221, N = 5 SE +/- 0.00630, N = 5 SE +/- 0.01041, N = 5 SE +/- 0.00475, N = 5 SE +/- 0.00795, N = 5 SE +/- 0.01324, N = 5 SE +/- 0.00208, N = 5 SE +/- 0.00256, N = 5 SE +/- 0.00471, N = 5 SE +/- 0.01609, N = 5 SE +/- 0.00189, N = 5 SE +/- 0.00853, N = 5 SE +/- 0.00869, N = 5 SE +/- 0.01715, N = 5 1.12502 1.15943 1.22011 1.25154 2.28611 2.77826 2.95830 2.96283 3.76395 4.13382 4.47287 4.97512 6.68209 7.15030 MIN: 1.2 MIN: 2.2 MIN: 2.68 MIN: 2.88 MIN: 2.89 MIN: 3.68 MIN: 3.91 MIN: 4.3 MIN: 4.75 MIN: 6.52 MIN: 6.45 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: f32 - Engine: CPU EPYC 7662 EPYC 7702 EPYC 7642 EPYC 7532 EPYC 7552 EPYC 7F52 EPYC 7542 EPYC 7502P EPYC 7302P EPYC 7402P EPYC 7282 EPYC 7272 EPYC 7F32 EPYC 7232P 3 6 9 12 15 Min: 1.1 / Avg: 1.13 / Max: 1.17 Min: 1.14 / Avg: 1.16 / Max: 1.17 Min: 1.19 / Avg: 1.22 / Max: 1.25 Min: 1.24 / Avg: 1.25 / Max: 1.26 Min: 2.26 / Avg: 2.29 / Max: 2.3 Min: 2.75 / Avg: 2.78 / Max: 2.83 Min: 2.95 / Avg: 2.96 / Max: 2.97 Min: 2.96 / Avg: 2.96 / Max: 2.97 Min: 3.75 / Avg: 3.76 / Max: 3.78 Min: 4.08 / Avg: 4.13 / Max: 4.18 Min: 4.47 / Avg: 4.47 / Max: 4.48 Min: 4.94 / Avg: 4.98 / Max: 4.99 Min: 6.66 / Avg: 6.68 / Max: 6.71 Min: 7.11 / Avg: 7.15 / Max: 7.19 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 7662 EPYC 7702 EPYC 7552 EPYC 7542 EPYC 7502P EPYC 7532 EPYC 7402P EPYC 7F52 EPYC 7302P EPYC 7282 EPYC 7272 EPYC 7F32 EPYC 7232P 20 40 60 80 100 SE +/- 0.03, N = 4 SE +/- 0.03, N = 4 SE +/- 0.06, N = 4 SE +/- 0.05, N = 3 SE +/- 0.05, N = 3 SE +/- 0.03, N = 3 SE +/- 0.08, N = 3 SE +/- 0.01, N = 3 SE +/- 0.02, N = 3 SE +/- 0.04, N = 3 SE +/- 0.02, N = 3 SE +/- 0.01, N = 3 SE +/- 0.01, N = 3 13.75 13.84 16.61 21.37 22.63 23.05 28.19 35.92 42.38 43.74 58.22 71.58 87.19 1. (CXX) g++ options: -fopenmp -O2 -march=native
Result Confidence
OpenBenchmarking.org Seconds, Fewer Is Better m-queens 1.2 Time To Solve EPYC 7662 EPYC 7702 EPYC 7552 EPYC 7542 EPYC 7502P EPYC 7532 EPYC 7402P EPYC 7F52 EPYC 7302P EPYC 7282 EPYC 7272 EPYC 7F32 EPYC 7232P 20 40 60 80 100 Min: 13.72 / Avg: 13.75 / Max: 13.84 Min: 13.77 / Avg: 13.84 / Max: 13.89 Min: 16.48 / Avg: 16.61 / Max: 16.78 Min: 21.31 / Avg: 21.37 / Max: 21.46 Min: 22.57 / Avg: 22.63 / Max: 22.73 Min: 23.01 / Avg: 23.05 / Max: 23.09 Min: 28.07 / Avg: 28.19 / Max: 28.33 Min: 35.9 / Avg: 35.92 / Max: 35.93 Min: 42.35 / Avg: 42.38 / Max: 42.41 Min: 43.69 / Avg: 43.74 / Max: 43.81 Min: 58.19 / Avg: 58.22 / Max: 58.26 Min: 71.55 / Avg: 71.58 / Max: 71.6 Min: 87.19 / Avg: 87.19 / Max: 87.2 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 7702 EPYC 7662 EPYC 7552 EPYC 7542 EPYC 7502P EPYC 7532 EPYC 7402P EPYC 7F52 EPYC 7302P EPYC 7282 EPYC 7272 EPYC 7F32 EPYC 7232P 20M 40M 60M 80M 100M SE +/- 597478.91, N = 3 SE +/- 1212155.43, N = 4 SE +/- 82765.80, N = 3 SE +/- 88880.09, N = 3 SE +/- 436034.06, N = 15 SE +/- 708563.50, N = 4 SE +/- 304616.08, N = 3 SE +/- 416432.88, N = 3 SE +/- 332801.18, N = 6 SE +/- 236966.05, N = 10 SE +/- 71263.56, N = 3 SE +/- 79798.13, N = 3 SE +/- 150250.14, N = 3 100908453 98847469 82397132 64152929 60864616 58384026 48804732 39043410 32973749 31246137 24314443 19191199 16034994 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 7662 EPYC 7702 EPYC 7552 EPYC 7502P EPYC 7542 EPYC 7532 EPYC 7402P EPYC 7282 EPYC 7302P EPYC 7272 EPYC 7232P EPYC 7F52 EPYC 7F32 120K 240K 360K 480K 600K 560733.59 552076.25 491891.78 419124.02 391203.16 369416.83 325661.01 311552.67 271259.26 246303.77 205655.17 179617.03 162559.29
Result Confidence
OpenBenchmarking.org Nodes Per Second, More Is Better Stockfish 12 Total Time EPYC 7702 EPYC 7662 EPYC 7552 EPYC 7542 EPYC 7502P EPYC 7532 EPYC 7402P EPYC 7F52 EPYC 7302P EPYC 7282 EPYC 7272 EPYC 7F32 EPYC 7232P 20M 40M 60M 80M 100M Min: 99825755 / Avg: 100908453 / Max: 101887714 Min: 95322228 / Avg: 98847468.5 / Max: 100858323 Min: 82260216 / Avg: 82397132 / Max: 82546157 Min: 63992140 / Avg: 64152928.67 / Max: 64298968 Min: 57227030 / Avg: 60864616.13 / Max: 63501145 Min: 56735799 / Avg: 58384025.75 / Max: 60090226 Min: 48420286 / Avg: 48804732.33 / Max: 49406252 Min: 38530677 / Avg: 39043410.33 / Max: 39868176 Min: 32141990 / Avg: 32973748.83 / Max: 34537511 Min: 30342075 / Avg: 31246136.8 / Max: 32525396 Min: 24195092 / Avg: 24314443.33 / Max: 24441587 Min: 19064701 / Avg: 19191199.33 / Max: 19338721 Min: 15735361 / Avg: 16034994 / Max: 16204568 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 7662 EPYC 7702 EPYC 7552 EPYC 7542 EPYC 7502P EPYC 7532 EPYC 7402P EPYC 7F52 EPYC 7302P EPYC 7282 EPYC 7272 EPYC 7F32 EPYC 7232P 4 8 12 16 20 SE +/- 0.001, N = 10 SE +/- 0.001, N = 10 SE +/- 0.001, N = 9 SE +/- 0.000, N = 8 SE +/- 0.001, N = 8 SE +/- 0.001, N = 8 SE +/- 0.001, N = 7 SE +/- 0.000, N = 6 SE +/- 0.000, N = 5 SE +/- 0.004, N = 5 SE +/- 0.000, N = 4 SE +/- 0.000, N = 4 SE +/- 0.001, N = 3 2.787 2.802 3.352 4.273 4.599 4.710 5.645 7.152 8.449 8.785 11.618 14.298 17.421 1. (CC) gcc options: -static -fopenmp -O3 -march=native
Result Confidence
OpenBenchmarking.org Seconds, Fewer Is Better N-Queens 1.0 Elapsed Time EPYC 7662 EPYC 7702 EPYC 7552 EPYC 7542 EPYC 7502P EPYC 7532 EPYC 7402P EPYC 7F52 EPYC 7302P EPYC 7282 EPYC 7272 EPYC 7F32 EPYC 7232P 4 8 12 16 20 Min: 2.78 / Avg: 2.79 / Max: 2.79 Min: 2.8 / Avg: 2.8 / Max: 2.81 Min: 3.35 / Avg: 3.35 / Max: 3.36 Min: 4.27 / Avg: 4.27 / Max: 4.27 Min: 4.6 / Avg: 4.6 / Max: 4.6 Min: 4.71 / Avg: 4.71 / Max: 4.71 Min: 5.64 / Avg: 5.65 / Max: 5.65 Min: 7.15 / Avg: 7.15 / Max: 7.15 Min: 8.45 / Avg: 8.45 / Max: 8.45 Min: 8.78 / Avg: 8.79 / Max: 8.8 Min: 11.62 / Avg: 11.62 / Max: 11.62 Min: 14.3 / Avg: 14.3 / Max: 14.3 Min: 17.42 / Avg: 17.42 / Max: 17.42 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 7662 EPYC 7702 EPYC 7642 EPYC 7552 EPYC 7542 EPYC 7502P EPYC 7532 EPYC 7402P EPYC 7F52 EPYC 7302P EPYC 7282 EPYC 7272 EPYC 7F32 EPYC 7232P 20 40 60 80 100 SE +/- 0.02, N = 4 SE +/- 0.01, N = 4 SE +/- 0.01, N = 4 SE +/- 0.02, N = 4 SE +/- 0.03, 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 +/- 0.03, N = 3 SE +/- 0.01, N = 3 SE +/- 0.02, N = 3 SE +/- 0.03, N = 3 12.82 12.85 15.04 15.21 19.55 20.91 21.43 25.68 32.58 38.49 39.66 52.81 64.97 79.17 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 7662 EPYC 7702 EPYC 7642 EPYC 7552 EPYC 7542 EPYC 7502P EPYC 7532 EPYC 7402P EPYC 7F52 EPYC 7302P EPYC 7282 EPYC 7272 EPYC 7F32 EPYC 7232P 15 30 45 60 75 Min: 12.79 / Avg: 12.81 / Max: 12.87 Min: 12.83 / Avg: 12.85 / Max: 12.87 Min: 15.01 / Avg: 15.04 / Max: 15.06 Min: 15.17 / Avg: 15.21 / Max: 15.24 Min: 19.49 / Avg: 19.55 / Max: 19.6 Min: 20.89 / Avg: 20.91 / Max: 20.94 Min: 21.4 / Avg: 21.43 / Max: 21.45 Min: 25.67 / Avg: 25.68 / Max: 25.7 Min: 32.55 / Avg: 32.58 / Max: 32.61 Min: 38.48 / Avg: 38.49 / Max: 38.51 Min: 39.61 / Avg: 39.66 / Max: 39.7 Min: 52.8 / Avg: 52.81 / Max: 52.82 Min: 64.93 / Avg: 64.97 / Max: 64.99 Min: 79.13 / Avg: 79.17 / Max: 79.22 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 7702 EPYC 7662 EPYC 7642 EPYC 7552 EPYC 7542 EPYC 7502P EPYC 7532 EPYC 7402P EPYC 7F52 EPYC 7302P EPYC 7282 EPYC 7272 EPYC 7F32 EPYC 7232P 5 10 15 20 25 SE +/- 0.043, N = 3 SE +/- 0.063, N = 3 SE +/- 0.035, N = 3 SE +/- 0.038, N = 3 SE +/- 0.008, N = 3 SE +/- 0.031, N = 3 SE +/- 0.016, N = 3 SE +/- 0.014, N = 3 SE +/- 0.013, N = 3 SE +/- 0.006, N = 3 SE +/- 0.005, N = 3 SE +/- 0.010, N = 3 SE +/- 0.002, N = 3 SE +/- 0.002, N = 3 19.095 19.062 16.230 15.984 12.738 11.854 11.531 9.630 7.684 6.575 6.214 4.855 3.883 3.117
M samples/s Per Watt
OpenBenchmarking.org M samples/s Per Watt, More Is Better IndigoBench 4.4 Acceleration: CPU - Scene: Supercar EPYC 7662 EPYC 7702 EPYC 7642 EPYC 7552 EPYC 7542 EPYC 7502P EPYC 7532 EPYC 7282 EPYC 7402P EPYC 7272 EPYC 7302P EPYC 7232P EPYC 7F32 EPYC 7F52 0.0225 0.045 0.0675 0.09 0.1125 0.10 0.10 0.09 0.09 0.08 0.08 0.07 0.06 0.06 0.05 0.05 0.04 0.03 0.03
Result Confidence
OpenBenchmarking.org M samples/s, More Is Better IndigoBench 4.4 Acceleration: CPU - Scene: Supercar EPYC 7702 EPYC 7662 EPYC 7642 EPYC 7552 EPYC 7542 EPYC 7502P EPYC 7532 EPYC 7402P EPYC 7F52 EPYC 7302P EPYC 7282 EPYC 7272 EPYC 7F32 EPYC 7232P 5 10 15 20 25 Min: 19.02 / Avg: 19.1 / Max: 19.16 Min: 18.94 / Avg: 19.06 / Max: 19.14 Min: 16.18 / Avg: 16.23 / Max: 16.3 Min: 15.93 / Avg: 15.98 / Max: 16.06 Min: 12.72 / Avg: 12.74 / Max: 12.75 Min: 11.8 / Avg: 11.85 / Max: 11.9 Min: 11.52 / Avg: 11.53 / Max: 11.56 Min: 9.6 / Avg: 9.63 / Max: 9.65 Min: 7.67 / Avg: 7.68 / Max: 7.71 Min: 6.57 / Avg: 6.58 / Max: 6.59 Min: 6.21 / Avg: 6.21 / Max: 6.22 Min: 4.84 / Avg: 4.85 / Max: 4.87 Min: 3.88 / Avg: 3.88 / Max: 3.89 Min: 3.11 / Avg: 3.12 / Max: 3.12
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 7662 EPYC 7702 EPYC 7642 EPYC 7552 EPYC 7542 EPYC 7502P EPYC 7532 EPYC 7402P EPYC 7F52 EPYC 7302P EPYC 7282 EPYC 7272 EPYC 7F32 EPYC 7232P 30K 60K 90K 120K 150K SE +/- 32.87, N = 3 SE +/- 31.81, N = 3 SE +/- 45.55, N = 3 SE +/- 87.07, N = 3 SE +/- 28.55, N = 3 SE +/- 15.49, N = 3 SE +/- 7.45, N = 3 SE +/- 16.32, N = 3 SE +/- 28.27, N = 3 SE +/- 34.38, N = 3 SE +/- 30.64, N = 3 SE +/- 28.65, N = 3 SE +/- 28.30, N = 3 SE +/- 6.91, N = 3 143292.79 143169.12 120520.68 119683.65 94237.65 87391.79 85303.35 71372.79 56973.85 48284.83 46017.20 35086.95 28528.34 23406.40 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 7662 EPYC 7702 EPYC 7552 EPYC 7642 EPYC 7502P EPYC 7542 EPYC 7532 EPYC 7402P EPYC 7282 EPYC 7302P EPYC 7272 EPYC 7232P EPYC 7F52 EPYC 7F32 200 400 600 800 1000 819.37 798.57 725.65 669.52 628.13 584.98 551.30 481.81 473.01 426.14 387.56 334.92 275.97 262.96
Result Confidence
OpenBenchmarking.org k/s, More Is Better Aircrack-ng 1.5.2 EPYC 7662 EPYC 7702 EPYC 7642 EPYC 7552 EPYC 7542 EPYC 7502P EPYC 7532 EPYC 7402P EPYC 7F52 EPYC 7302P EPYC 7282 EPYC 7272 EPYC 7F32 EPYC 7232P 20K 40K 60K 80K 100K Min: 143233.45 / Avg: 143292.79 / Max: 143346.95 Min: 143136.28 / Avg: 143169.12 / Max: 143232.73 Min: 120433.36 / Avg: 120520.68 / Max: 120586.84 Min: 119543.75 / Avg: 119683.65 / Max: 119843.41 Min: 94189.9 / Avg: 94237.65 / Max: 94288.64 Min: 87370.61 / Avg: 87391.79 / Max: 87421.95 Min: 85294.1 / Avg: 85303.35 / Max: 85318.1 Min: 71350.26 / Avg: 71372.79 / Max: 71404.51 Min: 56938.61 / Avg: 56973.85 / Max: 57029.76 Min: 48218.5 / Avg: 48284.83 / Max: 48333.69 Min: 45958.39 / Avg: 46017.2 / Max: 46061.5 Min: 35057.87 / Avg: 35086.95 / Max: 35144.26 Min: 28484.88 / Avg: 28528.34 / Max: 28581.47 Min: 23398.23 / Avg: 23406.4 / Max: 23420.13 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 7662 EPYC 7702 EPYC 7642 EPYC 7552 EPYC 7542 EPYC 7502P EPYC 7532 EPYC 7402P EPYC 7F52 EPYC 7302P EPYC 7282 EPYC 7272 EPYC 7F32 EPYC 7232P 2 4 6 8 10 SE +/- 0.013, N = 3 SE +/- 0.006, N = 3 SE +/- 0.020, N = 3 SE +/- 0.007, N = 3 SE +/- 0.002, N = 3 SE +/- 0.006, N = 3 SE +/- 0.008, N = 3 SE +/- 0.009, N = 3 SE +/- 0.004, N = 3 SE +/- 0.006, N = 3 SE +/- 0.001, N = 3 SE +/- 0.001, N = 3 SE +/- 0.002, N = 3 SE +/- 0.002, N = 3 8.898 8.811 7.596 7.555 5.950 5.477 5.415 4.494 3.461 3.129 2.932 2.289 1.808 1.456
M samples/s Per Watt
OpenBenchmarking.org M samples/s Per Watt, More Is Better IndigoBench 4.4 Acceleration: CPU - Scene: Bedroom EPYC 7662 EPYC 7702 EPYC 7642 EPYC 7502P EPYC 7552 EPYC 7532 EPYC 7282 EPYC 7542 EPYC 7302P EPYC 7402P EPYC 7F32 EPYC 7F52 EPYC 7272 EPYC 7232P 0.0113 0.0226 0.0339 0.0452 0.0565 0.05 0.05 0.04 0.04 0.04 0.03 0.03 0.03 0.03 0.03 0.02 0.02 0.02 0.02
Result Confidence
OpenBenchmarking.org M samples/s, More Is Better IndigoBench 4.4 Acceleration: CPU - Scene: Bedroom EPYC 7662 EPYC 7702 EPYC 7642 EPYC 7552 EPYC 7542 EPYC 7502P EPYC 7532 EPYC 7402P EPYC 7F52 EPYC 7302P EPYC 7282 EPYC 7272 EPYC 7F32 EPYC 7232P 3 6 9 12 15 Min: 8.88 / Avg: 8.9 / Max: 8.93 Min: 8.8 / Avg: 8.81 / Max: 8.82 Min: 7.57 / Avg: 7.6 / Max: 7.64 Min: 7.54 / Avg: 7.56 / Max: 7.57 Min: 5.95 / Avg: 5.95 / Max: 5.96 Min: 5.47 / Avg: 5.48 / Max: 5.49 Min: 5.4 / Avg: 5.42 / Max: 5.43 Min: 4.48 / Avg: 4.49 / Max: 4.51 Min: 3.46 / Avg: 3.46 / Max: 3.47 Min: 3.12 / Avg: 3.13 / Max: 3.14 Min: 2.93 / Avg: 2.93 / Max: 2.93 Min: 2.29 / Avg: 2.29 / Max: 2.29 Min: 1.8 / Avg: 1.81 / Max: 1.81 Min: 1.45 / Avg: 1.46 / Max: 1.46
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 7662 EPYC 7702 EPYC 7552 EPYC 7542 EPYC 7502P EPYC 7532 EPYC 7402P EPYC 7F52 EPYC 7302P EPYC 7282 EPYC 7272 EPYC 7F32 EPYC 7232P 4M 8M 12M 16M 20M SE +/- 163606.09, N = 3 SE +/- 235328.27, N = 3 SE +/- 29075.41, N = 3 SE +/- 65922.96, N = 3 SE +/- 19374.10, N = 3 SE +/- 55451.20, N = 3 SE +/- 28222.94, N = 3 SE +/- 30731.73, N = 3 SE +/- 35625.01, N = 3 SE +/- 32954.83, N = 3 SE +/- 15626.15, N = 3 SE +/- 6120.44, N = 3 SE +/- 9437.39, N = 3 20981193.88 20917619.76 17727598.84 13858394.61 12896969.64 12627261.93 10443329.12 8225794.40 7003110.18 6612368.67 5095560.16 4265815.03 3438510.35 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: Context Switching EPYC 7662 EPYC 7702 EPYC 7552 EPYC 7502P EPYC 7542 EPYC 7532 EPYC 7402P EPYC 7282 EPYC 7302P EPYC 7272 EPYC 7232P EPYC 7F52 EPYC 7F32 30K 60K 90K 120K 150K 120719.38 117242.06 107976.93 93564.11 86092.82 80883.70 70344.07 68963.86 63978.31 58318.22 50370.93 41954.82 40925.63
Result Confidence
OpenBenchmarking.org Bogo Ops/s, More Is Better Stress-NG 0.11.07 Test: Context Switching EPYC 7662 EPYC 7702 EPYC 7552 EPYC 7542 EPYC 7502P EPYC 7532 EPYC 7402P EPYC 7F52 EPYC 7302P EPYC 7282 EPYC 7272 EPYC 7F32 EPYC 7232P 4M 8M 12M 16M 20M Min: 20708784.06 / Avg: 20981193.88 / Max: 21274387.73 Min: 20467620.04 / Avg: 20917619.76 / Max: 21262048.98 Min: 17694612.55 / Avg: 17727598.84 / Max: 17785565.68 Min: 13729117.41 / Avg: 13858394.61 / Max: 13945462.29 Min: 12861868.91 / Avg: 12896969.64 / Max: 12928733.42 Min: 12516504.31 / Avg: 12627261.93 / Max: 12687546.78 Min: 10405966.38 / Avg: 10443329.12 / Max: 10498652.3 Min: 8193174.36 / Avg: 8225794.4 / Max: 8287218.36 Min: 6942183.09 / Avg: 7003110.18 / Max: 7065563.44 Min: 6549932.25 / Avg: 6612368.67 / Max: 6661871.66 Min: 5064455.01 / Avg: 5095560.16 / Max: 5113736.06 Min: 4253702.33 / Avg: 4265815.03 / Max: 4273401.47 Min: 3425266.43 / Avg: 3438510.35 / Max: 3456778.84 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 7662 EPYC 7702 EPYC 7642 EPYC 7552 EPYC 7542 EPYC 7502P EPYC 7532 EPYC 7402P EPYC 7F52 EPYC 7302P EPYC 7282 EPYC 7272 EPYC 7F32 EPYC 7232P 2 4 6 8 10 SE +/- 0.01, N = 3 SE +/- 0.00, 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 +/- 0.01, 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 6.00 5.92 5.15 5.10 4.04 3.75 3.70 3.07 2.34 2.15 1.98 1.55 1.27 0.99 MIN: 5.92 / MAX: 6.06 MIN: 5.85 / MAX: 5.99 MIN: 5.08 / MAX: 5.21 MIN: 5.05 / MAX: 5.15 MIN: 3.98 / MAX: 4.07 MIN: 3.72 / MAX: 3.77 MIN: 3.64 / MAX: 3.73 MIN: 3.02 / MAX: 3.11 MIN: 2.29 / MAX: 2.38 MIN: 2.13 / MAX: 2.16 MIN: 1.96 / MAX: 1.99 MIN: 1.54 / MAX: 1.57 MIN: 1.26 / MAX: 1.28 MAX: 1
FPS Per Watt
OpenBenchmarking.org FPS Per Watt, More Is Better OSPray 1.8.5 Demo: XFrog Forest - Renderer: Path Tracer EPYC 7662 EPYC 7642 EPYC 7502P EPYC 7552 EPYC 7702 EPYC 7532 EPYC 7282 EPYC 7542 EPYC 7272 EPYC 7302P EPYC 7402P EPYC 7F32 EPYC 7F52 EPYC 7232P 0.009 0.018 0.027 0.036 0.045 0.04 0.03 0.03 0.03 0.03 0.02 0.02 0.02 0.02 0.02 0.02 0.01 0.01 0.01
Result Confidence
OpenBenchmarking.org FPS, More Is Better OSPray 1.8.5 Demo: XFrog Forest - Renderer: Path Tracer EPYC 7662 EPYC 7702 EPYC 7642 EPYC 7552 EPYC 7542 EPYC 7502P EPYC 7532 EPYC 7402P EPYC 7F52 EPYC 7302P EPYC 7282 EPYC 7272 EPYC 7F32 EPYC 7232P 2 4 6 8 10 Min: 5.99 / Avg: 6 / Max: 6.02 Min: 5.92 / Avg: 5.92 / Max: 5.92 Min: 5.13 / Avg: 5.15 / Max: 5.15 Min: 5.1 / Avg: 5.1 / Max: 5.1 Min: 4.03 / Avg: 4.04 / Max: 4.05 Min: 3.75 / Avg: 3.75 / Max: 3.75 Min: 3.7 / Avg: 3.7 / Max: 3.7 Min: 3.06 / Avg: 3.07 / Max: 3.08 Min: 2.33 / Avg: 2.34 / Max: 2.35 Min: 2.15 / Avg: 2.15 / Max: 2.15 Min: 1.98 / Avg: 1.98 / Max: 1.98 Min: 1.55 / Avg: 1.55 / Max: 1.55 Min: 1.27 / Avg: 1.27 / Max: 1.27 Min: 0.99 / Avg: 0.99 / Max: 0.99
Result
OpenBenchmarking.org FPS, More Is Better OSPray 1.8.5 Demo: NASA Streamlines - Renderer: Path Tracer EPYC 7662 EPYC 7702 EPYC 7642 EPYC 7552 EPYC 7542 EPYC 7502P EPYC 7532 EPYC 7402P EPYC 7F52 EPYC 7302P EPYC 7282 EPYC 7272 EPYC 7F32 EPYC 7232P 4 8 12 16 20 SE +/- 0.00, N = 4 SE +/- 0.00, N = 4 SE +/- 0.00, N = 3 SE +/- 0.00, N = 3 SE +/- 0.00, N = 3 SE +/- 0.04, N = 3 SE +/- 0.00, N = 3 SE +/- 0.00, N = 3 SE +/- 0.02, 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 16.95 16.67 14.49 14.29 11.36 10.60 10.42 8.77 6.83 6.07 5.65 4.39 3.65 2.82 MIN: 16.39 / MAX: 17.24 MIN: 16.39 / MAX: 16.95 MIN: 14.08 / MAX: 14.71 MIN: 13.89 / MAX: 14.49 MIN: 11.11 / MAX: 11.49 MIN: 10.42 / MAX: 10.75 MIN: 10.2 / MAX: 10.53 MIN: 8.62 / MAX: 8.85 MIN: 6.67 / MAX: 6.94 MIN: 5.99 / MAX: 6.13 MIN: 5.59 / MAX: 5.75 MIN: 4.33 / MAX: 4.44 MIN: 3.58 / MAX: 3.69 MIN: 2.79 / MAX: 2.86
FPS Per Watt
OpenBenchmarking.org FPS Per Watt, More Is Better OSPray 1.8.5 Demo: NASA Streamlines - Renderer: Path Tracer EPYC 7662 EPYC 7702 EPYC 7552 EPYC 7642 EPYC 7542 EPYC 7502P EPYC 7532 EPYC 7282 EPYC 7402P EPYC 7272 EPYC 7302P EPYC 7232P EPYC 7F32 EPYC 7F52 0.027 0.054 0.081 0.108 0.135 0.12 0.11 0.10 0.09 0.08 0.08 0.07 0.06 0.06 0.05 0.05 0.04 0.03 0.03
Result Confidence
OpenBenchmarking.org FPS, More Is Better OSPray 1.8.5 Demo: NASA Streamlines - Renderer: Path Tracer EPYC 7662 EPYC 7702 EPYC 7642 EPYC 7552 EPYC 7542 EPYC 7502P EPYC 7532 EPYC 7402P EPYC 7F52 EPYC 7302P EPYC 7282 EPYC 7272 EPYC 7F32 EPYC 7232P 4 8 12 16 20 Min: 16.95 / Avg: 16.95 / Max: 16.95 Min: 16.67 / Avg: 16.67 / Max: 16.67 Min: 14.49 / Avg: 14.49 / Max: 14.49 Min: 14.29 / Avg: 14.29 / Max: 14.29 Min: 11.36 / Avg: 11.36 / Max: 11.36 Min: 10.53 / Avg: 10.6 / Max: 10.64 Min: 10.42 / Avg: 10.42 / Max: 10.42 Min: 8.77 / Avg: 8.77 / Max: 8.77 Min: 6.8 / Avg: 6.83 / Max: 6.85 Min: 6.06 / Avg: 6.07 / Max: 6.1 Min: 5.65 / Avg: 5.65 / Max: 5.65 Min: 4.39 / Avg: 4.39 / Max: 4.39 Min: 3.64 / Avg: 3.65 / Max: 3.65 Min: 2.82 / Avg: 2.82 / Max: 2.83
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 7662 EPYC 7702 EPYC 7552 EPYC 7542 EPYC 7502P EPYC 7532 EPYC 7402P EPYC 7F52 EPYC 7302P EPYC 7282 EPYC 7272 EPYC 7F32 EPYC 7232P 30M 60M 90M 120M 150M SE +/- 1202983.30, N = 3 SE +/- 688813.01, N = 3 SE +/- 373542.05, N = 3 SE +/- 394553.31, N = 3 SE +/- 375595.74, N = 3 SE +/- 939330.26, N = 3 SE +/- 395352.82, N = 3 SE +/- 491333.28, N = 3 SE +/- 230890.74, N = 3 SE +/- 215295.19, N = 3 SE +/- 91373.33, N = 3 SE +/- 83002.90, N = 3 SE +/- 57670.67, N = 3 126290077 122849461 105304578 82716262 78084684 74422699 62581775 46342665 42112219 41583844 31791813 24675753 21027795
Nodes/second Per Watt
OpenBenchmarking.org Nodes/second Per Watt, More Is Better asmFish 2018-07-23 1024 Hash Memory, 26 Depth EPYC 7662 EPYC 7702 EPYC 7552 EPYC 7502P EPYC 7542 EPYC 7532 EPYC 7282 EPYC 7402P EPYC 7302P EPYC 7272 EPYC 7232P EPYC 7F52 EPYC 7F32 140K 280K 420K 560K 700K 665647.19 630429.66 586425.64 513107.47 473583.96 437974.87 394905.45 390336.76 359777.90 333068.50 282725.36 231626.04 228242.13
Result Confidence
OpenBenchmarking.org Nodes/second, More Is Better asmFish 2018-07-23 1024 Hash Memory, 26 Depth EPYC 7662 EPYC 7702 EPYC 7552 EPYC 7542 EPYC 7502P EPYC 7532 EPYC 7402P EPYC 7F52 EPYC 7302P EPYC 7282 EPYC 7272 EPYC 7F32 EPYC 7232P 20M 40M 60M 80M 100M Min: 124900585 / Avg: 126290076.67 / Max: 128685849 Min: 122057435 / Avg: 122849461.33 / Max: 124221646 Min: 104841596 / Avg: 105304577.67 / Max: 106043845 Min: 82311763 / Avg: 82716261.67 / Max: 83505284 Min: 77335639 / Avg: 78084684 / Max: 78508351 Min: 72577275 / Avg: 74422699 / Max: 75650094 Min: 61945670 / Avg: 62581775.33 / Max: 63306570 Min: 45648904 / Avg: 46342664.67 / Max: 47292245 Min: 41683109 / Avg: 42112219 / Max: 42474524 Min: 41298645 / Avg: 41583844.33 / Max: 42005822 Min: 31610049 / Avg: 31791813.33 / Max: 31899083 Min: 24510321 / Avg: 24675752.67 / Max: 24770415 Min: 20912491 / Avg: 21027794.67 / Max: 21087999
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 7662 EPYC 7702 EPYC 7642 EPYC 7552 EPYC 7542 EPYC 7502P EPYC 7532 EPYC 7402P EPYC 7F52 EPYC 7302P EPYC 7282 EPYC 7272 EPYC 7F32 EPYC 7232P 3 6 9 12 15 SE +/- 0.00, N = 3 SE +/- 0.04, N = 3 SE +/- 0.03, N = 3 SE +/- 0.00, N = 3 SE +/- 0.00, N = 3 SE +/- 0.02, 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 SE +/- 0.00, N = 3 11.24 11.07 9.58 9.52 7.58 7.01 6.90 5.76 4.45 4.02 3.72 2.93 2.39 1.89 MIN: 10.99 / MAX: 11.36 MIN: 10.75 / MAX: 11.24 MIN: 9.17 / MAX: 9.71 MIN: 9.35 / MAX: 9.62 MIN: 7.46 / MAX: 7.63 MIN: 6.94 / MAX: 7.09 MIN: 6.8 / MAX: 6.99 MIN: 5.68 / MAX: 5.81 MIN: 4.31 / MAX: 4.52 MIN: 3.98 / MAX: 4.05 MIN: 3.69 / MAX: 3.76 MIN: 2.9 / MAX: 2.97 MIN: 2.37 / MAX: 2.42 MIN: 1.84 / MAX: 1.91
FPS Per Watt
OpenBenchmarking.org FPS Per Watt, More Is Better OSPray 1.8.5 Demo: XFrog Forest - Renderer: SciVis EPYC 7662 EPYC 7702 EPYC 7642 EPYC 7552 EPYC 7532 EPYC 7542 EPYC 7502P EPYC 7282 EPYC 7402P EPYC 7272 EPYC 7302P EPYC 7F32 EPYC 7F52 EPYC 7232P 0.0158 0.0316 0.0474 0.0632 0.079 0.07 0.07 0.06 0.06 0.05 0.05 0.05 0.04 0.04 0.03 0.03 0.02 0.02 0.02
Result Confidence
OpenBenchmarking.org FPS, More Is Better OSPray 1.8.5 Demo: XFrog Forest - Renderer: SciVis EPYC 7662 EPYC 7702 EPYC 7642 EPYC 7552 EPYC 7542 EPYC 7502P EPYC 7532 EPYC 7402P EPYC 7F52 EPYC 7302P EPYC 7282 EPYC 7272 EPYC 7F32 EPYC 7232P 3 6 9 12 15 Min: 11.24 / Avg: 11.24 / Max: 11.24 Min: 10.99 / Avg: 11.07 / Max: 11.11 Min: 9.52 / Avg: 9.58 / Max: 9.62 Min: 9.52 / Avg: 9.52 / Max: 9.52 Min: 7.58 / Avg: 7.58 / Max: 7.58 Min: 6.99 / Avg: 7.01 / Max: 7.04 Min: 6.9 / Avg: 6.9 / Max: 6.9 Min: 5.75 / Avg: 5.76 / Max: 5.78 Min: 4.44 / Avg: 4.45 / Max: 4.46 Min: 4.02 / Avg: 4.02 / Max: 4.02 Min: 3.72 / Avg: 3.72 / Max: 3.72 Min: 2.93 / Avg: 2.93 / Max: 2.93 Min: 2.39 / Avg: 2.39 / Max: 2.39 Min: 1.89 / Avg: 1.89 / Max: 1.89
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 7642 EPYC 7662 EPYC 7532 EPYC 7702 EPYC 7552 EPYC 7F52 EPYC 7402P EPYC 7542 EPYC 7502P EPYC 7302P EPYC 7F32 EPYC 7282 EPYC 7272 EPYC 7232P 5K 10K 15K 20K 25K SE +/- 111.87, N = 3 SE +/- 233.09, N = 3 SE +/- 197.85, N = 2 SE +/- 0.00, N = 3 SE +/- 0.00, N = 3 SE +/- 82.20, N = 3 SE +/- 136.29, N = 3 SE +/- 101.60, N = 3 SE +/- 0.00, N = 3 SE +/- 66.13, N = 4 SE +/- 69.42, N = 3 SE +/- 54.85, N = 9 SE +/- 50.92, N = 3 23040.70 20991.70 20585.30 20382.20 17300.80 16399.70 13892.50 12699.50 12698.20 12204.40 8265.99 7358.19 7130.89 3879.10 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 7642 EPYC 7532 EPYC 7302P EPYC 7402P EPYC 7662 EPYC 7552 EPYC 7F52 EPYC 7702 EPYC 7542 EPYC 7502P EPYC 7272 EPYC 7F32 EPYC 7282 EPYC 7232P 30 60 90 120 150 139.29 137.34 132.05 123.63 123.10 117.11 117.06 116.25 105.62 104.15 97.15 93.74 92.77 62.30
Result Confidence
OpenBenchmarking.org Mpix/sec, More Is Better ASKAP 1.0 Test: tConvolve MPI - Gridding EPYC 7642 EPYC 7662 EPYC 7532 EPYC 7702 EPYC 7552 EPYC 7F52 EPYC 7402P EPYC 7542 EPYC 7502P EPYC 7302P EPYC 7F32 EPYC 7282 EPYC 7272 EPYC 7232P 4K 8K 12K 16K 20K Min: 22817 / Avg: 23040.73 / Max: 23152.6 Min: 20184.3 / Avg: 20585.33 / Max: 20991.7 Min: 20184.3 / Avg: 20382.15 / Max: 20580 Min: 17300.8 / Avg: 17300.8 / Max: 17300.8 Min: 16399.7 / Avg: 16399.7 / Max: 16399.7 Min: 13810.3 / Avg: 13892.5 / Max: 14056.9 Min: 12495 / Avg: 12699.47 / Max: 12957.8 Min: 12495 / Avg: 12698.2 / Max: 12799.8 Min: 12204.4 / Avg: 12204.4 / Max: 12204.4 Min: 8199.86 / Avg: 8265.99 / Max: 8464.38 Min: 7288.77 / Avg: 7358.19 / Max: 7497.02 Min: 6786.09 / Avg: 7130.89 / Max: 7288.77 Min: 3802.84 / Avg: 3879.1 / Max: 3975.69 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 7662 EPYC 7702 EPYC 7642 EPYC 7552 EPYC 7542 EPYC 7502P EPYC 7532 EPYC 7402P EPYC 7F52 EPYC 7302P EPYC 7282 EPYC 7272 EPYC 7F32 EPYC 7232P 30 60 90 120 150 SE +/- 0.02, N = 3 SE +/- 0.01, N = 3 SE +/- 0.03, N = 3 SE +/- 0.03, N = 3 SE +/- 0.05, N = 3 SE +/- 0.02, N = 3 SE +/- 0.02, N = 3 SE +/- 0.07, N = 3 SE +/- 0.05, N = 3 SE +/- 0.03, N = 3 SE +/- 0.27, N = 3 SE +/- 0.04, N = 3 SE +/- 0.14, N = 3 SE +/- 0.26, N = 3 19.08 19.12 22.56 22.81 28.59 30.90 31.57 37.73 46.59 54.84 58.47 75.04 92.16 112.39 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 7662 EPYC 7702 EPYC 7642 EPYC 7552 EPYC 7542 EPYC 7502P EPYC 7532 EPYC 7402P EPYC 7F52 EPYC 7302P EPYC 7282 EPYC 7272 EPYC 7F32 EPYC 7232P 20 40 60 80 100 Min: 19.06 / Avg: 19.08 / Max: 19.12 Min: 19.11 / Avg: 19.12 / Max: 19.14 Min: 22.52 / Avg: 22.56 / Max: 22.63 Min: 22.76 / Avg: 22.81 / Max: 22.84 Min: 28.5 / Avg: 28.59 / Max: 28.69 Min: 30.86 / Avg: 30.9 / Max: 30.92 Min: 31.53 / Avg: 31.57 / Max: 31.59 Min: 37.62 / Avg: 37.73 / Max: 37.87 Min: 46.49 / Avg: 46.59 / Max: 46.65 Min: 54.8 / Avg: 54.84 / Max: 54.9 Min: 58.2 / Avg: 58.47 / Max: 59 Min: 74.96 / Avg: 75.04 / Max: 75.08 Min: 91.95 / Avg: 92.16 / Max: 92.42 Min: 112.07 / Avg: 112.39 / Max: 112.9 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 7662 EPYC 7702 EPYC 7552 EPYC 7542 EPYC 7502P EPYC 7532 EPYC 7402P EPYC 7F52 EPYC 7302P EPYC 7282 EPYC 7272 EPYC 7F32 EPYC 7232P 60K 120K 180K 240K 300K SE +/- 419.38, N = 3 SE +/- 226.28, N = 3 SE +/- 453.51, N = 3 SE +/- 190.42, N = 3 SE +/- 249.88, N = 3 SE +/- 894.75, N = 3 SE +/- 315.33, N = 3 SE +/- 558.99, N = 3 SE +/- 192.03, N = 3 SE +/- 313.91, N = 3 SE +/- 108.98, N = 3 SE +/- 288.04, N = 3 SE +/- 84.48, N = 3 270140 264908 229747 176148 171362 171242 138575 109069 95137 90588 69655 56955 45941 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 7662 EPYC 7702 EPYC 7552 EPYC 7502P EPYC 7542 EPYC 7532 EPYC 7402P EPYC 7282 EPYC 7302P EPYC 7272 EPYC 7232P EPYC 7F52 EPYC 7F32 400 800 1200 1600 2000 1860.21 1772.21 1667.35 1397.09 1318.89 1207.72 1091.49 1034.12 969.68 872.02 710.08 654.08 601.78
Result Confidence
OpenBenchmarking.org MIPS, More Is Better 7-Zip Compression 16.02 Compress Speed Test EPYC 7662 EPYC 7702 EPYC 7552 EPYC 7542 EPYC 7502P EPYC 7532 EPYC 7402P EPYC 7F52 EPYC 7302P EPYC 7282 EPYC 7272 EPYC 7F32 EPYC 7232P 50K 100K 150K 200K 250K Min: 269353 / Avg: 270139.67 / Max: 270785 Min: 264563 / Avg: 264907.67 / Max: 265334 Min: 229189 / Avg: 229746.67 / Max: 230645 Min: 175784 / Avg: 176148 / Max: 176427 Min: 170978 / Avg: 171362 / Max: 171831 Min: 169527 / Avg: 171242 / Max: 172542 Min: 138164 / Avg: 138575.33 / Max: 139195 Min: 108136 / Avg: 109069.33 / Max: 110069 Min: 94939 / Avg: 95137 / Max: 95521 Min: 90180 / Avg: 90587.67 / Max: 91205 Min: 69500 / Avg: 69654.67 / Max: 69865 Min: 56532 / Avg: 56954.67 / Max: 57505 Min: 45801 / Avg: 45941.33 / Max: 46093 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 7662 EPYC 7702 EPYC 7642 EPYC 7552 EPYC 7542 EPYC 7502P EPYC 7532 EPYC 7402P EPYC 7F52 EPYC 7302P EPYC 7282 EPYC 7272 EPYC 7F32 EPYC 7232P 900K 1800K 2700K 3600K 4500K SE +/- 3282.95, N = 3 SE +/- 881.92, N = 3 SE +/- 881.92, N = 3 SE +/- 2905.93, N = 3 SE +/- 2185.81, N = 3 SE +/- 1527.53, N = 3 SE +/- 1452.97, N = 3 SE +/- 1763.83, N = 3 SE +/- 2603.42, N = 3 SE +/- 2000.00, N = 3 SE +/- 881.92, N = 3 SE +/- 525.27, N = 3 SE +/- 798.79, N = 3 4195333 4183000 3557667 3528667 2798667 2596333 2534000 2127333 1731667 1460333 1354000 1072333 874700 717175 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 7662 EPYC 7702 EPYC 7552 EPYC 7642 EPYC 7502P EPYC 7542 EPYC 7532 EPYC 7402P EPYC 7282 EPYC 7302P EPYC 7272 EPYC 7232P EPYC 7F52 EPYC 7F32 5K 10K 15K 20K 25K 22927.63 22232.88 20367.12 18839.03 17709.04 16435.49 15619.65 13762.68 13466.23 11851.02 10769.05 9459.27 7625.61 7334.16
Result Confidence
OpenBenchmarking.org Real C/S, More Is Better John The Ripper 1.9.0-jumbo-1 Test: MD5 EPYC 7662 EPYC 7702 EPYC 7642 EPYC 7552 EPYC 7542 EPYC 7502P EPYC 7532 EPYC 7402P EPYC 7F52 EPYC 7302P EPYC 7282 EPYC 7272 EPYC 7F32 EPYC 7232P 700K 1400K 2100K 2800K 3500K Min: 4189000 / Avg: 4195333.33 / Max: 4200000 Min: 3556000 / Avg: 3557666.67 / Max: 3559000 Min: 3527000 / Avg: 3528666.67 / Max: 3530000 Min: 2794000 / Avg: 2798666.67 / Max: 2804000 Min: 2592000 / Avg: 2596333.33 / Max: 2599000 Min: 2531000 / Avg: 2534000 / Max: 2536000 Min: 2125000 / Avg: 2127333.33 / Max: 2130000 Min: 1729000 / Avg: 1731666.67 / Max: 1735000 Min: 1456000 / Avg: 1460333.33 / Max: 1465000 Min: 1352000 / Avg: 1354000 / Max: 1358000 Min: 1071000 / Avg: 1072333.33 / Max: 1074000 Min: 873984 / Avg: 874700.33 / Max: 875724 Min: 716134 / Avg: 717175 / Max: 718745 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 7702 EPYC 7662 EPYC 7552 EPYC 7542 EPYC 7502P EPYC 7532 EPYC 7F52 EPYC 7282 EPYC 7272 EPYC 7F32 EPYC 7232P 10K 20K 30K 40K 50K SE +/- 469.86, N = 3 SE +/- 392.90, N = 8 SE +/- 284.86, N = 11 SE +/- 305.20, N = 6 SE +/- 298.29, N = 3 SE +/- 144.16, N = 3 SE +/- 165.84, N = 3 SE +/- 120.35, N = 3 SE +/- 140.41, N = 4 SE +/- 117.08, N = 4 SE +/- 50.21, N = 3 45292 44658 37843 30632 28448 28401 19521 15246 12198 10044 7864
vsamples Per Watt
OpenBenchmarking.org vsamples Per Watt, More Is Better Chaos Group V-RAY 5 Mode: CPU EPYC 7662 EPYC 7552 EPYC 7502P EPYC 7542 EPYC 7532 EPYC 7282 EPYC 7272 EPYC 7F52 EPYC 7F32 60 120 180 240 300 272.08 244.21 212.71 202.52 193.49 168.70 135.50 94.82 84.74
Result Confidence
OpenBenchmarking.org vsamples, More Is Better Chaos Group V-RAY 5 Mode: CPU EPYC 7702 EPYC 7662 EPYC 7552 EPYC 7542 EPYC 7502P EPYC 7532 EPYC 7F52 EPYC 7282 EPYC 7272 EPYC 7F32 EPYC 7232P 8K 16K 24K 32K 40K Min: 44695 / Avg: 45292 / Max: 46219 Min: 43124 / Avg: 44658.38 / Max: 46027 Min: 36221 / Avg: 37842.73 / Max: 38879 Min: 29652 / Avg: 30632 / Max: 31469 Min: 28095 / Avg: 28448 / Max: 29041 Min: 28141 / Avg: 28400.67 / Max: 28639 Min: 19190 / Avg: 19521 / Max: 19705 Min: 15016 / Avg: 15246.33 / Max: 15422 Min: 11788 / Avg: 12198.25 / Max: 12425 Min: 9719 / Avg: 10044.25 / Max: 10235 Min: 7769 / Avg: 7863.67 / Max: 7940
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 7702 EPYC 7662 EPYC 7552 EPYC 7542 EPYC 7502P EPYC 7532 EPYC 7402P EPYC 7F52 EPYC 7302P EPYC 7282 EPYC 7272 EPYC 7F32 EPYC 7232P 60 120 180 240 300 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 SE +/- 0.16, N = 3 SE +/- 0.05, N = 3 SE +/- 0.02, N = 3 SE +/- 0.01, N = 3 SE +/- 0.02, N = 3 SE +/- 0.12, N = 3 45.80 45.84 54.34 67.95 73.38 75.27 89.07 109.17 129.26 137.78 176.04 214.44 262.14 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 7702 EPYC 7662 EPYC 7552 EPYC 7542 EPYC 7502P EPYC 7532 EPYC 7402P EPYC 7F52 EPYC 7302P EPYC 7282 EPYC 7272 EPYC 7F32 EPYC 7232P 50 100 150 200 250 Min: 45.79 / Avg: 45.8 / Max: 45.82 Min: 45.83 / Avg: 45.84 / Max: 45.85 Min: 54.32 / Avg: 54.34 / Max: 54.35 Min: 67.93 / Avg: 67.95 / Max: 67.96 Min: 73.37 / Avg: 73.38 / Max: 73.4 Min: 75.26 / Avg: 75.27 / Max: 75.27 Min: 89.06 / Avg: 89.07 / Max: 89.08 Min: 108.86 / Avg: 109.17 / Max: 109.35 Min: 129.21 / Avg: 129.26 / Max: 129.36 Min: 137.74 / Avg: 137.78 / Max: 137.82 Min: 176.03 / Avg: 176.04 / Max: 176.05 Min: 214.41 / Avg: 214.44 / Max: 214.47 Min: 262.01 / Avg: 262.14 / Max: 262.39 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 7662 EPYC 7702 EPYC 7642 EPYC 7552 EPYC 7542 EPYC 7502P EPYC 7532 EPYC 7402P EPYC 7302P EPYC 7282 EPYC 7F52 EPYC 7272 EPYC 7F32 EPYC 7232P 9 18 27 36 45 SE +/- 0.00, N = 6 SE +/- 0.00, N = 6 SE +/- 0.00, N = 5 SE +/- 0.17, N = 5 SE +/- 0.00, N = 5 SE +/- 0.00, N = 4 SE +/- 0.00, N = 4 SE +/- 0.06, N = 3 SE +/- 0.00, N = 3 SE +/- 0.08, N = 6 SE +/- 0.00, N = 3 40.00 40.00 34.48 34.48 27.78 26.05 25.00 20.83 14.08 13.89 13.45 10.42 8.16 6.99 MIN: 38.46 / MAX: 41.67 MIN: 34.48 / MAX: 41.67 MIN: 33.33 / MAX: 35.71 MIN: 33.33 / MAX: 35.71 MIN: 27.03 MIN: 25.64 / MAX: 26.32 MIN: 23.81 / MAX: 25.64 MIN: 20.41 / MAX: 21.28 MIN: 12.99 / MAX: 14.29 MIN: 13.33 / MAX: 14.08 MIN: 12.82 / MAX: 13.89 MIN: 10.1 / MAX: 10.64 MIN: 6.85 / MAX: 8.4 MIN: 5.95 / MAX: 7.04
FPS Per Watt
OpenBenchmarking.org FPS Per Watt, More Is Better OSPray 1.8.5 Demo: Magnetic Reconnection - Renderer: SciVis EPYC 7662 EPYC 7702 EPYC 7552 EPYC 7642 EPYC 7502P EPYC 7542 EPYC 7532 EPYC 7402P EPYC 7282 EPYC 7302P EPYC 7272 EPYC 7232P EPYC 7F52 EPYC 7F32 0.0698 0.1396 0.2094 0.2792 0.349 0.31 0.30 0.28 0.25 0.23 0.22 0.19 0.17 0.16 0.15 0.13 0.11 0.09 0.08
Result Confidence
OpenBenchmarking.org FPS, More Is Better OSPray 1.8.5 Demo: Magnetic Reconnection - Renderer: SciVis EPYC 7662 EPYC 7702 EPYC 7642 EPYC 7552 EPYC 7542 EPYC 7502P EPYC 7532 EPYC 7402P EPYC 7302P EPYC 7282 EPYC 7F52 EPYC 7272 EPYC 7F32 EPYC 7232P 8 16 24 32 40 Min: 34.48 / Avg: 34.48 / Max: 34.48 Min: 34.48 / Avg: 34.48 / Max: 34.48 Min: 27.78 / Avg: 27.78 / Max: 27.78 Min: 25.64 / Avg: 26.05 / Max: 26.32 Min: 20.83 / Avg: 20.83 / Max: 20.83 Min: 14.08 / Avg: 14.08 / Max: 14.08 Min: 13.89 / Avg: 13.89 / Max: 13.89 Min: 13.33 / Avg: 13.45 / Max: 13.51 Min: 10.42 / Avg: 10.42 / Max: 10.42 Min: 7.75 / Avg: 8.16 / Max: 8.26 Min: 6.99 / Avg: 6.99 / Max: 6.99
Result
OpenBenchmarking.org FPS, More Is Better OSPray 1.8.5 Demo: San Miguel - Renderer: SciVis EPYC 7662 EPYC 7702 EPYC 7642 EPYC 7552 EPYC 7542 EPYC 7502P EPYC 7532 EPYC 7402P EPYC 7F52 EPYC 7302P EPYC 7282 EPYC 7272 EPYC 7F32 EPYC 7232P 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 +/- 0.17, 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 58.82 55.56 50.00 50.00 40.00 37.04 35.71 30.30 22.56 20.83 19.61 15.63 12.50 10.31 MIN: 52.63 / MAX: 62.5 MIN: 50 / MAX: 62.5 MIN: 47.62 / MAX: 52.63 MIN: 47.62 / MAX: 52.63 MIN: 37.04 / MAX: 41.67 MIN: 34.48 / MAX: 40 MIN: 33.33 / MAX: 38.46 MIN: 29.41 / MAX: 32.26 MIN: 21.28 / MAX: 24.39 MIN: 20.41 / MAX: 22.73 MIN: 19.23 / MAX: 21.28 MIN: 15.15 / MAX: 16.67 MIN: 12.2 / MAX: 13.33 MIN: 10.1 / MAX: 10.99
FPS Per Watt
OpenBenchmarking.org FPS Per Watt, More Is Better OSPray 1.8.5 Demo: San Miguel - Renderer: SciVis EPYC 7662 EPYC 7552 EPYC 7702 EPYC 7642 EPYC 7542 EPYC 7502P EPYC 7402P EPYC 7532 EPYC 7282 EPYC 7302P EPYC 7272 EPYC 7F52 EPYC 7232P EPYC 7F32 0.162 0.324 0.486 0.648 0.81 0.72 0.69 0.67 0.62 0.59 0.57 0.44 0.43 0.34 0.31 0.26 0.21 0.19 0.16
Result Confidence
OpenBenchmarking.org FPS, More Is Better OSPray 1.8.5 Demo: San Miguel - Renderer: SciVis EPYC 7662 EPYC 7702 EPYC 7642 EPYC 7552 EPYC 7542 EPYC 7502P EPYC 7532 EPYC 7402P EPYC 7F52 EPYC 7302P EPYC 7282 EPYC 7272 EPYC 7F32 EPYC 7232P 12 24 36 48 60 Min: 58.82 / Avg: 58.82 / Max: 58.82 Min: 55.56 / Avg: 55.56 / Max: 55.56 Min: 37.04 / Avg: 37.04 / Max: 37.04 Min: 35.71 / Avg: 35.71 / Max: 35.71 Min: 30.3 / Avg: 30.3 / Max: 30.3 Min: 22.22 / Avg: 22.56 / Max: 22.73 Min: 20.83 / Avg: 20.83 / Max: 20.83 Min: 19.61 / Avg: 19.61 / Max: 19.61 Min: 15.63 / Avg: 15.63 / Max: 15.63 Min: 12.5 / Avg: 12.5 / Max: 12.5 Min: 10.31 / Avg: 10.31 / Max: 10.31
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 7662 EPYC 7702 EPYC 7552 EPYC 7542 EPYC 7502P EPYC 7532 EPYC 7402P EPYC 7F52 EPYC 7302P EPYC 7282 EPYC 7272 EPYC 7F32 EPYC 7232P 40K 80K 120K 160K 200K SE +/- 1795.92, N = 3 SE +/- 558.83, N = 3 SE +/- 457.19, N = 3 SE +/- 157.32, N = 3 SE +/- 1288.21, N = 3 SE +/- 270.71, N = 3 SE +/- 377.08, N = 3 SE +/- 417.25, N = 3 SE +/- 123.36, N = 3 SE +/- 294.16, N = 3 SE +/- 183.06, N = 3 SE +/- 382.53, N = 3 SE +/- 186.09, N = 3 179496.78 179226.24 152001.95 122762.96 112205.01 110766.79 92207.07 76923.39 63930.72 59431.03 46780.94 38378.08 31690.60 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 7662 EPYC 7702 EPYC 7552 EPYC 7502P EPYC 7542 EPYC 7532 EPYC 7402P EPYC 7282 EPYC 7302P EPYC 7272 EPYC 7232P EPYC 7F52 EPYC 7F32 200 400 600 800 1000 1022.61 987.36 911.37 791.90 751.29 717.75 638.73 617.90 545.34 484.49 412.61 348.06 324.00
Result Confidence
OpenBenchmarking.org Bogo Ops/s, More Is Better Stress-NG 0.11.07 Test: Matrix Math EPYC 7662 EPYC 7702 EPYC 7552 EPYC 7542 EPYC 7502P EPYC 7532 EPYC 7402P EPYC 7F52 EPYC 7302P EPYC 7282 EPYC 7272 EPYC 7F32 EPYC 7232P 30K 60K 90K 120K 150K Min: 175929.7 / Avg: 179496.78 / Max: 181644.9 Min: 178344.47 / Avg: 179226.24 / Max: 180261.88 Min: 151506.09 / Avg: 152001.95 / Max: 152915.2 Min: 122497.64 / Avg: 122762.96 / Max: 123042.09 Min: 109640.44 / Avg: 112205.01 / Max: 113701 Min: 110323.78 / Avg: 110766.79 / Max: 111257.86 Min: 91633.53 / Avg: 92207.07 / Max: 92917.94 Min: 76194.59 / Avg: 76923.39 / Max: 77639.82 Min: 63684.02 / Avg: 63930.72 / Max: 64057.16 Min: 59024.95 / Avg: 59431.03 / Max: 60002.73 Min: 46417.91 / Avg: 46780.94 / Max: 47003.53 Min: 37633.18 / Avg: 38378.08 / Max: 38901.65 Min: 31367.04 / Avg: 31690.6 / Max: 32011.65 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 7702 EPYC 7662 EPYC 7642 EPYC 7552 EPYC 7542 EPYC 7502P EPYC 7532 EPYC 7402P EPYC 7F52 EPYC 7302P EPYC 7282 EPYC 7272 EPYC 7F32 EPYC 7232P 13K 26K 39K 52K 65K SE +/- 487.40, N = 3 SE +/- 467.21, N = 3 SE +/- 179.29, N = 3 SE +/- 328.54, N = 3 SE +/- 391.02, N = 6 SE +/- 264.62, N = 15 SE +/- 397.54, N = 5 SE +/- 87.62, N = 3 SE +/- 71.92, N = 3 SE +/- 114.11, N = 3 SE +/- 122.98, N = 3 SE +/- 80.88, N = 3 SE +/- 31.21, N = 3 SE +/- 44.44, N = 3 62754 62295 54445 53570 38904 37085 36223 33184 27132 23486 22022 17550 14204 11136
Ksamples Per Watt
OpenBenchmarking.org Ksamples Per Watt, More Is Better Chaos Group V-RAY 4.10.07 Mode: CPU EPYC 7662 EPYC 7702 EPYC 7552 EPYC 7642 EPYC 7502P EPYC 7542 EPYC 7532 EPYC 7402P EPYC 7282 EPYC 7302P EPYC 7272 EPYC 7232P EPYC 7F52 EPYC 7F32 80 160 240 320 400 364.02 353.18 328.86 306.53 275.92 257.36 243.18 235.77 233.63 202.24 185.79 152.41 127.66 124.47
Result Confidence
OpenBenchmarking.org Ksamples, More Is Better Chaos Group V-RAY 4.10.07 Mode: CPU EPYC 7702 EPYC 7662 EPYC 7642 EPYC 7552 EPYC 7542 EPYC 7502P EPYC 7532 EPYC 7402P EPYC 7F52 EPYC 7302P EPYC 7282 EPYC 7272 EPYC 7F32 EPYC 7232P 11K 22K 33K 44K 55K Min: 62183 / Avg: 62754.33 / Max: 63724 Min: 61378 / Avg: 62294.67 / Max: 62910 Min: 54235 / Avg: 54445.33 / Max: 54802 Min: 53078 / Avg: 53569.67 / Max: 54193 Min: 37112 / Avg: 38903.83 / Max: 39603 Min: 35376 / Avg: 37084.67 / Max: 38925 Min: 35373 / Avg: 36223.2 / Max: 37595 Min: 33018 / Avg: 33183.67 / Max: 33316 Min: 27010 / Avg: 27132 / Max: 27259 Min: 23305 / Avg: 23486.33 / Max: 23697 Min: 21875 / Avg: 22021.67 / Max: 22266 Min: 17397 / Avg: 17550 / Max: 17672 Min: 14151 / Avg: 14203.67 / Max: 14259 Min: 11048 / Avg: 11136.33 / Max: 11189
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 7662 EPYC 7702 EPYC 7552 EPYC 7532 EPYC 7542 EPYC 7502P EPYC 7F52 EPYC 7402P EPYC 7302P EPYC 7282 EPYC 7272 EPYC 7F32 EPYC 7232P 15 30 45 60 75 SE +/- 0.03, N = 4 SE +/- 0.03, N = 4 SE +/- 0.02, N = 4 SE +/- 0.02, N = 3 SE +/- 0.08, N = 3 SE +/- 0.10, N = 3 SE +/- 0.02, N = 3 SE +/- 0.05, N = 3 SE +/- 0.07, N = 3 SE +/- 0.06, N = 3 SE +/- 0.11, N = 3 SE +/- 0.02, N = 3 SE +/- 0.14, N = 3 11.80 11.94 15.35 18.06 22.23 23.03 25.88 25.89 34.03 41.69 49.11 52.79 66.42 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 7662 EPYC 7702 EPYC 7552 EPYC 7532 EPYC 7542 EPYC 7502P EPYC 7F52 EPYC 7402P EPYC 7302P EPYC 7282 EPYC 7272 EPYC 7F32 EPYC 7232P 13 26 39 52 65 Min: 11.75 / Avg: 11.8 / Max: 11.87 Min: 11.88 / Avg: 11.94 / Max: 12 Min: 15.3 / Avg: 15.35 / Max: 15.39 Min: 18.03 / Avg: 18.06 / Max: 18.09 Min: 22.07 / Avg: 22.23 / Max: 22.32 Min: 22.87 / Avg: 23.03 / Max: 23.23 Min: 25.85 / Avg: 25.88 / Max: 25.92 Min: 25.8 / Avg: 25.89 / Max: 25.96 Min: 33.93 / Avg: 34.03 / Max: 34.16 Min: 41.58 / Avg: 41.69 / Max: 41.79 Min: 48.99 / Avg: 49.11 / Max: 49.32 Min: 52.75 / Avg: 52.79 / Max: 52.81 Min: 66.13 / Avg: 66.42 / Max: 66.58 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 7662 EPYC 7702 EPYC 7642 EPYC 7552 EPYC 7542 EPYC 7502P EPYC 7532 EPYC 7402P EPYC 7F52 EPYC 7302P EPYC 7282 EPYC 7272 EPYC 7F32 EPYC 7232P 200 400 600 800 1000 SE +/- 0.20, N = 3 SE +/- 0.04, N = 3 SE +/- 0.23, N = 3 SE +/- 0.31, N = 3 SE +/- 0.07, N = 3 SE +/- 0.46, N = 3 SE +/- 0.14, N = 3 SE +/- 0.35, N = 3 SE +/- 0.69, N = 3 SE +/- 0.25, N = 3 SE +/- 0.65, N = 3 SE +/- 1.20, N = 3 SE +/- 0.11, N = 3 SE +/- 0.62, N = 3 154.23 154.42 179.18 180.94 223.08 237.65 243.58 291.52 356.90 411.56 432.92 554.64 683.81 866.85
Result Confidence
OpenBenchmarking.org Seconds, Fewer Is Better Blender 2.90 Blend File: Barbershop - Compute: CPU-Only EPYC 7662 EPYC 7702 EPYC 7642 EPYC 7552 EPYC 7542 EPYC 7502P EPYC 7532 EPYC 7402P EPYC 7F52 EPYC 7302P EPYC 7282 EPYC 7272 EPYC 7F32 EPYC 7232P 150 300 450 600 750 Min: 153.83 / Avg: 154.23 / Max: 154.49 Min: 154.37 / Avg: 154.42 / Max: 154.49 Min: 178.74 / Avg: 179.18 / Max: 179.54 Min: 180.32 / Avg: 180.94 / Max: 181.27 Min: 222.95 / Avg: 223.08 / Max: 223.18 Min: 237.18 / Avg: 237.65 / Max: 238.58 Min: 243.32 / Avg: 243.58 / Max: 243.79 Min: 291.13 / Avg: 291.52 / Max: 292.22 Min: 356.09 / Avg: 356.9 / Max: 358.27 Min: 411.08 / Avg: 411.56 / Max: 411.94 Min: 432.21 / Avg: 432.92 / Max: 434.21 Min: 552.98 / Avg: 554.64 / Max: 556.98 Min: 683.61 / Avg: 683.81 / Max: 683.97 Min: 865.62 / Avg: 866.85 / Max: 867.52
Result
OpenBenchmarking.org Seconds, Fewer Is Better Blender 2.90 Blend File: Pabellon Barcelona - Compute: CPU-Only EPYC 7662 EPYC 7702 EPYC 7642 EPYC 7552 EPYC 7542 EPYC 7502P EPYC 7532 EPYC 7402P EPYC 7F52 EPYC 7302P EPYC 7282 EPYC 7272 EPYC 7F32 EPYC 7232P 140 280 420 560 700 SE +/- 0.39, N = 3 SE +/- 0.15, N = 3 SE +/- 0.14, N = 3 SE +/- 0.92, N = 3 SE +/- 0.07, N = 3 SE +/- 0.14, N = 3 SE +/- 0.33, N = 3 SE +/- 1.69, N = 3 SE +/- 0.98, N = 3 SE +/- 0.50, N = 3 SE +/- 1.19, N = 3 SE +/- 0.64, N = 3 SE +/- 0.51, N = 3 SE +/- 0.72, N = 3 118.26 119.17 137.83 139.21 167.99 182.76 189.09 219.75 265.13 317.27 338.52 426.59 508.26 664.29
Result Confidence
OpenBenchmarking.org Seconds, Fewer Is Better Blender 2.90 Blend File: Pabellon Barcelona - Compute: CPU-Only EPYC 7662 EPYC 7702 EPYC 7642 EPYC 7552 EPYC 7542 EPYC 7502P EPYC 7532 EPYC 7402P EPYC 7F52 EPYC 7302P EPYC 7282 EPYC 7272 EPYC 7F32 EPYC 7232P 120 240 360 480 600 Min: 117.87 / Avg: 118.26 / Max: 119.05 Min: 118.86 / Avg: 119.17 / Max: 119.35 Min: 137.55 / Avg: 137.83 / Max: 138.03 Min: 138.06 / Avg: 139.21 / Max: 141.03 Min: 167.9 / Avg: 167.99 / Max: 168.12 Min: 182.48 / Avg: 182.76 / Max: 182.95 Min: 188.42 / Avg: 189.09 / Max: 189.45 Min: 217.98 / Avg: 219.75 / Max: 223.14 Min: 263.71 / Avg: 265.13 / Max: 267.02 Min: 316.57 / Avg: 317.27 / Max: 318.25 Min: 336.65 / Avg: 338.52 / Max: 340.74 Min: 425.64 / Avg: 426.59 / Max: 427.81 Min: 507.47 / Avg: 508.26 / Max: 509.22 Min: 662.88 / Avg: 664.29 / Max: 665.27
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 7702 EPYC 7662 EPYC 7552 EPYC 7642 EPYC 7542 EPYC 7502P EPYC 7532 EPYC 7402P EPYC 7302P EPYC 7282 EPYC 7F52 EPYC 7272 EPYC 7F32 EPYC 7232P 2M 4M 6M 8M 10M SE +/- 47749.78, N = 3 SE +/- 27617.12, N = 3 SE +/- 44027.23, N = 3 SE +/- 69440.76, N = 6 SE +/- 55384.00, N = 3 SE +/- 24292.51, N = 3 SE +/- 32730.71, N = 3 SE +/- 43537.48, N = 3 SE +/- 25144.15, N = 3 SE +/- 26792.49, N = 3 SE +/- 8186.58, N = 3 SE +/- 24217.23, N = 3 SE +/- 10805.74, N = 13 SE +/- 1710.84, N = 3 8232474 8175383 7183579 7131600 5564433 5486066 5214302 4397695 3086237 3023239 3012387 2357928 1603673 1470621 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 7662 EPYC 7702 EPYC 7552 EPYC 7642 EPYC 7502P EPYC 7542 EPYC 7532 EPYC 7282 EPYC 7402P EPYC 7302P EPYC 7272 EPYC 7232P EPYC 7F52 EPYC 7F32 9K 18K 27K 36K 45K 44350.10 43072.97 40538.44 37151.16 36657.22 32038.20 31284.41 29403.11 28233.69 24738.50 23416.29 18803.69 14841.44 14725.01
Result Confidence
OpenBenchmarking.org Op/s, More Is Better Facebook RocksDB 6.3.6 Test: Read While Writing EPYC 7702 EPYC 7662 EPYC 7552 EPYC 7642 EPYC 7542 EPYC 7502P EPYC 7532 EPYC 7402P EPYC 7302P EPYC 7282 EPYC 7F52 EPYC 7272 EPYC 7F32 EPYC 7232P 1.4M 2.8M 4.2M 5.6M 7M Min: 8181136 / Avg: 8232473.67 / Max: 8327881 Min: 8142180 / Avg: 8175382.67 / Max: 8230211 Min: 7101279 / Avg: 7183579 / Max: 7251844 Min: 7048399 / Avg: 7131599.5 / Max: 7477000 Min: 5463565 / Avg: 5564432.67 / Max: 5654508 Min: 5439082 / Avg: 5486065.67 / Max: 5520271 Min: 5150993 / Avg: 5214301.67 / Max: 5260375 Min: 4337144 / Avg: 4397695 / Max: 4482162 Min: 3036500 / Avg: 3086236.67 / Max: 3117538 Min: 2989438 / Avg: 3023238.67 / Max: 3076148 Min: 3002918 / Avg: 3012386.67 / Max: 3028689 Min: 2309505 / Avg: 2357928 / Max: 2383052 Min: 1550246 / Avg: 1603672.85 / Max: 1683898 Min: 1467509 / Avg: 1470620.67 / Max: 1473409 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 7662 EPYC 7702 EPYC 7642 EPYC 7552 EPYC 7542 EPYC 7502P EPYC 7532 EPYC 7402P EPYC 7F52 EPYC 7302P EPYC 7282 EPYC 7272 EPYC 7F32 EPYC 7232P 0.6132 1.2264 1.8396 2.4528 3.066 SE +/- 0.00014, N = 3 SE +/- 0.00053, N = 3 SE +/- 0.00034, N = 3 SE +/- 0.00037, N = 3 SE +/- 0.00071, N = 3 SE +/- 0.00041, N = 3 SE +/- 0.00074, N = 3 SE +/- 0.00125, N = 3 SE +/- 0.00173, N = 3 SE +/- 0.00048, N = 3 SE +/- 0.00125, N = 3 SE +/- 0.00045, N = 3 SE +/- 0.00063, N = 3 SE +/- 0.00080, N = 3 0.48908 0.49264 0.57048 0.57484 0.71549 0.77439 0.79079 0.93705 1.14375 1.35058 1.45145 1.83895 2.22949 2.72553
Result Confidence
OpenBenchmarking.org days/ns, Fewer Is Better NAMD 2.14 ATPase Simulation - 327,506 Atoms EPYC 7662 EPYC 7702 EPYC 7642 EPYC 7552 EPYC 7542 EPYC 7502P EPYC 7532 EPYC 7402P EPYC 7F52 EPYC 7302P EPYC 7282 EPYC 7272 EPYC 7F32 EPYC 7232P 2 4 6 8 10 Min: 0.49 / Avg: 0.49 / Max: 0.49 Min: 0.49 / Avg: 0.49 / Max: 0.49 Min: 0.57 / Avg: 0.57 / Max: 0.57 Min: 0.57 / Avg: 0.57 / Max: 0.58 Min: 0.71 / Avg: 0.72 / Max: 0.72 Min: 0.77 / Avg: 0.77 / Max: 0.78 Min: 0.79 / Avg: 0.79 / Max: 0.79 Min: 0.94 / Avg: 0.94 / Max: 0.94 Min: 1.14 / Avg: 1.14 / Max: 1.15 Min: 1.35 / Avg: 1.35 / Max: 1.35 Min: 1.45 / Avg: 1.45 / Max: 1.45 Min: 1.84 / Avg: 1.84 / Max: 1.84 Min: 2.23 / Avg: 2.23 / Max: 2.23 Min: 2.72 / Avg: 2.73 / Max: 2.73
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 7702 EPYC 7662 EPYC 7642 EPYC 7552 EPYC 7542 EPYC 7502P EPYC 7532 EPYC 7402P EPYC 7F52 EPYC 7302P EPYC 7282 EPYC 7272 EPYC 7F32 EPYC 7232P 50M 100M 150M 200M 250M SE +/- 2628540.04, N = 3 SE +/- 1573991.80, N = 3 SE +/- 1627088.40, N = 3 SE +/- 1503518.94, N = 3 SE +/- 979987.31, N = 3 SE +/- 298644.62, N = 3 SE +/- 577476.24, N = 3 SE +/- 701112.41, N = 3 SE +/- 33050.19, N = 3 SE +/- 731623.27, N = 6 SE +/- 860580.20, N = 3 SE +/- 532212.35, N = 3 SE +/- 173513.15, N = 3 SE +/- 468827.18, N = 3 218469824 214717760 185712982 185095008 147488280 139338056 133038550 114391434 93883130 76972090 74816560 56928967 48331735 39206156 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 7662 EPYC 7702 EPYC 7552 EPYC 7642 EPYC 7502P EPYC 7542 EPYC 7532 EPYC 7402P EPYC 7282 EPYC 7302P EPYC 7272 EPYC 7232P EPYC 7F52 EPYC 7F32 200K 400K 600K 800K 1000K 1165531.87 1144599.80 1055932.79 966385.49 931173.20 861998.88 820332.86 752967.14 744401.17 623360.93 561814.90 482400.32 405107.75 383902.17
Result Confidence
OpenBenchmarking.org Op/s, More Is Better Facebook RocksDB 6.3.6 Test: Random Read EPYC 7702 EPYC 7662 EPYC 7642 EPYC 7552 EPYC 7542 EPYC 7502P EPYC 7532 EPYC 7402P EPYC 7F52 EPYC 7302P EPYC 7282 EPYC 7272 EPYC 7F32 EPYC 7232P 40M 80M 120M 160M 200M Min: 213921113 / Avg: 218469824.33 / Max: 223026632 Min: 211571907 / Avg: 214717760.33 / Max: 216390965 Min: 182486843 / Avg: 185712982.33 / Max: 187695198 Min: 182409655 / Avg: 185095007.67 / Max: 187609592 Min: 146389489 / Avg: 147488280.33 / Max: 149443243 Min: 138995330 / Avg: 139338056 / Max: 139933058 Min: 131941123 / Avg: 133038549.67 / Max: 133898996 Min: 112997116 / Avg: 114391434.33 / Max: 115217369 Min: 93839853 / Avg: 93883129.67 / Max: 93948038 Min: 75222240 / Avg: 76972090.17 / Max: 79656987 Min: 73275140 / Avg: 74816560.33 / Max: 76250454 Min: 55956147 / Avg: 56928967.33 / Max: 57789497 Min: 48063107 / Avg: 48331734.67 / Max: 48656311 Min: 38308495 / Avg: 39206155.67 / Max: 39889615 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 7662 EPYC 7702 EPYC 7552 EPYC 7642 EPYC 7542 EPYC 7502P EPYC 7532 EPYC 7402P EPYC 7F52 EPYC 7302P EPYC 7282 EPYC 7272 EPYC 7F32 EPYC 7232P 200K 400K 600K 800K 1000K SE +/- 6923.68, N = 3 SE +/- 5067.03, N = 3 SE +/- 3710.21, N = 3 SE +/- 1360.28, N = 3 SE +/- 1178.79, N = 3 SE +/- 1108.32, N = 3 SE +/- 853.89, N = 3 SE +/- 1318.12, N = 3 SE +/- 248.26, N = 3 SE +/- 891.46, N = 3 SE +/- 804.68, N = 3 SE +/- 696.35, N = 3 SE +/- 681.51, N = 3 SE +/- 518.37, N = 3 939750 899992 791456 775687 655774 614183 587548 521653 397038 368449 343229 275677 213345 169832 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 7662 EPYC 7702 EPYC 7552 EPYC 7642 EPYC 7542 EPYC 7502P EPYC 7532 EPYC 7402P EPYC 7F52 EPYC 7302P EPYC 7282 EPYC 7272 EPYC 7F32 EPYC 7232P 160K 320K 480K 640K 800K Min: 926183.25 / Avg: 939750.48 / Max: 948934.04 Min: 889916.01 / Avg: 899992.3 / Max: 905966.24 Min: 784040.65 / Avg: 791455.71 / Max: 795407.24 Min: 773949.79 / Avg: 775687.15 / Max: 778368.93 Min: 654021.41 / Avg: 655774.08 / Max: 658015.96 Min: 613074.34 / Avg: 614182.67 / Max: 616399.31 Min: 585986.61 / Avg: 587547.73 / Max: 588927.93 Min: 519362.06 / Avg: 521653.42 / Max: 523928.08 Min: 396660.01 / Avg: 397038.18 / Max: 397505.91 Min: 367104.95 / Avg: 368449.41 / Max: 370135.74 Min: 341698.14 / Avg: 343228.63 / Max: 344424.83 Min: 274390.74 / Avg: 275676.66 / Max: 276782.78 Min: 212208.72 / Avg: 213344.58 / Max: 214564.99 Min: 168803.67 / Avg: 169832.3 / Max: 170458.78 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 7662 EPYC 7702 EPYC 7552 EPYC 7642 EPYC 7542 EPYC 7502P EPYC 7532 EPYC 7402P EPYC 7F52 EPYC 7302P EPYC 7282 EPYC 7272 EPYC 7F32 EPYC 7232P 0.3314 0.6628 0.9942 1.3256 1.657 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 +/- 0.001, N = 3 SE +/- 0.002, N = 3 SE +/- 0.002, N = 3 SE +/- 0.002, N = 3 SE +/- 0.004, N = 3 SE +/- 0.005, N = 3 0.267 0.279 0.316 0.323 0.382 0.407 0.426 0.480 0.630 0.679 0.729 0.908 1.173 1.473 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 7662 EPYC 7702 EPYC 7552 EPYC 7642 EPYC 7542 EPYC 7502P EPYC 7532 EPYC 7402P EPYC 7F52 EPYC 7302P EPYC 7282 EPYC 7272 EPYC 7F32 EPYC 7232P 2 4 6 8 10 Min: 0.26 / Avg: 0.27 / Max: 0.27 Min: 0.28 / Avg: 0.28 / Max: 0.28 Min: 0.32 / Avg: 0.32 / Max: 0.32 Min: 0.32 / Avg: 0.32 / Max: 0.32 Min: 0.38 / Avg: 0.38 / Max: 0.38 Min: 0.41 / Avg: 0.41 / Max: 0.41 Min: 0.43 / Avg: 0.43 / Max: 0.43 Min: 0.48 / Avg: 0.48 / Max: 0.48 Min: 0.63 / Avg: 0.63 / Max: 0.63 Min: 0.68 / Avg: 0.68 / Max: 0.68 Min: 0.73 / Avg: 0.73 / Max: 0.73 Min: 0.9 / Avg: 0.91 / Max: 0.91 Min: 1.17 / Avg: 1.17 / Max: 1.18 Min: 1.47 / Avg: 1.47 / Max: 1.48 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 7662 EPYC 7702 EPYC 7642 EPYC 7552 EPYC 7542 EPYC 7502P EPYC 7532 EPYC 7402P EPYC 7F52 EPYC 7302P EPYC 7282 EPYC 7272 EPYC 7F32 EPYC 7232P 120 240 360 480 600 SE +/- 0.25, N = 3 SE +/- 0.41, N = 3 SE +/- 0.77, N = 3 SE +/- 0.69, N = 3 SE +/- 0.41, N = 3 SE +/- 0.20, N = 3 SE +/- 1.09, N = 3 SE +/- 0.04, N = 3 SE +/- 0.74, N = 3 SE +/- 0.64, N = 3 SE +/- 0.83, N = 3 SE +/- 0.31, N = 3 SE +/- 0.25, N = 3 SE +/- 0.21, N = 3 101.68 103.55 121.21 122.03 148.50 162.29 168.40 196.70 237.79 287.81 304.34 387.23 454.49 558.87
Result Confidence
OpenBenchmarking.org Seconds, Fewer Is Better Blender 2.90 Blend File: Classroom - Compute: CPU-Only EPYC 7662 EPYC 7702 EPYC 7642 EPYC 7552 EPYC 7542 EPYC 7502P EPYC 7532 EPYC 7402P EPYC 7F52 EPYC 7302P EPYC 7282 EPYC 7272 EPYC 7F32 EPYC 7232P 100 200 300 400 500 Min: 101.18 / Avg: 101.68 / Max: 101.94 Min: 103.02 / Avg: 103.55 / Max: 104.35 Min: 120.06 / Avg: 121.21 / Max: 122.68 Min: 120.66 / Avg: 122.03 / Max: 122.86 Min: 147.97 / Avg: 148.5 / Max: 149.3 Min: 161.98 / Avg: 162.29 / Max: 162.65 Min: 167.27 / Avg: 168.4 / Max: 170.57 Min: 196.63 / Avg: 196.7 / Max: 196.77 Min: 236.43 / Avg: 237.79 / Max: 238.96 Min: 286.64 / Avg: 287.81 / Max: 288.83 Min: 303.05 / Avg: 304.34 / Max: 305.88 Min: 386.68 / Avg: 387.23 / Max: 387.74 Min: 454.13 / Avg: 454.49 / Max: 454.97 Min: 558.51 / Avg: 558.87 / Max: 559.22
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 7662 EPYC 7702 EPYC 7642 EPYC 7552 EPYC 7542 EPYC 7502P EPYC 7532 EPYC 7402P EPYC 7F52 EPYC 7302P EPYC 7282 EPYC 7272 EPYC 7F32 EPYC 7232P 60 120 180 240 300 SE +/- 0.19, N = 3 SE +/- 0.02, N = 3 SE +/- 0.08, N = 3 SE +/- 0.06, N = 3 SE +/- 0.08, N = 3 SE +/- 0.11, N = 3 SE +/- 0.12, N = 3 SE +/- 0.13, N = 3 SE +/- 0.09, N = 3 SE +/- 0.16, N = 3 SE +/- 0.20, N = 3 SE +/- 0.51, N = 3 SE +/- 0.03, N = 3 SE +/- 0.05, N = 3 54.65 54.71 63.47 64.21 79.11 85.01 87.56 103.00 125.53 147.38 157.17 200.35 243.84 296.69 1. (CXX) g++ options: -O2 -lOpenCL
Result Confidence
OpenBenchmarking.org Seconds, Fewer Is Better Rodinia 3.1 Test: OpenMP LavaMD EPYC 7662 EPYC 7702 EPYC 7642 EPYC 7552 EPYC 7542 EPYC 7502P EPYC 7532 EPYC 7402P EPYC 7F52 EPYC 7302P EPYC 7282 EPYC 7272 EPYC 7F32 EPYC 7232P 50 100 150 200 250 Min: 54.27 / Avg: 54.65 / Max: 54.89 Min: 54.68 / Avg: 54.71 / Max: 54.75 Min: 63.31 / Avg: 63.47 / Max: 63.56 Min: 64.09 / Avg: 64.21 / Max: 64.3 Min: 79.03 / Avg: 79.11 / Max: 79.27 Min: 84.8 / Avg: 85 / Max: 85.18 Min: 87.32 / Avg: 87.56 / Max: 87.75 Min: 102.75 / Avg: 103 / Max: 103.2 Min: 125.35 / Avg: 125.53 / Max: 125.64 Min: 147.07 / Avg: 147.38 / Max: 147.56 Min: 156.97 / Avg: 157.17 / Max: 157.56 Min: 199.81 / Avg: 200.35 / Max: 201.37 Min: 243.81 / Avg: 243.84 / Max: 243.89 Min: 296.63 / Avg: 296.69 / Max: 296.79 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 7662 EPYC 7702 EPYC 7642 EPYC 7552 EPYC 7542 EPYC 7502P EPYC 7532 EPYC 7402P EPYC 7F52 EPYC 7302P EPYC 7282 EPYC 7272 EPYC 7F32 EPYC 7232P 20 40 60 80 100 SE +/- 0.00, N = 7 SE +/- 0.00, N = 7 SE +/- 0.00, N = 7 SE +/- 0.00, N = 7 SE +/- 0.49, N = 6 SE +/- 0.00, N = 6 SE +/- 0.00, N = 6 SE +/- 0.18, N = 5 SE +/- 0.00, N = 5 SE +/- 0.00, N = 5 SE +/- 0.00, N = 4 SE +/- 0.00, N = 4 SE +/- 0.00, N = 3 76.92 76.92 66.67 66.67 55.07 50.00 47.62 41.67 29.59 29.41 27.78 21.74 17.24 14.29 MIN: 62.5 / MAX: 83.33 MIN: 71.43 / MAX: 83.33 MIN: 62.5 / MAX: 71.43 MIN: 58.82 / MAX: 71.43 MIN: 50 / MAX: 55.56 MIN: 45.45 / MAX: 52.63 MIN: 45.45 / MAX: 50 MIN: 38.46 / MAX: 43.48 MIN: 27.78 / MAX: 31.25 MIN: 27.78 MIN: 26.32 MIN: 20.83 / MAX: 22.22 MIN: 16.67 / MAX: 17.86 MIN: 13.89 / MAX: 14.49
FPS Per Watt
OpenBenchmarking.org FPS Per Watt, More Is Better OSPray 1.8.5 Demo: NASA Streamlines - Renderer: SciVis EPYC 7662 EPYC 7702 EPYC 7552 EPYC 7642 EPYC 7542 EPYC 7502P EPYC 7532 EPYC 7402P EPYC 7282 EPYC 7302P EPYC 7272 EPYC 7232P EPYC 7F52 EPYC 7F32 0.1755 0.351 0.5265 0.702 0.8775 0.78 0.76 0.71 0.65 0.59 0.57 0.47 0.44 0.38 0.34 0.29 0.22 0.21 0.18
Result Confidence
OpenBenchmarking.org FPS, More Is Better OSPray 1.8.5 Demo: NASA Streamlines - Renderer: SciVis EPYC 7662 EPYC 7702 EPYC 7642 EPYC 7552 EPYC 7542 EPYC 7502P EPYC 7532 EPYC 7402P EPYC 7F52 EPYC 7302P EPYC 7282 EPYC 7272 EPYC 7F32 EPYC 7232P 15 30 45 60 75 Min: 76.92 / Avg: 76.92 / Max: 76.92 Min: 76.92 / Avg: 76.92 / Max: 76.92 Min: 66.67 / Avg: 66.67 / Max: 66.67 Min: 66.67 / Avg: 66.67 / Max: 66.67 Min: 52.63 / Avg: 55.07 / Max: 55.56 Min: 47.62 / Avg: 47.62 / Max: 47.62 Min: 41.67 / Avg: 41.67 / Max: 41.67 Min: 29.41 / Avg: 29.59 / Max: 30.3 Min: 29.41 / Avg: 29.41 / Max: 29.41 Min: 27.78 / Avg: 27.78 / Max: 27.78 Min: 21.74 / Avg: 21.74 / Max: 21.74 Min: 17.24 / Avg: 17.24 / Max: 17.24 Min: 14.29 / Avg: 14.29 / Max: 14.29
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 7662 EPYC 7702 EPYC 7642 EPYC 7552 EPYC 7542 EPYC 7502P EPYC 7532 EPYC 7402P EPYC 7F52 EPYC 7302P EPYC 7282 EPYC 7272 EPYC 7F32 EPYC 7232P 2 4 6 8 10 SE +/- 0.04, N = 3 SE +/- 0.07, N = 3 SE +/- 0.05, N = 3 SE +/- 0.01, N = 3 SE +/- 0.01, N = 3 SE +/- 0.05, N = 3 SE +/- 0.06, N = 3 SE +/- 0.03, 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 SE +/- 0.00, N = 3 7.92 7.82 6.81 6.75 5.54 5.04 4.92 4.17 3.57 2.91 2.74 2.14 1.84 1.50 MIN: 7.72 / MAX: 8.01 MIN: 7.53 / MAX: 7.98 MIN: 6.61 / MAX: 6.89 MIN: 6.64 / MAX: 6.79 MIN: 5.5 / MAX: 5.57 MIN: 4.94 / MAX: 5.12 MIN: 4.81 / MAX: 5.05 MIN: 4.11 / MAX: 4.26 MIN: 3.48 / MAX: 3.63 MIN: 2.88 / MAX: 2.96 MIN: 2.69 / MAX: 2.78 MIN: 2.08 / MAX: 2.17 MIN: 1.81 / MAX: 1.92 MIN: 1.48 / MAX: 1.54
M samples/sec Per Watt
OpenBenchmarking.org M samples/sec Per Watt, More Is Better LuxCoreRender 2.3 Scene: Rainbow Colors and Prism EPYC 7642 EPYC 7662 EPYC 7552 EPYC 7702 EPYC 7532 EPYC 7282 EPYC 7542 EPYC 7502P EPYC 7402P EPYC 7F52 EPYC 7272 EPYC 7232P EPYC 7302P EPYC 7F32 0.009 0.018 0.027 0.036 0.045 0.04 0.04 0.04 0.04 0.03 0.03 0.03 0.03 0.03 0.02 0.02 0.02 0.02 0.01
Result Confidence
OpenBenchmarking.org M samples/sec, More Is Better LuxCoreRender 2.3 Scene: Rainbow Colors and Prism EPYC 7662 EPYC 7702 EPYC 7642 EPYC 7552 EPYC 7542 EPYC 7502P EPYC 7532 EPYC 7402P EPYC 7F52 EPYC 7302P EPYC 7282 EPYC 7272 EPYC 7F32 EPYC 7232P 3 6 9 12 15 Min: 7.83 / Avg: 7.92 / Max: 7.98 Min: 7.71 / Avg: 7.82 / Max: 7.94 Min: 6.71 / Avg: 6.81 / Max: 6.88 Min: 6.73 / Avg: 6.75 / Max: 6.78 Min: 5.52 / Avg: 5.54 / Max: 5.55 Min: 4.94 / Avg: 5.04 / Max: 5.12 Min: 4.81 / Avg: 4.92 / Max: 5.01 Min: 4.11 / Avg: 4.17 / Max: 4.22 Min: 3.53 / Avg: 3.57 / Max: 3.6 Min: 2.89 / Avg: 2.91 / Max: 2.95 Min: 2.73 / Avg: 2.74 / Max: 2.76 Min: 2.12 / Avg: 2.14 / Max: 2.15 Min: 1.83 / Avg: 1.84 / Max: 1.87 Min: 1.5 / Avg: 1.5 / Max: 1.51
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 7662 EPYC 7702 EPYC 7642 EPYC 7552 EPYC 7542 EPYC 7502P EPYC 7532 EPYC 7402P EPYC 7F52 EPYC 7302P EPYC 7282 EPYC 7272 EPYC 7F32 EPYC 7232P 2 4 6 8 10 SE +/- 0.04, N = 3 SE +/- 0.03, N = 3 SE +/- 0.04, N = 3 SE +/- 0.05, N = 3 SE +/- 0.04, N = 3 SE +/- 0.06, N = 3 SE +/- 0.05, 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 7.21 7.04 6.19 6.13 5.03 4.65 4.54 3.83 3.27 2.68 2.53 1.98 1.68 1.38 MIN: 7.03 / MAX: 7.62 MIN: 6.88 / MAX: 7.39 MIN: 6.04 / MAX: 6.75 MIN: 5.97 / MAX: 6.57 MIN: 4.8 / MAX: 5.35 MIN: 4.49 / MAX: 5.07 MIN: 4.38 / MAX: 4.8 MIN: 3.74 / MAX: 4.01 MIN: 3.18 / MAX: 3.41 MIN: 2.58 / MAX: 2.77 MIN: 2.46 / MAX: 2.62 MIN: 1.91 / MAX: 2.03 MIN: 1.61 / MAX: 1.72 MIN: 1.34 / MAX: 1.42
M samples/sec Per Watt
OpenBenchmarking.org M samples/sec Per Watt, More Is Better LuxCoreRender 2.3 Scene: DLSC EPYC 7662 EPYC 7552 EPYC 7702 EPYC 7642 EPYC 7532 EPYC 7282 EPYC 7542 EPYC 7502P EPYC 7402P EPYC 7272 EPYC 7232P EPYC 7302P EPYC 7F32 EPYC 7F52 0.009 0.018 0.027 0.036 0.045 0.04 0.04 0.04 0.03 0.03 0.03 0.03 0.03 0.03 0.02 0.02 0.02 0.01 0.01
Result Confidence
OpenBenchmarking.org M samples/sec, More Is Better LuxCoreRender 2.3 Scene: DLSC EPYC 7662 EPYC 7702 EPYC 7642 EPYC 7552 EPYC 7542 EPYC 7502P EPYC 7532 EPYC 7402P EPYC 7F52 EPYC 7302P EPYC 7282 EPYC 7272 EPYC 7F32 EPYC 7232P 3 6 9 12 15 Min: 7.13 / Avg: 7.21 / Max: 7.27 Min: 6.98 / Avg: 7.04 / Max: 7.07 Min: 6.14 / Avg: 6.19 / Max: 6.26 Min: 6.07 / Avg: 6.13 / Max: 6.22 Min: 4.96 / Avg: 5.03 / Max: 5.09 Min: 4.58 / Avg: 4.65 / Max: 4.76 Min: 4.47 / Avg: 4.54 / Max: 4.64 Min: 3.81 / Avg: 3.83 / Max: 3.84 Min: 3.26 / Avg: 3.27 / Max: 3.29 Min: 2.66 / Avg: 2.68 / Max: 2.71 Min: 2.52 / Avg: 2.53 / Max: 2.55 Min: 1.97 / Avg: 1.98 / Max: 1.99 Min: 1.66 / Avg: 1.68 / Max: 1.69 Min: 1.37 / Avg: 1.38 / Max: 1.39
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 7702 EPYC 7662 EPYC 7552 EPYC 7542 EPYC 7502P EPYC 7532 EPYC 7402P EPYC 7F52 EPYC 7302P EPYC 7282 EPYC 7272 EPYC 7F32 EPYC 7232P 8 16 24 32 40 SE +/- 0.00, N = 4 SE +/- 0.01, N = 4 SE +/- 0.00, N = 4 SE +/- 0.00, N = 4 SE +/- 0.00, N = 4 SE +/- 0.00, N = 4 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 +/- 0.01, N = 3 SE +/- 0.01, N = 3 6.35 6.38 7.42 9.08 9.73 9.99 11.71 14.02 16.68 17.73 22.40 27.16 33.15 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 7702 EPYC 7662 EPYC 7552 EPYC 7542 EPYC 7502P EPYC 7532 EPYC 7402P EPYC 7F52 EPYC 7302P EPYC 7282 EPYC 7272 EPYC 7F32 EPYC 7232P 7 14 21 28 35 Min: 6.35 / Avg: 6.35 / Max: 6.36 Min: 6.36 / Avg: 6.38 / Max: 6.4 Min: 7.41 / Avg: 7.42 / Max: 7.42 Min: 9.08 / Avg: 9.08 / Max: 9.08 Min: 9.73 / Avg: 9.73 / Max: 9.74 Min: 9.99 / Avg: 9.99 / Max: 9.99 Min: 11.71 / Avg: 11.71 / Max: 11.72 Min: 14 / Avg: 14.02 / Max: 14.03 Min: 16.67 / Avg: 16.68 / Max: 16.69 Min: 17.72 / Avg: 17.73 / Max: 17.74 Min: 22.39 / Avg: 22.4 / Max: 22.42 Min: 27.15 / Avg: 27.16 / Max: 27.17 Min: 33.13 / Avg: 33.15 / Max: 33.18 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 7662 EPYC 7702 EPYC 7642 EPYC 7552 EPYC 7542 EPYC 7502P EPYC 7532 EPYC 7402P EPYC 7F52 EPYC 7302P EPYC 7282 EPYC 7272 EPYC 7F32 EPYC 7232P 3 6 9 12 15 SE +/- 0.01, N = 3 SE +/- 0.02, 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 +/- 0.03, N = 3 SE +/- 0.00, N = 3 SE +/- 0.00, N = 3 SE +/- 0.02, N = 3 SE +/- 0.02, N = 3 SE +/- 0.01, N = 3 SE +/- 0.01, N = 3 8.98 7.88 7.79 7.22 6.13 5.72 5.68 4.73 4.02 3.32 3.23 2.47 2.16 1.74
Result Confidence
OpenBenchmarking.org FPS, More Is Better OpenVINO 2021.1 Model: Face Detection 0106 FP32 - Device: CPU EPYC 7662 EPYC 7702 EPYC 7642 EPYC 7552 EPYC 7542 EPYC 7502P EPYC 7532 EPYC 7402P EPYC 7F52 EPYC 7302P EPYC 7282 EPYC 7272 EPYC 7F32 EPYC 7232P 3 6 9 12 15 Min: 8.97 / Avg: 8.98 / Max: 9.01 Min: 7.84 / Avg: 7.88 / Max: 7.9 Min: 7.78 / Avg: 7.79 / Max: 7.81 Min: 7.19 / Avg: 7.22 / Max: 7.24 Min: 6.03 / Avg: 6.13 / Max: 6.19 Min: 5.7 / Avg: 5.72 / Max: 5.74 Min: 5.67 / Avg: 5.68 / Max: 5.69 Min: 4.68 / Avg: 4.73 / Max: 4.79 Min: 4.02 / Avg: 4.02 / Max: 4.03 Min: 3.31 / Avg: 3.32 / Max: 3.32 Min: 3.2 / Avg: 3.23 / Max: 3.25 Min: 2.44 / Avg: 2.47 / Max: 2.5 Min: 2.14 / Avg: 2.16 / Max: 2.18 Min: 1.71 / Avg: 1.74 / Max: 1.76
Result
OpenBenchmarking.org FPS, More Is Better OpenVINO 2021.1 Model: Person Detection 0106 FP32 - Device: CPU EPYC 7662 EPYC 7702 EPYC 7642 EPYC 7552 EPYC 7542 EPYC 7502P EPYC 7532 EPYC 7402P EPYC 7F52 EPYC 7302P EPYC 7282 EPYC 7272 EPYC 7F32 EPYC 7232P 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 6.60 6.05 5.67 5.53 4.70 4.36 4.19 3.51 2.98 2.51 2.38 1.81 1.64 1.28
Result Confidence
OpenBenchmarking.org FPS, More Is Better OpenVINO 2021.1 Model: Person Detection 0106 FP32 - Device: CPU EPYC 7662 EPYC 7702 EPYC 7642 EPYC 7552 EPYC 7542 EPYC 7502P EPYC 7532 EPYC 7402P EPYC 7F52 EPYC 7302P EPYC 7282 EPYC 7272 EPYC 7F32 EPYC 7232P 3 6 9 12 15 Min: 6.58 / Avg: 6.6 / Max: 6.63 Min: 6.03 / Avg: 6.05 / Max: 6.06 Min: 5.66 / Avg: 5.67 / Max: 5.68 Min: 5.52 / Avg: 5.53 / Max: 5.54 Min: 4.69 / Avg: 4.7 / Max: 4.72 Min: 4.32 / Avg: 4.36 / Max: 4.4 Min: 4.18 / Avg: 4.19 / Max: 4.2 Min: 3.5 / Avg: 3.51 / Max: 3.53 Min: 2.97 / Avg: 2.98 / Max: 2.99 Min: 2.5 / Avg: 2.51 / Max: 2.52 Min: 2.37 / Avg: 2.38 / Max: 2.39 Min: 1.8 / Avg: 1.81 / Max: 1.82 Min: 1.64 / Avg: 1.64 / Max: 1.65 Min: 1.27 / Avg: 1.28 / Max: 1.29
Result
OpenBenchmarking.org FPS, More Is Better OpenVINO 2021.1 Model: Person Detection 0106 FP16 - Device: CPU EPYC 7662 EPYC 7702 EPYC 7642 EPYC 7552 EPYC 7542 EPYC 7502P EPYC 7532 EPYC 7402P EPYC 7F52 EPYC 7302P EPYC 7282 EPYC 7272 EPYC 7F32 EPYC 7232P 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 +/- 0.02, 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 +/- 0.01, N = 3 SE +/- 0.00, N = 3 6.62 6.02 5.67 5.53 4.74 4.37 4.20 3.53 2.99 2.51 2.37 1.81 1.66 1.29
Result Confidence
OpenBenchmarking.org FPS, More Is Better OpenVINO 2021.1 Model: Person Detection 0106 FP16 - Device: CPU EPYC 7662 EPYC 7702 EPYC 7642 EPYC 7552 EPYC 7542 EPYC 7502P EPYC 7532 EPYC 7402P EPYC 7F52 EPYC 7302P EPYC 7282 EPYC 7272 EPYC 7F32 EPYC 7232P 3 6 9 12 15 Min: 6.6 / Avg: 6.62 / Max: 6.64 Min: 6.01 / Avg: 6.02 / Max: 6.03 Min: 5.66 / Avg: 5.67 / Max: 5.68 Min: 5.51 / Avg: 5.53 / Max: 5.56 Min: 4.72 / Avg: 4.74 / Max: 4.75 Min: 4.33 / Avg: 4.37 / Max: 4.4 Min: 4.19 / Avg: 4.2 / Max: 4.21 Min: 3.52 / Avg: 3.53 / Max: 3.56 Min: 2.97 / Avg: 2.99 / Max: 3.01 Min: 2.5 / Avg: 2.51 / Max: 2.52 Min: 2.34 / Avg: 2.37 / Max: 2.38 Min: 1.8 / Avg: 1.81 / Max: 1.82 Min: 1.65 / Avg: 1.66 / Max: 1.67 Min: 1.29 / Avg: 1.29 / Max: 1.3
Result
OpenBenchmarking.org FPS, More Is Better OpenVINO 2021.1 Model: Face Detection 0106 FP16 - Device: CPU EPYC 7662 EPYC 7702 EPYC 7642 EPYC 7552 EPYC 7542 EPYC 7502P EPYC 7532 EPYC 7402P EPYC 7F52 EPYC 7302P EPYC 7282 EPYC 7272 EPYC 7F32 EPYC 7232P 3 6 9 12 15 SE +/- 0.00, N = 3 SE +/- 0.02, 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 +/- 0.01, N = 3 SE +/- 0.01, N = 3 SE +/- 0.02, N = 3 SE +/- 0.01, N = 3 8.97 7.88 7.81 7.20 6.17 5.73 5.68 4.76 4.04 3.31 3.16 2.47 2.16 1.75
Result Confidence
OpenBenchmarking.org FPS, More Is Better OpenVINO 2021.1 Model: Face Detection 0106 FP16 - Device: CPU EPYC 7662 EPYC 7702 EPYC 7642 EPYC 7552 EPYC 7542 EPYC 7502P EPYC 7532 EPYC 7402P EPYC 7F52 EPYC 7302P EPYC 7282 EPYC 7272 EPYC 7F32 EPYC 7232P 3 6 9 12 15 Min: 8.97 / Avg: 8.97 / Max: 8.97 Min: 7.84 / Avg: 7.88 / Max: 7.9 Min: 7.8 / Avg: 7.81 / Max: 7.83 Min: 7.19 / Avg: 7.2 / Max: 7.22 Min: 6.13 / Avg: 6.17 / Max: 6.19 Min: 5.73 / Avg: 5.73 / Max: 5.73 Min: 5.67 / Avg: 5.68 / Max: 5.68 Min: 4.74 / Avg: 4.76 / Max: 4.8 Min: 4.02 / Avg: 4.04 / Max: 4.07 Min: 3.3 / Avg: 3.31 / Max: 3.32 Min: 3.14 / Avg: 3.16 / Max: 3.18 Min: 2.45 / Avg: 2.47 / Max: 2.48 Min: 2.14 / Avg: 2.16 / Max: 2.2 Min: 1.72 / Avg: 1.75 / Max: 1.76
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 7642 EPYC 7662 EPYC 7702 EPYC 7552 EPYC 7532 EPYC 7542 EPYC 7502P EPYC 7402P EPYC 7F52 EPYC 7302P EPYC 7F32 EPYC 7282 EPYC 7272 EPYC 7232P 16 32 48 64 80 SE +/- 0.08, N = 4 SE +/- 0.07, N = 4 SE +/- 0.05, N = 4 SE +/- 0.02, N = 4 SE +/- 0.07, N = 4 SE +/- 0.03, N = 3 SE +/- 0.04, N = 3 SE +/- 0.06, N = 3 SE +/- 0.06, N = 3 SE +/- 0.09, N = 3 SE +/- 0.09, N = 3 SE +/- 0.04, N = 3 SE +/- 0.05, N = 3 SE +/- 0.03, N = 3 13.66 14.03 14.70 15.28 15.29 18.61 19.07 20.35 22.83 25.21 36.80 45.46 48.29 69.91 1. (F9X) gfortran options: -O3 -march=native -funroll-loops -fopenmp
Result Confidence
OpenBenchmarking.org Seconds, Fewer Is Better CloverLeaf Lagrangian-Eulerian Hydrodynamics EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7552 EPYC 7532 EPYC 7542 EPYC 7502P EPYC 7402P EPYC 7F52 EPYC 7302P EPYC 7F32 EPYC 7282 EPYC 7272 EPYC 7232P 14 28 42 56 70 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: 15.23 / Avg: 15.28 / Max: 15.32 Min: 15.1 / Avg: 15.29 / Max: 15.4 Min: 18.57 / Avg: 18.61 / Max: 18.67 Min: 19 / Avg: 19.07 / Max: 19.13 Min: 20.26 / Avg: 20.35 / Max: 20.46 Min: 22.76 / Avg: 22.83 / Max: 22.94 Min: 25.12 / Avg: 25.21 / Max: 25.39 Min: 36.61 / Avg: 36.8 / Max: 36.9 Min: 45.38 / Avg: 45.46 / Max: 45.52 Min: 48.21 / Avg: 48.29 / Max: 48.38 Min: 69.87 / Avg: 69.91 / Max: 69.96 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 7702 EPYC 7662 EPYC 7642 EPYC 7532 EPYC 7552 EPYC 7542 EPYC 7502P EPYC 7402P EPYC 7302P EPYC 7F32 EPYC 7282 EPYC 7272 EPYC 7232P EPYC 7F52 1500 3000 4500 6000 7500 SE +/- 47.34, N = 4 SE +/- 42.67, N = 4 SE +/- 40.59, N = 4 SE +/- 38.66, N = 4 SE +/- 36.86, N = 4 SE +/- 0.00, N = 4 SE +/- 0.00, N = 4 SE +/- 35.55, N = 4 SE +/- 37.73, N = 3 SE +/- 30.11, N = 2 SE +/- 10.27, N = 4 SE +/- 10.02, N = 4 SE +/- 6.46, N = 4 SE +/- 3.57, N = 4 7148.77 6699.07 6615.81 6455.40 6302.57 5788.17 5788.17 5726.60 5509.30 4004.08 3317.93 3257.04 2616.81 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 7402P EPYC 7502P EPYC 7542 EPYC 7302P EPYC 7552 EPYC 7702 EPYC 7642 EPYC 7662 EPYC 7532 EPYC 7282 EPYC 7272 EPYC 7F32 EPYC 7232P EPYC 7F52 20 40 60 80 100 109.78 108.49 108.46 103.76 100.05 96.86 93.63 92.78 89.44 72.91 72.53 70.19 58.97 17.31
Result Confidence
OpenBenchmarking.org Million Grid Points Per Second, More Is Better ASKAP 1.0 Test: tConvolve OpenMP - Degridding EPYC 7702 EPYC 7662 EPYC 7642 EPYC 7532 EPYC 7552 EPYC 7542 EPYC 7502P EPYC 7402P EPYC 7302P EPYC 7F32 EPYC 7282 EPYC 7272 EPYC 7232P EPYC 7F52 1200 2400 3600 4800 6000 Min: 7006.74 / Avg: 7148.77 / Max: 7196.11 Min: 6656.4 / Avg: 6699.07 / Max: 6827.08 Min: 6494.05 / Avg: 6615.81 / Max: 6656.4 Min: 6339.43 / Avg: 6455.4 / Max: 6494.05 Min: 6192 / Avg: 6302.57 / Max: 6339.43 Min: 5788.17 / Avg: 5788.17 / Max: 5788.17 Min: 5788.17 / Avg: 5788.17 / Max: 5788.17 Min: 5665.02 / Avg: 5726.6 / Max: 5788.17 Min: 5433.8 / Avg: 5509.27 / Max: 5547 Min: 3973.97 / Avg: 4004.08 / Max: 4034.18 Min: 3287.11 / Avg: 3317.93 / Max: 3328.2 Min: 3247.02 / Avg: 3257.04 / Max: 3287.11 Min: 2610.35 / Avg: 2616.81 / Max: 2636.2 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 7702 EPYC 7662 EPYC 7642 EPYC 7552 EPYC 7542 EPYC 7502P EPYC 7532 EPYC 7402P EPYC 7F52 EPYC 7302P EPYC 7282 EPYC 7272 EPYC 7F32 EPYC 7232P 50 100 150 200 250 SE +/- 0.20, N = 7 SE +/- 0.21, N = 7 SE +/- 0.11, N = 7 SE +/- 0.08, N = 7 SE +/- 0.03, N = 6 SE +/- 0.06, N = 6 SE +/- 0.06, N = 6 SE +/- 0.04, N = 6 SE +/- 0.10, N = 5 SE +/- 0.08, N = 5 SE +/- 0.06, N = 4 SE +/- 0.04, N = 4 SE +/- 0.01, N = 4 SE +/- 0.08, N = 3 243.57 243.25 218.73 217.70 182.59 167.75 163.00 134.19 109.91 90.37 84.54 68.51 59.60 48.61
mrays/s Per Watt
OpenBenchmarking.org mrays/s Per Watt, More Is Better rays1bench 2020-01-09 Large Scene EPYC 7662 EPYC 7702 EPYC 7552 EPYC 7642 EPYC 7542 EPYC 7502P EPYC 7532 EPYC 7402P EPYC 7282 EPYC 7302P EPYC 7272 EPYC 7F52 EPYC 7232P EPYC 7F32 0.5378 1.0756 1.6134 2.1512 2.689 2.39 2.33 2.24 2.04 1.85 1.81 1.54 1.34 1.09 0.97 0.85 0.69 0.68 0.54
Result Confidence
OpenBenchmarking.org mrays/s, More Is Better rays1bench 2020-01-09 Large Scene EPYC 7702 EPYC 7662 EPYC 7642 EPYC 7552 EPYC 7542 EPYC 7502P EPYC 7532 EPYC 7402P EPYC 7F52 EPYC 7302P EPYC 7282 EPYC 7272 EPYC 7F32 EPYC 7232P 40 80 120 160 200 Min: 242.82 / Avg: 243.57 / Max: 244.37 Min: 242.31 / Avg: 243.25 / Max: 243.89 Min: 218.36 / Avg: 218.73 / Max: 219.13 Min: 217.39 / Avg: 217.7 / Max: 217.92 Min: 182.51 / Avg: 182.59 / Max: 182.66 Min: 167.52 / Avg: 167.75 / Max: 167.95 Min: 162.8 / Avg: 163 / Max: 163.17 Min: 134.04 / Avg: 134.19 / Max: 134.3 Min: 109.61 / Avg: 109.91 / Max: 110.19 Min: 90.09 / Avg: 90.37 / Max: 90.53 Min: 84.42 / Avg: 84.54 / Max: 84.72 Min: 68.41 / Avg: 68.51 / Max: 68.59 Min: 59.57 / Avg: 59.6 / Max: 59.62 Min: 48.46 / Avg: 48.61 / Max: 48.73
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 7662 EPYC 7702 EPYC 7542 EPYC 7642 EPYC 7502P EPYC 7532 EPYC 7552 EPYC 7402P EPYC 7F52 EPYC 7302P EPYC 7282 EPYC 7272 EPYC 7F32 EPYC 7232P 40K 80K 120K 160K 200K SE +/- 61.64, N = 3 SE +/- 118.11, N = 3 SE +/- 72.07, N = 3 SE +/- 392.20, N = 3 SE +/- 44.27, N = 3 SE +/- 69.37, N = 3 SE +/- 518.49, N = 3 SE +/- 40.77, N = 3 SE +/- 61.58, N = 3 SE +/- 15.21, N = 3 SE +/- 47.75, N = 3 SE +/- 28.48, N = 3 SE +/- 13.05, N = 3 SE +/- 20.79, N = 3 33024.0 36468.8 45118.1 45818.8 47911.7 49078.5 50401.8 62904.1 70154.5 82490.4 86277.6 120119.0 136023.0 165426.0
Result Confidence
OpenBenchmarking.org Microseconds, Fewer Is Better TensorFlow Lite 2020-08-23 Model: Mobilenet Quant EPYC 7662 EPYC 7702 EPYC 7542 EPYC 7642 EPYC 7502P EPYC 7532 EPYC 7552 EPYC 7402P EPYC 7F52 EPYC 7302P EPYC 7282 EPYC 7272 EPYC 7F32 EPYC 7232P 30K 60K 90K 120K 150K Min: 32924.1 / Avg: 33024 / Max: 33136.5 Min: 36258.5 / Avg: 36468.83 / Max: 36667.1 Min: 45013.3 / Avg: 45118.1 / Max: 45256.2 Min: 45327.1 / Avg: 45818.77 / Max: 46593.9 Min: 47856.7 / Avg: 47911.7 / Max: 47999.3 Min: 48987 / Avg: 49078.53 / Max: 49214.6 Min: 49377.6 / Avg: 50401.83 / Max: 51054.3 Min: 62851.8 / Avg: 62904.07 / Max: 62984.4 Min: 70069.3 / Avg: 70154.47 / Max: 70274.1 Min: 82465 / Avg: 82490.43 / Max: 82517.6 Min: 86198 / Avg: 86277.57 / Max: 86363.1 Min: 120062 / Avg: 120118.67 / Max: 120152 Min: 135998 / Avg: 136023 / Max: 136042 Min: 165394 / Avg: 165426 / Max: 165465
Result
OpenBenchmarking.org Microseconds, Fewer Is Better TensorFlow Lite 2020-08-23 Model: Mobilenet Float EPYC 7662 EPYC 7702 EPYC 7542 EPYC 7642 EPYC 7502P EPYC 7532 EPYC 7552 EPYC 7402P EPYC 7F52 EPYC 7302P EPYC 7282 EPYC 7272 EPYC 7F32 EPYC 7232P 30K 60K 90K 120K 150K SE +/- 187.50, N = 3 SE +/- 280.28, N = 3 SE +/- 86.41, N = 3 SE +/- 322.42, N = 3 SE +/- 76.82, N = 3 SE +/- 28.71, N = 3 SE +/- 194.69, N = 3 SE +/- 193.63, N = 3 SE +/- 13.80, N = 3 SE +/- 21.22, N = 3 SE +/- 63.38, N = 3 SE +/- 107.22, N = 3 SE +/- 599.00, N = 3 SE +/- 22.85, N = 3 32085.5 35037.4 43977.9 45436.6 47083.4 48084.7 48507.4 61419.9 68637.6 80320.5 84723.5 117060.0 133236.0 160713.0
Result Confidence
OpenBenchmarking.org Microseconds, Fewer Is Better TensorFlow Lite 2020-08-23 Model: Mobilenet Float EPYC 7662 EPYC 7702 EPYC 7542 EPYC 7642 EPYC 7502P EPYC 7532 EPYC 7552 EPYC 7402P EPYC 7F52 EPYC 7302P EPYC 7282 EPYC 7272 EPYC 7F32 EPYC 7232P 30K 60K 90K 120K 150K Min: 31772.4 / Avg: 32085.53 / Max: 32420.8 Min: 34603.7 / Avg: 35037.37 / Max: 35561.8 Min: 43815.4 / Avg: 43977.87 / Max: 44110.1 Min: 44937.4 / Avg: 45436.6 / Max: 46039.7 Min: 46946.3 / Avg: 47083.37 / Max: 47212 Min: 48044.8 / Avg: 48084.67 / Max: 48140.4 Min: 48205.1 / Avg: 48507.43 / Max: 48871.1 Min: 61061.3 / Avg: 61419.9 / Max: 61725.8 Min: 68610.2 / Avg: 68637.6 / Max: 68654.2 Min: 80284 / Avg: 80320.5 / Max: 80357.5 Min: 84636.8 / Avg: 84723.47 / Max: 84846.9 Min: 116941 / Avg: 117060 / Max: 117274 Min: 132636 / Avg: 133236 / Max: 134434 Min: 160685 / Avg: 160712.67 / Max: 160758
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 7662 EPYC 7702 EPYC 7552 EPYC 7642 EPYC 7542 EPYC 7502P EPYC 7532 EPYC 7402P EPYC 7F52 EPYC 7302P EPYC 7282 EPYC 7272 EPYC 7F32 EPYC 7232P 0.1222 0.2444 0.3666 0.4888 0.611 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 +/- 0.000, N = 3 SE +/- 0.001, N = 3 SE +/- 0.001, N = 3 SE +/- 0.001, N = 3 SE +/- 0.001, N = 3 0.109 0.112 0.120 0.120 0.153 0.164 0.173 0.201 0.263 0.280 0.290 0.359 0.464 0.543 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 7662 EPYC 7702 EPYC 7552 EPYC 7642 EPYC 7542 EPYC 7502P EPYC 7532 EPYC 7402P EPYC 7F52 EPYC 7302P EPYC 7282 EPYC 7272 EPYC 7F32 EPYC 7232P 2 4 6 8 10 Min: 0.11 / Avg: 0.11 / Max: 0.11 Min: 0.11 / Avg: 0.11 / Max: 0.11 Min: 0.12 / Avg: 0.12 / Max: 0.12 Min: 0.12 / Avg: 0.12 / Max: 0.12 Min: 0.15 / Avg: 0.15 / Max: 0.15 Min: 0.16 / Avg: 0.16 / Max: 0.16 Min: 0.17 / Avg: 0.17 / Max: 0.17 Min: 0.2 / Avg: 0.2 / Max: 0.2 Min: 0.26 / Avg: 0.26 / Max: 0.26 Min: 0.28 / Avg: 0.28 / Max: 0.28 Min: 0.29 / Avg: 0.29 / Max: 0.29 Min: 0.36 / Avg: 0.36 / Max: 0.36 Min: 0.46 / Avg: 0.46 / Max: 0.47 Min: 0.54 / Avg: 0.54 / Max: 0.54 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 7662 EPYC 7702 EPYC 7642 EPYC 7552 EPYC 7542 EPYC 7502P EPYC 7532 EPYC 7402P EPYC 7F52 EPYC 7302P EPYC 7282 EPYC 7272 EPYC 7F32 EPYC 7232P 200K 400K 600K 800K 1000K SE +/- 2726.39, N = 3 SE +/- 3714.01, N = 3 SE +/- 492.11, N = 3 SE +/- 2696.01, N = 3 SE +/- 684.57, N = 3 SE +/- 1605.99, N = 3 SE +/- 1146.88, N = 3 SE +/- 1145.86, N = 3 SE +/- 501.41, N = 3 SE +/- 406.00, N = 3 SE +/- 721.66, N = 3 SE +/- 527.65, N = 3 SE +/- 196.73, N = 3 SE +/- 258.28, N = 3 915523 897453 835457 832509 654914 610667 578340 499138 381184 357781 344598 278510 215617 184251 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 7662 EPYC 7702 EPYC 7642 EPYC 7552 EPYC 7542 EPYC 7502P EPYC 7532 EPYC 7402P EPYC 7F52 EPYC 7302P EPYC 7282 EPYC 7272 EPYC 7F32 EPYC 7232P 160K 320K 480K 640K 800K Min: 911128.88 / Avg: 915522.69 / Max: 920516.11 Min: 891671.21 / Avg: 897453.24 / Max: 904382.54 Min: 834632.97 / Avg: 835456.65 / Max: 836335.05 Min: 827135.25 / Avg: 832508.89 / Max: 835580.98 Min: 654192.39 / Avg: 654914.4 / Max: 656282.85 Min: 608958.8 / Avg: 610666.61 / Max: 613876.39 Min: 576053.18 / Avg: 578339.82 / Max: 579639.5 Min: 497224.75 / Avg: 499138.43 / Max: 501187.22 Min: 380600.92 / Avg: 381183.76 / Max: 382181.9 Min: 357317.88 / Avg: 357781.31 / Max: 358590.46 Min: 343314.32 / Avg: 344597.63 / Max: 345811.31 Min: 277469.8 / Avg: 278509.56 / Max: 279185.65 Min: 215250.14 / Avg: 215616.98 / Max: 215923.6 Min: 183809.92 / Avg: 184251.3 / Max: 184704.38 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 7662 EPYC 7702 EPYC 7642 EPYC 7552 EPYC 7532 EPYC 7542 EPYC 7502P EPYC 7402P EPYC 7F52 EPYC 7302P EPYC 7282 EPYC 7F32 EPYC 7272 EPYC 7232P 30 60 90 120 150 SE +/- 0.10, N = 3 SE +/- 0.18, N = 3 SE +/- 0.07, N = 3 SE +/- 0.09, N = 3 SE +/- 0.09, N = 3 SE +/- 0.09, N = 3 SE +/- 0.06, N = 3 SE +/- 0.08, N = 3 SE +/- 0.05, N = 3 SE +/- 0.17, N = 3 SE +/- 0.05, N = 3 SE +/- 0.11, N = 3 SE +/- 0.08, N = 3 SE +/- 0.30, N = 3 22.83 23.35 23.43 25.17 26.53 29.62 30.62 33.81 39.89 40.87 56.57 60.50 67.23 113.16 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
Result Confidence
OpenBenchmarking.org Seconds, Fewer Is Better OpenFOAM 8 Input: Motorbike 30M EPYC 7662 EPYC 7702 EPYC 7642 EPYC 7552 EPYC 7532 EPYC 7542 EPYC 7502P EPYC 7402P EPYC 7F52 EPYC 7302P EPYC 7282 EPYC 7F32 EPYC 7272 EPYC 7232P 20 40 60 80 100 Min: 22.63 / Avg: 22.83 / Max: 22.97 Min: 23.06 / Avg: 23.35 / Max: 23.68 Min: 23.3 / Avg: 23.43 / Max: 23.53 Min: 25.06 / Avg: 25.17 / Max: 25.35 Min: 26.35 / Avg: 26.53 / Max: 26.65 Min: 29.5 / Avg: 29.62 / Max: 29.8 Min: 30.52 / Avg: 30.62 / Max: 30.71 Min: 33.73 / Avg: 33.81 / Max: 33.97 Min: 39.79 / Avg: 39.89 / Max: 39.94 Min: 40.67 / Avg: 40.87 / Max: 41.21 Min: 56.49 / Avg: 56.57 / Max: 56.65 Min: 60.32 / Avg: 60.5 / Max: 60.7 Min: 67.08 / Avg: 67.23 / Max: 67.35 Min: 112.77 / Avg: 113.16 / Max: 113.75 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 7662 EPYC 7702 EPYC 7642 EPYC 7542 EPYC 7552 EPYC 7502P EPYC 7532 EPYC 7402P EPYC 7F52 EPYC 7302P EPYC 7282 EPYC 7272 EPYC 7F32 EPYC 7232P 700K 1400K 2100K 2800K 3500K SE +/- 3136.75, N = 3 SE +/- 6069.08, N = 3 SE +/- 1781.71, N = 3 SE +/- 425.74, N = 3 SE +/- 907.34, N = 3 SE +/- 487.90, N = 3 SE +/- 143.80, N = 3 SE +/- 1233.46, N = 3 SE +/- 192.21, N = 3 SE +/- 272.21, N = 3 SE +/- 565.25, N = 3 SE +/- 436.36, N = 3 SE +/- 227.03, N = 3 SE +/- 1129.29, N = 3 700833 764269 938691 943229 978828 1006347 1034367 1366410 1499183 1742890 1820153 2493747 2872227 3472940
Result Confidence
OpenBenchmarking.org Microseconds, Fewer Is Better TensorFlow Lite 2020-08-23 Model: Inception V4 EPYC 7662 EPYC 7702 EPYC 7642 EPYC 7542 EPYC 7552 EPYC 7502P EPYC 7532 EPYC 7402P EPYC 7F52 EPYC 7302P EPYC 7282 EPYC 7272 EPYC 7F32 EPYC 7232P 600K 1200K 1800K 2400K 3000K Min: 695393 / Avg: 700833.33 / Max: 706259 Min: 752152 / Avg: 764269 / Max: 770948 Min: 935608 / Avg: 938691 / Max: 941780 Min: 942378 / Avg: 943229 / Max: 943679 Min: 977917 / Avg: 978828.33 / Max: 980643 Min: 1005560 / Avg: 1006346.67 / Max: 1007240 Min: 1034080 / Avg: 1034366.67 / Max: 1034530 Min: 1365020 / Avg: 1366410 / Max: 1368870 Min: 1498800 / Avg: 1499183.33 / Max: 1499400 Min: 1742350 / Avg: 1742890 / Max: 1743220 Min: 1819400 / Avg: 1820153.33 / Max: 1821260 Min: 2492910 / Avg: 2493746.67 / Max: 2494380 Min: 2871920 / Avg: 2872226.67 / Max: 2872670 Min: 3471470 / Avg: 3472940 / Max: 3475160
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 7702 EPYC 7662 EPYC 7642 EPYC 7552 EPYC 7542 EPYC 7502P EPYC 7532 EPYC 7402P EPYC 7F52 EPYC 7302P EPYC 7282 EPYC 7272 EPYC 7F32 EPYC 7232P 40 80 120 160 200 SE +/- 0.12, N = 3 SE +/- 0.27, N = 3 SE +/- 0.19, N = 3 SE +/- 0.42, N = 3 SE +/- 0.06, N = 3 SE +/- 0.37, N = 3 SE +/- 0.21, N = 3 SE +/- 0.08, N = 3 SE +/- 0.27, N = 3 SE +/- 0.95, N = 3 SE +/- 0.34, N = 3 SE +/- 0.34, N = 3 SE +/- 0.25, N = 3 SE +/- 1.01, N = 3 40.07 40.33 45.78 46.59 55.32 60.75 61.25 69.84 83.45 102.29 108.34 136.20 156.31 198.45
Result Confidence
OpenBenchmarking.org Seconds, Fewer Is Better Blender 2.90 Blend File: BMW27 - Compute: CPU-Only EPYC 7702 EPYC 7662 EPYC 7642 EPYC 7552 EPYC 7542 EPYC 7502P EPYC 7532 EPYC 7402P EPYC 7F52 EPYC 7302P EPYC 7282 EPYC 7272 EPYC 7F32 EPYC 7232P 40 80 120 160 200 Min: 39.84 / Avg: 40.07 / Max: 40.23 Min: 39.99 / Avg: 40.33 / Max: 40.86 Min: 45.39 / Avg: 45.78 / Max: 45.99 Min: 45.95 / Avg: 46.59 / Max: 47.39 Min: 55.22 / Avg: 55.32 / Max: 55.43 Min: 60 / Avg: 60.75 / Max: 61.17 Min: 60.93 / Avg: 61.25 / Max: 61.64 Min: 69.76 / Avg: 69.84 / Max: 69.99 Min: 83.1 / Avg: 83.45 / Max: 83.98 Min: 100.63 / Avg: 102.29 / Max: 103.93 Min: 107.74 / Avg: 108.34 / Max: 108.92 Min: 135.6 / Avg: 136.2 / Max: 136.76 Min: 155.93 / Avg: 156.31 / Max: 156.78 Min: 196.87 / Avg: 198.45 / Max: 200.33
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 7702 EPYC 7662 EPYC 7642 EPYC 7552 EPYC 7542 EPYC 7502P EPYC 7532 EPYC 7402P EPYC 7F52 EPYC 7302P EPYC 7282 EPYC 7272 EPYC 7F32 EPYC 7232P 13 26 39 52 65 SE +/- 0.02, N = 4 SE +/- 0.03, N = 4 SE +/- 0.04, N = 4 SE +/- 0.04, N = 4 SE +/- 0.01, N = 3 SE +/- 0.01, N = 3 SE +/- 0.02, N = 3 SE +/- 0.05, N = 3 SE +/- 0.02, N = 3 SE +/- 0.01, N = 3 SE +/- 0.05, N = 3 SE +/- 0.04, N = 3 SE +/- 0.02, N = 3 SE +/- 0.24, N = 3 11.50 11.50 13.27 13.27 15.94 17.14 17.67 20.46 24.18 28.70 30.51 38.41 45.47 55.78 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 7702 EPYC 7662 EPYC 7642 EPYC 7552 EPYC 7542 EPYC 7502P EPYC 7532 EPYC 7402P EPYC 7F52 EPYC 7302P EPYC 7282 EPYC 7272 EPYC 7F32 EPYC 7232P 11 22 33 44 55 Min: 11.45 / Avg: 11.5 / Max: 11.55 Min: 11.4 / Avg: 11.5 / Max: 11.56 Min: 13.19 / Avg: 13.27 / Max: 13.35 Min: 13.17 / Avg: 13.27 / Max: 13.35 Min: 15.92 / Avg: 15.94 / Max: 15.96 Min: 17.12 / Avg: 17.14 / Max: 17.17 Min: 17.65 / Avg: 17.67 / Max: 17.7 Min: 20.41 / Avg: 20.46 / Max: 20.56 Min: 24.15 / Avg: 24.18 / Max: 24.23 Min: 28.69 / Avg: 28.7 / Max: 28.72 Min: 30.42 / Avg: 30.51 / Max: 30.57 Min: 38.36 / Avg: 38.41 / Max: 38.49 Min: 45.44 / Avg: 45.47 / Max: 45.5 Min: 55.44 / Avg: 55.78 / Max: 56.24 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 7702 EPYC 7662 EPYC 7642 EPYC 7552 EPYC 7542 EPYC 7502P EPYC 7532 EPYC 7402P EPYC 7F52 EPYC 7302P EPYC 7282 EPYC 7272 EPYC 7F32 EPYC 7232P 60 120 180 240 300 SE +/- 0.11, N = 3 SE +/- 0.03, N = 3 SE +/- 0.14, N = 3 SE +/- 0.22, N = 3 SE +/- 0.12, N = 3 SE +/- 0.04, N = 3 SE +/- 0.30, N = 3 SE +/- 0.46, N = 3 SE +/- 0.20, N = 3 SE +/- 0.08, N = 3 SE +/- 0.24, N = 3 SE +/- 0.81, N = 3 SE +/- 0.04, N = 3 SE +/- 0.21, N = 3 55.40 55.82 61.93 62.72 72.27 78.01 78.94 91.81 108.40 129.81 139.46 177.65 207.12 267.24
Result Confidence
OpenBenchmarking.org Seconds, Fewer Is Better Blender 2.90 Blend File: Fishy Cat - Compute: CPU-Only EPYC 7702 EPYC 7662 EPYC 7642 EPYC 7552 EPYC 7542 EPYC 7502P EPYC 7532 EPYC 7402P EPYC 7F52 EPYC 7302P EPYC 7282 EPYC 7272 EPYC 7F32 EPYC 7232P 50 100 150 200 250 Min: 55.2 / Avg: 55.4 / Max: 55.58 Min: 55.77 / Avg: 55.82 / Max: 55.85 Min: 61.67 / Avg: 61.93 / Max: 62.15 Min: 62.45 / Avg: 62.72 / Max: 63.15 Min: 72.03 / Avg: 72.27 / Max: 72.43 Min: 77.95 / Avg: 78.01 / Max: 78.08 Min: 78.44 / Avg: 78.94 / Max: 79.47 Min: 90.99 / Avg: 91.81 / Max: 92.58 Min: 108.03 / Avg: 108.4 / Max: 108.72 Min: 129.68 / Avg: 129.81 / Max: 129.95 Min: 139.16 / Avg: 139.46 / Max: 139.93 Min: 176.74 / Avg: 177.65 / Max: 179.26 Min: 207.06 / Avg: 207.12 / Max: 207.19 Min: 267.03 / Avg: 267.24 / Max: 267.66
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 7662 EPYC 7702 EPYC 7642 EPYC 7552 EPYC 7542 EPYC 7502P EPYC 7532 EPYC 7272 EPYC 7F52 EPYC 7402P EPYC 7302P EPYC 7282 EPYC 7F32 EPYC 7232P 2 4 6 8 10 SE +/- 0.00798, N = 3 SE +/- 0.00645, N = 3 SE +/- 0.00608, N = 3 SE +/- 0.00201, N = 3 SE +/- 0.00531, N = 3 SE +/- 0.00464, N = 3 SE +/- 0.00309, N = 3 SE +/- 0.00535, N = 3 SE +/- 0.02104, N = 3 SE +/- 0.02587, N = 3 SE +/- 0.00946, N = 3 SE +/- 0.02527, N = 3 SE +/- 0.00611, N = 3 SE +/- 0.02294, N = 3 1.79874 1.88842 1.93042 1.99707 2.06983 2.15194 2.20543 5.25331 5.49605 5.92204 6.03497 6.06333 7.23763 8.67154 MIN: 1.69 MIN: 1.8 MIN: 1.82 MIN: 1.91 MIN: 2 MIN: 2.02 MIN: 2.05 MIN: 5.07 MIN: 5.32 MIN: 5.79 MIN: 5.92 MIN: 5.87 MIN: 7.01 MIN: 8.41 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 7662 EPYC 7702 EPYC 7642 EPYC 7552 EPYC 7542 EPYC 7502P EPYC 7532 EPYC 7272 EPYC 7F52 EPYC 7402P EPYC 7302P EPYC 7282 EPYC 7F32 EPYC 7232P 3 6 9 12 15 Min: 1.78 / Avg: 1.8 / Max: 1.81 Min: 1.88 / Avg: 1.89 / Max: 1.9 Min: 1.92 / Avg: 1.93 / Max: 1.94 Min: 1.99 / Avg: 2 / Max: 2 Min: 2.06 / Avg: 2.07 / Max: 2.08 Min: 2.15 / Avg: 2.15 / Max: 2.16 Min: 2.2 / Avg: 2.21 / Max: 2.21 Min: 5.25 / Avg: 5.25 / Max: 5.26 Min: 5.46 / Avg: 5.5 / Max: 5.54 Min: 5.89 / Avg: 5.92 / Max: 5.97 Min: 6.02 / Avg: 6.03 / Max: 6.04 Min: 6.02 / Avg: 6.06 / Max: 6.1 Min: 7.23 / Avg: 7.24 / Max: 7.25 Min: 8.63 / Avg: 8.67 / Max: 8.71 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 7662 EPYC 7702 EPYC 7642 EPYC 7542 EPYC 7552 EPYC 7502P EPYC 7532 EPYC 7402P EPYC 7F52 EPYC 7302P EPYC 7282 EPYC 7272 EPYC 7F32 EPYC 7232P 700K 1400K 2100K 2800K 3500K SE +/- 4181.60, N = 3 SE +/- 6234.46, N = 7 SE +/- 837.49, N = 3 SE +/- 149.07, N = 3 SE +/- 1818.31, N = 3 SE +/- 466.83, N = 3 SE +/- 386.91, N = 3 SE +/- 1259.14, N = 3 SE +/- 1646.01, N = 3 SE +/- 366.38, N = 3 SE +/- 1027.95, N = 3 SE +/- 518.11, N = 3 SE +/- 314.32, N = 3 SE +/- 326.24, N = 3 655279 702607 830730 840604 893517 897884 921865 1206790 1346153 1567070 1639167 2242950 2592970 3136920
Result Confidence
OpenBenchmarking.org Microseconds, Fewer Is Better TensorFlow Lite 2020-08-23 Model: Inception ResNet V2 EPYC 7662 EPYC 7702 EPYC 7642 EPYC 7542 EPYC 7552 EPYC 7502P EPYC 7532 EPYC 7402P EPYC 7F52 EPYC 7302P EPYC 7282 EPYC 7272 EPYC 7F32 EPYC 7232P 500K 1000K 1500K 2000K 2500K Min: 649807 / Avg: 655278.67 / Max: 663492 Min: 690630 / Avg: 702607 / Max: 737249 Min: 829366 / Avg: 830730.33 / Max: 832254 Min: 840370 / Avg: 840604 / Max: 840881 Min: 889933 / Avg: 893516.67 / Max: 895844 Min: 897006 / Avg: 897884 / Max: 898598 Min: 921416 / Avg: 921864.67 / Max: 922635 Min: 1205130 / Avg: 1206790 / Max: 1209260 Min: 1343550 / Avg: 1346153.33 / Max: 1349200 Min: 1566650 / Avg: 1567070 / Max: 1567800 Min: 1637410 / Avg: 1639166.67 / Max: 1640970 Min: 2241960 / Avg: 2242950 / Max: 2243710 Min: 2592570 / Avg: 2592970 / Max: 2593590 Min: 3136350 / Avg: 3136920 / Max: 3137480
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 7662 EPYC 7702 EPYC 7642 EPYC 7552 EPYC 7542 EPYC 7502P EPYC 7532 EPYC 7402P EPYC 7F52 EPYC 7302P EPYC 7282 EPYC 7272 EPYC 7F32 EPYC 7232P 2 4 6 8 10 SE +/- 0.00834, N = 9 SE +/- 0.00637, N = 9 SE +/- 0.00625, N = 9 SE +/- 0.00157, N = 9 SE +/- 0.00215, N = 9 SE +/- 0.00338, N = 9 SE +/- 0.00104, N = 9 SE +/- 0.00168, N = 9 SE +/- 0.00628, N = 9 SE +/- 0.00304, N = 9 SE +/- 0.00324, N = 9 SE +/- 0.00336, N = 9 SE +/- 0.00176, N = 9 SE +/- 0.00235, N = 9 1.43124 1.49446 1.53915 1.55494 1.89624 1.94845 1.98809 2.38306 3.02897 3.34663 3.45290 4.52758 5.58260 6.79445 MIN: 1.26 MIN: 1.36 MIN: 1.37 MIN: 1.42 MIN: 1.77 MIN: 1.82 MIN: 1.83 MIN: 2.33 MIN: 2.92 MIN: 3.25 MIN: 3.34 MIN: 4.47 MIN: 5.52 MIN: 6.75 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 7662 EPYC 7702 EPYC 7642 EPYC 7552 EPYC 7542 EPYC 7502P EPYC 7532 EPYC 7402P EPYC 7F52 EPYC 7302P EPYC 7282 EPYC 7272 EPYC 7F32 EPYC 7232P 3 6 9 12 15 Min: 1.41 / Avg: 1.43 / Max: 1.48 Min: 1.48 / Avg: 1.49 / Max: 1.53 Min: 1.52 / Avg: 1.54 / Max: 1.57 Min: 1.55 / Avg: 1.55 / Max: 1.56 Min: 1.89 / Avg: 1.9 / Max: 1.91 Min: 1.94 / Avg: 1.95 / Max: 1.97 Min: 1.98 / Avg: 1.99 / Max: 1.99 Min: 2.38 / Avg: 2.38 / Max: 2.39 Min: 2.99 / Avg: 3.03 / Max: 3.05 Min: 3.33 / Avg: 3.35 / Max: 3.36 Min: 3.44 / Avg: 3.45 / Max: 3.47 Min: 4.51 / Avg: 4.53 / Max: 4.54 Min: 5.57 / Avg: 5.58 / Max: 5.59 Min: 6.79 / Avg: 6.79 / Max: 6.81 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 7662 EPYC 7702 EPYC 7642 EPYC 7552 EPYC 7542 EPYC 7502P EPYC 7532 EPYC 7402P EPYC 7F52 EPYC 7302P EPYC 7282 EPYC 7272 EPYC 7F32 EPYC 7232P 6 12 18 24 30 SE +/- 0.056, N = 3 SE +/- 0.024, N = 3 SE +/- 0.029, N = 3 SE +/- 0.112, N = 3 SE +/- 0.062, N = 3 SE +/- 0.059, N = 3 SE +/- 0.016, N = 3 SE +/- 0.010, N = 3 SE +/- 0.053, N = 3 SE +/- 0.009, N = 3 SE +/- 0.021, N = 3 SE +/- 0.023, N = 3 SE +/- 0.004, N = 3 SE +/- 0.007, N = 3 25.206 24.818 22.442 22.046 18.156 17.614 17.525 14.907 11.757 10.602 9.889 7.737 6.705 5.406 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 7662 EPYC 7552 EPYC 7702 EPYC 7502P EPYC 7642 EPYC 7542 EPYC 7532 EPYC 7282 EPYC 7402P EPYC 7302P EPYC 7272 EPYC 7232P EPYC 7F32 EPYC 7F52 0.0315 0.063 0.0945 0.126 0.1575 0.14 0.13 0.13 0.12 0.11 0.11 0.10 0.10 0.10 0.09 0.08 0.07 0.06 0.06
Result Confidence
OpenBenchmarking.org ns/day, More Is Better LAMMPS Molecular Dynamics Simulator 29Oct2020 Model: 20k Atoms EPYC 7662 EPYC 7702 EPYC 7642 EPYC 7552 EPYC 7542 EPYC 7502P EPYC 7532 EPYC 7402P EPYC 7F52 EPYC 7302P EPYC 7282 EPYC 7272 EPYC 7F32 EPYC 7232P 6 12 18 24 30 Min: 25.11 / Avg: 25.21 / Max: 25.31 Min: 24.78 / Avg: 24.82 / Max: 24.86 Min: 22.4 / Avg: 22.44 / Max: 22.5 Min: 21.83 / Avg: 22.05 / Max: 22.19 Min: 18.03 / Avg: 18.16 / Max: 18.22 Min: 17.51 / Avg: 17.61 / Max: 17.71 Min: 17.5 / Avg: 17.53 / Max: 17.55 Min: 14.89 / Avg: 14.91 / Max: 14.93 Min: 11.66 / Avg: 11.76 / Max: 11.85 Min: 10.58 / Avg: 10.6 / Max: 10.62 Min: 9.85 / Avg: 9.89 / Max: 9.92 Min: 7.71 / Avg: 7.74 / Max: 7.78 Min: 6.7 / Avg: 6.7 / Max: 6.71 Min: 5.39 / Avg: 5.41 / Max: 5.41 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 7662 EPYC 7702 EPYC 7642 EPYC 7552 EPYC 7542 EPYC 7532 EPYC 7502P EPYC 7402P EPYC 7302P EPYC 7F52 EPYC 7282 EPYC 7272 EPYC 7F32 EPYC 7232P 1.0217 2.0434 3.0651 4.0868 5.1085 SE +/- 0.008, N = 3 SE +/- 0.003, N = 3 SE +/- 0.013, N = 3 SE +/- 0.004, N = 3 SE +/- 0.002, N = 3 SE +/- 0.008, N = 3 SE +/- 0.011, N = 3 SE +/- 0.001, N = 3 SE +/- 0.004, N = 3 SE +/- 0.005, N = 3 SE +/- 0.001, N = 3 SE +/- 0.001, N = 3 SE +/- 0.003, N = 3 SE +/- 0.003, N = 3 4.541 4.373 4.117 3.863 3.323 3.267 3.128 2.741 2.014 1.995 1.677 1.409 1.345 0.985 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 7662 EPYC 7642 EPYC 7532 EPYC 7282 EPYC 7542 EPYC 7502P EPYC 7552 EPYC 7302P EPYC 7402P EPYC 7702 EPYC 7F32 EPYC 7F52 EPYC 7272 EPYC 7232P 0.0068 0.0136 0.0204 0.0272 0.034 0.03 0.02 0.02 0.02 0.02 0.02 0.02 0.02 0.02 0.02 0.01 0.01 0.01 0.01
Result Confidence
OpenBenchmarking.org Ns Per Day, More Is Better GROMACS 2020.3 Water Benchmark EPYC 7662 EPYC 7702 EPYC 7642 EPYC 7552 EPYC 7542 EPYC 7532 EPYC 7502P EPYC 7402P EPYC 7302P EPYC 7F52 EPYC 7282 EPYC 7272 EPYC 7F32 EPYC 7232P 2 4 6 8 10 Min: 4.53 / Avg: 4.54 / Max: 4.55 Min: 4.37 / Avg: 4.37 / Max: 4.38 Min: 4.09 / Avg: 4.12 / Max: 4.13 Min: 3.86 / Avg: 3.86 / Max: 3.87 Min: 3.32 / Avg: 3.32 / Max: 3.33 Min: 3.25 / Avg: 3.27 / Max: 3.28 Min: 3.11 / Avg: 3.13 / Max: 3.14 Min: 2.74 / Avg: 2.74 / Max: 2.74 Min: 2.01 / Avg: 2.01 / Max: 2.02 Min: 1.99 / Avg: 2 / Max: 2.01 Min: 1.68 / Avg: 1.68 / Max: 1.68 Min: 1.41 / Avg: 1.41 / Max: 1.41 Min: 1.34 / Avg: 1.35 / Max: 1.35 Min: 0.98 / Avg: 0.99 / Max: 0.99 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 7662 EPYC 7702 EPYC 7642 EPYC 7552 EPYC 7542 EPYC 7502P EPYC 7532 EPYC 7402P EPYC 7F52 EPYC 7302P EPYC 7282 EPYC 7272 EPYC 7F32 EPYC 7232P 0.8063 1.6126 2.4189 3.2252 4.0315 SE +/- 0.000537, N = 4 SE +/- 0.002127, N = 4 SE +/- 0.001659, N = 4 SE +/- 0.000788, N = 4 SE +/- 0.005244, N = 4 SE +/- 0.003967, N = 4 SE +/- 0.001948, N = 4 SE +/- 0.009261, N = 15 SE +/- 0.001361, N = 4 SE +/- 0.001219, N = 4 SE +/- 0.001269, N = 4 SE +/- 0.001298, N = 4 SE +/- 0.000640, N = 4 SE +/- 0.001594, N = 4 0.780803 0.800643 0.863146 0.868024 1.015820 1.073990 1.104860 1.295990 1.565030 1.841780 1.913050 2.493720 3.012920 3.583630 MIN: 0.7 MIN: 0.76 MIN: 0.77 MIN: 0.81 MIN: 0.98 MIN: 0.98 MIN: 0.99 MIN: 1.25 MIN: 1.54 MIN: 1.82 MIN: 1.87 MIN: 2.45 MIN: 2.73 MIN: 3.54 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 7662 EPYC 7702 EPYC 7642 EPYC 7552 EPYC 7542 EPYC 7502P EPYC 7532 EPYC 7402P EPYC 7F52 EPYC 7302P EPYC 7282 EPYC 7272 EPYC 7F32 EPYC 7232P 2 4 6 8 10 Min: 0.78 / Avg: 0.78 / Max: 0.78 Min: 0.79 / Avg: 0.8 / Max: 0.8 Min: 0.86 / Avg: 0.86 / Max: 0.87 Min: 0.87 / Avg: 0.87 / Max: 0.87 Min: 1 / Avg: 1.02 / Max: 1.03 Min: 1.07 / Avg: 1.07 / Max: 1.08 Min: 1.1 / Avg: 1.1 / Max: 1.11 Min: 1.27 / Avg: 1.3 / Max: 1.37 Min: 1.56 / Avg: 1.57 / Max: 1.57 Min: 1.84 / Avg: 1.84 / Max: 1.85 Min: 1.91 / Avg: 1.91 / Max: 1.92 Min: 2.49 / Avg: 2.49 / Max: 2.5 Min: 3.01 / Avg: 3.01 / Max: 3.01 Min: 3.58 / Avg: 3.58 / Max: 3.59 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 7542 EPYC 7502P EPYC 7552 EPYC 7702 EPYC 7662 EPYC 7642 EPYC 7532 EPYC 7402P EPYC 7F52 EPYC 7282 EPYC 7302P EPYC 7272 EPYC 7F32 EPYC 7232P 50K 100K 150K 200K 250K SE +/- 2207.46, N = 15 SE +/- 2790.65, N = 3 SE +/- 1126.54, N = 3 SE +/- 1230.73, N = 3 SE +/- 2776.27, N = 3 SE +/- 1690.31, N = 3 SE +/- 2221.55, N = 3 SE +/- 2693.44, N = 3 SE +/- 1803.14, N = 3 SE +/- 936.51, N = 3 SE +/- 1793.27, N = 3 SE +/- 388.59, N = 3 SE +/- 224.51, N = 3 SE +/- 244.34, N = 3 236524 233730 230871 227564 219380 215576 211361 200705 144123 136442 135260 93155 58118 51734
Op/s Per Watt
OpenBenchmarking.org Op/s Per Watt, More Is Better Apache Cassandra 3.11.4 Test: Writes EPYC 7542 EPYC 7502P EPYC 7552 EPYC 7402P EPYC 7282 EPYC 7702 EPYC 7662 EPYC 7642 EPYC 7532 EPYC 7302P EPYC 7272 EPYC 7F52 EPYC 7232P EPYC 7F32 400 800 1200 1600 2000 2007.98 1934.28 1765.84 1745.18 1607.35 1563.40 1537.85 1507.25 1502.63 1456.94 1222.04 945.02 837.71 654.20
Result Confidence
OpenBenchmarking.org Op/s, More Is Better Apache Cassandra 3.11.4 Test: Writes EPYC 7542 EPYC 7502P EPYC 7552 EPYC 7702 EPYC 7662 EPYC 7642 EPYC 7532 EPYC 7402P EPYC 7F52 EPYC 7282 EPYC 7302P EPYC 7272 EPYC 7F32 EPYC 7232P 40K 80K 120K 160K 200K Min: 227162 / Avg: 236524.33 / Max: 255532 Min: 228668 / Avg: 233730 / Max: 238297 Min: 229505 / Avg: 230871.33 / Max: 233106 Min: 225103 / Avg: 227564.33 / Max: 228816 Min: 214454 / Avg: 219380 / Max: 224062 Min: 212562 / Avg: 215576 / Max: 218409 Min: 208632 / Avg: 211361 / Max: 215762 Min: 197409 / Avg: 200705 / Max: 206043 Min: 141196 / Avg: 144123.33 / Max: 147411 Min: 134572 / Avg: 136442 / Max: 137469 Min: 131775 / Avg: 135259.67 / Max: 137737 Min: 92380 / Avg: 93154.67 / Max: 93596 Min: 57842 / Avg: 58118.33 / Max: 58563 Min: 51248 / Avg: 51734.33 / Max: 52019
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 7662 EPYC 7702 EPYC 7642 EPYC 7552 EPYC 7532 EPYC 7542 EPYC 7502P EPYC 7402P EPYC 7302P EPYC 7282 EPYC 7F32 EPYC 7272 EPYC 7232P EPYC 7F52 2K 4K 6K 8K 10K SE +/- 0.00, N = 4 SE +/- 0.00, N = 4 SE +/- 81.97, N = 4 SE +/- 77.48, N = 4 SE +/- 63.04, N = 4 SE +/- 67.99, N = 4 SE +/- 79.54, N = 4 SE +/- 72.46, N = 4 SE +/- 57.68, N = 5 SE +/- 0.00, N = 4 SE +/- 35.30, N = 4 SE +/- 17.38, N = 4 SE +/- 7.61, N = 4 SE +/- 0.00, N = 4 9509.14 9509.14 9427.17 8454.70 8257.47 6658.48 6617.90 6379.88 5503.59 4294.45 4035.11 4004.08 2840.13 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 7662 EPYC 7702 EPYC 7642 EPYC 7552 EPYC 7532 EPYC 7542 EPYC 7502P EPYC 7402P EPYC 7302P EPYC 7282 EPYC 7F32 EPYC 7272 EPYC 7232P EPYC 7F52 1700 3400 5100 6800 8500 Min: 9509.14 / Avg: 9509.14 / Max: 9509.14 Min: 9509.14 / Avg: 9509.14 / Max: 9509.14 Min: 9181.24 / Avg: 9427.17 / Max: 9509.14 Min: 8320.5 / Avg: 8454.7 / Max: 8588.9 Min: 8068.36 / Avg: 8257.47 / Max: 8320.5 Min: 6494.05 / Avg: 6658.48 / Max: 6827.08 Min: 6494.05 / Avg: 6617.9 / Max: 6827.08 Min: 6192 / Avg: 6379.88 / Max: 6494.05 Min: 5325.12 / Avg: 5503.59 / Max: 5665.02 Min: 4294.45 / Avg: 4294.45 / Max: 4294.45 Min: 3973.97 / Avg: 4035.11 / Max: 4096.25 Min: 3973.97 / Avg: 4004.08 / Max: 4034.18 Min: 2832.51 / Avg: 2840.13 / Max: 2862.97 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 7662 EPYC 7702 EPYC 7552 EPYC 7542 EPYC 7502P EPYC 7532 EPYC 7402P EPYC 7F52 EPYC 7302P EPYC 7282 EPYC 7272 EPYC 7F32 EPYC 7232P 7 14 21 28 35 SE +/- 0.04, N = 6 SE +/- 0.03, N = 6 SE +/- 0.02, N = 6 SE +/- 0.01, N = 5 SE +/- 0.01, N = 5 SE +/- 0.01, N = 5 SE +/- 0.01, N = 4 SE +/- 0.02, N = 4 SE +/- 0.12, N = 6 SE +/- 0.01, N = 3 SE +/- 0.00, N = 3 SE +/- 0.01, N = 3 SE +/- 0.00, N = 3 29.41 27.67 26.13 21.55 20.25 20.14 17.17 14.24 12.18 11.34 9.03 7.94 6.55
Images / Sec Per Watt
OpenBenchmarking.org Images / Sec Per Watt, More Is Better Intel Open Image Denoise 1.2.0 Scene: Memorial EPYC 7662 EPYC 7552 EPYC 7702 EPYC 7542 EPYC 7502P EPYC 7532 EPYC 7402P EPYC 7282 EPYC 7302P EPYC 7272 EPYC 7232P EPYC 7F52 EPYC 7F32 0.0473 0.0946 0.1419 0.1892 0.2365 0.21 0.20 0.20 0.16 0.16 0.15 0.13 0.12 0.11 0.10 0.08 0.07 0.06
Result Confidence
OpenBenchmarking.org Images / Sec, More Is Better Intel Open Image Denoise 1.2.0 Scene: Memorial EPYC 7662 EPYC 7702 EPYC 7552 EPYC 7542 EPYC 7502P EPYC 7532 EPYC 7402P EPYC 7F52 EPYC 7302P EPYC 7282 EPYC 7272 EPYC 7F32 EPYC 7232P 7 14 21 28 35 Min: 29.29 / Avg: 29.41 / Max: 29.54 Min: 27.55 / Avg: 27.67 / Max: 27.73 Min: 26.05 / Avg: 26.13 / Max: 26.17 Min: 21.52 / Avg: 21.55 / Max: 21.6 Min: 20.23 / Avg: 20.25 / Max: 20.28 Min: 20.11 / Avg: 20.14 / Max: 20.18 Min: 17.16 / Avg: 17.17 / Max: 17.19 Min: 14.2 / Avg: 14.24 / Max: 14.27 Min: 11.56 / Avg: 12.18 / Max: 12.32 Min: 11.34 / Avg: 11.34 / Max: 11.36 Min: 9.02 / Avg: 9.03 / Max: 9.03 Min: 7.92 / Avg: 7.94 / Max: 7.96 Min: 6.54 / Avg: 6.55 / Max: 6.55
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 7662 EPYC 7642 EPYC 7702 EPYC 7552 EPYC 7542 EPYC 7532 EPYC 7502P EPYC 7402P EPYC 7F52 EPYC 7302P EPYC 7282 EPYC 7272 EPYC 7F32 EPYC 7232P 600K 1200K 1800K 2400K 3000K SE +/- 34594.95, N = 12 SE +/- 37169.94, N = 3 SE +/- 25794.01, N = 15 SE +/- 24033.50, N = 3 SE +/- 8453.72, N = 3 SE +/- 15669.57, N = 3 SE +/- 10663.27, N = 3 SE +/- 15686.47, N = 3 SE +/- 7117.75, N = 3 SE +/- 8057.83, N = 3 SE +/- 8956.45, N = 3 SE +/- 906.56, N = 3 SE +/- 6904.71, N = 7 SE +/- 4933.88, N = 3 2762647 2719388 2701767 2456511 2136850 1977325 1947836 1721854 1475280 1208466 1021990 883965 776880 623272 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 7662 EPYC 7702 EPYC 7642 EPYC 7552 EPYC 7502P EPYC 7542 EPYC 7532 EPYC 7402P EPYC 7282 EPYC 7302P EPYC 7272 EPYC 7232P EPYC 7F52 EPYC 7F32 4K 8K 12K 16K 20K 16672.76 16026.57 15813.47 15696.63 14373.63 13548.39 13352.11 12779.06 11127.27 10725.42 9696.42 7399.84 7194.42 5966.03
Result Confidence
OpenBenchmarking.org Records/s, More Is Better ebizzy 0.3 EPYC 7662 EPYC 7642 EPYC 7702 EPYC 7552 EPYC 7542 EPYC 7532 EPYC 7502P EPYC 7402P EPYC 7F52 EPYC 7302P EPYC 7282 EPYC 7272 EPYC 7F32 EPYC 7232P 500K 1000K 1500K 2000K 2500K Min: 2508914 / Avg: 2762646.92 / Max: 2926207 Min: 2645052 / Avg: 2719388 / Max: 2757214 Min: 2510210 / Avg: 2701767.07 / Max: 2845248 Min: 2420178 / Avg: 2456510.67 / Max: 2501931 Min: 2127912 / Avg: 2136850 / Max: 2153748 Min: 1951917 / Avg: 1977324.67 / Max: 2005917 Min: 1926759 / Avg: 1947835.67 / Max: 1961193 Min: 1691610 / Avg: 1721854 / Max: 1744199 Min: 1461618 / Avg: 1475280 / Max: 1485575 Min: 1192406 / Avg: 1208466.33 / Max: 1217652 Min: 1009030 / Avg: 1021990 / Max: 1039179 Min: 882270 / Avg: 883965 / Max: 885370 Min: 747575 / Avg: 776880.43 / Max: 796470 Min: 616705 / Avg: 623272 / Max: 632934 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 7702 EPYC 7662 EPYC 7642 EPYC 7552 EPYC 7542 EPYC 7502P EPYC 7532 EPYC 7402P EPYC 7F52 EPYC 7302P EPYC 7282 EPYC 7272 EPYC 7F32 EPYC 7232P 8 16 24 32 40 SE +/- 0.02278, N = 6 SE +/- 0.02077, N = 6 SE +/- 0.03455, N = 5 SE +/- 0.04134, N = 5 SE +/- 0.02895, N = 5 SE +/- 0.00983, N = 5 SE +/- 0.03618, N = 5 SE +/- 0.02622, N = 4 SE +/- 0.03705, N = 4 SE +/- 0.02745, N = 3 SE +/- 0.03890, N = 3 SE +/- 0.03918, N = 3 SE +/- 0.01111, N = 3 SE +/- 0.03115, N = 3 7.50706 7.55093 8.56828 8.71953 9.92849 10.57400 10.81310 12.26230 14.13270 16.61750 17.65420 21.99580 26.51610 32.53880 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 7702 EPYC 7662 EPYC 7642 EPYC 7552 EPYC 7542 EPYC 7502P EPYC 7532 EPYC 7402P EPYC 7F52 EPYC 7302P EPYC 7282 EPYC 7272 EPYC 7F32 EPYC 7232P 7 14 21 28 35 Min: 7.46 / Avg: 7.51 / Max: 7.59 Min: 7.5 / Avg: 7.55 / Max: 7.63 Min: 8.43 / Avg: 8.57 / Max: 8.61 Min: 8.63 / Avg: 8.72 / Max: 8.86 Min: 9.86 / Avg: 9.93 / Max: 10.01 Min: 10.56 / Avg: 10.57 / Max: 10.61 Min: 10.71 / Avg: 10.81 / Max: 10.91 Min: 12.21 / Avg: 12.26 / Max: 12.33 Min: 14.08 / Avg: 14.13 / Max: 14.23 Min: 16.56 / Avg: 16.62 / Max: 16.65 Min: 17.6 / Avg: 17.65 / Max: 17.73 Min: 21.93 / Avg: 22 / Max: 22.07 Min: 26.5 / Avg: 26.52 / Max: 26.54 Min: 32.48 / Avg: 32.54 / Max: 32.59 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 7662 EPYC 7702 EPYC 7642 EPYC 7552 EPYC 7542 EPYC 7502P EPYC 7532 EPYC 7402P EPYC 7F52 EPYC 7302P EPYC 7282 EPYC 7272 EPYC 7F32 EPYC 7232P 50K 100K 150K 200K 250K SE +/- 174.48, N = 3 SE +/- 39.50, N = 3 SE +/- 111.10, N = 3 SE +/- 74.34, N = 3 SE +/- 77.46, N = 3 SE +/- 126.18, N = 3 SE +/- 39.58, N = 3 SE +/- 6.99, N = 3 SE +/- 132.22, N = 3 SE +/- 25.85, N = 3 SE +/- 38.26, N = 3 SE +/- 82.39, N = 3 SE +/- 44.74, N = 3 SE +/- 202.36, N = 3 56195.5 61679.6 65104.4 68430.4 70622.9 75080.0 77264.7 93404.1 107391.0 123947.0 129293.0 173807.0 201258.0 242480.0
Result Confidence
OpenBenchmarking.org Microseconds, Fewer Is Better TensorFlow Lite 2020-08-23 Model: SqueezeNet EPYC 7662 EPYC 7702 EPYC 7642 EPYC 7552 EPYC 7542 EPYC 7502P EPYC 7532 EPYC 7402P EPYC 7F52 EPYC 7302P EPYC 7282 EPYC 7272 EPYC 7F32 EPYC 7232P 40K 80K 120K 160K 200K Min: 55903.9 / Avg: 56195.5 / Max: 56507.3 Min: 61602.1 / Avg: 61679.57 / Max: 61731.7 Min: 64904.3 / Avg: 65104.43 / Max: 65288.1 Min: 68340.5 / Avg: 68430.4 / Max: 68577.9 Min: 70510.4 / Avg: 70622.9 / Max: 70771.4 Min: 74862.2 / Avg: 75080 / Max: 75299.3 Min: 77193.3 / Avg: 77264.7 / Max: 77330 Min: 93391.7 / Avg: 93404.1 / Max: 93415.9 Min: 107127 / Avg: 107390.67 / Max: 107540 Min: 123895 / Avg: 123946.67 / Max: 123974 Min: 129222 / Avg: 129293.33 / Max: 129353 Min: 173701 / Avg: 173806.67 / Max: 173969 Min: 201180 / Avg: 201257.67 / Max: 201335 Min: 242075 / Avg: 242479.67 / Max: 242688
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 7662 EPYC 7702 EPYC 7642 EPYC 7552 EPYC 7542 EPYC 7502P EPYC 7532 EPYC 7402P EPYC 7F52 EPYC 7282 EPYC 7302P EPYC 7272 EPYC 7F32 EPYC 7232P 3 6 9 12 15 SE +/- 0.01113, N = 9 SE +/- 0.00885, N = 9 SE +/- 0.06689, N = 15 SE +/- 0.01129, N = 9 SE +/- 0.00498, N = 9 SE +/- 0.00918, N = 9 SE +/- 0.00744, N = 8 SE +/- 0.01244, N = 7 SE +/- 0.01335, N = 7 SE +/- 0.01670, N = 7 SE +/- 0.00686, N = 6 SE +/- 0.01455, N = 5 SE +/- 0.02852, N = 5 SE +/- 0.02902, N = 4 2.80142 2.88175 3.19889 3.31262 3.47096 3.56555 3.70234 5.71426 5.84607 6.21815 6.36513 9.83106 10.90090 11.96540 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 7662 EPYC 7702 EPYC 7642 EPYC 7552 EPYC 7542 EPYC 7502P EPYC 7532 EPYC 7402P EPYC 7F52 EPYC 7282 EPYC 7302P EPYC 7272 EPYC 7F32 EPYC 7232P 3 6 9 12 15 Min: 2.77 / Avg: 2.8 / Max: 2.88 Min: 2.85 / Avg: 2.88 / Max: 2.93 Min: 2.55 / Avg: 3.2 / Max: 3.35 Min: 3.27 / Avg: 3.31 / Max: 3.37 Min: 3.44 / Avg: 3.47 / Max: 3.49 Min: 3.5 / Avg: 3.57 / Max: 3.61 Min: 3.66 / Avg: 3.7 / Max: 3.73 Min: 5.67 / Avg: 5.71 / Max: 5.76 Min: 5.8 / Avg: 5.85 / Max: 5.89 Min: 6.17 / Avg: 6.22 / Max: 6.29 Min: 6.35 / Avg: 6.37 / Max: 6.39 Min: 9.79 / Avg: 9.83 / Max: 9.88 Min: 10.84 / Avg: 10.9 / Max: 11 Min: 11.89 / Avg: 11.97 / Max: 12.03 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 7662 EPYC 7702 EPYC 7552 EPYC 7642 EPYC 7542 EPYC 7502P EPYC 7532 EPYC 7402P EPYC 7F52 EPYC 7282 EPYC 7302P EPYC 7F32 EPYC 7272 EPYC 7232P 0.7261 1.4522 2.1783 2.9044 3.6305 SE +/- 0.001641, N = 13 SE +/- 0.002056, N = 13 SE +/- 0.001391, N = 13 SE +/- 0.001666, N = 13 SE +/- 0.005531, N = 12 SE +/- 0.006410, N = 12 SE +/- 0.006800, N = 12 SE +/- 0.003909, N = 12 SE +/- 0.007208, N = 11 SE +/- 0.005522, N = 11 SE +/- 0.010317, N = 11 SE +/- 0.019546, N = 10 SE +/- 0.006375, N = 9 SE +/- 0.016438, N = 9 0.762238 0.773474 0.890726 0.902611 1.134961 1.149282 1.256882 1.561688 1.715944 1.783589 1.873804 2.796277 2.965136 3.227103 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 7662 EPYC 7702 EPYC 7552 EPYC 7642 EPYC 7542 EPYC 7502P EPYC 7532 EPYC 7402P EPYC 7F52 EPYC 7282 EPYC 7302P EPYC 7F32 EPYC 7272 EPYC 7232P 2 4 6 8 10 Min: 0.75 / Avg: 0.76 / Max: 0.77 Min: 0.76 / Avg: 0.77 / Max: 0.79 Min: 0.88 / Avg: 0.89 / Max: 0.9 Min: 0.89 / Avg: 0.9 / Max: 0.91 Min: 1.11 / Avg: 1.13 / Max: 1.17 Min: 1.12 / Avg: 1.15 / Max: 1.18 Min: 1.22 / Avg: 1.26 / Max: 1.3 Min: 1.54 / Avg: 1.56 / Max: 1.59 Min: 1.66 / Avg: 1.72 / Max: 1.74 Min: 1.76 / Avg: 1.78 / Max: 1.82 Min: 1.83 / Avg: 1.87 / Max: 1.93 Min: 2.71 / Avg: 2.8 / Max: 2.88 Min: 2.92 / Avg: 2.97 / Max: 2.99 Min: 3.17 / Avg: 3.23 / Max: 3.29 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 7642 EPYC 7542 EPYC 7662 EPYC 7552 EPYC 7502P EPYC 7532 EPYC 7702 EPYC 7402P EPYC 7F52 EPYC 7302P EPYC 7282 EPYC 7272 EPYC 7F32 EPYC 7232P 0.4541 0.9082 1.3623 1.8164 2.2705 SE +/- 0.003528, N = 4 SE +/- 0.000738, N = 4 SE +/- 0.005359, N = 5 SE +/- 0.004962, N = 15 SE +/- 0.000902, N = 4 SE +/- 0.005528, N = 6 SE +/- 0.002887, N = 4 SE +/- 0.000660, N = 4 SE +/- 0.001140, N = 4 SE +/- 0.000863, N = 4 SE +/- 0.000258, N = 4 SE +/- 0.000447, N = 4 SE +/- 0.001580, N = 4 SE +/- 0.005714, N = 4 0.484219 0.500521 0.517023 0.533961 0.537636 0.553444 0.587443 0.592308 0.660419 0.802272 0.875749 1.093440 1.160170 2.018380 MIN: 0.46 MIN: 0.48 MIN: 0.47 MIN: 0.49 MIN: 0.51 MIN: 0.49 MIN: 0.54 MIN: 0.56 MIN: 0.62 MIN: 0.72 MIN: 0.74 MIN: 0.96 MIN: 1.13 MIN: 1.95 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 7642 EPYC 7542 EPYC 7662 EPYC 7552 EPYC 7502P EPYC 7532 EPYC 7702 EPYC 7402P EPYC 7F52 EPYC 7302P EPYC 7282 EPYC 7272 EPYC 7F32 EPYC 7232P 2 4 6 8 10 Min: 0.48 / Avg: 0.48 / Max: 0.49 Min: 0.5 / Avg: 0.5 / Max: 0.5 Min: 0.5 / Avg: 0.52 / Max: 0.53 Min: 0.51 / Avg: 0.53 / Max: 0.57 Min: 0.54 / Avg: 0.54 / Max: 0.54 Min: 0.54 / Avg: 0.55 / Max: 0.58 Min: 0.58 / Avg: 0.59 / Max: 0.6 Min: 0.59 / Avg: 0.59 / Max: 0.59 Min: 0.66 / Avg: 0.66 / Max: 0.66 Min: 0.8 / Avg: 0.8 / Max: 0.8 Min: 0.88 / Avg: 0.88 / Max: 0.88 Min: 1.09 / Avg: 1.09 / Max: 1.09 Min: 1.16 / Avg: 1.16 / Max: 1.16 Min: 2 / Avg: 2.02 / Max: 2.03 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 7662 EPYC 7702 EPYC 7642 EPYC 7552 EPYC 7542 EPYC 7532 EPYC 7502P EPYC 7402P EPYC 7F52 EPYC 7302P EPYC 7282 EPYC 7272 EPYC 7F32 EPYC 7232P 5 10 15 20 25 SE +/- 0.301, N = 15 SE +/- 0.257, N = 15 SE +/- 0.291, N = 15 SE +/- 0.286, N = 15 SE +/- 0.252, N = 15 SE +/- 0.178, N = 15 SE +/- 0.286, N = 15 SE +/- 0.089, N = 15 SE +/- 0.028, N = 11 SE +/- 0.024, N = 10 SE +/- 0.026, N = 10 SE +/- 0.008, N = 9 SE +/- 0.003, N = 9 SE +/- 0.002, N = 8 21.763 19.997 19.328 18.506 16.564 16.265 15.685 14.038 11.521 10.374 9.685 7.582 6.470 5.237 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 7662 EPYC 7542 EPYC 7552 EPYC 7642 EPYC 7502P EPYC 7702 EPYC 7402P EPYC 7532 EPYC 7282 EPYC 7302P EPYC 7272 EPYC 7F52 EPYC 7232P EPYC 7F32 0.0653 0.1306 0.1959 0.2612 0.3265 0.29 0.26 0.26 0.25 0.25 0.25 0.23 0.22 0.18 0.18 0.15 0.14 0.11 0.10
Result Confidence
OpenBenchmarking.org ns/day, More Is Better LAMMPS Molecular Dynamics Simulator 29Oct2020 Model: Rhodopsin Protein EPYC 7662 EPYC 7702 EPYC 7642 EPYC 7552 EPYC 7542 EPYC 7532 EPYC 7502P EPYC 7402P EPYC 7F52 EPYC 7302P EPYC 7282 EPYC 7272 EPYC 7F32 EPYC 7232P 5 10 15 20 25 Min: 20.67 / Avg: 21.76 / Max: 24.47 Min: 19.07 / Avg: 20 / Max: 22.21 Min: 18.26 / Avg: 19.33 / Max: 21.71 Min: 17.37 / Avg: 18.51 / Max: 20.7 Min: 14.32 / Avg: 16.56 / Max: 18.32 Min: 14.97 / Avg: 16.27 / Max: 17.08 Min: 13.34 / Avg: 15.69 / Max: 17.35 Min: 13.39 / Avg: 14.04 / Max: 14.46 Min: 11.4 / Avg: 11.52 / Max: 11.65 Min: 10.19 / Avg: 10.37 / Max: 10.46 Min: 9.59 / Avg: 9.69 / Max: 9.82 Min: 7.55 / Avg: 7.58 / Max: 7.61 Min: 6.45 / Avg: 6.47 / Max: 6.49 Min: 5.23 / Avg: 5.24 / Max: 5.25 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 7662 EPYC 7702 EPYC 7552 EPYC 7542 EPYC 7502P EPYC 7532 EPYC 7402P EPYC 7302P EPYC 7282 EPYC 7F52 EPYC 7272 EPYC 7F32 EPYC 7232P 4K 8K 12K 16K 20K SE +/- 64.33, N = 3 SE +/- 57.10, N = 3 SE +/- 24.65, N = 3 SE +/- 32.93, N = 3 SE +/- 30.09, N = 3 SE +/- 125.44, N = 9 SE +/- 16.45, N = 3 SE +/- 6.53, N = 3 SE +/- 16.90, N = 3 SE +/- 17.97, N = 3 SE +/- 8.24, N = 3 SE +/- 13.57, N = 3 SE +/- 24.34, N = 3 19990.75 19577.03 18192.32 17266.21 16396.57 15568.24 13570.83 9499.33 9134.72 8415.19 7332.82 5638.53 4965.96 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 7662 EPYC 7502P EPYC 7552 EPYC 7702 EPYC 7542 EPYC 7532 EPYC 7282 EPYC 7402P EPYC 7302P EPYC 7272 EPYC 7232P EPYC 7F32 EPYC 7F52 30 60 90 120 150 115.18 114.89 110.23 109.94 104.78 98.20 93.40 92.04 79.41 75.36 67.53 51.33 42.43
Result Confidence
OpenBenchmarking.org Bogo Ops/s, More Is Better Stress-NG 0.11.07 Test: Socket Activity EPYC 7662 EPYC 7702 EPYC 7552 EPYC 7542 EPYC 7502P EPYC 7532 EPYC 7402P EPYC 7302P EPYC 7282 EPYC 7F52 EPYC 7272 EPYC 7F32 EPYC 7232P 3K 6K 9K 12K 15K Min: 19911.11 / Avg: 19990.75 / Max: 20118.07 Min: 19482.9 / Avg: 19577.03 / Max: 19680.11 Min: 18145.03 / Avg: 18192.32 / Max: 18228.03 Min: 17206.64 / Avg: 17266.21 / Max: 17320.33 Min: 16363.28 / Avg: 16396.57 / Max: 16456.63 Min: 14571.02 / Avg: 15568.24 / Max: 15743.07 Min: 13539.78 / Avg: 13570.83 / Max: 13595.76 Min: 9488.78 / Avg: 9499.33 / Max: 9511.28 Min: 9104 / Avg: 9134.72 / Max: 9162.29 Min: 8394.92 / Avg: 8415.19 / Max: 8451.03 Min: 7316.76 / Avg: 7332.82 / Max: 7344.03 Min: 5624.62 / Avg: 5638.53 / Max: 5665.66 Min: 4920.56 / Avg: 4965.96 / Max: 5003.89 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 7662 EPYC 7702 EPYC 7642 EPYC 7552 EPYC 7532 EPYC 7542 EPYC 7502P EPYC 7402P EPYC 7F52 EPYC 7302P EPYC 7282 EPYC 7272 EPYC 7F32 EPYC 7232P 30 60 90 120 150 SE +/- 0.55, N = 3 SE +/- 1.22, N = 3 SE +/- 0.12, N = 3 SE +/- 0.15, N = 3 SE +/- 0.00, N = 3 SE +/- 0.15, N = 3 SE +/- 0.09, N = 3 SE +/- 0.09, N = 3 SE +/- 0.79, N = 3 SE +/- 0.03, N = 3 SE +/- 0.12, N = 3 SE +/- 0.06, N = 3 SE +/- 0.03, N = 3 SE +/- 0.06, N = 3 149.6 147.5 130.1 125.7 122.7 114.4 114.3 96.9 76.1 73.8 66.4 55.2 47.0 37.3 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 7542 EPYC 7502P EPYC 7662 EPYC 7552 EPYC 7702 EPYC 7642 EPYC 7402P EPYC 7532 EPYC 7282 EPYC 7302P EPYC 7272 EPYC 7F52 EPYC 7232P EPYC 7F32 0.3218 0.6436 0.9654 1.2872 1.609 1.43 1.38 1.38 1.33 1.31 1.24 1.20 1.17 1.01 1.00 0.89 0.69 0.66 0.63
Result Confidence
OpenBenchmarking.org MB/s, More Is Better Zstd Compression 1.4.5 Compression Level: 19 EPYC 7662 EPYC 7702 EPYC 7642 EPYC 7552 EPYC 7532 EPYC 7542 EPYC 7502P EPYC 7402P EPYC 7F52 EPYC 7302P EPYC 7282 EPYC 7272 EPYC 7F32 EPYC 7232P 30 60 90 120 150 Min: 148.7 / Avg: 149.6 / Max: 150.6 Min: 145.1 / Avg: 147.53 / Max: 148.8 Min: 129.9 / Avg: 130.1 / Max: 130.3 Min: 125.4 / Avg: 125.67 / Max: 125.9 Min: 122.7 / Avg: 122.7 / Max: 122.7 Min: 114.2 / Avg: 114.4 / Max: 114.7 Min: 114.2 / Avg: 114.33 / Max: 114.5 Min: 96.8 / Avg: 96.93 / Max: 97.1 Min: 74.9 / Avg: 76.13 / Max: 77.6 Min: 73.8 / Avg: 73.83 / Max: 73.9 Min: 66.2 / Avg: 66.4 / Max: 66.6 Min: 55.1 / Avg: 55.2 / Max: 55.3 Min: 47 / Avg: 47.03 / Max: 47.1 Min: 37.2 / Avg: 37.3 / Max: 37.4 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 7662 EPYC 7702 EPYC 7552 EPYC 7532 EPYC 7542 EPYC 7502P EPYC 7402P EPYC 7F52 EPYC 7302P EPYC 7282 EPYC 7272 2K 4K 6K 8K 10K 2220.7 2247.0 2716.7 3653.6 3653.9 3678.8 4709.5 5684.6 6676.4 7056.0 8844.1 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 7702 EPYC 7662 EPYC 7642 EPYC 7552 EPYC 7532 EPYC 7F52 EPYC 7542 EPYC 7502P EPYC 7402P EPYC 7302P EPYC 7F32 EPYC 7282 EPYC 7272 EPYC 7232P 600 1200 1800 2400 3000 SE +/- 26.03, N = 3 SE +/- 29.49, N = 9 SE +/- 37.70, N = 9 SE +/- 31.31, N = 9 SE +/- 20.90, N = 3 SE +/- 17.43, N = 5 SE +/- 9.84, N = 3 SE +/- 14.82, N = 9 SE +/- 5.90, N = 3 SE +/- 12.27, N = 9 SE +/- 16.37, N = 9 SE +/- 11.49, N = 9 SE +/- 11.79, N = 9 SE +/- 8.88, N = 3 2686 2408 2311 1927 1769 1699 1617 1539 1439 1233 1104 1051 925 681 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 7702 EPYC 7662 EPYC 7642 EPYC 7552 EPYC 7532 EPYC 7502P EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7542 EPYC 7272 EPYC 7F32 EPYC 7232P EPYC 7F52 4 8 12 16 20 15.06 14.75 13.41 12.55 11.26 11.09 11.06 10.97 10.56 10.30 10.05 8.98 8.61 8.39
Result Confidence
OpenBenchmarking.org Nodes Per Second, More Is Better LeelaChessZero 0.26 Backend: Eigen EPYC 7702 EPYC 7662 EPYC 7642 EPYC 7552 EPYC 7532 EPYC 7F52 EPYC 7542 EPYC 7502P EPYC 7402P EPYC 7302P EPYC 7F32 EPYC 7282 EPYC 7272 EPYC 7232P 500 1000 1500 2000 2500 Min: 2634 / Avg: 2685.67 / Max: 2717 Min: 2310 / Avg: 2408 / Max: 2551 Min: 2112 / Avg: 2311.33 / Max: 2527 Min: 1773 / Avg: 1926.89 / Max: 2050 Min: 1729 / Avg: 1769.33 / Max: 1799 Min: 1639 / Avg: 1699.2 / Max: 1747 Min: 1597 / Avg: 1616.67 / Max: 1627 Min: 1454 / Avg: 1538.78 / Max: 1593 Min: 1432 / Avg: 1439.33 / Max: 1451 Min: 1194 / Avg: 1232.78 / Max: 1292 Min: 1024 / Avg: 1103.67 / Max: 1176 Min: 1008 / Avg: 1051.22 / Max: 1107 Min: 870 / Avg: 924.56 / Max: 993 Min: 663 / Avg: 680.67 / Max: 691 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 7662 EPYC 7702 EPYC 7642 EPYC 7552 EPYC 7542 EPYC 7502P EPYC 7532 EPYC 7402P EPYC 7F52 EPYC 7302P EPYC 7282 EPYC 7272 EPYC 7F32 EPYC 7232P 60 120 180 240 300 67.33 67.74 70.49 73.33 81.83 87.51 89.01 105.69 118.48 149.34 151.86 195.08 225.09 265.54
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 7662 EPYC 7702 EPYC 7552 EPYC 7542 EPYC 7502P EPYC 7532 EPYC 7402P EPYC 7F52 EPYC 7302P EPYC 7282 EPYC 7272 EPYC 7F32 EPYC 7232P 16 32 48 64 80 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 +/- 0.01, N = 3 SE +/- 0.00, N = 3 SE +/- 0.03, N = 3 SE +/- 0.01, N = 3 SE +/- 0.01, N = 3 SE +/- 0.01, N = 3 18.66 18.87 20.80 23.97 25.28 25.88 29.16 33.80 39.75 41.24 51.77 60.40 73.43 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 7662 EPYC 7702 EPYC 7552 EPYC 7542 EPYC 7502P EPYC 7532 EPYC 7402P EPYC 7F52 EPYC 7302P EPYC 7282 EPYC 7272 EPYC 7F32 EPYC 7232P 14 28 42 56 70 Min: 18.65 / Avg: 18.66 / Max: 18.66 Min: 18.86 / Avg: 18.87 / Max: 18.88 Min: 20.77 / Avg: 20.8 / Max: 20.82 Min: 23.96 / Avg: 23.97 / Max: 23.98 Min: 25.27 / Avg: 25.28 / Max: 25.31 Min: 25.87 / Avg: 25.88 / Max: 25.91 Min: 29.15 / Avg: 29.16 / Max: 29.17 Min: 33.79 / Avg: 33.8 / Max: 33.81 Min: 39.75 / Avg: 39.75 / Max: 39.76 Min: 41.2 / Avg: 41.24 / Max: 41.3 Min: 51.75 / Avg: 51.77 / Max: 51.78 Min: 60.39 / Avg: 60.4 / Max: 60.41 Min: 73.43 / Avg: 73.43 / Max: 73.44 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 7F32 EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7F52 EPYC 7402P EPYC 7502P EPYC 7542 EPYC 7532 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 30 60 90 120 150 SE +/- 0.30, N = 3 SE +/- 0.20, N = 3 SE +/- 0.04, N = 3 SE +/- 0.34, N = 3 SE +/- 0.51, N = 3 SE +/- 0.05, N = 3 SE +/- 0.47, N = 3 SE +/- 0.89, N = 3 SE +/- 1.20, N = 3 SE +/- 0.60, N = 11 SE +/- 2.91, N = 3 SE +/- 1.44, N = 12 SE +/- 1.58, N = 9 SE +/- 0.92, N = 9 31.16 32.16 34.24 40.27 41.35 46.30 51.09 60.77 61.29 66.90 91.90 93.95 115.48 119.33 MIN: 30.33 / MAX: 33.9 MIN: 31.34 / MAX: 32.97 MIN: 33.82 / MAX: 47.56 MIN: 38.44 / MAX: 167.34 MIN: 40.02 / MAX: 44.02 MIN: 45.45 / MAX: 121.75 MIN: 49.4 / MAX: 53.35 MIN: 58.26 / MAX: 140.56 MIN: 59.46 / MAX: 72.41 MIN: 63.42 / MAX: 212.32 MIN: 86.84 / MAX: 102.42 MIN: 86.48 / MAX: 1086.99 MIN: 104.38 / MAX: 272.84 MIN: 110.56 / MAX: 268.86 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 7F32 EPYC 7272 EPYC 7282 EPYC 7302P EPYC 7F52 EPYC 7402P EPYC 7502P EPYC 7542 EPYC 7532 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 20 40 60 80 100 Min: 30.61 / Avg: 31.16 / Max: 31.62 Min: 31.76 / Avg: 32.16 / Max: 32.37 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: 46.2 / Avg: 46.3 / Max: 46.36 Min: 50.14 / Avg: 51.09 / Max: 51.59 Min: 59.06 / Avg: 60.77 / Max: 62.06 Min: 60 / Avg: 61.29 / Max: 63.69 Min: 64.25 / Avg: 66.9 / Max: 69.82 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 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 7662 EPYC 7702 EPYC 7642 EPYC 7552 EPYC 7542 EPYC 7502P EPYC 7532 EPYC 7402P EPYC 7F52 EPYC 7302P EPYC 7282 EPYC 7272 EPYC 7F32 EPYC 7232P 20 40 60 80 100 SE +/- 0.32, N = 5 SE +/- 0.27, N = 5 SE +/- 0.16, N = 5 SE +/- 0.20, N = 5 SE +/- 0.18, N = 6 SE +/- 0.25, N = 6 SE +/- 0.17, N = 6 SE +/- 0.03, N = 6 SE +/- 0.21, N = 5 SE +/- 0.17, N = 5 SE +/- 0.09, N = 5 SE +/- 0.11, N = 4 SE +/- 0.03, N = 4 SE +/- 0.07, N = 4 83.40 79.82 63.21 62.40 59.94 57.32 56.53 54.87 42.84 37.04 35.38 30.38 26.13 21.76 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 7662 EPYC 7702 EPYC 7552 EPYC 7542 EPYC 7502P EPYC 7642 EPYC 7402P EPYC 7532 EPYC 7282 EPYC 7302P EPYC 7272 EPYC 7232P EPYC 7F52 EPYC 7F32 0.2003 0.4006 0.6009 0.8012 1.0015 0.89 0.83 0.69 0.68 0.68 0.62 0.61 0.56 0.49 0.44 0.41 0.33 0.32 0.28
Result Confidence
OpenBenchmarking.org Frames Per Second, More Is Better SVT-AV1 0.8 Encoder Mode: Enc Mode 8 - Input: 1080p EPYC 7662 EPYC 7702 EPYC 7642 EPYC 7552 EPYC 7542 EPYC 7502P EPYC 7532 EPYC 7402P EPYC 7F52 EPYC 7302P EPYC 7282 EPYC 7272 EPYC 7F32 EPYC 7232P 16 32 48 64 80 Min: 82.2 / Avg: 83.4 / Max: 84.06 Min: 79.13 / Avg: 79.82 / Max: 80.5 Min: 62.71 / Avg: 63.21 / Max: 63.66 Min: 61.9 / Avg: 62.4 / Max: 62.94 Min: 59.31 / Avg: 59.94 / Max: 60.53 Min: 56.32 / Avg: 57.32 / Max: 57.97 Min: 56.08 / Avg: 56.53 / Max: 57.07 Min: 54.76 / Avg: 54.87 / Max: 54.97 Min: 42.28 / Avg: 42.84 / Max: 43.39 Min: 36.48 / Avg: 37.04 / Max: 37.5 Min: 35.07 / Avg: 35.38 / Max: 35.57 Min: 30.14 / Avg: 30.38 / Max: 30.6 Min: 26.07 / Avg: 26.13 / Max: 26.22 Min: 21.59 / Avg: 21.76 / Max: 21.91 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 7F32 EPYC 7F52 EPYC 7272 EPYC 7282 EPYC 7402P EPYC 7232P EPYC 7542 EPYC 7502P EPYC 7552 EPYC 7642 EPYC 7302P EPYC 7662 EPYC 7702 EPYC 7532 30 60 90 120 150 SE +/- 0.15, N = 3 SE +/- 0.24, N = 3 SE +/- 0.24, N = 3 SE +/- 0.21, N = 3 SE +/- 0.03, N = 3 SE +/- 0.88, N = 3 SE +/- 0.29, N = 3 SE +/- 0.22, N = 3 SE +/- 0.29, N = 3 SE +/- 0.83, N = 3 SE +/- 0.11, N = 3 SE +/- 0.63, N = 3 SE +/- 0.77, N = 3 SE +/- 0.28, N = 3 34.04 49.01 51.65 62.29 65.42 75.43 75.44 76.19 93.48 95.40 95.77 109.30 110.47 128.29 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 7F32 EPYC 7F52 EPYC 7272 EPYC 7282 EPYC 7402P EPYC 7232P EPYC 7542 EPYC 7502P EPYC 7552 EPYC 7642 EPYC 7302P EPYC 7662 EPYC 7702 EPYC 7532 20 40 60 80 100 Min: 33.82 / Avg: 34.04 / Max: 34.32 Min: 48.58 / Avg: 49.01 / Max: 49.42 Min: 51.36 / Avg: 51.65 / Max: 52.13 Min: 61.91 / Avg: 62.29 / Max: 62.65 Min: 65.38 / Avg: 65.42 / Max: 65.48 Min: 73.67 / Avg: 75.43 / Max: 76.37 Min: 75.01 / Avg: 75.44 / Max: 76 Min: 75.76 / Avg: 76.19 / Max: 76.51 Min: 93.04 / Avg: 93.48 / Max: 94.02 Min: 93.75 / Avg: 95.4 / Max: 96.31 Min: 95.59 / Avg: 95.77 / Max: 95.96 Min: 108.54 / Avg: 109.3 / Max: 110.55 Min: 109.25 / Avg: 110.47 / Max: 111.89 Min: 127.98 / Avg: 128.29 / Max: 128.85 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 7F52 EPYC 7302P EPYC 7532 EPYC 7402P EPYC 7F32 EPYC 7642 EPYC 7282 EPYC 7502P EPYC 7542 EPYC 7272 EPYC 7552 EPYC 7662 EPYC 7702 EPYC 7232P 0.4004 0.8008 1.2012 1.6016 2.002 SE +/- 0.002832, N = 5 SE +/- 0.001293, N = 5 SE +/- 0.002578, N = 5 SE +/- 0.003852, N = 5 SE +/- 0.006135, N = 5 SE +/- 0.002582, N = 5 SE +/- 0.003097, N = 5 SE +/- 0.001432, N = 5 SE +/- 0.003216, N = 5 SE +/- 0.003339, N = 5 SE +/- 0.005510, N = 5 SE +/- 0.000841, N = 5 SE +/- 0.001522, N = 5 SE +/- 0.002555, N = 5 0.489983 0.601288 0.641197 0.711317 0.798217 0.813280 0.816826 0.990316 1.000426 1.038950 1.132370 1.146010 1.162730 1.779470 MIN: 0.45 MIN: 0.56 MIN: 0.58 MIN: 0.66 MIN: 0.75 MIN: 0.76 MIN: 0.74 MIN: 0.95 MIN: 0.94 MIN: 0.95 MIN: 1.07 MIN: 1.09 MIN: 1.1 MIN: 1.6 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 7F52 EPYC 7302P EPYC 7532 EPYC 7402P EPYC 7F32 EPYC 7642 EPYC 7282 EPYC 7502P EPYC 7542 EPYC 7272 EPYC 7552 EPYC 7662 EPYC 7702 EPYC 7232P 2 4 6 8 10 Min: 0.48 / Avg: 0.49 / Max: 0.5 Min: 0.6 / Avg: 0.6 / Max: 0.6 Min: 0.63 / Avg: 0.64 / Max: 0.65 Min: 0.7 / Avg: 0.71 / Max: 0.72 Min: 0.79 / Avg: 0.8 / Max: 0.82 Min: 0.81 / Avg: 0.81 / Max: 0.82 Min: 0.81 / Avg: 0.82 / Max: 0.83 Min: 0.99 / Avg: 0.99 / Max: 1 Min: 0.99 / Avg: 1 / Max: 1.01 Min: 1.03 / Avg: 1.04 / Max: 1.05 Min: 1.11 / Avg: 1.13 / Max: 1.14 Min: 1.14 / Avg: 1.15 / Max: 1.15 Min: 1.16 / Avg: 1.16 / Max: 1.17 Min: 1.78 / Avg: 1.78 / Max: 1.79 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 7662 EPYC 7702 EPYC 7642 EPYC 7552 EPYC 7542 EPYC 7502P EPYC 7532 EPYC 7402P EPYC 7F52 EPYC 7302P EPYC 7282 EPYC 7272 EPYC 7F32 EPYC 7232P 20 40 60 80 100 SE +/- 0.28, N = 6 SE +/- 0.26, N = 7 SE +/- 0.30, N = 6 SE +/- 0.30, N = 6 SE +/- 0.41, N = 4 SE +/- 0.42, N = 4 SE +/- 0.42, N = 4 SE +/- 0.47, N = 4 SE +/- 0.43, N = 3 SE +/- 0.65, N = 4 SE +/- 0.75, N = 3 SE +/- 0.59, N = 3 SE +/- 0.46, N = 3 SE +/- 0.42, N = 3 27.98 28.13 30.08 30.21 34.55 36.39 36.85 41.50 46.91 53.40 57.91 69.61 79.66 101.09
Result Confidence
OpenBenchmarking.org Seconds, Fewer Is Better Timed Linux Kernel Compilation 5.4 Time To Compile EPYC 7662 EPYC 7702 EPYC 7642 EPYC 7552 EPYC 7542 EPYC 7502P EPYC 7532 EPYC 7402P EPYC 7F52 EPYC 7302P EPYC 7282 EPYC 7272 EPYC 7F32 EPYC 7232P 20 40 60 80 100 Min: 27.59 / Avg: 27.98 / Max: 29.37 Min: 27.79 / Avg: 28.13 / Max: 29.66 Min: 29.67 / Avg: 30.08 / Max: 31.58 Min: 29.87 / Avg: 30.21 / Max: 31.71 Min: 34.07 / Avg: 34.55 / Max: 35.78 Min: 35.93 / Avg: 36.39 / Max: 37.65 Min: 36.38 / Avg: 36.85 / Max: 38.1 Min: 40.71 / Avg: 41.5 / Max: 42.85 Min: 46.21 / Avg: 46.91 / Max: 47.7 Min: 52.39 / Avg: 53.4 / Max: 55.3 Min: 56.64 / Avg: 57.91 / Max: 59.25 Min: 68.52 / Avg: 69.61 / Max: 70.53 Min: 79.06 / Avg: 79.66 / Max: 80.57 Min: 100.61 / Avg: 101.09 / Max: 101.92
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 7702 EPYC 7662 EPYC 7642 EPYC 7552 EPYC 7F52 EPYC 7532 EPYC 7542 EPYC 7502P EPYC 7402P EPYC 7302P EPYC 7F32 EPYC 7282 EPYC 7272 EPYC 7232P 600 1200 1800 2400 3000 SE +/- 14.38, N = 3 SE +/- 41.44, N = 9 SE +/- 26.91, N = 3 SE +/- 27.18, N = 3 SE +/- 31.35, N = 9 SE +/- 22.27, N = 9 SE +/- 20.09, N = 3 SE +/- 23.71, N = 9 SE +/- 20.26, N = 3 SE +/- 13.76, N = 9 SE +/- 22.57, N = 9 SE +/- 3.71, N = 3 SE +/- 7.54, N = 3 SE +/- 4.36, N = 3 2699 2376 2203 1969 1758 1735 1666 1559 1521 1253 1052 1042 946 747 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 7702 EPYC 7662 EPYC 7642 EPYC 7552 EPYC 7502P EPYC 7532 EPYC 7302P EPYC 7402P EPYC 7282 EPYC 7542 EPYC 7272 EPYC 7232P EPYC 7F32 EPYC 7F52 4 8 12 16 20 14.95 14.58 12.86 12.82 11.37 11.33 11.29 11.26 11.09 10.83 10.33 9.44 8.98 8.60
Result Confidence
OpenBenchmarking.org Nodes Per Second, More Is Better LeelaChessZero 0.26 Backend: BLAS EPYC 7702 EPYC 7662 EPYC 7642 EPYC 7552 EPYC 7F52 EPYC 7532 EPYC 7542 EPYC 7502P EPYC 7402P EPYC 7302P EPYC 7F32 EPYC 7282 EPYC 7272 EPYC 7232P 500 1000 1500 2000 2500 Min: 2683 / Avg: 2699.33 / Max: 2728 Min: 2146 / Avg: 2376 / Max: 2558 Min: 2155 / Avg: 2203.33 / Max: 2248 Min: 1916 / Avg: 1969 / Max: 2006 Min: 1652 / Avg: 1758 / Max: 1943 Min: 1624 / Avg: 1734.78 / Max: 1815 Min: 1626 / Avg: 1665.67 / Max: 1691 Min: 1445 / Avg: 1559.33 / Max: 1649 Min: 1492 / Avg: 1521 / Max: 1560 Min: 1190 / Avg: 1253.33 / Max: 1313 Min: 958 / Avg: 1052.44 / Max: 1142 Min: 1035 / Avg: 1042.33 / Max: 1047 Min: 931 / Avg: 945.67 / Max: 956 Min: 739 / Avg: 747 / Max: 754 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 7642 EPYC 7552 EPYC 7402P EPYC 7F52 EPYC 7662 EPYC 7532 EPYC 7702 EPYC 7302P EPYC 7542 EPYC 7502P EPYC 7282 EPYC 7272 EPYC 7F32 EPYC 7232P 900 1800 2700 3600 4500 SE +/- 2.03, N = 3 SE +/- 1.92, N = 3 SE +/- 1.08, N = 3 SE +/- 6.65, N = 3 SE +/- 11.35, N = 3 SE +/- 5.23, N = 3 SE +/- 3.86, N = 3 SE +/- 0.38, N = 3 SE +/- 2.43, N = 3 SE +/- 2.18, N = 3 SE +/- 2.25, N = 3 SE +/- 3.17, N = 3 SE +/- 0.89, N = 3 SE +/- 1.97, N = 3 1210.04 1352.62 1674.66 2013.24 2230.18 2230.35 2296.53 2410.23 2721.87 2743.71 2834.09 3057.08 3345.67 4347.66 MIN: 1190.59 MIN: 1333.53 MIN: 1660.31 MIN: 1992.69 MIN: 2194.78 MIN: 2212.66 MIN: 2270.01 MIN: 2395.31 MIN: 2708.11 MIN: 2727.14 MIN: 2799.34 MIN: 3044.36 MIN: 3327 MIN: 4308.62 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: Recurrent Neural Network Training - Data Type: u8s8f32 - Engine: CPU EPYC 7642 EPYC 7552 EPYC 7402P EPYC 7F52 EPYC 7662 EPYC 7532 EPYC 7702 EPYC 7302P EPYC 7542 EPYC 7502P EPYC 7282 EPYC 7272 EPYC 7F32 EPYC 7232P 800 1600 2400 3200 4000 Min: 1206.71 / Avg: 1210.04 / Max: 1213.71 Min: 1350.2 / Avg: 1352.62 / Max: 1356.42 Min: 1672.87 / Avg: 1674.66 / Max: 1676.6 Min: 2003.33 / Avg: 2013.24 / Max: 2025.88 Min: 2212.51 / Avg: 2230.18 / Max: 2251.36 Min: 2221.2 / Avg: 2230.35 / Max: 2239.31 Min: 2288.81 / Avg: 2296.53 / Max: 2300.61 Min: 2409.5 / Avg: 2410.23 / Max: 2410.77 Min: 2718.51 / Avg: 2721.87 / Max: 2726.6 Min: 2741.09 / Avg: 2743.71 / Max: 2748.05 Min: 2829.71 / Avg: 2834.09 / Max: 2837.17 Min: 3051.79 / Avg: 3057.08 / Max: 3062.75 Min: 3344.19 / Avg: 3345.67 / Max: 3347.26 Min: 4343.96 / Avg: 4347.66 / Max: 4350.69 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 7642 EPYC 7552 EPYC 7402P EPYC 7F52 EPYC 7662 EPYC 7532 EPYC 7702 EPYC 7302P EPYC 7542 EPYC 7502P EPYC 7282 EPYC 7272 EPYC 7F32 EPYC 7232P 900 1800 2700 3600 4500 SE +/- 3.66, N = 3 SE +/- 1.28, N = 3 SE +/- 0.94, N = 3 SE +/- 0.63, N = 3 SE +/- 0.34, N = 3 SE +/- 5.96, N = 3 SE +/- 9.75, N = 3 SE +/- 3.71, N = 3 SE +/- 2.51, N = 3 SE +/- 4.79, N = 3 SE +/- 1.77, N = 3 SE +/- 0.81, N = 3 SE +/- 2.55, N = 3 SE +/- 4.35, N = 3 1211.54 1350.13 1673.31 1997.39 2203.16 2221.37 2314.36 2407.93 2716.54 2740.52 2835.35 3059.19 3348.06 4348.88 MIN: 1187.15 MIN: 1333.75 MIN: 1660.31 MIN: 1989.1 MIN: 2183.71 MIN: 2198.48 MIN: 2276.78 MIN: 2392.45 MIN: 2705.25 MIN: 2722.51 MIN: 2800.15 MIN: 3051.11 MIN: 3331.21 MIN: 4311.94 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 7642 EPYC 7552 EPYC 7402P EPYC 7F52 EPYC 7662 EPYC 7532 EPYC 7702 EPYC 7302P EPYC 7542 EPYC 7502P EPYC 7282 EPYC 7272 EPYC 7F32 EPYC 7232P 800 1600 2400 3200 4000 Min: 1207.18 / Avg: 1211.54 / Max: 1218.81 Min: 1347.63 / Avg: 1350.13 / Max: 1351.85 Min: 1671.47 / Avg: 1673.31 / Max: 1674.53 Min: 1996.27 / Avg: 1997.39 / Max: 1998.44 Min: 2202.51 / Avg: 2203.16 / Max: 2203.65 Min: 2213.13 / Avg: 2221.37 / Max: 2232.96 Min: 2296.67 / Avg: 2314.36 / Max: 2330.29 Min: 2401.58 / Avg: 2407.93 / Max: 2414.43 Min: 2713.68 / Avg: 2716.54 / Max: 2721.54 Min: 2731.74 / Avg: 2740.52 / Max: 2748.21 Min: 2831.82 / Avg: 2835.35 / Max: 2837.39 Min: 3057.83 / Avg: 3059.19 / Max: 3060.62 Min: 3342.99 / Avg: 3348.06 / Max: 3351.09 Min: 4341.28 / Avg: 4348.88 / Max: 4356.33 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 7642 EPYC 7552 EPYC 7402P EPYC 7F52 EPYC 7532 EPYC 7662 EPYC 7702 EPYC 7302P EPYC 7542 EPYC 7502P EPYC 7282 EPYC 7272 EPYC 7F32 EPYC 7232P 900 1800 2700 3600 4500 SE +/- 0.57, N = 3 SE +/- 1.32, N = 3 SE +/- 0.54, N = 3 SE +/- 2.05, N = 3 SE +/- 2.63, N = 3 SE +/- 8.27, N = 3 SE +/- 5.75, N = 3 SE +/- 2.99, N = 3 SE +/- 1.42, N = 3 SE +/- 5.60, N = 3 SE +/- 1.43, N = 3 SE +/- 1.59, N = 3 SE +/- 0.86, N = 3 SE +/- 5.10, N = 3 1213.58 1350.55 1672.24 2013.75 2214.79 2221.33 2306.33 2412.79 2718.68 2738.42 2836.68 3056.05 3345.10 4345.12 MIN: 1190.99 MIN: 1331.05 MIN: 1658.48 MIN: 1995.38 MIN: 2191.84 MIN: 2189.19 MIN: 2274.33 MIN: 2397.68 MIN: 2705.41 MIN: 2722.76 MIN: 2798.53 MIN: 3041.35 MIN: 3322.56 MIN: 4298.14 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 7642 EPYC 7552 EPYC 7402P EPYC 7F52 EPYC 7532 EPYC 7662 EPYC 7702 EPYC 7302P EPYC 7542 EPYC 7502P EPYC 7282 EPYC 7272 EPYC 7F32 EPYC 7232P 800 1600 2400 3200 4000 Min: 1212.83 / Avg: 1213.58 / Max: 1214.69 Min: 1347.94 / Avg: 1350.55 / Max: 1352.2 Min: 1671.4 / Avg: 1672.24 / Max: 1673.25 Min: 2010.58 / Avg: 2013.75 / Max: 2017.58 Min: 2209.9 / Avg: 2214.79 / Max: 2218.93 Min: 2206.05 / Avg: 2221.33 / Max: 2234.44 Min: 2294.83 / Avg: 2306.33 / Max: 2312.48 Min: 2408.58 / Avg: 2412.79 / Max: 2418.57 Min: 2716.43 / Avg: 2718.68 / Max: 2721.31 Min: 2731.04 / Avg: 2738.42 / Max: 2749.41 Min: 2834.78 / Avg: 2836.68 / Max: 2839.49 Min: 3053.73 / Avg: 3056.05 / Max: 3059.09 Min: 3343.83 / Avg: 3345.1 / Max: 3346.73 Min: 4339.98 / Avg: 4345.12 / Max: 4355.32 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 7662 EPYC 7642 EPYC 7552 EPYC 7702 EPYC 7502P EPYC 7542 EPYC 7532 EPYC 7402P EPYC 7F52 EPYC 7282 EPYC 7302P EPYC 7272 EPYC 7F32 EPYC 7232P 70K 140K 210K 280K 350K SE +/- 735.95, N = 3 SE +/- 768.33, N = 3 SE +/- 749.32, N = 3 SE +/- 166.32, N = 3 SE +/- 219.22, N = 3 SE +/- 344.84, N = 3 SE +/- 622.13, N = 3 SE +/- 607.97, N = 3 SE +/- 436.15, N = 3 SE +/- 203.74, N = 3 SE +/- 223.01, N = 3 SE +/- 175.05, N = 3 SE +/- 204.78, N = 3 333412 331791 331300 287115 259353 258759 253689 216427 172585 163535 163248 131583 100843 94371 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 7542 EPYC 7502P EPYC 7552 EPYC 7282 EPYC 7402P EPYC 7702 EPYC 7642 EPYC 7272 EPYC 7302P EPYC 7532 EPYC 7662 EPYC 7232P EPYC 7F52 EPYC 7F32 700 1400 2100 2800 3500 3314.42 3252.08 3130.89 3041.80 3035.68 2752.63 2741.84 2715.04 2693.49 2535.97 2353.30 2127.71 1704.39 1654.28
Result Confidence
OpenBenchmarking.org Op/s, More Is Better Facebook RocksDB 6.3.6 Test: Random Fill Sync EPYC 7662 EPYC 7642 EPYC 7552 EPYC 7702 EPYC 7502P EPYC 7542 EPYC 7532 EPYC 7402P EPYC 7F52 EPYC 7282 EPYC 7302P EPYC 7272 EPYC 7F32 EPYC 7232P 60K 120K 180K 240K 300K Min: 332027 / Avg: 333412 / Max: 334536 Min: 330767 / Avg: 331790.67 / Max: 333295 Min: 329808 / Avg: 331300 / Max: 332168 Min: 286867 / Avg: 287115 / Max: 287431 Min: 259071 / Avg: 259353.33 / Max: 259785 Min: 258263 / Avg: 258759 / Max: 259422 Min: 252478 / Avg: 253689 / Max: 254542 Min: 215402 / Avg: 216427 / Max: 217506 Min: 171773 / Avg: 172585 / Max: 173267 Min: 163163 / Avg: 163535 / Max: 163865 Min: 131216 / Avg: 131583 / Max: 131986 Min: 100631 / Avg: 100842.67 / Max: 101190 Min: 93963 / Avg: 94371 / Max: 94606 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 7662 EPYC 7702 EPYC 7642 EPYC 7552 EPYC 7542 EPYC 7532 EPYC 7502P EPYC 7402P EPYC 7F52 EPYC 7302P EPYC 7282 EPYC 7272 EPYC 7F32 EPYC 7232P 10 20 30 40 50 SE +/- 0.03, N = 4 SE +/- 0.04, N = 4 SE +/- 0.04, N = 4 SE +/- 0.03, N = 4 SE +/- 0.07, N = 4 SE +/- 0.02, N = 3 SE +/- 0.03, N = 3 SE +/- 0.05, N = 3 SE +/- 0.07, N = 3 SE +/- 0.01, N = 3 SE +/- 0.02, N = 3 SE +/- 0.03, N = 3 SE +/- 0.02, N = 3 SE +/- 0.03, N = 3 12.96 12.99 13.71 13.82 15.69 16.38 16.46 18.59 20.57 24.06 26.27 31.14 35.25 45.59
Result Confidence
OpenBenchmarking.org Seconds, Fewer Is Better Timed MPlayer Compilation 1.4 Time To Compile EPYC 7662 EPYC 7702 EPYC 7642 EPYC 7552 EPYC 7542 EPYC 7532 EPYC 7502P EPYC 7402P EPYC 7F52 EPYC 7302P EPYC 7282 EPYC 7272 EPYC 7F32 EPYC 7232P 9 18 27 36 45 Min: 12.87 / Avg: 12.96 / Max: 13.01 Min: 12.91 / Avg: 12.99 / Max: 13.09 Min: 13.64 / Avg: 13.71 / Max: 13.81 Min: 13.75 / Avg: 13.82 / Max: 13.87 Min: 15.6 / Avg: 15.69 / Max: 15.9 Min: 16.35 / Avg: 16.38 / Max: 16.42 Min: 16.42 / Avg: 16.46 / Max: 16.52 Min: 18.5 / Avg: 18.59 / Max: 18.68 Min: 20.43 / Avg: 20.57 / Max: 20.67 Min: 24.05 / Avg: 24.06 / Max: 24.07 Min: 26.23 / Avg: 26.27 / Max: 26.29 Min: 31.1 / Avg: 31.14 / Max: 31.21 Min: 35.21 / Avg: 35.25 / Max: 35.28 Min: 45.54 / Avg: 45.59 / Max: 45.62
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 7662 EPYC 7642 EPYC 7702 EPYC 7542 EPYC 7502P EPYC 7552 EPYC 7532 EPYC 7402P EPYC 7302P EPYC 7282 EPYC 7F52 EPYC 7272 EPYC 7F32 EPYC 7232P 30K 60K 90K 120K 150K SE +/- 1366.04, N = 15 SE +/- 641.51, N = 9 SE +/- 1033.87, N = 15 SE +/- 143.74, N = 9 SE +/- 160.95, N = 8 SE +/- 375.36, N = 8 SE +/- 154.09, N = 8 SE +/- 134.09, N = 10 SE +/- 80.44, N = 9 SE +/- 71.59, N = 9 SE +/- 308.97, N = 9 SE +/- 22.37, N = 11 SE +/- 37.94, N = 10 SE +/- 139.55, N = 9 155375.98 149967.74 145868.29 144583.87 136276.50 135838.12 135786.94 111563.84 84316.23 76796.04 71767.96 61838.52 54800.99 44242.98 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 7502P EPYC 7402P EPYC 7542 EPYC 7662 EPYC 7642 EPYC 7532 EPYC 7552 EPYC 7702 EPYC 7282 EPYC 7272 EPYC 7302P EPYC 7232P EPYC 7F32 EPYC 7F52 300 600 900 1200 1500 1457.28 1403.88 1396.95 1389.25 1309.22 1272.00 1263.45 1260.43 1200.32 1139.68 1116.04 839.58 805.56 604.59
Result Confidence
OpenBenchmarking.org MFLOPS, More Is Better FFTE 7.0 N=256, 3D Complex FFT Routine EPYC 7662 EPYC 7642 EPYC 7702 EPYC 7542 EPYC 7502P EPYC 7552 EPYC 7532 EPYC 7402P EPYC 7302P EPYC 7282 EPYC 7F52 EPYC 7272 EPYC 7F32 EPYC 7232P 30K 60K 90K 120K 150K Min: 151616.85 / Avg: 155375.98 / Max: 173605.93 Min: 148789.93 / Avg: 149967.74 / Max: 154980.74 Min: 143378.84 / Avg: 145868.29 / Max: 159924 Min: 143957.47 / Avg: 144583.87 / Max: 145193.47 Min: 135695.57 / Avg: 136276.5 / Max: 136949.63 Min: 133822.4 / Avg: 135838.12 / Max: 137193.41 Min: 135207.86 / Avg: 135786.94 / Max: 136435.92 Min: 110544.87 / Avg: 111563.84 / Max: 112037.3 Min: 83921.86 / Avg: 84316.23 / Max: 84643.19 Min: 76508.11 / Avg: 76796.04 / Max: 77062.73 Min: 70448.73 / Avg: 71767.96 / Max: 73371.09 Min: 61730.3 / Avg: 61838.52 / Max: 61950.09 Min: 54543.54 / Avg: 54800.99 / Max: 54955.54 Min: 43253.52 / Avg: 44242.98 / Max: 44735.98 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 7662 EPYC 7642 EPYC 7552 EPYC 7542 EPYC 7702 EPYC 7502P EPYC 7532 EPYC 7402P EPYC 7F52 EPYC 7302P EPYC 7282 EPYC 7272 EPYC 7F32 EPYC 7232P 4 8 12 16 20 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 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 +/- 0.02, N = 3 SE +/- 0.00, N = 3 SE +/- 0.01, N = 3 SE +/- 0.00, N = 3 16.44 15.94 15.50 14.94 14.94 13.97 13.65 11.22 10.66 9.15 8.61 6.49 5.73 4.72 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 7502P EPYC 7662 EPYC 7552 EPYC 7642 EPYC 7532 EPYC 7282 EPYC 7542 EPYC 7702 EPYC 7302P EPYC 7402P EPYC 7272 EPYC 7232P EPYC 7F32 EPYC 7F52 0.0225 0.045 0.0675 0.09 0.1125 0.10 0.10 0.10 0.09 0.09 0.09 0.09 0.09 0.08 0.08 0.07 0.06 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 7662 EPYC 7642 EPYC 7552 EPYC 7542 EPYC 7702 EPYC 7502P EPYC 7532 EPYC 7402P EPYC 7F52 EPYC 7302P EPYC 7282 EPYC 7272 EPYC 7F32 EPYC 7232P 4 8 12 16 20 Min: 16.42 / Avg: 16.44 / Max: 16.48 Min: 15.92 / Avg: 15.94 / Max: 15.97 Min: 15.49 / Avg: 15.5 / Max: 15.51 Min: 14.93 / Avg: 14.94 / Max: 14.95 Min: 14.93 / Avg: 14.94 / Max: 14.97 Min: 13.95 / Avg: 13.97 / Max: 13.98 Min: 13.61 / Avg: 13.65 / Max: 13.67 Min: 11.18 / Avg: 11.22 / Max: 11.24 Min: 10.64 / Avg: 10.66 / Max: 10.69 Min: 9.13 / Avg: 9.15 / Max: 9.17 Min: 8.58 / Avg: 8.61 / Max: 8.63 Min: 6.48 / Avg: 6.49 / Max: 6.49 Min: 5.71 / Avg: 5.73 / Max: 5.74 Min: 4.72 / Avg: 4.72 / Max: 4.73 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 7662 EPYC 7642 EPYC 7702 EPYC 7552 EPYC 7532 EPYC 7542 EPYC 7502P EPYC 7402P EPYC 7302P EPYC 7F52 EPYC 7282 EPYC 7F32 EPYC 7272 EPYC 7232P 60 120 180 240 300 SE +/- 0.05, N = 3 SE +/- 0.26, N = 3 SE +/- 0.15, N = 3 SE +/- 0.11, N = 3 SE +/- 0.02, N = 3 SE +/- 0.27, N = 3 SE +/- 0.20, N = 3 SE +/- 0.46, N = 3 SE +/- 0.19, N = 3 SE +/- 0.87, N = 3 SE +/- 0.09, N = 3 SE +/- 0.20, N = 3 SE +/- 0.37, N = 3 SE +/- 0.67, N = 3 78.39 79.98 81.06 86.74 93.24 103.30 105.67 116.41 139.15 165.41 177.91 200.41 205.89 271.16 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 7662 EPYC 7642 EPYC 7702 EPYC 7552 EPYC 7532 EPYC 7542 EPYC 7502P EPYC 7402P EPYC 7302P EPYC 7F52 EPYC 7282 EPYC 7F32 EPYC 7272 EPYC 7232P 50 100 150 200 250 Min: 78.29 / Avg: 78.39 / Max: 78.44 Min: 79.56 / Avg: 79.98 / Max: 80.47 Min: 80.78 / Avg: 81.06 / Max: 81.29 Min: 86.54 / Avg: 86.74 / Max: 86.91 Min: 93.21 / Avg: 93.24 / Max: 93.28 Min: 102.87 / Avg: 103.3 / Max: 103.79 Min: 105.35 / Avg: 105.67 / Max: 106.04 Min: 115.76 / Avg: 116.41 / Max: 117.3 Min: 138.85 / Avg: 139.15 / Max: 139.52 Min: 163.66 / Avg: 165.41 / Max: 166.3 Min: 177.8 / Avg: 177.9 / Max: 178.09 Min: 200.15 / Avg: 200.41 / Max: 200.81 Min: 205.17 / Avg: 205.89 / Max: 206.37 Min: 270.41 / Avg: 271.16 / Max: 272.49 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 7642 EPYC 7662 EPYC 7552 EPYC 7702 EPYC 7402P EPYC 7542 EPYC 7532 EPYC 7502P EPYC 7F52 EPYC 7302P EPYC 7282 EPYC 7272 EPYC 7F32 EPYC 7232P 2 4 6 8 10 SE +/- 0.01930, N = 15 SE +/- 0.02912, N = 15 SE +/- 0.00950, N = 9 SE +/- 0.03302, N = 15 SE +/- 0.00636, N = 9 SE +/- 0.00582, N = 9 SE +/- 0.00881, N = 9 SE +/- 0.00414, N = 9 SE +/- 0.00511, N = 9 SE +/- 0.00474, N = 9 SE +/- 0.00482, N = 9 SE +/- 0.00724, N = 9 SE +/- 0.00118, N = 9 SE +/- 0.00735, N = 9 2.40380 2.52363 2.55335 2.82015 3.34633 3.44118 3.60130 3.68833 3.92737 4.72608 5.08328 6.29135 6.46398 8.27184 MIN: 2.23 MIN: 2.25 MIN: 2.41 MIN: 2.49 MIN: 3.15 MIN: 3.03 MIN: 3.22 MIN: 3.26 MIN: 3.81 MIN: 4.52 MIN: 4.73 MIN: 6.07 MIN: 6.38 MIN: 8 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 7642 EPYC 7662 EPYC 7552 EPYC 7702 EPYC 7402P EPYC 7542 EPYC 7532 EPYC 7502P EPYC 7F52 EPYC 7302P EPYC 7282 EPYC 7272 EPYC 7F32 EPYC 7232P 3 6 9 12 15 Min: 2.29 / Avg: 2.4 / Max: 2.52 Min: 2.43 / Avg: 2.52 / Max: 2.85 Min: 2.52 / Avg: 2.55 / Max: 2.62 Min: 2.71 / Avg: 2.82 / Max: 3.12 Min: 3.33 / Avg: 3.35 / Max: 3.39 Min: 3.42 / Avg: 3.44 / Max: 3.47 Min: 3.57 / Avg: 3.6 / Max: 3.64 Min: 3.67 / Avg: 3.69 / Max: 3.7 Min: 3.89 / Avg: 3.93 / Max: 3.94 Min: 4.71 / Avg: 4.73 / Max: 4.74 Min: 5.06 / Avg: 5.08 / Max: 5.11 Min: 6.26 / Avg: 6.29 / Max: 6.32 Min: 6.46 / Avg: 6.46 / Max: 6.47 Min: 8.23 / Avg: 8.27 / Max: 8.29 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 7662 EPYC 7642 EPYC 7542 EPYC 7552 EPYC 7502P EPYC 7702 EPYC 7532 EPYC 7402P EPYC 7F52 EPYC 7302P EPYC 7282 EPYC 7272 EPYC 7F32 EPYC 7232P 7 14 21 28 35 SE +/- 0.26, N = 3 SE +/- 0.12, N = 3 SE +/- 0.14, N = 3 SE +/- 0.02, N = 3 SE +/- 0.21, N = 3 SE +/- 0.05, N = 3 SE +/- 0.04, N = 3 SE +/- 0.12, N = 3 SE +/- 0.12, N = 3 SE +/- 0.06, N = 3 SE +/- 0.06, N = 3 SE +/- 0.12, N = 3 SE +/- 0.06, N = 3 SE +/- 0.06, N = 3 31.84 29.37 27.67 27.50 26.51 26.49 25.35 23.34 20.00 17.39 16.61 13.67 12.06 9.30
FPS Per Watt
OpenBenchmarking.org FPS Per Watt, More Is Better PlaidML FP16: No - Mode: Inference - Network: VGG19 - Device: CPU EPYC 7662 EPYC 7502P EPYC 7552 EPYC 7542 EPYC 7702 EPYC 7642 EPYC 7532 EPYC 7402P EPYC 7282 EPYC 7302P EPYC 7272 EPYC 7F52 EPYC 7232P EPYC 7F32 0.054 0.108 0.162 0.216 0.27 0.24 0.22 0.22 0.21 0.21 0.20 0.19 0.19 0.18 0.16 0.15 0.11 0.11 0.09
Result Confidence
OpenBenchmarking.org FPS, More Is Better PlaidML FP16: No - Mode: Inference - Network: VGG19 - Device: CPU EPYC 7662 EPYC 7642 EPYC 7542 EPYC 7552 EPYC 7502P EPYC 7702 EPYC 7532 EPYC 7402P EPYC 7F52 EPYC 7302P EPYC 7282 EPYC 7272 EPYC 7F32 EPYC 7232P 7 14 21 28 35 Min: 31.48 / Avg: 31.84 / Max: 32.35 Min: 29.23 / Avg: 29.37 / Max: 29.61 Min: 27.53 / Avg: 27.67 / Max: 27.96 Min: 27.47 / Avg: 27.5 / Max: 27.53 Min: 26.11 / Avg: 26.51 / Max: 26.82 Min: 26.42 / Avg: 26.49 / Max: 26.59 Min: 25.31 / Avg: 25.35 / Max: 25.42 Min: 23.11 / Avg: 23.34 / Max: 23.52 Min: 19.79 / Avg: 20 / Max: 20.19 Min: 17.26 / Avg: 17.39 / Max: 17.46 Min: 16.52 / Avg: 16.61 / Max: 16.72 Min: 13.44 / Avg: 13.67 / Max: 13.83 Min: 11.98 / Avg: 12.06 / Max: 12.18 Min: 9.23 / Avg: 9.3 / Max: 9.41
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 7662 EPYC 7702 EPYC 7542 EPYC 7532 EPYC 7502P EPYC 7F52 EPYC 7282 EPYC 7272 EPYC 7F32 1.0199 2.0398 3.0597 4.0796 5.0995 SE +/- 0.005, N = 3 SE +/- 0.001, N = 3 SE +/- 0.004, N = 3 SE +/- 0.007, N = 3 SE +/- 0.002, N = 3 SE +/- 0.006, N = 3 SE +/- 0.001, N = 3 SE +/- 0.001, N = 3 SE +/- 0.001, N = 3 4.533 4.371 3.317 3.256 3.140 2.313 1.675 1.407 1.348 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 7662 EPYC 7532 EPYC 7282 EPYC 7542 EPYC 7502P EPYC 7F32 EPYC 7F52 0.0068 0.0136 0.0204 0.0272 0.034 0.03 0.02 0.02 0.02 0.02 0.01 0.01
Result Confidence
OpenBenchmarking.org Ns Per Day, More Is Better GROMACS 2021 Input: water_GMX50_bare EPYC 7662 EPYC 7702 EPYC 7542 EPYC 7532 EPYC 7502P EPYC 7F52 EPYC 7282 EPYC 7272 EPYC 7F32 2 4 6 8 10 Min: 4.52 / Avg: 4.53 / Max: 4.54 Min: 4.37 / Avg: 4.37 / Max: 4.37 Min: 3.31 / Avg: 3.32 / Max: 3.33 Min: 3.24 / Avg: 3.26 / Max: 3.27 Min: 3.14 / Avg: 3.14 / Max: 3.14 Min: 2.31 / Avg: 2.31 / Max: 2.33 Min: 1.67 / Avg: 1.68 / Max: 1.68 Min: 1.41 / Avg: 1.41 / Max: 1.41 Min: 1.35 / Avg: 1.35 / Max: 1.35 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 7662 EPYC 7642 EPYC 7542 EPYC 7552 EPYC 7502P EPYC 7702 EPYC 7532 EPYC 7402P EPYC 7F52 EPYC 7302P EPYC 7282 EPYC 7272 EPYC 7F32 EPYC 7232P 9 18 27 36 45 SE +/- 0.46, N = 4 SE +/- 0.45, N = 3 SE +/- 0.37, N = 3 SE +/- 0.16, N = 3 SE +/- 0.19, N = 3 SE +/- 0.28, N = 3 SE +/- 0.11, N = 3 SE +/- 0.12, N = 3 SE +/- 0.09, N = 3 SE +/- 0.10, N = 3 SE +/- 0.05, N = 3 SE +/- 0.22, N = 3 SE +/- 0.07, N = 3 SE +/- 0.15, N = 3 37.38 35.25 33.33 32.68 32.05 31.89 30.36 27.81 24.29 21.24 20.34 16.79 14.67 11.41
FPS Per Watt
OpenBenchmarking.org FPS Per Watt, More Is Better PlaidML FP16: No - Mode: Inference - Network: VGG16 - Device: CPU EPYC 7502P EPYC 7662 EPYC 7542 EPYC 7552 EPYC 7702 EPYC 7642 EPYC 7532 EPYC 7282 EPYC 7402P EPYC 7302P EPYC 7272 EPYC 7232P EPYC 7F52 EPYC 7F32 0.063 0.126 0.189 0.252 0.315 0.28 0.28 0.27 0.27 0.26 0.25 0.23 0.23 0.23 0.20 0.19 0.14 0.13 0.11
Result Confidence
OpenBenchmarking.org FPS, More Is Better PlaidML FP16: No - Mode: Inference - Network: VGG16 - Device: CPU EPYC 7662 EPYC 7642 EPYC 7542 EPYC 7552 EPYC 7502P EPYC 7702 EPYC 7532 EPYC 7402P EPYC 7F52 EPYC 7302P EPYC 7282 EPYC 7272 EPYC 7F32 EPYC 7232P 8 16 24 32 40 Min: 36.33 / Avg: 37.38 / Max: 38.57 Min: 34.41 / Avg: 35.25 / Max: 35.93 Min: 32.65 / Avg: 33.33 / Max: 33.94 Min: 32.38 / Avg: 32.68 / Max: 32.94 Min: 31.69 / Avg: 32.05 / Max: 32.3 Min: 31.34 / Avg: 31.89 / Max: 32.28 Min: 30.21 / Avg: 30.36 / Max: 30.58 Min: 27.57 / Avg: 27.81 / Max: 27.96 Min: 24.18 / Avg: 24.29 / Max: 24.46 Min: 21.13 / Avg: 21.24 / Max: 21.44 Min: 20.24 / Avg: 20.34 / Max: 20.43 Min: 16.5 / Avg: 16.79 / Max: 17.22 Min: 14.6 / Avg: 14.67 / Max: 14.82 Min: 11.13 / Avg: 11.41 / Max: 11.63
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 7662 EPYC 7702 EPYC 7552 EPYC 7642 EPYC 7542 EPYC 7532 EPYC 7502P EPYC 7402P EPYC 7F52 EPYC 7282 EPYC 7302P EPYC 7272 EPYC 7F32 EPYC 7232P 6 12 18 24 30 SE +/- 0.051, N = 15 SE +/- 0.066, N = 8 SE +/- 0.083, N = 6 SE +/- 0.073, N = 5 SE +/- 0.005, N = 5 SE +/- 0.057, N = 5 SE +/- 0.030, N = 5 SE +/- 0.007, N = 4 SE +/- 0.022, N = 4 SE +/- 0.009, N = 4 SE +/- 0.022, N = 4 SE +/- 0.065, N = 3 SE +/- 0.078, N = 3 SE +/- 0.030, N = 3 7.747 7.819 8.405 8.434 9.806 9.858 9.892 11.577 13.530 14.792 15.445 18.134 22.218 25.374 1. (CXX) g++ options: -O2 -lOpenCL
Result Confidence
OpenBenchmarking.org Seconds, Fewer Is Better Rodinia 3.1 Test: OpenMP CFD Solver EPYC 7662 EPYC 7702 EPYC 7552 EPYC 7642 EPYC 7542 EPYC 7532 EPYC 7502P EPYC 7402P EPYC 7F52 EPYC 7282 EPYC 7302P EPYC 7272 EPYC 7F32 EPYC 7232P 6 12 18 24 30 Min: 7.37 / Avg: 7.75 / Max: 8.02 Min: 7.45 / Avg: 7.82 / Max: 8.05 Min: 8.14 / Avg: 8.41 / Max: 8.71 Min: 8.16 / Avg: 8.43 / Max: 8.59 Min: 9.79 / Avg: 9.81 / Max: 9.82 Min: 9.76 / Avg: 9.86 / Max: 10.08 Min: 9.81 / Avg: 9.89 / Max: 9.96 Min: 11.57 / Avg: 11.58 / Max: 11.6 Min: 13.49 / Avg: 13.53 / Max: 13.59 Min: 14.76 / Avg: 14.79 / Max: 14.8 Min: 15.41 / Avg: 15.44 / Max: 15.51 Min: 18.02 / Avg: 18.13 / Max: 18.24 Min: 22.12 / Avg: 22.22 / Max: 22.37 Min: 25.33 / Avg: 25.37 / Max: 25.43 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 7642 EPYC 7552 EPYC 7662 EPYC 7532 EPYC 7702 EPYC 7542 EPYC 7502P EPYC 7402P EPYC 7F52 EPYC 7302P EPYC 7F32 EPYC 7282 EPYC 7272 EPYC 7232P 500 1000 1500 2000 2500 SE +/- 1.28, N = 3 SE +/- 2.70, N = 3 SE +/- 1.17, N = 3 SE +/- 1.51, N = 3 SE +/- 3.54, N = 3 SE +/- 4.31, N = 3 SE +/- 5.72, N = 3 SE +/- 0.91, N = 3 SE +/- 1.61, N = 3 SE +/- 0.19, N = 3 SE +/- 0.51, N = 3 SE +/- 3.12, N = 3 SE +/- 2.69, N = 3 SE +/- 2.26, N = 3 732.81 787.43 793.20 813.12 874.44 890.48 902.26 972.93 997.85 1229.69 1745.54 1882.64 2022.45 2397.56 MIN: 712.9 MIN: 769.99 MIN: 776.66 MIN: 799.88 MIN: 847.07 MIN: 867.03 MIN: 882.8 MIN: 960.02 MIN: 987.15 MIN: 1221.64 MIN: 1733.89 MIN: 1853.21 MIN: 2012.67 MIN: 2367.09 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: f32 - Engine: CPU EPYC 7642 EPYC 7552 EPYC 7662 EPYC 7532 EPYC 7702 EPYC 7542 EPYC 7502P EPYC 7402P EPYC 7F52 EPYC 7302P EPYC 7F32 EPYC 7282 EPYC 7272 EPYC 7232P 400 800 1200 1600 2000 Min: 731.06 / Avg: 732.81 / Max: 735.31 Min: 782.55 / Avg: 787.43 / Max: 791.88 Min: 790.85 / Avg: 793.2 / Max: 794.46 Min: 810.1 / Avg: 813.12 / Max: 814.7 Min: 868.68 / Avg: 874.44 / Max: 880.89 Min: 882.05 / Avg: 890.48 / Max: 896.25 Min: 890.83 / Avg: 902.26 / Max: 908.5 Min: 971.59 / Avg: 972.93 / Max: 974.66 Min: 995.25 / Avg: 997.85 / Max: 1000.79 Min: 1229.46 / Avg: 1229.69 / Max: 1230.06 Min: 1744.59 / Avg: 1745.54 / Max: 1746.31 Min: 1876.41 / Avg: 1882.64 / Max: 1885.98 Min: 2018.73 / Avg: 2022.45 / Max: 2027.68 Min: 2394.02 / Avg: 2397.56 / Max: 2401.75 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 7662 EPYC 7702 EPYC 7642 EPYC 7552 EPYC 7542 EPYC 7532 EPYC 7502P EPYC 7402P EPYC 7F52 EPYC 7302P EPYC 7282 EPYC 7272 EPYC 7F32 EPYC 7232P 160 320 480 640 800 SE +/- 0.89, N = 3 SE +/- 1.73, N = 3 SE +/- 1.29, N = 3 SE +/- 1.44, N = 3 SE +/- 1.12, N = 3 SE +/- 1.56, N = 3 SE +/- 2.29, N = 3 SE +/- 3.16, N = 9 SE +/- 2.67, N = 3 SE +/- 5.04, N = 4 SE +/- 3.68, N = 3 SE +/- 0.47, N = 3 SE +/- 0.89, N = 3 SE +/- 2.05, N = 3 233.51 234.21 243.92 245.40 275.35 280.78 289.36 312.70 343.39 404.33 440.00 529.62 581.30 763.56
Result Confidence
OpenBenchmarking.org Seconds, Fewer Is Better Timed LLVM Compilation 10.0 Time To Compile EPYC 7662 EPYC 7702 EPYC 7642 EPYC 7552 EPYC 7542 EPYC 7532 EPYC 7502P EPYC 7402P EPYC 7F52 EPYC 7302P EPYC 7282 EPYC 7272 EPYC 7F32 EPYC 7232P 130 260 390 520 650 Min: 232.12 / Avg: 233.51 / Max: 235.17 Min: 230.9 / Avg: 234.2 / Max: 236.76 Min: 241.53 / Avg: 243.91 / Max: 245.95 Min: 242.68 / Avg: 245.4 / Max: 247.61 Min: 273.43 / Avg: 275.35 / Max: 277.3 Min: 278.05 / Avg: 280.78 / Max: 283.44 Min: 286.12 / Avg: 289.36 / Max: 293.79 Min: 297.71 / Avg: 312.7 / Max: 321.97 Min: 340.62 / Avg: 343.39 / Max: 348.73 Min: 391.86 / Avg: 404.33 / Max: 414.08 Min: 432.97 / Avg: 440 / Max: 445.42 Min: 528.7 / Avg: 529.62 / Max: 530.26 Min: 579.68 / Avg: 581.3 / Max: 582.76 Min: 759.57 / Avg: 763.56 / Max: 766.35
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 7642 EPYC 7552 EPYC 7662 EPYC 7532 EPYC 7702 EPYC 7542 EPYC 7502P EPYC 7402P EPYC 7F52 EPYC 7302P EPYC 7F32 EPYC 7282 EPYC 7272 EPYC 7232P 500 1000 1500 2000 2500 SE +/- 3.28, N = 3 SE +/- 2.09, N = 3 SE +/- 1.88, N = 3 SE +/- 1.32, N = 3 SE +/- 2.81, N = 3 SE +/- 1.35, N = 3 SE +/- 2.58, N = 3 SE +/- 1.57, N = 3 SE +/- 3.97, N = 3 SE +/- 0.54, N = 3 SE +/- 0.95, N = 3 SE +/- 5.33, N = 3 SE +/- 4.61, N = 3 SE +/- 3.61, N = 3 734.40 784.82 793.23 812.99 878.20 886.88 919.61 974.12 998.67 1227.56 1742.79 1886.30 2032.88 2397.22 MIN: 716.82 MIN: 771.05 MIN: 777.03 MIN: 799.51 MIN: 851.72 MIN: 865.5 MIN: 906.32 MIN: 962.55 MIN: 987.09 MIN: 1218.44 MIN: 1728.82 MIN: 1851.55 MIN: 2016.92 MIN: 2370.41 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 7642 EPYC 7552 EPYC 7662 EPYC 7532 EPYC 7702 EPYC 7542 EPYC 7502P EPYC 7402P EPYC 7F52 EPYC 7302P EPYC 7F32 EPYC 7282 EPYC 7272 EPYC 7232P 400 800 1200 1600 2000 Min: 728.04 / Avg: 734.4 / Max: 738.94 Min: 780.67 / Avg: 784.82 / Max: 787.4 Min: 791.29 / Avg: 793.23 / Max: 796.99 Min: 810.37 / Avg: 812.99 / Max: 814.64 Min: 873.24 / Avg: 878.2 / Max: 882.97 Min: 884.18 / Avg: 886.88 / Max: 888.33 Min: 916.98 / Avg: 919.61 / Max: 924.77 Min: 971.07 / Avg: 974.12 / Max: 976.32 Min: 991.29 / Avg: 998.67 / Max: 1004.91 Min: 1226.72 / Avg: 1227.56 / Max: 1228.57 Min: 1741.68 / Avg: 1742.79 / Max: 1744.69 Min: 1876.6 / Avg: 1886.3 / Max: 1894.99 Min: 2023.66 / Avg: 2032.88 / Max: 2037.71 Min: 2392.08 / Avg: 2397.22 / Max: 2404.17 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 7642 EPYC 7552 EPYC 7662 EPYC 7532 EPYC 7702 EPYC 7542 EPYC 7502P EPYC 7402P EPYC 7F52 EPYC 7302P EPYC 7F32 EPYC 7282 EPYC 7272 EPYC 7232P 500 1000 1500 2000 2500 SE +/- 2.51, N = 3 SE +/- 1.66, N = 3 SE +/- 0.96, N = 3 SE +/- 2.11, N = 3 SE +/- 3.99, N = 3 SE +/- 1.82, N = 3 SE +/- 5.94, N = 3 SE +/- 0.65, N = 3 SE +/- 0.99, N = 3 SE +/- 1.03, N = 3 SE +/- 2.16, N = 3 SE +/- 4.32, N = 3 SE +/- 1.28, N = 3 SE +/- 4.09, N = 3 735.82 782.65 792.55 814.03 875.71 888.54 917.61 972.77 999.14 1228.50 1744.75 1884.70 2029.28 2398.98 MIN: 715.63 MIN: 769.36 MIN: 773.96 MIN: 801.22 MIN: 846.67 MIN: 872.96 MIN: 892.04 MIN: 962.66 MIN: 991.16 MIN: 1219.05 MIN: 1731.94 MIN: 1853.9 MIN: 2020.38 MIN: 2367.55 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 7642 EPYC 7552 EPYC 7662 EPYC 7532 EPYC 7702 EPYC 7542 EPYC 7502P EPYC 7402P EPYC 7F52 EPYC 7302P EPYC 7F32 EPYC 7282 EPYC 7272 EPYC 7232P 400 800 1200 1600 2000 Min: 731.42 / Avg: 735.82 / Max: 740.12 Min: 779.51 / Avg: 782.65 / Max: 785.17 Min: 791.43 / Avg: 792.55 / Max: 794.46 Min: 810.97 / Avg: 814.03 / Max: 818.07 Min: 869.12 / Avg: 875.71 / Max: 882.9 Min: 885.37 / Avg: 888.54 / Max: 891.69 Min: 907.1 / Avg: 917.61 / Max: 927.67 Min: 971.9 / Avg: 972.77 / Max: 974.05 Min: 997.98 / Avg: 999.14 / Max: 1001.1 Min: 1226.65 / Avg: 1228.5 / Max: 1230.2 Min: 1742.54 / Avg: 1744.75 / Max: 1749.07 Min: 1878.26 / Avg: 1884.7 / Max: 1892.91 Min: 2026.92 / Avg: 2029.28 / Max: 2031.33 Min: 2391.8 / Avg: 2398.98 / Max: 2405.96 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 7642 EPYC 7542 EPYC 7662 EPYC 7502P EPYC 7552 EPYC 7532 EPYC 7702 EPYC 7402P EPYC 7F52 EPYC 7302P EPYC 7282 EPYC 7F32 EPYC 7272 EPYC 7232P 1.0662 2.1324 3.1986 4.2648 5.331 SE +/- 0.00906, N = 4 SE +/- 0.00341, N = 4 SE +/- 0.01406, N = 4 SE +/- 0.00185, N = 4 SE +/- 0.00439, N = 4 SE +/- 0.00891, N = 4 SE +/- 0.00178, N = 4 SE +/- 0.00090, N = 4 SE +/- 0.01053, N = 4 SE +/- 0.00144, N = 4 SE +/- 0.00488, N = 4 SE +/- 0.00382, N = 4 SE +/- 0.00316, N = 4 SE +/- 0.00331, N = 4 1.46775 1.47222 1.48981 1.59300 1.59938 1.61502 1.70360 1.82951 1.98035 2.41082 3.44668 3.56020 3.80955 4.73866 MIN: 1.39 MIN: 1.41 MIN: 1.33 MIN: 1.51 MIN: 1.51 MIN: 1.5 MIN: 1.48 MIN: 1.74 MIN: 1.86 MIN: 2.2 MIN: 2.92 MIN: 3.44 MIN: 3.44 MIN: 4.55 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 7642 EPYC 7542 EPYC 7662 EPYC 7502P EPYC 7552 EPYC 7532 EPYC 7702 EPYC 7402P EPYC 7F52 EPYC 7302P EPYC 7282 EPYC 7F32 EPYC 7272 EPYC 7232P 2 4 6 8 10 Min: 1.45 / Avg: 1.47 / Max: 1.49 Min: 1.46 / Avg: 1.47 / Max: 1.48 Min: 1.45 / Avg: 1.49 / Max: 1.52 Min: 1.59 / Avg: 1.59 / Max: 1.6 Min: 1.59 / Avg: 1.6 / Max: 1.61 Min: 1.6 / Avg: 1.62 / Max: 1.64 Min: 1.7 / Avg: 1.7 / Max: 1.71 Min: 1.83 / Avg: 1.83 / Max: 1.83 Min: 1.96 / Avg: 1.98 / Max: 2.01 Min: 2.41 / Avg: 2.41 / Max: 2.41 Min: 3.43 / Avg: 3.45 / Max: 3.45 Min: 3.55 / Avg: 3.56 / Max: 3.57 Min: 3.8 / Avg: 3.81 / Max: 3.81 Min: 4.73 / Avg: 4.74 / Max: 4.74 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 7662 EPYC 7642 EPYC 7552 EPYC 7702 EPYC 7542 EPYC 7502P EPYC 7532 EPYC 7402P EPYC 7F52 EPYC 7282 EPYC 7302P EPYC 7272 EPYC 7F32 EPYC 7232P 4 8 12 16 20 SE +/- 0.00245, N = 8 SE +/- 0.00169, N = 8 SE +/- 0.00349, N = 8 SE +/- 0.00214, N = 8 SE +/- 0.00749, N = 8 SE +/- 0.00220, N = 8 SE +/- 0.00562, N = 7 SE +/- 0.01885, N = 7 SE +/- 0.05079, N = 6 SE +/- 0.04707, N = 6 SE +/- 0.03030, N = 6 SE +/- 0.06509, N = 5 SE +/- 0.08977, N = 4 SE +/- 0.01019, N = 4 4.32609 4.36145 4.36372 4.46261 4.54904 4.69550 4.84256 5.27499 6.56276 7.40074 7.46871 9.81098 12.41410 13.92660 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 7662 EPYC 7642 EPYC 7552 EPYC 7702 EPYC 7542 EPYC 7502P EPYC 7532 EPYC 7402P EPYC 7F52 EPYC 7282 EPYC 7302P EPYC 7272 EPYC 7F32 EPYC 7232P 4 8 12 16 20 Min: 4.32 / Avg: 4.33 / Max: 4.34 Min: 4.35 / Avg: 4.36 / Max: 4.37 Min: 4.35 / Avg: 4.36 / Max: 4.38 Min: 4.46 / Avg: 4.46 / Max: 4.47 Min: 4.51 / Avg: 4.55 / Max: 4.57 Min: 4.68 / Avg: 4.7 / Max: 4.7 Min: 4.83 / Avg: 4.84 / Max: 4.87 Min: 5.21 / Avg: 5.27 / Max: 5.33 Min: 6.4 / Avg: 6.56 / Max: 6.75 Min: 7.21 / Avg: 7.4 / Max: 7.56 Min: 7.35 / Avg: 7.47 / Max: 7.56 Min: 9.7 / Avg: 9.81 / Max: 10.01 Min: 12.18 / Avg: 12.41 / Max: 12.6 Min: 13.91 / Avg: 13.93 / Max: 13.96 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 7642 EPYC 7662 EPYC 7552 EPYC 7702 EPYC 7542 EPYC 7502P EPYC 7532 EPYC 7402P EPYC 7F52 EPYC 7302P EPYC 7282 EPYC 7272 EPYC 7F32 EPYC 7232P 30 60 90 120 150 SE +/- 0.47, N = 15 SE +/- 0.47, N = 3 SE +/- 0.82, N = 15 SE +/- 0.61, N = 14 SE +/- 0.28, N = 3 SE +/- 0.26, N = 3 SE +/- 0.42, N = 3 SE +/- 0.25, N = 3 SE +/- 0.52, N = 3 SE +/- 1.14, N = 3 SE +/- 0.76, N = 10 SE +/- 0.53, N = 3 SE +/- 0.11, N = 3 SE +/- 0.41, N = 3 46.53 47.37 47.43 48.72 57.68 57.98 59.44 59.65 90.52 98.19 99.72 107.97 130.98 148.20 1. (CXX) g++ options: -O2 -lOpenCL
Result Confidence
OpenBenchmarking.org Seconds, Fewer Is Better Rodinia 3.1 Test: OpenMP Leukocyte EPYC 7642 EPYC 7662 EPYC 7552 EPYC 7702 EPYC 7542 EPYC 7502P EPYC 7532 EPYC 7402P EPYC 7F52 EPYC 7302P EPYC 7282 EPYC 7272 EPYC 7F32 EPYC 7232P 30 60 90 120 150 Min: 44.25 / Avg: 46.53 / Max: 49.64 Min: 46.63 / Avg: 47.37 / Max: 48.23 Min: 44.96 / Avg: 47.42 / Max: 54.58 Min: 46.16 / Avg: 48.72 / Max: 52.95 Min: 57.12 / Avg: 57.68 / Max: 57.99 Min: 57.58 / Avg: 57.98 / Max: 58.48 Min: 58.61 / Avg: 59.44 / Max: 59.95 Min: 59.34 / Avg: 59.65 / Max: 60.14 Min: 89.7 / Avg: 90.52 / Max: 91.49 Min: 96.7 / Avg: 98.19 / Max: 100.44 Min: 96.18 / Avg: 99.72 / Max: 103.91 Min: 106.91 / Avg: 107.97 / Max: 108.52 Min: 130.76 / Avg: 130.98 / Max: 131.14 Min: 147.55 / Avg: 148.2 / Max: 148.96 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 7542 EPYC 7642 EPYC 7662 EPYC 7552 EPYC 7502P EPYC 7532 EPYC 7402P EPYC 7702 EPYC 7302P EPYC 7282 EPYC 7F52 EPYC 7272 EPYC 7F32 EPYC 7232P 100 200 300 400 500 SE +/- 0.74, N = 11 SE +/- 0.61, N = 10 SE +/- 0.96, N = 10 SE +/- 0.97, N = 10 SE +/- 0.76, N = 11 SE +/- 1.03, N = 11 SE +/- 0.86, N = 11 SE +/- 3.60, N = 15 SE +/- 0.29, N = 10 SE +/- 0.35, N = 10 SE +/- 0.36, N = 10 SE +/- 0.45, N = 9 SE +/- 0.26, N = 8 SE +/- 0.15, N = 8 459.14 458.24 448.08 445.92 437.88 426.52 413.09 409.36 316.49 295.80 263.13 239.47 167.08 144.32 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 7542 EPYC 7502P EPYC 7402P EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7532 EPYC 7282 EPYC 7702 EPYC 7302P EPYC 7272 EPYC 7F52 EPYC 7232P EPYC 7F32 2 4 6 8 10 7.38 7.27 6.59 6.57 6.14 5.97 5.70 5.47 5.28 5.07 4.25 2.76 2.72 2.34
Result Confidence
OpenBenchmarking.org Frames Per Second, More Is Better SVT-VP9 0.1 Tuning: PSNR/SSIM Optimized - Input: Bosphorus 1080p EPYC 7542 EPYC 7642 EPYC 7662 EPYC 7552 EPYC 7502P EPYC 7532 EPYC 7402P EPYC 7702 EPYC 7302P EPYC 7282 EPYC 7F52 EPYC 7272 EPYC 7F32 EPYC 7232P 80 160 240 320 400 Min: 454.55 / Avg: 459.14 / Max: 462.25 Min: 456.27 / Avg: 458.24 / Max: 462.61 Min: 442.15 / Avg: 448.08 / Max: 452.83 Min: 441.83 / Avg: 445.92 / Max: 451.13 Min: 434.47 / Avg: 437.88 / Max: 443.13 Min: 419.29 / Avg: 426.52 / Max: 430.73 Min: 407.89 / Avg: 413.09 / Max: 416.67 Min: 379.51 / Avg: 409.36 / Max: 426.74 Min: 315.62 / Avg: 316.49 / Max: 317.97 Min: 293.54 / Avg: 295.8 / Max: 297.47 Min: 260.87 / Avg: 263.13 / Max: 264.67 Min: 237.06 / Avg: 239.47 / Max: 241.16 Min: 165.84 / Avg: 167.08 / Max: 168.07 Min: 143.85 / Avg: 144.32 / Max: 145.1 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 7662 EPYC 7642 EPYC 7702 EPYC 7552 EPYC 7542 EPYC 7502P EPYC 7532 EPYC 7402P EPYC 7F52 EPYC 7302P EPYC 7282 EPYC 7272 EPYC 7F32 EPYC 7232P 110 220 330 440 550 153.46 153.98 154.44 154.73 161.64 170.48 172.91 194.53 226.80 260.98 275.81 333.25 381.37 487.37
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 7662 EPYC 7642 EPYC 7702 EPYC 7532 EPYC 7552 EPYC 7502P EPYC 7542 EPYC 7402P EPYC 7302P EPYC 7282 EPYC 7F52 EPYC 7272 EPYC 7F32 EPYC 7232P 3 6 9 12 15 SE +/- 0.01107, N = 7 SE +/- 0.00965, N = 7 SE +/- 0.00551, N = 7 SE +/- 0.01167, N = 7 SE +/- 0.00723, N = 7 SE +/- 0.01750, N = 7 SE +/- 0.00813, N = 7 SE +/- 0.00525, N = 7 SE +/- 0.00742, N = 7 SE +/- 0.03193, N = 7 SE +/- 0.03514, N = 7 SE +/- 0.00984, N = 7 SE +/- 0.04127, N = 7 SE +/- 0.04608, N = 7 3.50412 3.54316 3.55892 3.61268 3.84018 3.97043 3.97699 4.25111 5.45400 6.76242 6.91561 7.60505 9.15124 10.95820 MIN: 3.39 MIN: 3.43 MIN: 3.47 MIN: 3.49 MIN: 3.75 MIN: 3.86 MIN: 3.87 MIN: 4.06 MIN: 5.12 MIN: 6.41 MIN: 6.67 MIN: 7.15 MIN: 8.56 MIN: 10.24 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 7662 EPYC 7642 EPYC 7702 EPYC 7532 EPYC 7552 EPYC 7502P EPYC 7542 EPYC 7402P EPYC 7302P EPYC 7282 EPYC 7F52 EPYC 7272 EPYC 7F32 EPYC 7232P 3 6 9 12 15 Min: 3.47 / Avg: 3.5 / Max: 3.54 Min: 3.52 / Avg: 3.54 / Max: 3.59 Min: 3.54 / Avg: 3.56 / Max: 3.58 Min: 3.55 / Avg: 3.61 / Max: 3.64 Min: 3.81 / Avg: 3.84 / Max: 3.86 Min: 3.92 / Avg: 3.97 / Max: 4.03 Min: 3.94 / Avg: 3.98 / Max: 4 Min: 4.23 / Avg: 4.25 / Max: 4.27 Min: 5.41 / Avg: 5.45 / Max: 5.47 Min: 6.64 / Avg: 6.76 / Max: 6.85 Min: 6.79 / Avg: 6.92 / Max: 7.05 Min: 7.56 / Avg: 7.61 / Max: 7.64 Min: 9.06 / Avg: 9.15 / Max: 9.39 Min: 10.75 / Avg: 10.96 / Max: 11.12 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 7542 EPYC 7502P EPYC 7662 EPYC 7532 EPYC 7702 EPYC 7642 EPYC 7402P EPYC 7302P EPYC 7552 EPYC 7F32 EPYC 7282 EPYC 7272 EPYC 7232P EPYC 7F52 100 200 300 400 500 SE +/- 1.71, N = 3 SE +/- 1.71, N = 3 SE +/- 1.71, N = 3 SE +/- 0.64, N = 3 SE +/- 2.16, N = 3 SE +/- 0.00, N = 3 SE +/- 3.44, N = 3 SE +/- 0.62, N = 3 SE +/- 0.98, N = 3 SE +/- 1.74, N = 3 SE +/- 2.18, N = 3 SE +/- 2.09, N = 3 SE +/- 1.09, N = 3 SE +/- 0.57, N = 3 439.25 439.25 439.25 439.24 432.92 432.90 432.33 432.28 411.53 380.73 378.81 370.39 351.71 140.92 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 7282 EPYC 7542 EPYC 7272 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7232P EPYC 7F32 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7532 EPYC 7702 EPYC 7F52 2 4 6 8 10 7.57 7.49 7.49 7.45 7.39 7.30 7.29 6.05 5.89 5.46 5.45 5.38 5.10 1.59
Result Confidence
OpenBenchmarking.org Iterations Per Second, More Is Better ASKAP 1.0 Test: Hogbom Clean OpenMP EPYC 7542 EPYC 7502P EPYC 7662 EPYC 7532 EPYC 7702 EPYC 7642 EPYC 7402P EPYC 7302P EPYC 7552 EPYC 7F32 EPYC 7282 EPYC 7272 EPYC 7232P EPYC 7F52 80 160 240 320 400 Min: 436.68 / Avg: 439.25 / Max: 442.48 Min: 436.68 / Avg: 439.25 / Max: 442.48 Min: 436.68 / Avg: 439.25 / Max: 442.48 Min: 438.6 / Avg: 439.24 / Max: 440.53 Min: 429.19 / Avg: 432.92 / Max: 436.68 Min: 432.9 / Avg: 432.9 / Max: 432.9 Min: 425.53 / Avg: 432.33 / Max: 436.68 Min: 431.03 / Avg: 432.28 / Max: 432.9 Min: 409.84 / Avg: 411.53 / Max: 413.22 Min: 377.36 / Avg: 380.73 / Max: 383.14 Min: 374.53 / Avg: 378.81 / Max: 381.68 Min: 366.3 / Avg: 370.39 / Max: 373.13 Min: 349.65 / Avg: 351.71 / Max: 353.36 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 7642 EPYC 7662 EPYC 7542 EPYC 7552 EPYC 7502P EPYC 7532 EPYC 7702 EPYC 7402P EPYC 7F52 EPYC 7302P EPYC 7282 EPYC 7272 EPYC 7F32 EPYC 7232P 2 4 6 8 10 SE +/- 0.02012, N = 3 SE +/- 0.01627, N = 15 SE +/- 0.00152, N = 3 SE +/- 0.01668, N = 15 SE +/- 0.01343, N = 3 SE +/- 0.01295, N = 3 SE +/- 0.00813, N = 3 SE +/- 0.00832, N = 3 SE +/- 0.00961, N = 3 SE +/- 0.01740, N = 3 SE +/- 0.01071, N = 3 SE +/- 0.00923, N = 3 SE +/- 0.06606, N = 3 SE +/- 0.02020, N = 3 1.98726 2.02231 2.04866 2.15794 2.19727 2.22242 2.33519 2.48977 2.75743 3.28377 3.50175 4.44077 5.03236 6.12261 MIN: 1.87 MIN: 1.84 MIN: 1.99 MIN: 1.99 MIN: 2.12 MIN: 2.06 MIN: 2.08 MIN: 2.4 MIN: 2.63 MIN: 3.08 MIN: 3.1 MIN: 4.2 MIN: 4.86 MIN: 5.93 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 7642 EPYC 7662 EPYC 7542 EPYC 7552 EPYC 7502P EPYC 7532 EPYC 7702 EPYC 7402P EPYC 7F52 EPYC 7302P EPYC 7282 EPYC 7272 EPYC 7F32 EPYC 7232P 2 4 6 8 10 Min: 1.95 / Avg: 1.99 / Max: 2.02 Min: 1.93 / Avg: 2.02 / Max: 2.15 Min: 2.05 / Avg: 2.05 / Max: 2.05 Min: 2.07 / Avg: 2.16 / Max: 2.28 Min: 2.18 / Avg: 2.2 / Max: 2.22 Min: 2.21 / Avg: 2.22 / Max: 2.25 Min: 2.32 / Avg: 2.34 / Max: 2.35 Min: 2.48 / Avg: 2.49 / Max: 2.51 Min: 2.74 / Avg: 2.76 / Max: 2.77 Min: 3.25 / Avg: 3.28 / Max: 3.3 Min: 3.49 / Avg: 3.5 / Max: 3.52 Min: 4.43 / Avg: 4.44 / Max: 4.46 Min: 4.94 / Avg: 5.03 / Max: 5.16 Min: 6.1 / Avg: 6.12 / Max: 6.16 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 7662 EPYC 7702 EPYC 7642 EPYC 7552 EPYC 7532 EPYC 7542 EPYC 7502P EPYC 7402P EPYC 7302P EPYC 7282 EPYC 7F52 EPYC 7272 EPYC 7F32 EPYC 7232P 20K 40K 60K 80K 100K SE +/- 298.03, N = 3 SE +/- 34.41, N = 3 SE +/- 281.17, N = 3 SE +/- 82.31, N = 3 SE +/- 26.26, N = 3 SE +/- 207.08, N = 3 SE +/- 106.91, N = 3 SE +/- 81.46, N = 3 SE +/- 3.68, N = 3 SE +/- 22.56, N = 3 SE +/- 82.34, N = 3 SE +/- 24.66, N = 3 SE +/- 31.62, N = 3 SE +/- 12.95, N = 3 103985.91 102548.95 99557.23 95079.41 86547.28 79644.88 78846.96 74421.61 61041.27 49617.92 44891.69 43321.38 43172.51 33816.48 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 7662 EPYC 7552 EPYC 7542 EPYC 7702 EPYC 7502P EPYC 7402P EPYC 7642 EPYC 7302P EPYC 7282 EPYC 7532 EPYC 7272 EPYC 7232P EPYC 7F32 EPYC 7F52 140 280 420 560 700 660.15 655.10 638.72 629.05 616.99 607.37 602.66 593.84 573.26 572.31 529.25 486.72 419.08 297.36
Result Confidence
OpenBenchmarking.org Total Mop/s, More Is Better NAS Parallel Benchmarks 3.4 Test / Class: LU.C EPYC 7662 EPYC 7702 EPYC 7642 EPYC 7552 EPYC 7532 EPYC 7542 EPYC 7502P EPYC 7402P EPYC 7302P EPYC 7282 EPYC 7F52 EPYC 7272 EPYC 7F32 EPYC 7232P 20K 40K 60K 80K 100K Min: 103567 / Avg: 103985.91 / Max: 104562.59 Min: 102490.22 / Avg: 102548.95 / Max: 102609.37 Min: 98994.91 / Avg: 99557.23 / Max: 99842.55 Min: 94922.44 / Avg: 95079.41 / Max: 95200.87 Min: 86498.25 / Avg: 86547.28 / Max: 86588.09 Min: 79399.38 / Avg: 79644.88 / Max: 80056.49 Min: 78710.27 / Avg: 78846.96 / Max: 79057.7 Min: 74315 / Avg: 74421.61 / Max: 74581.6 Min: 61034.85 / Avg: 61041.27 / Max: 61047.59 Min: 49572.87 / Avg: 49617.92 / Max: 49642.69 Min: 44754.21 / Avg: 44891.69 / Max: 45038.95 Min: 43285.83 / Avg: 43321.38 / Max: 43368.77 Min: 43122.35 / Avg: 43172.51 / Max: 43230.93 Min: 33792.21 / Avg: 33816.48 / Max: 33836.43 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 7662 EPYC 7702 EPYC 7552 EPYC 7642 EPYC 7542 EPYC 7502P EPYC 7532 EPYC 7402P EPYC 7282 EPYC 7302P EPYC 7F52 EPYC 7272 EPYC 7F32 EPYC 7232P 12K 24K 36K 48K 60K SE +/- 734.82, N = 3 SE +/- 365.68, N = 3 SE +/- 725.42, N = 3 SE +/- 308.59, N = 3 SE +/- 320.52, N = 13 SE +/- 468.05, N = 3 SE +/- 489.37, N = 5 SE +/- 510.25, N = 4 SE +/- 44.96, N = 3 SE +/- 306.40, N = 6 SE +/- 92.29, N = 3 SE +/- 98.97, N = 3 SE +/- 32.87, N = 3 SE +/- 5.29, N = 3 54318 52181 51444 50381 46655 45671 44343 41273 32115 30313 28193 25170 20541 17709 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 7662 EPYC 7702 EPYC 7552 EPYC 7642 EPYC 7542 EPYC 7502P EPYC 7532 EPYC 7402P EPYC 7282 EPYC 7302P EPYC 7F52 EPYC 7272 EPYC 7F32 EPYC 7232P 9K 18K 27K 36K 45K Min: 53010.6 / Avg: 54318.48 / Max: 55552.89 Min: 51458.66 / Avg: 52181.25 / Max: 52640.41 Min: 50134.59 / Avg: 51444.21 / Max: 52639.74 Min: 49982.78 / Avg: 50381.39 / Max: 50988.76 Min: 46038.91 / Avg: 46655.09 / Max: 50394.39 Min: 45084.17 / Avg: 45670.73 / Max: 46595.8 Min: 42733.56 / Avg: 44342.61 / Max: 45416.75 Min: 40219.85 / Avg: 41272.74 / Max: 42149.61 Min: 32033.65 / Avg: 32115.45 / Max: 32188.7 Min: 29631.74 / Avg: 30313.35 / Max: 31648.97 Min: 28026.73 / Avg: 28193.29 / Max: 28345.44 Min: 25002.83 / Avg: 25170.22 / Max: 25345.42 Min: 20498.68 / Avg: 20541.36 / Max: 20606 Min: 17702.56 / Avg: 17709.27 / Max: 17719.71 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 7662 EPYC 7702 EPYC 7552 EPYC 7642 EPYC 7542 EPYC 7502P EPYC 7532 EPYC 7402P EPYC 7282 EPYC 7302P EPYC 7F52 EPYC 7272 EPYC 7F32 EPYC 7232P 4 8 12 16 20 SE +/- 0.063, N = 3 SE +/- 0.034, N = 3 SE +/- 0.069, N = 3 SE +/- 0.031, N = 3 SE +/- 0.034, N = 13 SE +/- 0.056, N = 3 SE +/- 0.063, N = 5 SE +/- 0.075, N = 4 SE +/- 0.011, N = 3 SE +/- 0.082, N = 6 SE +/- 0.029, N = 3 SE +/- 0.040, N = 3 SE +/- 0.020, N = 3 SE +/- 0.004, N = 3 4.617 4.804 4.872 4.972 5.369 5.481 5.648 6.067 7.791 8.258 8.876 9.939 12.176 14.123 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 7662 EPYC 7702 EPYC 7552 EPYC 7642 EPYC 7542 EPYC 7502P EPYC 7532 EPYC 7402P EPYC 7282 EPYC 7302P EPYC 7F52 EPYC 7272 EPYC 7F32 EPYC 7232P 4 8 12 16 20 Min: 4.51 / Avg: 4.62 / Max: 4.73 Min: 4.76 / Avg: 4.8 / Max: 4.87 Min: 4.76 / Avg: 4.87 / Max: 5 Min: 4.91 / Avg: 4.97 / Max: 5.01 Min: 4.97 / Avg: 5.37 / Max: 5.44 Min: 5.37 / Avg: 5.48 / Max: 5.55 Min: 5.51 / Avg: 5.65 / Max: 5.86 Min: 5.94 / Avg: 6.07 / Max: 6.22 Min: 7.77 / Avg: 7.79 / Max: 7.81 Min: 7.91 / Avg: 8.26 / Max: 8.44 Min: 8.83 / Avg: 8.88 / Max: 8.93 Min: 9.87 / Avg: 9.94 / Max: 10.01 Min: 12.14 / Avg: 12.18 / Max: 12.2 Min: 14.12 / Avg: 14.12 / Max: 14.13 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 7662 EPYC 7702 EPYC 7642 EPYC 7552 EPYC 7542 EPYC 7502P EPYC 7532 EPYC 7402P EPYC 7302P EPYC 7F52 EPYC 7282 EPYC 7272 EPYC 7F32 EPYC 7232P 100 200 300 400 500 SE +/- 0.74, N = 3 SE +/- 0.34, N = 3 SE +/- 0.17, N = 3 SE +/- 0.66, N = 3 SE +/- 0.75, N = 3 SE +/- 0.16, N = 3 SE +/- 0.29, N = 3 SE +/- 0.61, N = 3 SE +/- 0.23, N = 3 SE +/- 0.46, N = 3 SE +/- 0.22, N = 3 SE +/- 0.16, N = 3 SE +/- 0.27, N = 3 SE +/- 0.14, N = 3 457.27 437.31 416.96 406.93 367.19 361.72 349.99 328.54 245.60 244.17 239.84 203.40 168.17 150.43 MIN: 225.33 / MAX: 494.73 MIN: 217.67 / MAX: 473.18 MIN: 251.44 / MAX: 465 MIN: 257.69 / MAX: 456.39 MIN: 288.65 / MAX: 424.55 MIN: 287.95 / MAX: 416.23 MIN: 266.02 / MAX: 399.72 MIN: 249.05 / MAX: 376.65 MIN: 210.68 / MAX: 281.84 MIN: 200.55 / MAX: 270.42 MIN: 211 / MAX: 275.93 MIN: 187.66 / MAX: 232.21 MIN: 157.91 / MAX: 191.26 MIN: 141.09 / MAX: 170.16 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 7662 EPYC 7542 EPYC 7552 EPYC 7502P EPYC 7642 EPYC 7702 EPYC 7402P EPYC 7282 EPYC 7532 EPYC 7302P EPYC 7272 EPYC 7232P EPYC 7F52 EPYC 7F32 1.107 2.214 3.321 4.428 5.535 4.92 4.91 4.65 4.62 4.61 4.45 4.14 3.73 3.54 3.32 3.13 2.51 2.06 2.00
Result Confidence
OpenBenchmarking.org FPS, More Is Better dav1d 0.8.1 Video Input: Summer Nature 4K EPYC 7662 EPYC 7702 EPYC 7642 EPYC 7552 EPYC 7542 EPYC 7502P EPYC 7532 EPYC 7402P EPYC 7302P EPYC 7F52 EPYC 7282 EPYC 7272 EPYC 7F32 EPYC 7232P 80 160 240 320 400 Min: 455.84 / Avg: 457.27 / Max: 458.3 Min: 436.66 / Avg: 437.31 / Max: 437.79 Min: 416.77 / Avg: 416.96 / Max: 417.29 Min: 405.7 / Avg: 406.93 / Max: 407.97 Min: 365.83 / Avg: 367.19 / Max: 368.43 Min: 361.4 / Avg: 361.72 / Max: 361.91 Min: 349.42 / Avg: 349.99 / Max: 350.39 Min: 327.42 / Avg: 328.54 / Max: 329.53 Min: 245.22 / Avg: 245.6 / Max: 246 Min: 243.51 / Avg: 244.17 / Max: 245.05 Min: 239.57 / Avg: 239.84 / Max: 240.27 Min: 203.1 / Avg: 203.4 / Max: 203.66 Min: 167.67 / Avg: 168.17 / Max: 168.6 Min: 150.28 / Avg: 150.43 / Max: 150.7 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 7662 EPYC 7642 EPYC 7702 EPYC 7552 EPYC 7542 EPYC 7502P EPYC 7532 EPYC 7402P EPYC 7F52 EPYC 7302P EPYC 7282 EPYC 7272 EPYC 7F32 EPYC 7232P 9 18 27 36 45 SE +/- 0.01, N = 4 SE +/- 0.03, N = 4 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 +/- 0.05, 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 39.15 37.39 36.07 35.81 35.06 33.25 32.72 26.61 26.31 22.94 21.70 17.83 15.56 12.98 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 7662 EPYC 7502P EPYC 7552 EPYC 7542 EPYC 7702 EPYC 7642 EPYC 7282 EPYC 7532 EPYC 7302P EPYC 7402P EPYC 7272 EPYC 7232P EPYC 7F32 EPYC 7F52 0.0608 0.1216 0.1824 0.2432 0.304 0.27 0.26 0.26 0.25 0.25 0.24 0.24 0.23 0.21 0.21 0.19 0.17 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 7662 EPYC 7642 EPYC 7702 EPYC 7552 EPYC 7542 EPYC 7502P EPYC 7532 EPYC 7402P EPYC 7F52 EPYC 7302P EPYC 7282 EPYC 7272 EPYC 7F32 EPYC 7232P 8 16 24 32 40 Min: 39.12 / Avg: 39.15 / Max: 39.19 Min: 37.31 / Avg: 37.39 / Max: 37.44 Min: 36 / Avg: 36.07 / Max: 36.11 Min: 35.77 / Avg: 35.81 / Max: 35.84 Min: 35.04 / Avg: 35.06 / Max: 35.09 Min: 33.24 / Avg: 33.25 / Max: 33.26 Min: 32.69 / Avg: 32.72 / Max: 32.73 Min: 26.56 / Avg: 26.61 / Max: 26.7 Min: 26.29 / Avg: 26.31 / Max: 26.33 Min: 22.92 / Avg: 22.94 / Max: 22.97 Min: 21.66 / Avg: 21.7 / Max: 21.75 Min: 17.82 / Avg: 17.83 / Max: 17.84 Min: 15.54 / Avg: 15.56 / Max: 15.61 Min: 12.97 / Avg: 12.98 / Max: 12.99 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 7662 EPYC 7702 EPYC 7552 EPYC 7542 EPYC 7502P EPYC 7532 EPYC 7402P EPYC 7F52 EPYC 7302P EPYC 7282 EPYC 7272 EPYC 7F32 EPYC 7232P 9 18 27 36 45 SE +/- 0.00, N = 4 SE +/- 0.01, N = 4 SE +/- 0.01, N = 4 SE +/- 0.00, N = 4 SE +/- 0.02, N = 4 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 SE +/- 0.00, N = 3 SE +/- 0.00, N = 3 13.21 13.30 14.24 15.64 16.31 16.70 18.17 19.86 23.34 24.24 29.24 32.63 39.67 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 7662 EPYC 7702 EPYC 7552 EPYC 7542 EPYC 7502P EPYC 7532 EPYC 7402P EPYC 7F52 EPYC 7302P EPYC 7282 EPYC 7272 EPYC 7F32 EPYC 7232P 8 16 24 32 40 Min: 13.2 / Avg: 13.21 / Max: 13.22 Min: 13.28 / Avg: 13.3 / Max: 13.33 Min: 14.23 / Avg: 14.24 / Max: 14.25 Min: 15.63 / Avg: 15.64 / Max: 15.64 Min: 16.28 / Avg: 16.31 / Max: 16.38 Min: 16.69 / Avg: 16.7 / Max: 16.71 Min: 18.16 / Avg: 18.17 / Max: 18.17 Min: 19.86 / Avg: 19.86 / Max: 19.87 Min: 23.32 / Avg: 23.34 / Max: 23.38 Min: 24.19 / Avg: 24.24 / Max: 24.27 Min: 29.23 / Avg: 29.24 / Max: 29.27 Min: 32.63 / Avg: 32.63 / Max: 32.64 Min: 39.66 / Avg: 39.67 / Max: 39.67 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 7532 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7552 EPYC 7F32 EPYC 7302P EPYC 7402P EPYC 7542 EPYC 7502P EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7F52 4K 8K 12K 16K 20K SE +/- 8.80, N = 3 SE +/- 29.81, N = 3 SE +/- 5.01, N = 3 SE +/- 34.52, N = 3 SE +/- 68.31, N = 3 SE +/- 8.04, N = 3 SE +/- 24.99, N = 3 SE +/- 5.98, N = 3 SE +/- 5.12, N = 3 SE +/- 22.39, N = 3 SE +/- 10.40, N = 3 SE +/- 16.20, N = 3 SE +/- 1.40, N = 3 SE +/- 66.01, N = 14 19645.40 19436.30 19256.70 19155.40 18424.10 17351.20 17082.40 16743.60 16649.70 16649.50 10156.60 10066.60 10003.60 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 7302P EPYC 7F32 EPYC 7402P EPYC 7542 EPYC 7532 EPYC 7502P EPYC 7552 EPYC 7232P EPYC 7662 EPYC 7642 EPYC 7702 EPYC 7272 EPYC 7282 EPYC 7F52 40 80 120 160 200 181.39 167.09 160.96 157.73 152.28 152.21 149.38 147.34 142.84 140.60 139.02 132.41 128.37 52.66
Result Confidence
OpenBenchmarking.org CG Mflops, More Is Better miniFE 2.2 Problem Size: Small EPYC 7532 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7552 EPYC 7F32 EPYC 7302P EPYC 7402P EPYC 7542 EPYC 7502P EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7F52 3K 6K 9K 12K 15K Min: 19632.2 / Avg: 19645.43 / Max: 19662.1 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: 18336.1 / Avg: 18424.1 / Max: 18558.6 Min: 17335.9 / Avg: 17351.17 / Max: 17363.2 Min: 17033.7 / Avg: 17082.43 / Max: 17116.4 Min: 16735 / Avg: 16743.6 / Max: 16755.1 Min: 16643.8 / Avg: 16649.7 / Max: 16659.9 Min: 16604.7 / Avg: 16649.47 / Max: 16672.4 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: 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 7542 EPYC 7502P EPYC 7532 EPYC 7402P EPYC 7F52 EPYC 7642 EPYC 7552 EPYC 7662 EPYC 7302P EPYC 7702 EPYC 7282 EPYC 7272 EPYC 7F32 EPYC 7232P 0.7576 1.5152 2.2728 3.0304 3.788 SE +/- 0.00302, N = 4 SE +/- 0.00119, N = 4 SE +/- 0.00172, N = 4 SE +/- 0.00089, N = 4 SE +/- 0.00643, N = 4 SE +/- 0.00473, N = 4 SE +/- 0.01048, N = 4 SE +/- 0.01452, N = 4 SE +/- 0.00055, N = 4 SE +/- 0.01081, N = 4 SE +/- 0.00098, N = 4 SE +/- 0.00157, N = 4 SE +/- 0.00055, N = 4 SE +/- 0.00108, N = 4 1.16402 1.18204 1.21230 1.43487 1.52143 1.66750 1.73007 1.74199 1.74975 1.80598 1.80647 2.43760 2.79034 3.36727 MIN: 1.12 MIN: 1.13 MIN: 1.14 MIN: 1.4 MIN: 1.48 MIN: 1.4 MIN: 1.5 MIN: 1.45 MIN: 1.72 MIN: 1.54 MIN: 1.75 MIN: 2.4 MIN: 2.71 MIN: 3.3 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 7542 EPYC 7502P EPYC 7532 EPYC 7402P EPYC 7F52 EPYC 7642 EPYC 7552 EPYC 7662 EPYC 7302P EPYC 7702 EPYC 7282 EPYC 7272 EPYC 7F32 EPYC 7232P 2 4 6 8 10 Min: 1.16 / Avg: 1.16 / Max: 1.17 Min: 1.18 / Avg: 1.18 / Max: 1.19 Min: 1.21 / Avg: 1.21 / Max: 1.22 Min: 1.43 / Avg: 1.43 / Max: 1.44 Min: 1.51 / Avg: 1.52 / Max: 1.54 Min: 1.65 / Avg: 1.67 / Max: 1.67 Min: 1.72 / Avg: 1.73 / Max: 1.76 Min: 1.72 / Avg: 1.74 / Max: 1.78 Min: 1.75 / Avg: 1.75 / Max: 1.75 Min: 1.78 / Avg: 1.81 / Max: 1.83 Min: 1.8 / Avg: 1.81 / Max: 1.81 Min: 2.43 / Avg: 2.44 / Max: 2.44 Min: 2.79 / Avg: 2.79 / Max: 2.79 Min: 3.37 / Avg: 3.37 / Max: 3.37 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 7552 EPYC 7542 EPYC 7662 EPYC 7702 EPYC 7642 EPYC 7502P EPYC 7402P EPYC 7532 EPYC 7282 EPYC 7302P EPYC 7F52 EPYC 7272 EPYC 7F32 EPYC 7232P 40 80 120 160 200 SE +/- 0.43, N = 14 SE +/- 0.43, N = 3 SE +/- 0.74, N = 3 SE +/- 0.72, N = 15 SE +/- 0.60, N = 15 SE +/- 0.38, N = 3 SE +/- 1.05, N = 3 SE +/- 0.21, N = 3 SE +/- 1.06, N = 3 SE +/- 1.37, N = 3 SE +/- 1.73, N = 3 SE +/- 0.80, N = 3 SE +/- 0.41, N = 3 SE +/- 0.97, N = 3 64.88 64.92 66.48 67.25 67.66 70.70 80.50 85.56 102.53 110.94 127.45 131.03 172.35 186.18 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 7552 EPYC 7542 EPYC 7662 EPYC 7702 EPYC 7642 EPYC 7502P EPYC 7402P EPYC 7532 EPYC 7282 EPYC 7302P EPYC 7F52 EPYC 7272 EPYC 7F32 EPYC 7232P 30 60 90 120 150 Min: 61.7 / Avg: 64.88 / Max: 67.09 Min: 64.15 / Avg: 64.92 / Max: 65.62 Min: 65.27 / Avg: 66.48 / Max: 67.84 Min: 61.8 / Avg: 67.25 / Max: 71.05 Min: 64.7 / Avg: 67.66 / Max: 71.97 Min: 69.95 / Avg: 70.7 / Max: 71.18 Min: 79.1 / Avg: 80.5 / Max: 82.54 Min: 85.16 / Avg: 85.56 / Max: 85.86 Min: 100.59 / Avg: 102.53 / Max: 104.24 Min: 108.85 / Avg: 110.94 / Max: 113.51 Min: 124 / Avg: 127.45 / Max: 129.28 Min: 129.53 / Avg: 131.03 / Max: 132.24 Min: 171.56 / Avg: 172.35 / Max: 172.91 Min: 184.7 / Avg: 186.18 / Max: 188.01 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 7662 EPYC 7642 EPYC 7552 EPYC 7702 EPYC 7542 EPYC 7502P EPYC 7402P EPYC 7532 EPYC 7282 EPYC 7302P EPYC 7F52 EPYC 7272 EPYC 7F32 EPYC 7232P 13K 26K 39K 52K 65K SE +/- 229.52, N = 3 SE +/- 539.78, N = 3 SE +/- 709.54, N = 3 SE +/- 486.09, N = 3 SE +/- 676.58, N = 3 SE +/- 406.89, N = 15 SE +/- 387.48, N = 3 SE +/- 174.06, N = 3 SE +/- 309.38, N = 15 SE +/- 447.90, N = 12 SE +/- 337.73, N = 15 SE +/- 91.21, N = 3 SE +/- 63.04, N = 3 SE +/- 18.98, N = 3 60949 58889 56945 55699 52325 51794 47662 47615 38586 38458 37152 31896 24137 21334 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 7662 EPYC 7642 EPYC 7552 EPYC 7702 EPYC 7542 EPYC 7502P EPYC 7402P EPYC 7532 EPYC 7282 EPYC 7302P EPYC 7F52 EPYC 7272 EPYC 7F32 EPYC 7232P 11K 22K 33K 44K 55K Min: 60636.54 / Avg: 60949.34 / Max: 61396.7 Min: 57853.09 / Avg: 58888.92 / Max: 59670.2 Min: 55594.88 / Avg: 56944.6 / Max: 57999 Min: 54882.69 / Avg: 55699.33 / Max: 56564.47 Min: 51433.97 / Avg: 52325.08 / Max: 53652.51 Min: 49652.94 / Avg: 51793.61 / Max: 54520.15 Min: 47265.69 / Avg: 47661.51 / Max: 48436.42 Min: 47424.2 / Avg: 47614.55 / Max: 47962.14 Min: 36728.54 / Avg: 38586.13 / Max: 40215.78 Min: 36956.38 / Avg: 38457.92 / Max: 41415.74 Min: 35001.56 / Avg: 37152.01 / Max: 39986.56 Min: 31714.82 / Avg: 31895.88 / Max: 32005.63 Min: 24025.48 / Avg: 24137.33 / Max: 24243.66 Min: 21301.63 / Avg: 21333.63 / Max: 21367.31 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 7662 EPYC 7702 EPYC 7642 EPYC 7552 EPYC 7542 EPYC 7502P EPYC 7532 EPYC 7402P EPYC 7F52 EPYC 7302P EPYC 7282 EPYC 7272 EPYC 7F32 EPYC 7232P 15 30 45 60 75 SE +/- 0.02, N = 3 SE +/- 0.06, N = 3 SE +/- 0.02, N = 3 SE +/- 0.03, N = 3 SE +/- 0.02, N = 3 SE +/- 0.03, N = 3 SE +/- 0.07, N = 3 SE +/- 0.03, N = 3 SE +/- 0.04, N = 3 SE +/- 0.06, N = 3 SE +/- 0.06, N = 3 SE +/- 0.10, N = 3 SE +/- 0.01, N = 3 SE +/- 0.06, N = 3 23.98 24.03 25.21 25.50 27.86 29.12 29.23 32.07 33.98 39.74 42.86 49.92 54.15 68.50
Result Confidence
OpenBenchmarking.org Seconds, Fewer Is Better Timed FFmpeg Compilation 4.2.2 Time To Compile EPYC 7662 EPYC 7702 EPYC 7642 EPYC 7552 EPYC 7542 EPYC 7502P EPYC 7532 EPYC 7402P EPYC 7F52 EPYC 7302P EPYC 7282 EPYC 7272 EPYC 7F32 EPYC 7232P 13 26 39 52 65 Min: 23.93 / Avg: 23.98 / Max: 24.01 Min: 23.95 / Avg: 24.03 / Max: 24.14 Min: 25.18 / Avg: 25.21 / Max: 25.25 Min: 25.47 / Avg: 25.5 / Max: 25.56 Min: 27.84 / Avg: 27.86 / Max: 27.89 Min: 29.07 / Avg: 29.12 / Max: 29.19 Min: 29.13 / Avg: 29.23 / Max: 29.37 Min: 32.01 / Avg: 32.07 / Max: 32.1 Min: 33.92 / Avg: 33.98 / Max: 34.07 Min: 39.64 / Avg: 39.74 / Max: 39.84 Min: 42.78 / Avg: 42.86 / Max: 42.98 Min: 49.75 / Avg: 49.92 / Max: 50.11 Min: 54.13 / Avg: 54.15 / Max: 54.16 Min: 68.42 / Avg: 68.5 / Max: 68.63
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 7662 EPYC 7642 EPYC 7552 EPYC 7702 EPYC 7542 EPYC 7502P EPYC 7402P EPYC 7532 EPYC 7282 EPYC 7302P EPYC 7F52 EPYC 7272 EPYC 7F32 EPYC 7232P 1.0553 2.1106 3.1659 4.2212 5.2765 SE +/- 0.006, N = 3 SE +/- 0.016, N = 3 SE +/- 0.022, N = 3 SE +/- 0.016, N = 3 SE +/- 0.024, N = 3 SE +/- 0.015, N = 15 SE +/- 0.017, N = 3 SE +/- 0.008, N = 3 SE +/- 0.021, N = 15 SE +/- 0.029, N = 12 SE +/- 0.024, N = 15 SE +/- 0.009, N = 3 SE +/- 0.011, N = 3 SE +/- 0.004, N = 3 1.643 1.701 1.759 1.798 1.915 1.935 2.101 2.103 2.596 2.606 2.697 3.137 4.145 4.690 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 7662 EPYC 7642 EPYC 7552 EPYC 7702 EPYC 7542 EPYC 7502P EPYC 7402P EPYC 7532 EPYC 7282 EPYC 7302P EPYC 7F52 EPYC 7272 EPYC 7F32 EPYC 7232P 2 4 6 8 10 Min: 1.63 / Avg: 1.64 / Max: 1.65 Min: 1.68 / Avg: 1.7 / Max: 1.73 Min: 1.73 / Avg: 1.76 / Max: 1.8 Min: 1.77 / Avg: 1.8 / Max: 1.82 Min: 1.87 / Avg: 1.91 / Max: 1.95 Min: 1.84 / Avg: 1.94 / Max: 2.02 Min: 2.07 / Avg: 2.1 / Max: 2.12 Min: 2.09 / Avg: 2.1 / Max: 2.11 Min: 2.49 / Avg: 2.6 / Max: 2.73 Min: 2.42 / Avg: 2.61 / Max: 2.71 Min: 2.5 / Avg: 2.7 / Max: 2.86 Min: 3.13 / Avg: 3.14 / Max: 3.16 Min: 4.13 / Avg: 4.14 / Max: 4.16 Min: 4.68 / Avg: 4.69 / Max: 4.7 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 7552 EPYC 7642 EPYC 7662 EPYC 7542 EPYC 7502P EPYC 7532 EPYC 7702 EPYC 7402P EPYC 7F52 EPYC 7282 EPYC 7302P EPYC 7272 EPYC 7F32 EPYC 7232P 200 400 600 800 1000 SE +/- 6.72, N = 12 SE +/- 12.71, N = 3 SE +/- 3.57, N = 3 SE +/- 1.67, N = 3 SE +/- 2.79, N = 3 SE +/- 3.72, N = 3 SE +/- 4.91, N = 3 SE +/- 2.84, N = 3 SE +/- 0.21, N = 3 SE +/- 1.34, N = 3 SE +/- 1.71, N = 3 SE +/- 0.85, N = 3 SE +/- 0.88, N = 3 SE +/- 0.73, N = 3 933.04 889.39 873.42 858.47 857.99 849.27 792.50 721.30 589.10 563.20 551.97 457.13 359.54 327.45 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 7542 EPYC 7502P EPYC 7282 EPYC 7552 EPYC 7402P EPYC 7532 EPYC 7302P EPYC 7272 EPYC 7642 EPYC 7662 EPYC 7232P EPYC 7702 EPYC 7F52 EPYC 7F32 3 6 9 12 15 9.07 8.75 8.15 8.10 7.79 7.17 7.06 6.96 6.80 6.31 5.67 5.54 4.63 4.41
Result Confidence
OpenBenchmarking.org FPS, More Is Better TTSIOD 3D Renderer 2.3b Phong Rendering With Soft-Shadow Mapping EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7542 EPYC 7502P EPYC 7532 EPYC 7702 EPYC 7402P EPYC 7F52 EPYC 7282 EPYC 7302P EPYC 7272 EPYC 7F32 EPYC 7232P 160 320 480 640 800 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: 855.29 / Avg: 858.47 / Max: 860.96 Min: 853.39 / Avg: 857.99 / Max: 863.04 Min: 843.53 / Avg: 849.27 / Max: 856.24 Min: 782.72 / Avg: 792.5 / Max: 798.09 Min: 716.79 / Avg: 721.3 / Max: 726.53 Min: 588.69 / Avg: 589.1 / Max: 589.38 Min: 561.8 / Avg: 563.2 / Max: 565.87 Min: 548.55 / Avg: 551.97 / Max: 553.8 Min: 455.79 / Avg: 457.13 / Max: 458.72 Min: 357.91 / Avg: 359.54 / Max: 360.93 Min: 326.51 / Avg: 327.45 / Max: 328.88 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 7662 EPYC 7642 EPYC 7702 EPYC 7552 EPYC 7542 EPYC 7502P EPYC 7532 EPYC 7402P EPYC 7F52 EPYC 7282 EPYC 7302P EPYC 7272 EPYC 7F32 EPYC 7232P 300 600 900 1200 1500 SE +/- 3.75, N = 3 SE +/- 1.10, N = 3 SE +/- 1.60, N = 3 SE +/- 3.10, N = 3 SE +/- 0.47, N = 3 SE +/- 1.87, N = 3 SE +/- 1.15, N = 3 SE +/- 2.68, N = 3 SE +/- 1.44, N = 3 SE +/- 0.46, N = 3 SE +/- 0.73, N = 3 SE +/- 0.90, N = 3 SE +/- 0.28, N = 3 SE +/- 0.82, N = 3 1193.66 1070.09 1050.99 1044.25 937.44 932.75 880.57 847.40 651.36 644.23 634.51 555.11 453.36 419.19 MIN: 500.62 / MAX: 1329.43 MIN: 574.58 / MAX: 1186.8 MIN: 478.51 / MAX: 1166.67 MIN: 554.63 / MAX: 1157.48 MIN: 659.51 / MAX: 1052.41 MIN: 659.65 / MAX: 1047.61 MIN: 567.79 / MAX: 985.57 MIN: 566.75 / MAX: 939.62 MIN: 480.87 / MAX: 706.63 MIN: 503.48 / MAX: 704.1 MIN: 482.67 / MAX: 693.38 MIN: 463.4 / MAX: 605.59 MIN: 400.76 / MAX: 488.59 MIN: 370.7 / MAX: 456.84 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 7542 EPYC 7502P EPYC 7662 EPYC 7552 EPYC 7642 EPYC 7402P EPYC 7702 EPYC 7282 EPYC 7272 EPYC 7532 EPYC 7302P EPYC 7232P EPYC 7F52 EPYC 7F32 4 8 12 16 20 16.36 15.80 15.54 15.42 14.70 14.37 13.08 12.88 11.35 11.30 10.93 8.74 7.40 7.06
Result Confidence
OpenBenchmarking.org FPS, More Is Better dav1d 0.8.1 Video Input: Summer Nature 1080p EPYC 7662 EPYC 7642 EPYC 7702 EPYC 7552 EPYC 7542 EPYC 7502P EPYC 7532 EPYC 7402P EPYC 7F52 EPYC 7282 EPYC 7302P EPYC 7272 EPYC 7F32 EPYC 7232P 200 400 600 800 1000 Min: 1186.16 / Avg: 1193.66 / Max: 1197.47 Min: 1068.71 / Avg: 1070.09 / Max: 1072.27 Min: 1048.15 / Avg: 1050.99 / Max: 1053.7 Min: 1038.12 / Avg: 1044.25 / Max: 1048.12 Min: 936.52 / Avg: 937.44 / Max: 938.02 Min: 929.58 / Avg: 932.75 / Max: 936.06 Min: 879.23 / Avg: 880.57 / Max: 882.86 Min: 842.07 / Avg: 847.4 / Max: 850.64 Min: 648.52 / Avg: 651.36 / Max: 653.25 Min: 643.31 / Avg: 644.23 / Max: 644.7 Min: 633.06 / Avg: 634.51 / Max: 635.27 Min: 553.68 / Avg: 555.11 / Max: 556.76 Min: 452.94 / Avg: 453.36 / Max: 453.9 Min: 417.79 / Avg: 419.19 / Max: 420.62 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 7662 EPYC 7552 EPYC 7642 EPYC 7542 EPYC 7502P EPYC 7702 EPYC 7402P EPYC 7532 EPYC 7302P EPYC 7282 EPYC 7F52 EPYC 7272 EPYC 7F32 EPYC 7232P 6 12 18 24 30 SE +/- 0.21, N = 3 SE +/- 0.06, N = 3 SE +/- 0.08, N = 3 SE +/- 0.07, N = 3 SE +/- 0.03, N = 3 SE +/- 0.08, N = 3 SE +/- 0.08, N = 3 SE +/- 0.05, N = 3 SE +/- 0.09, N = 3 SE +/- 0.04, N = 3 SE +/- 0.12, N = 3 SE +/- 0.07, N = 3 SE +/- 0.13, N = 4 SE +/- 0.09, N = 3 25.65 25.36 25.23 25.21 25.13 25.04 23.84 23.71 20.44 20.03 20.00 17.09 10.20 9.20 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 7282 EPYC 7542 EPYC 7502P EPYC 7552 EPYC 7402P EPYC 7662 EPYC 7272 EPYC 7302P EPYC 7642 EPYC 7532 EPYC 7702 EPYC 7232P EPYC 7F52 EPYC 7F32 0.0518 0.1036 0.1554 0.2072 0.259 0.23 0.23 0.22 0.21 0.21 0.20 0.20 0.20 0.18 0.18 0.18 0.14 0.12 0.11
Result Confidence
OpenBenchmarking.org Frames Per Second, More Is Better x265 3.4 Video Input: Bosphorus 4K EPYC 7662 EPYC 7552 EPYC 7642 EPYC 7542 EPYC 7502P EPYC 7702 EPYC 7402P EPYC 7532 EPYC 7302P EPYC 7282 EPYC 7F52 EPYC 7272 EPYC 7F32 EPYC 7232P 6 12 18 24 30 Min: 25.41 / Avg: 25.65 / Max: 26.06 Min: 25.3 / Avg: 25.36 / Max: 25.48 Min: 25.14 / Avg: 25.23 / Max: 25.39 Min: 25.09 / Avg: 25.21 / Max: 25.34 Min: 25.08 / Avg: 25.13 / Max: 25.16 Min: 24.94 / Avg: 25.04 / Max: 25.19 Min: 23.72 / Avg: 23.84 / Max: 23.98 Min: 23.64 / Avg: 23.71 / Max: 23.81 Min: 20.34 / Avg: 20.44 / Max: 20.61 Min: 19.97 / Avg: 20.03 / Max: 20.1 Min: 19.78 / Avg: 20 / Max: 20.2 Min: 16.96 / Avg: 17.09 / Max: 17.21 Min: 9.85 / Avg: 10.2 / Max: 10.45 Min: 9.07 / Avg: 9.2 / Max: 9.37 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 7642 EPYC 7662 EPYC 7552 EPYC 7702 EPYC 7542 EPYC 7502P EPYC 7532 EPYC 7402P EPYC 7F52 EPYC 7302P EPYC 7282 EPYC 7272 EPYC 7F32 EPYC 7232P 40 80 120 160 200 SE +/- 0.07, N = 3 SE +/- 0.17, N = 3 SE +/- 0.17, N = 3 SE +/- 0.31, N = 3 SE +/- 0.10, N = 3 SE +/- 0.17, N = 3 SE +/- 0.10, N = 3 SE +/- 0.12, N = 3 SE +/- 0.32, N = 3 SE +/- 0.07, N = 3 SE +/- 0.26, N = 3 SE +/- 0.14, N = 3 SE +/- 0.21, N = 3 SE +/- 0.30, N = 3 61.81 62.27 62.48 62.56 66.57 69.42 69.62 76.16 84.21 96.77 103.74 122.41 136.62 172.13
Result Confidence
OpenBenchmarking.org Seconds, Fewer Is Better Timed Godot Game Engine Compilation 3.2.3 Time To Compile EPYC 7642 EPYC 7662 EPYC 7552 EPYC 7702 EPYC 7542 EPYC 7502P EPYC 7532 EPYC 7402P EPYC 7F52 EPYC 7302P EPYC 7282 EPYC 7272 EPYC 7F32 EPYC 7232P 30 60 90 120 150 Min: 61.69 / Avg: 61.81 / Max: 61.9 Min: 61.99 / Avg: 62.27 / Max: 62.58 Min: 62.24 / Avg: 62.48 / Max: 62.81 Min: 62.22 / Avg: 62.56 / Max: 63.19 Min: 66.45 / Avg: 66.57 / Max: 66.76 Min: 69.16 / Avg: 69.42 / Max: 69.74 Min: 69.45 / Avg: 69.62 / Max: 69.79 Min: 75.93 / Avg: 76.16 / Max: 76.36 Min: 83.58 / Avg: 84.21 / Max: 84.54 Min: 96.64 / Avg: 96.77 / Max: 96.88 Min: 103.26 / Avg: 103.74 / Max: 104.13 Min: 122.19 / Avg: 122.41 / Max: 122.67 Min: 136.37 / Avg: 136.62 / Max: 137.03 Min: 171.71 / Avg: 172.13 / Max: 172.7
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 7662 EPYC 7702 EPYC 7642 EPYC 7552 EPYC 7542 EPYC 7532 EPYC 7502P EPYC 7402P EPYC 7F52 EPYC 7302P EPYC 7282 EPYC 7272 EPYC 7F32 EPYC 7232P 2 4 6 8 10 SE +/- 0.060, N = 3 SE +/- 0.003, N = 3 SE +/- 0.039, N = 4 SE +/- 0.012, N = 3 SE +/- 0.032, N = 4 SE +/- 0.048, N = 4 SE +/- 0.032, N = 3 SE +/- 0.043, N = 3 SE +/- 0.035, N = 4 SE +/- 0.017, N = 3 SE +/- 0.006, N = 3 SE +/- 0.008, N = 3 SE +/- 0.023, N = 3 SE +/- 0.008, N = 3 6.966 6.752 6.678 6.494 6.091 5.958 5.866 5.563 5.333 4.506 4.225 3.593 3.184 2.536 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 7642 EPYC 7542 EPYC 7502P EPYC 7662 EPYC 7552 EPYC 7702 EPYC 7532 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7272 EPYC 7232P EPYC 7F32 EPYC 7F52 0.0135 0.027 0.0405 0.054 0.0675 0.06 0.06 0.06 0.06 0.06 0.06 0.05 0.05 0.05 0.05 0.04 0.04 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 7662 EPYC 7702 EPYC 7642 EPYC 7552 EPYC 7542 EPYC 7532 EPYC 7502P EPYC 7402P EPYC 7F52 EPYC 7302P EPYC 7282 EPYC 7272 EPYC 7F32 EPYC 7232P 3 6 9 12 15 Min: 6.88 / Avg: 6.97 / Max: 7.08 Min: 6.75 / Avg: 6.75 / Max: 6.76 Min: 6.57 / Avg: 6.68 / Max: 6.75 Min: 6.47 / Avg: 6.49 / Max: 6.51 Min: 6.04 / Avg: 6.09 / Max: 6.18 Min: 5.88 / Avg: 5.96 / Max: 6.09 Min: 5.8 / Avg: 5.87 / Max: 5.91 Min: 5.48 / Avg: 5.56 / Max: 5.61 Min: 5.23 / Avg: 5.33 / Max: 5.39 Min: 4.47 / Avg: 4.51 / Max: 4.53 Min: 4.22 / Avg: 4.23 / Max: 4.24 Min: 3.58 / Avg: 3.59 / Max: 3.61 Min: 3.14 / Avg: 3.18 / Max: 3.21 Min: 2.52 / Avg: 2.54 / Max: 2.55 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 7662 EPYC 7642 EPYC 7702 EPYC 7552 EPYC 7542 EPYC 7502P EPYC 7532 EPYC 7402P EPYC 7F52 EPYC 7302P EPYC 7282 EPYC 7272 EPYC 7F32 EPYC 7232P 50 100 150 200 250 SE +/- 1.83, N = 15 SE +/- 1.24, N = 15 SE +/- 1.78, N = 15 SE +/- 1.18, N = 15 SE +/- 0.83, N = 9 SE +/- 1.00, N = 9 SE +/- 0.75, N = 9 SE +/- 0.75, N = 9 SE +/- 0.76, N = 9 SE +/- 0.59, N = 8 SE +/- 0.71, N = 8 SE +/- 0.60, N = 7 SE +/- 0.33, N = 7 SE +/- 0.37, N = 6 210.69 203.74 198.58 198.00 188.45 182.42 181.15 174.63 173.50 150.45 142.37 117.14 95.50 78.21 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 7542 EPYC 7502P EPYC 7552 EPYC 7662 EPYC 7282 EPYC 7402P EPYC 7642 EPYC 7702 EPYC 7302P EPYC 7532 EPYC 7272 EPYC 7F52 EPYC 7232P EPYC 7F32 0.5355 1.071 1.6065 2.142 2.6775 2.38 2.32 2.30 2.22 2.16 2.12 2.08 2.06 2.01 1.93 1.74 1.47 1.31 1.14
Result Confidence
OpenBenchmarking.org Frames Per Second, More Is Better x264 2019-12-17 H.264 Video Encoding EPYC 7662 EPYC 7642 EPYC 7702 EPYC 7552 EPYC 7542 EPYC 7502P EPYC 7532 EPYC 7402P EPYC 7F52 EPYC 7302P EPYC 7282 EPYC 7272 EPYC 7F32 EPYC 7232P 40 80 120 160 200 Min: 187.36 / Avg: 210.69 / Max: 218.31 Min: 187.17 / Avg: 203.74 / Max: 207.43 Min: 179.11 / Avg: 198.58 / Max: 206.01 Min: 182.68 / Avg: 198 / Max: 201.65 Min: 183.08 / Avg: 188.45 / Max: 190.79 Min: 175.43 / Avg: 182.42 / Max: 186.12 Min: 175.43 / Avg: 181.15 / Max: 183.15 Min: 169.05 / Avg: 174.63 / Max: 176.72 Min: 167.66 / Avg: 173.5 / Max: 175.1 Min: 146.52 / Avg: 150.45 / Max: 151.9 Min: 137.77 / Avg: 142.37 / Max: 143.62 Min: 113.91 / Avg: 117.14 / Max: 119.03 Min: 94.18 / Avg: 95.5 / Max: 96.44 Min: 76.63 / Avg: 78.21 / Max: 79.16 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 7542 EPYC 7532 EPYC 7502P EPYC 7642 EPYC 7662 EPYC 7552 EPYC 7702 EPYC 7402P EPYC 7F52 EPYC 7302P EPYC 7282 EPYC 7272 EPYC 7F32 EPYC 7232P 50K 100K 150K 200K 250K SE +/- 115.93, N = 3 SE +/- 115.78, N = 3 SE +/- 797.17, N = 15 SE +/- 34.51, N = 3 SE +/- 833.99, N = 6 SE +/- 275.99, N = 3 SE +/- 718.53, N = 15 SE +/- 414.30, N = 3 SE +/- 244.85, N = 3 SE +/- 652.17, N = 3 SE +/- 183.23, N = 3 SE +/- 219.52, N = 3 SE +/- 54.60, N = 3 SE +/- 42.10, N = 3 79313.6 84263.5 85462.8 86140.6 88093.7 92153.2 95873.7 105046.0 126743.0 144445.0 151235.0 177540.0 177928.0 212253.0
Result Confidence
OpenBenchmarking.org Microseconds, Fewer Is Better TensorFlow Lite 2020-08-23 Model: NASNet Mobile EPYC 7542 EPYC 7532 EPYC 7502P EPYC 7642 EPYC 7662 EPYC 7552 EPYC 7702 EPYC 7402P EPYC 7F52 EPYC 7302P EPYC 7282 EPYC 7272 EPYC 7F32 EPYC 7232P 40K 80K 120K 160K 200K Min: 79189.4 / Avg: 79313.63 / Max: 79545.3 Min: 84034.6 / Avg: 84263.47 / Max: 84408.4 Min: 82675.3 / Avg: 85462.75 / Max: 91289.3 Min: 86071.8 / Avg: 86140.57 / Max: 86180.1 Min: 85520.1 / Avg: 88093.72 / Max: 91636.7 Min: 91707.3 / Avg: 92153.17 / Max: 92657.9 Min: 91993.6 / Avg: 95873.69 / Max: 100262 Min: 104457 / Avg: 105045.67 / Max: 105845 Min: 126253 / Avg: 126742.67 / Max: 126993 Min: 143270 / Avg: 144444.67 / Max: 145523 Min: 150900 / Avg: 151235.33 / Max: 151531 Min: 177299 / Avg: 177539.67 / Max: 177978 Min: 177860 / Avg: 177928 / Max: 178036 Min: 212188 / Avg: 212253.33 / Max: 212332
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 7642 EPYC 7662 EPYC 7542 EPYC 7552 EPYC 7502P EPYC 7532 EPYC 7702 EPYC 7402P EPYC 7F52 EPYC 7302P EPYC 7282 EPYC 7272 EPYC 7F32 EPYC 7232P 13 26 39 52 65 SE +/- 0.16, N = 5 SE +/- 0.44, N = 5 SE +/- 0.05, N = 5 SE +/- 0.48, N = 5 SE +/- 0.05, N = 5 SE +/- 0.03, N = 5 SE +/- 0.54, N = 5 SE +/- 0.05, N = 4 SE +/- 0.02, N = 4 SE +/- 0.03, N = 4 SE +/- 0.03, N = 4 SE +/- 0.05, N = 3 SE +/- 0.04, N = 3 SE +/- 0.02, N = 3 59.59 58.64 56.98 55.99 54.92 54.07 53.52 48.33 47.17 41.52 39.65 31.39 27.16 23.11 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 7542 EPYC 7502P EPYC 7282 EPYC 7552 EPYC 7662 EPYC 7702 EPYC 7642 EPYC 7532 EPYC 7302P EPYC 7402P EPYC 7272 EPYC 7232P EPYC 7F52 EPYC 7F32 0.1058 0.2116 0.3174 0.4232 0.529 0.47 0.47 0.45 0.43 0.42 0.41 0.40 0.40 0.40 0.40 0.35 0.31 0.26 0.24
Result Confidence
OpenBenchmarking.org Frames Per Second, More Is Better Kvazaar 2.0 Video Input: Bosphorus 4K - Video Preset: Ultra Fast EPYC 7642 EPYC 7662 EPYC 7542 EPYC 7552 EPYC 7502P EPYC 7532 EPYC 7702 EPYC 7402P EPYC 7F52 EPYC 7302P EPYC 7282 EPYC 7272 EPYC 7F32 EPYC 7232P 12 24 36 48 60 Min: 59.13 / Avg: 59.59 / Max: 59.95 Min: 57.87 / Avg: 58.64 / Max: 60.27 Min: 56.85 / Avg: 56.98 / Max: 57.12 Min: 55.17 / Avg: 55.99 / Max: 57.85 Min: 54.78 / Avg: 54.92 / Max: 55.03 Min: 54 / Avg: 54.07 / Max: 54.14 Min: 52.03 / Avg: 53.52 / Max: 54.9 Min: 48.24 / Avg: 48.33 / Max: 48.45 Min: 47.11 / Avg: 47.17 / Max: 47.21 Min: 41.47 / Avg: 41.52 / Max: 41.57 Min: 39.58 / Avg: 39.65 / Max: 39.69 Min: 31.34 / Avg: 31.39 / Max: 31.49 Min: 27.11 / Avg: 27.16 / Max: 27.23 Min: 23.08 / Avg: 23.11 / Max: 23.14 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 7282 EPYC 7272 EPYC 7542 EPYC 7502P EPYC 7552 EPYC 7662 EPYC 7702 EPYC 7232P EPYC 7402P EPYC 7532 EPYC 7F32 EPYC 7302P EPYC 7F52 2M 4M 6M 8M 10M SE +/- 11575.58, N = 5 SE +/- 1918.40, N = 5 SE +/- 8561.16, N = 5 SE +/- 5458.69, N = 5 SE +/- 14871.56, N = 5 SE +/- 35042.66, N = 5 SE +/- 11992.02, N = 5 SE +/- 12382.78, N = 5 SE +/- 6709.34, N = 5 SE +/- 61191.25, N = 15 SE +/- 717.93, N = 5 SE +/- 780.60, N = 5 SE +/- 17904.29, N = 5 7880986.59 7232205.30 6618850.24 6612746.50 6380400.35 6374595.12 6302136.65 5942474.37 5614019.49 4720934.26 4656182.26 4502591.45 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 7282 EPYC 7272 EPYC 7232P EPYC 7542 EPYC 7502P EPYC 7402P EPYC 7F32 EPYC 7302P EPYC 7552 EPYC 7662 EPYC 7702 EPYC 7532 EPYC 7F52 30K 60K 90K 120K 150K 162496.00 160055.91 141909.12 105418.49 103730.05 93633.65 84636.76 83787.81 80342.22 66221.01 62605.70 57649.40 37471.23
Result Confidence
OpenBenchmarking.org Events Per Second, More Is Better Sysbench 2018-07-28 Test: Memory EPYC 7282 EPYC 7272 EPYC 7542 EPYC 7502P EPYC 7552 EPYC 7662 EPYC 7702 EPYC 7232P EPYC 7402P EPYC 7532 EPYC 7F32 EPYC 7302P EPYC 7F52 1.4M 2.8M 4.2M 5.6M 7M Min: 7856776.88 / Avg: 7880986.59 / Max: 7920212.37 Min: 7225906.31 / Avg: 7232205.3 / Max: 7236184.18 Min: 6607713.8 / Avg: 6618850.24 / Max: 6652865.09 Min: 6604337.31 / Avg: 6612746.5 / Max: 6634214.25 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: 5895950.69 / Avg: 5942474.37 / Max: 5962905.57 Min: 5602311.72 / Avg: 5614019.49 / Max: 5638809.43 Min: 4407088.34 / Avg: 4720934.26 / Max: 5255661.79 Min: 4654731.01 / Avg: 4656182.26 / Max: 4658759.57 Min: 4500022.71 / Avg: 4502591.45 / Max: 4504708.71 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 7662 EPYC 7702 EPYC 7532 EPYC 7542 EPYC 7502P EPYC 7302P EPYC 7282 EPYC 7F32 EPYC 7F52 EPYC 7232P 12K 24K 36K 48K 60K SE +/- 50.60, N = 5 SE +/- 40.27, N = 5 SE +/- 17.78, N = 5 SE +/- 17.91, N = 5 SE +/- 36.50, N = 5 SE +/- 19.15, N = 4 SE +/- 23.10, N = 4 SE +/- 10.84, N = 4 SE +/- 44.41, N = 3 SE +/- 23.87, N = 3 55668.63 55136.50 49235.92 47098.22 46206.33 37175.20 29526.97 27284.69 22117.17 21822.06 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 7502P EPYC 7542 EPYC 7662 EPYC 7702 EPYC 7302P EPYC 7532 EPYC 7282 EPYC 7232P EPYC 7F32 EPYC 7F52 100 200 300 400 500 440.80 436.08 419.28 399.60 398.01 395.37 373.22 297.55 260.77 153.51
Result Confidence
OpenBenchmarking.org Total Mop/s, More Is Better NAS Parallel Benchmarks 3.4 Test / Class: FT.C EPYC 7662 EPYC 7702 EPYC 7532 EPYC 7542 EPYC 7502P EPYC 7302P EPYC 7282 EPYC 7F32 EPYC 7F52 EPYC 7232P 10K 20K 30K 40K 50K Min: 55491.76 / Avg: 55668.63 / Max: 55799.49 Min: 55002.69 / Avg: 55136.5 / Max: 55211.78 Min: 49168.13 / Avg: 49235.92 / Max: 49272.59 Min: 47048.85 / Avg: 47098.22 / Max: 47153.11 Min: 46062.44 / Avg: 46206.33 / Max: 46260.89 Min: 37140.1 / Avg: 37175.2 / Max: 37216.01 Min: 29462.38 / Avg: 29526.97 / Max: 29571 Min: 27272.21 / Avg: 27284.69 / Max: 27317.11 Min: 22040.65 / Avg: 22117.17 / Max: 22194.48 Min: 21777.28 / Avg: 21822.06 / Max: 21858.76 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 7532 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7552 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7542 EPYC 7F32 EPYC 7272 EPYC 7282 EPYC 7232P EPYC 7F52 4 8 12 16 20 SE +/- 0.00249, N = 3 SE +/- 0.00479, N = 3 SE +/- 0.00378, N = 3 SE +/- 0.03096, N = 3 SE +/- 0.00667, N = 3 SE +/- 0.07483, N = 3 SE +/- 0.01008, N = 3 SE +/- 0.00324, N = 3 SE +/- 0.00275, N = 3 SE +/- 0.06375, N = 3 SE +/- 0.00448, N = 3 SE +/- 0.00263, N = 3 SE +/- 0.00542, N = 3 SE +/- 0.05299, N = 11 17.96770 17.68500 17.38630 17.30750 16.64940 15.63290 15.56290 15.29200 15.27940 12.95600 9.09743 9.05154 8.64661 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 7302P EPYC 7542 EPYC 7402P EPYC 7F32 EPYC 7502P EPYC 7272 EPYC 7232P EPYC 7642 EPYC 7532 EPYC 7282 EPYC 7552 EPYC 7662 EPYC 7702 EPYC 7F52 0.0315 0.063 0.0945 0.126 0.1575 0.14 0.12 0.12 0.11 0.11 0.11 0.11 0.10 0.10 0.10 0.10 0.09 0.09 0.05
Result Confidence
OpenBenchmarking.org GFLOP/s, More Is Better High Performance Conjugate Gradient 3.1 EPYC 7532 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7552 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7542 EPYC 7F32 EPYC 7272 EPYC 7282 EPYC 7232P EPYC 7F52 5 10 15 20 25 Min: 17.96 / Avg: 17.97 / Max: 17.97 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: 16.64 / Avg: 16.65 / Max: 16.66 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: 15.28 / Avg: 15.28 / Max: 15.28 Min: 12.86 / Avg: 12.96 / Max: 13.08 Min: 9.09 / Avg: 9.1 / Max: 9.1 Min: 9.05 / Avg: 9.05 / Max: 9.05 Min: 8.64 / Avg: 8.65 / Max: 8.66 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 7662 EPYC 7702 EPYC 7642 EPYC 7532 EPYC 7552 EPYC 7302P EPYC 7402P EPYC 7542 EPYC 7502P EPYC 7F32 EPYC 7F52 EPYC 7282 EPYC 7272 EPYC 7232P 120 240 360 480 600 SE +/- 0.24, N = 3 SE +/- 0.04, N = 3 SE +/- 0.31, N = 3 SE +/- 0.57, N = 3 SE +/- 0.13, N = 3 SE +/- 0.15, N = 3 SE +/- 0.21, N = 3 SE +/- 0.59, N = 3 SE +/- 0.44, N = 3 SE +/- 0.36, N = 3 SE +/- 1.71, N = 3 SE +/- 0.84, N = 3 SE +/- 1.13, N = 3 SE +/- 0.29, N = 3 232.98 233.34 233.73 236.99 260.78 313.64 314.06 319.87 320.20 362.74 454.84 520.45 530.10 573.04 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 7662 EPYC 7702 EPYC 7642 EPYC 7532 EPYC 7552 EPYC 7302P EPYC 7402P EPYC 7542 EPYC 7502P EPYC 7F32 EPYC 7F52 EPYC 7282 EPYC 7272 EPYC 7232P 100 200 300 400 500 Min: 232.55 / Avg: 232.98 / Max: 233.38 Min: 233.29 / Avg: 233.34 / Max: 233.42 Min: 233.28 / Avg: 233.73 / Max: 234.33 Min: 235.98 / Avg: 236.99 / Max: 237.94 Min: 260.58 / Avg: 260.78 / Max: 261.02 Min: 313.39 / Avg: 313.64 / Max: 313.91 Min: 313.84 / Avg: 314.06 / Max: 314.48 Min: 319.1 / Avg: 319.87 / Max: 321.04 Min: 319.73 / Avg: 320.2 / Max: 321.08 Min: 362.09 / Avg: 362.74 / Max: 363.35 Min: 452.49 / Avg: 454.84 / Max: 458.16 Min: 518.85 / Avg: 520.45 / Max: 521.68 Min: 528.05 / Avg: 530.1 / Max: 531.94 Min: 572.49 / Avg: 573.04 / Max: 573.47 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 7662 EPYC 7642 EPYC 7552 EPYC 7702 EPYC 7542 EPYC 7502P EPYC 7532 EPYC 7402P EPYC 7282 EPYC 7302P EPYC 7F52 EPYC 7272 EPYC 7F32 EPYC 7232P 200 400 600 800 1000 SE +/- 2.82, N = 3 SE +/- 0.45, N = 3 SE +/- 2.26, N = 3 SE +/- 3.47, N = 3 SE +/- 0.52, N = 3 SE +/- 0.95, N = 3 SE +/- 2.20, N = 3 SE +/- 1.22, N = 3 SE +/- 0.66, N = 3 SE +/- 0.72, N = 3 SE +/- 1.86, N = 3 SE +/- 1.45, N = 3 SE +/- 0.38, N = 3 SE +/- 0.34, N = 3 1158.08 1116.83 1095.40 983.61 939.90 937.73 892.42 839.06 712.26 698.08 671.07 624.79 496.11 473.82 MIN: 644.06 / MAX: 1489.95 MIN: 672.49 / MAX: 1434.66 MIN: 671.87 / MAX: 1406.03 MIN: 616.84 / MAX: 1260.07 MIN: 689.36 / MAX: 1207.51 MIN: 687.68 / MAX: 1200.87 MIN: 641.23 / MAX: 1144.96 MIN: 646.27 / MAX: 1067.76 MIN: 546.18 / MAX: 898.36 MIN: 539.13 / MAX: 873.36 MIN: 524.48 / MAX: 829.64 MIN: 483.27 / MAX: 784.91 MIN: 390.79 / MAX: 704.31 MIN: 365.77 / MAX: 674.59 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 7542 EPYC 7502P EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7282 EPYC 7402P EPYC 7272 EPYC 7702 EPYC 7302P EPYC 7532 EPYC 7232P EPYC 7F52 EPYC 7F32 4 8 12 16 20 17.37 16.80 16.67 15.55 15.25 15.03 14.96 13.08 12.64 12.61 11.84 10.24 8.07 7.83
Result Confidence
OpenBenchmarking.org FPS, More Is Better dav1d 0.8.1 Video Input: Chimera 1080p EPYC 7662 EPYC 7642 EPYC 7552 EPYC 7702 EPYC 7542 EPYC 7502P EPYC 7532 EPYC 7402P EPYC 7282 EPYC 7302P EPYC 7F52 EPYC 7272 EPYC 7F32 EPYC 7232P 200 400 600 800 1000 Min: 1153.84 / Avg: 1158.08 / Max: 1163.42 Min: 1116.14 / Avg: 1116.83 / Max: 1117.68 Min: 1091.59 / Avg: 1095.4 / Max: 1099.4 Min: 977.12 / Avg: 983.61 / Max: 988.98 Min: 938.86 / Avg: 939.9 / Max: 940.47 Min: 935.96 / Avg: 937.73 / Max: 939.19 Min: 888.17 / Avg: 892.42 / Max: 895.56 Min: 837.5 / Avg: 839.06 / Max: 841.47 Min: 711 / Avg: 712.26 / Max: 713.24 Min: 697.03 / Avg: 698.08 / Max: 699.47 Min: 667.49 / Avg: 671.07 / Max: 673.75 Min: 622.12 / Avg: 624.79 / Max: 627.09 Min: 495.72 / Avg: 496.11 / Max: 496.87 Min: 473.15 / Avg: 473.82 / Max: 474.25 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 7662 EPYC 7532 EPYC 7702 EPYC 7302P EPYC 7F32 EPYC 7542 EPYC 7502P EPYC 7232P EPYC 7282 EPYC 7F52 11K 22K 33K 44K 55K SE +/- 122.43, N = 8 SE +/- 218.93, N = 8 SE +/- 224.56, N = 8 SE +/- 17.34, N = 8 SE +/- 20.16, N = 8 SE +/- 86.13, N = 8 SE +/- 76.06, N = 8 SE +/- 37.32, N = 7 SE +/- 23.57, N = 6 SE +/- 80.46, N = 5 52245.23 52022.76 51795.61 47349.29 45336.89 44205.80 44082.95 30311.94 29776.81 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 7302P EPYC 7F32 EPYC 7542 EPYC 7502P EPYC 7232P EPYC 7532 EPYC 7662 EPYC 7702 EPYC 7282 EPYC 7F52 140 280 420 560 700 660.02 592.89 555.62 538.87 525.61 520.26 490.40 476.11 463.71 197.31
Result Confidence
OpenBenchmarking.org Total Mop/s, More Is Better NAS Parallel Benchmarks 3.4 Test / Class: MG.C EPYC 7662 EPYC 7532 EPYC 7702 EPYC 7302P EPYC 7F32 EPYC 7542 EPYC 7502P EPYC 7232P EPYC 7282 EPYC 7F52 9K 18K 27K 36K 45K Min: 51776.39 / Avg: 52245.23 / Max: 52860.72 Min: 50688.93 / Avg: 52022.76 / Max: 52586.47 Min: 50825.97 / Avg: 51795.61 / Max: 52696.05 Min: 47278.3 / Avg: 47349.29 / Max: 47425.88 Min: 45233.69 / Avg: 45336.89 / Max: 45424.87 Min: 43844.26 / Avg: 44205.8 / Max: 44502.94 Min: 43772.91 / Avg: 44082.95 / Max: 44328.66 Min: 30136.45 / Avg: 30311.94 / Max: 30404.24 Min: 29684.13 / Avg: 29776.81 / Max: 29837.83 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 7542 EPYC 7502P EPYC 7532 EPYC 7642 EPYC 7402P EPYC 7552 EPYC 7662 EPYC 7702 EPYC 7F52 EPYC 7302P EPYC 7282 EPYC 7272 EPYC 7F32 EPYC 7232P 100 200 300 400 500 SE +/- 0.39, N = 3 SE +/- 0.52, N = 3 SE +/- 0.57, N = 3 SE +/- 0.73, N = 3 SE +/- 0.20, N = 3 SE +/- 1.22, N = 3 SE +/- 0.75, N = 3 SE +/- 0.50, N = 3 SE +/- 0.68, N = 3 SE +/- 0.25, N = 3 SE +/- 0.47, N = 3 SE +/- 0.37, N = 3 SE +/- 0.12, N = 3 SE +/- 1.04, N = 3 187.60 189.66 193.92 195.34 200.21 206.58 206.95 224.62 230.94 262.63 270.72 325.84 375.70 450.85 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 7542 EPYC 7502P EPYC 7532 EPYC 7642 EPYC 7402P EPYC 7552 EPYC 7662 EPYC 7702 EPYC 7F52 EPYC 7302P EPYC 7282 EPYC 7272 EPYC 7F32 EPYC 7232P 80 160 240 320 400 Min: 186.85 / Avg: 187.6 / Max: 188.17 Min: 188.81 / Avg: 189.66 / Max: 190.61 Min: 192.99 / Avg: 193.92 / Max: 194.97 Min: 194.23 / Avg: 195.34 / Max: 196.73 Min: 199.84 / Avg: 200.21 / Max: 200.55 Min: 204.79 / Avg: 206.58 / Max: 208.92 Min: 206.04 / Avg: 206.95 / Max: 208.44 Min: 224.11 / Avg: 224.62 / Max: 225.62 Min: 229.71 / Avg: 230.94 / Max: 232.08 Min: 262.32 / Avg: 262.63 / Max: 263.13 Min: 270.13 / Avg: 270.72 / Max: 271.65 Min: 325.11 / Avg: 325.84 / Max: 326.32 Min: 375.47 / Avg: 375.7 / Max: 375.88 Min: 449.53 / Avg: 450.85 / Max: 452.91 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 7532 EPYC 7302P EPYC 7662 EPYC 7702 EPYC 7542 EPYC 7502P EPYC 7F32 EPYC 7232P EPYC 7282 EPYC 7F52 4K 8K 12K 16K 20K SE +/- 25.61, N = 5 SE +/- 15.81, N = 5 SE +/- 27.38, N = 5 SE +/- 15.75, N = 5 SE +/- 30.70, N = 5 SE +/- 69.28, N = 5 SE +/- 18.04, N = 4 SE +/- 22.89, N = 4 SE +/- 18.07, N = 4 SE +/- 43.06, N = 3 18019.01 15688.57 15230.23 15079.08 14977.29 14759.40 12350.87 9844.95 9697.83 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 7302P EPYC 7542 EPYC 7532 EPYC 7232P EPYC 7502P EPYC 7F32 EPYC 7282 EPYC 7662 EPYC 7702 EPYC 7F52 40 80 120 160 200 159.36 137.33 137.30 136.77 129.34 120.79 119.50 107.24 103.87 56.39
Result Confidence
OpenBenchmarking.org Total Mop/s, More Is Better NAS Parallel Benchmarks 3.4 Test / Class: CG.C EPYC 7532 EPYC 7302P EPYC 7662 EPYC 7702 EPYC 7542 EPYC 7502P EPYC 7F32 EPYC 7232P EPYC 7282 EPYC 7F52 3K 6K 9K 12K 15K Min: 17953.88 / Avg: 18019.01 / Max: 18084.24 Min: 15654.67 / Avg: 15688.57 / Max: 15744.56 Min: 15146.06 / Avg: 15230.23 / Max: 15316.01 Min: 15027.23 / Avg: 15079.08 / Max: 15122.17 Min: 14873.66 / Avg: 14977.29 / Max: 15062.42 Min: 14524.99 / Avg: 14759.4 / Max: 14889.39 Min: 12309.98 / Avg: 12350.87 / Max: 12395.51 Min: 9819.42 / Avg: 9844.95 / Max: 9913.54 Min: 9644.91 / Avg: 9697.83 / Max: 9725.86 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 7F32 EPYC 7302P EPYC 7272 EPYC 7402P EPYC 7232P EPYC 7282 EPYC 7542 EPYC 7502P EPYC 7F52 EPYC 7532 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 8 16 24 32 40 SE +/- 0.10, N = 3 SE +/- 0.01, N = 3 SE +/- 0.28, N = 3 SE +/- 0.02, N = 3 SE +/- 0.03, N = 3 SE +/- 0.48, N = 3 SE +/- 0.12, N = 3 SE +/- 0.33, N = 3 SE +/- 0.27, N = 3 SE +/- 0.29, N = 11 SE +/- 0.14, N = 3 SE +/- 0.86, N = 12 SE +/- 1.29, N = 9 SE +/- 1.15, N = 9 16.32 16.83 17.58 17.64 17.87 18.84 19.94 20.35 21.84 21.93 23.97 27.68 34.00 36.76 MIN: 15.69 / MAX: 79.67 MIN: 16.42 / MAX: 20.42 MIN: 17.05 / MAX: 18.64 MIN: 17.29 / MAX: 30.94 MIN: 17.59 / MAX: 19.75 MIN: 17.66 / MAX: 132.29 MIN: 19.43 / MAX: 22.28 MIN: 19.39 / MAX: 62.1 MIN: 20.88 / MAX: 25.6 MIN: 20.32 / MAX: 95.63 MIN: 23.45 / MAX: 28.72 MIN: 23.41 / MAX: 138.56 MIN: 27.04 / MAX: 97.01 MIN: 28.46 / MAX: 174.17 1. (CXX) g++ options: -O3 -rdynamic -lgomp -lpthread
Result Confidence
OpenBenchmarking.org ms, Fewer Is Better NCNN 20201218 Target: CPU - Model: googlenet EPYC 7F32 EPYC 7302P EPYC 7272 EPYC 7402P EPYC 7232P EPYC 7282 EPYC 7542 EPYC 7502P EPYC 7F52 EPYC 7532 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 8 16 24 32 40 Min: 16.12 / Avg: 16.32 / Max: 16.47 Min: 16.81 / Avg: 16.83 / Max: 16.84 Min: 17.28 / Avg: 17.58 / Max: 18.13 Min: 17.62 / Avg: 17.64 / Max: 17.68 Min: 17.81 / Avg: 17.87 / Max: 17.93 Min: 18.11 / Avg: 18.84 / Max: 19.74 Min: 19.7 / Avg: 19.94 / Max: 20.06 Min: 19.9 / Avg: 20.35 / Max: 20.99 Min: 21.32 / Avg: 21.84 / Max: 22.24 Min: 20.81 / Avg: 21.93 / Max: 23.79 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 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 7662 EPYC 7702 EPYC 7642 EPYC 7532 EPYC 7552 EPYC 7542 EPYC 7502P EPYC 7402P EPYC 7F52 EPYC 7232P EPYC 7272 EPYC 7302P EPYC 7282 EPYC 7F32 5 10 15 20 25 SE +/- 0.030, N = 5 SE +/- 0.017, N = 5 SE +/- 0.074, N = 15 SE +/- 0.016, N = 5 SE +/- 0.119, N = 4 SE +/- 0.022, N = 4 SE +/- 0.007, N = 4 SE +/- 0.042, N = 4 SE +/- 0.049, N = 4 SE +/- 0.040, N = 4 SE +/- 0.079, N = 3 SE +/- 0.034, N = 3 SE +/- 0.159, N = 8 SE +/- 0.017, N = 3 8.905 8.928 9.185 9.913 12.027 14.316 14.320 14.761 15.049 15.540 16.895 17.729 18.189 19.707 1. (CXX) g++ options: -O2 -lOpenCL
Result Confidence
OpenBenchmarking.org Seconds, Fewer Is Better Rodinia 3.1 Test: OpenMP Streamcluster EPYC 7662 EPYC 7702 EPYC 7642 EPYC 7532 EPYC 7552 EPYC 7542 EPYC 7502P EPYC 7402P EPYC 7F52 EPYC 7232P EPYC 7272 EPYC 7302P EPYC 7282 EPYC 7F32 5 10 15 20 25 Min: 8.85 / Avg: 8.91 / Max: 9.02 Min: 8.9 / Avg: 8.93 / Max: 8.99 Min: 9.06 / Avg: 9.19 / Max: 10.22 Min: 9.88 / Avg: 9.91 / Max: 9.97 Min: 11.69 / Avg: 12.03 / Max: 12.26 Min: 14.25 / Avg: 14.32 / Max: 14.36 Min: 14.31 / Avg: 14.32 / Max: 14.34 Min: 14.65 / Avg: 14.76 / Max: 14.83 Min: 14.94 / Avg: 15.05 / Max: 15.15 Min: 15.47 / Avg: 15.54 / Max: 15.65 Min: 16.76 / Avg: 16.9 / Max: 17.03 Min: 17.66 / Avg: 17.73 / Max: 17.77 Min: 17.99 / Avg: 18.19 / Max: 19.3 Min: 19.68 / Avg: 19.71 / Max: 19.74 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 7702 EPYC 7662 EPYC 7642 EPYC 7552 EPYC 7542 EPYC 7532 EPYC 7502P EPYC 7402P EPYC 7F52 EPYC 7302P EPYC 7282 EPYC 7272 EPYC 7F32 EPYC 7232P 9 18 27 36 45 SE +/- 0.08, N = 3 SE +/- 0.10, N = 3 SE +/- 0.09, N = 3 SE +/- 0.09, N = 3 SE +/- 0.05, N = 3 SE +/- 0.06, N = 3 SE +/- 0.02, N = 3 SE +/- 0.07, N = 3 SE +/- 0.15, N = 3 SE +/- 0.04, N = 3 SE +/- 0.16, N = 3 SE +/- 0.02, N = 3 SE +/- 0.10, N = 3 SE +/- 0.17, N = 3 17.12 17.19 17.67 18.06 18.94 19.27 19.41 20.43 21.63 23.55 25.46 28.22 28.60 37.72
Result Confidence
OpenBenchmarking.org Seconds, Fewer Is Better Timed ImageMagick Compilation 6.9.0 Time To Compile EPYC 7702 EPYC 7662 EPYC 7642 EPYC 7552 EPYC 7542 EPYC 7532 EPYC 7502P EPYC 7402P EPYC 7F52 EPYC 7302P EPYC 7282 EPYC 7272 EPYC 7F32 EPYC 7232P 8 16 24 32 40 Min: 16.99 / Avg: 17.11 / Max: 17.27 Min: 16.99 / Avg: 17.19 / Max: 17.31 Min: 17.49 / Avg: 17.67 / Max: 17.79 Min: 17.88 / Avg: 18.06 / Max: 18.19 Min: 18.83 / Avg: 18.93 / Max: 19.02 Min: 19.16 / Avg: 19.27 / Max: 19.35 Min: 19.38 / Avg: 19.4 / Max: 19.45 Min: 20.3 / Avg: 20.43 / Max: 20.52 Min: 21.4 / Avg: 21.63 / Max: 21.91 Min: 23.47 / Avg: 23.55 / Max: 23.6 Min: 25.14 / Avg: 25.46 / Max: 25.64 Min: 28.17 / Avg: 28.22 / Max: 28.26 Min: 28.39 / Avg: 28.6 / Max: 28.73 Min: 37.4 / Avg: 37.72 / Max: 38.01
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 7F32 EPYC 7F52 EPYC 7232P EPYC 7302P EPYC 7272 EPYC 7402P EPYC 7282 EPYC 7542 EPYC 7502P EPYC 7532 EPYC 7642 EPYC 7552 EPYC 7662 EPYC 7702 900 1800 2700 3600 4500 SE +/- 19.31, N = 3 SE +/- 3.08, N = 3 SE +/- 14.48, N = 3 SE +/- 1.52, N = 3 SE +/- 9.26, N = 3 SE +/- 12.54, N = 3 SE +/- 7.78, N = 3 SE +/- 3.65, N = 3 SE +/- 1.04, N = 3 SE +/- 1.33, N = 3 SE +/- 2.50, N = 3 SE +/- 2.44, N = 3 SE +/- 0.31, N = 3 SE +/- 12.73, N = 3 1836.51 1976.70 2298.63 2414.74 2434.17 2507.58 2527.86 2579.79 2794.25 2815.80 3059.05 3325.99 3562.63 4029.98
Result Confidence
OpenBenchmarking.org ms, Fewer Is Better OpenVINO 2021.1 Model: Face Detection 0106 FP16 - Device: CPU EPYC 7F32 EPYC 7F52 EPYC 7232P EPYC 7302P EPYC 7272 EPYC 7402P EPYC 7282 EPYC 7542 EPYC 7502P EPYC 7532 EPYC 7642 EPYC 7552 EPYC 7662 EPYC 7702 700 1400 2100 2800 3500 Min: 1797.95 / Avg: 1836.51 / Max: 1857.52 Min: 1971.22 / Avg: 1976.7 / Max: 1981.88 Min: 2271.79 / Avg: 2298.63 / Max: 2321.46 Min: 2412.09 / Avg: 2414.74 / Max: 2417.36 Min: 2418.87 / Avg: 2434.17 / Max: 2450.86 Min: 2482.49 / Avg: 2507.58 / Max: 2520.14 Min: 2515.93 / Avg: 2527.86 / Max: 2542.47 Min: 2575.39 / Avg: 2579.79 / Max: 2587.03 Min: 2792.4 / Avg: 2794.25 / Max: 2795.99 Min: 2813.23 / Avg: 2815.8 / Max: 2817.7 Min: 3056.48 / Avg: 3059.05 / Max: 3064.04 Min: 3322.37 / Avg: 3325.99 / Max: 3330.62 Min: 3562.19 / Avg: 3562.63 / Max: 3563.22 Min: 4015.57 / Avg: 4029.98 / Max: 4055.36
Result
OpenBenchmarking.org ms, Fewer Is Better OpenVINO 2021.1 Model: Face Detection 0106 FP32 - Device: CPU EPYC 7F32 EPYC 7F52 EPYC 7232P EPYC 7272 EPYC 7302P EPYC 7282 EPYC 7402P EPYC 7542 EPYC 7502P EPYC 7532 EPYC 7642 EPYC 7552 EPYC 7662 EPYC 7702 900 1800 2700 3600 4500 SE +/- 14.55, N = 3 SE +/- 1.86, N = 3 SE +/- 17.95, N = 3 SE +/- 34.12, N = 3 SE +/- 2.67, N = 3 SE +/- 13.37, N = 3 SE +/- 3.50, N = 3 SE +/- 2.29, N = 3 SE +/- 0.81, N = 3 SE +/- 2.24, N = 3 SE +/- 1.92, N = 3 SE +/- 3.41, N = 3 SE +/- 0.45, N = 3 SE +/- 8.92, N = 3 1844.31 1980.56 2314.66 2406.22 2413.45 2446.02 2522.61 2572.36 2791.54 2814.15 3069.38 3327.50 3558.09 4030.53
Result Confidence
OpenBenchmarking.org ms, Fewer Is Better OpenVINO 2021.1 Model: Face Detection 0106 FP32 - Device: CPU EPYC 7F32 EPYC 7F52 EPYC 7232P EPYC 7272 EPYC 7302P EPYC 7282 EPYC 7402P EPYC 7542 EPYC 7502P EPYC 7532 EPYC 7642 EPYC 7552 EPYC 7662 EPYC 7702 700 1400 2100 2800 3500 Min: 1815.75 / Avg: 1844.31 / Max: 1863.4 Min: 1978.38 / Avg: 1980.56 / Max: 1984.26 Min: 2283.58 / Avg: 2314.66 / Max: 2345.75 Min: 2355.5 / Avg: 2406.22 / Max: 2471.13 Min: 2410.34 / Avg: 2413.45 / Max: 2418.77 Min: 2426.14 / Avg: 2446.02 / Max: 2471.46 Min: 2516.2 / Avg: 2522.61 / Max: 2528.27 Min: 2567.84 / Avg: 2572.36 / Max: 2575.2 Min: 2789.93 / Avg: 2791.54 / Max: 2792.44 Min: 2809.91 / Avg: 2814.15 / Max: 2817.55 Min: 3065.61 / Avg: 3069.38 / Max: 3071.93 Min: 3322.21 / Avg: 3327.5 / Max: 3333.86 Min: 3557.24 / Avg: 3558.09 / Max: 3558.76 Min: 4020.18 / Avg: 4030.53 / Max: 4048.29
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 7702 EPYC 7662 EPYC 7642 EPYC 7532 EPYC 7552 EPYC 7542 EPYC 7502P EPYC 7F32 EPYC 7402P EPYC 7302P EPYC 7282 EPYC 7272 EPYC 7F52 EPYC 7232P 3K 6K 9K 12K 15K SE +/- 146.93, N = 12 SE +/- 142.13, N = 3 SE +/- 58.13, N = 4 SE +/- 43.36, N = 4 SE +/- 60.62, N = 4 SE +/- 157.59, N = 4 SE +/- 131.70, N = 5 SE +/- 12.34, N = 6 SE +/- 9.05, N = 6 SE +/- 8.39, N = 6 SE +/- 15.52, N = 6 SE +/- 38.61, N = 6 SE +/- 40.17, N = 6 SE +/- 11.79, N = 6 14612.21 14603.33 14015.66 13938.25 13435.30 13099.62 12840.64 8720.88 8024.37 7954.15 6954.80 6871.93 6839.17 6757.99 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 7542 EPYC 7502P EPYC 7302P EPYC 7402P EPYC 7282 EPYC 7552 EPYC 7232P EPYC 7272 EPYC 7F32 EPYC 7532 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F52 30 60 90 120 150 125.40 123.94 122.94 122.19 119.53 118.64 117.45 116.78 114.72 113.53 109.48 95.62 91.64 69.83
Result Confidence
OpenBenchmarking.org z/s, More Is Better LULESH 2.0.3 EPYC 7702 EPYC 7662 EPYC 7642 EPYC 7532 EPYC 7552 EPYC 7542 EPYC 7502P EPYC 7F32 EPYC 7402P EPYC 7302P EPYC 7282 EPYC 7272 EPYC 7F52 EPYC 7232P 3K 6K 9K 12K 15K Min: 13024.64 / Avg: 14612.21 / Max: 14895.69 Min: 14340.08 / Avg: 14603.33 / Max: 14827.83 Min: 13885.31 / Avg: 14015.66 / Max: 14137.76 Min: 13879.03 / Avg: 13938.25 / Max: 14067.14 Min: 13262.26 / Avg: 13435.3 / Max: 13545.43 Min: 12632.05 / Avg: 13099.62 / Max: 13300.62 Min: 12361.8 / Avg: 12840.64 / Max: 13103.71 Min: 8666.52 / Avg: 8720.88 / Max: 8753.04 Min: 7986.3 / Avg: 8024.37 / Max: 8053.74 Min: 7941.34 / Avg: 7954.15 / Max: 7995.56 Min: 6907.71 / Avg: 6954.8 / Max: 7005.82 Min: 6730.47 / Avg: 6871.93 / Max: 6957.51 Min: 6733.72 / Avg: 6839.17 / Max: 6954.28 Min: 6718.89 / Avg: 6757.99 / Max: 6804.97 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 7F32 EPYC 7F52 EPYC 7232P EPYC 7302P EPYC 7272 EPYC 7542 EPYC 7402P EPYC 7282 EPYC 7502P EPYC 7532 EPYC 7642 EPYC 7552 EPYC 7662 EPYC 7702 1100 2200 3300 4400 5500 SE +/- 4.62, N = 3 SE +/- 1.31, N = 3 SE +/- 3.19, N = 3 SE +/- 5.57, N = 3 SE +/- 9.03, N = 3 SE +/- 2.78, N = 3 SE +/- 14.72, N = 3 SE +/- 2.79, N = 3 SE +/- 1.53, N = 3 SE +/- 10.25, N = 3 SE +/- 4.94, N = 3 SE +/- 5.33, N = 3 SE +/- 6.15, N = 3 SE +/- 6.77, N = 3 2399.19 2643.39 3071.91 3145.89 3264.49 3276.52 3310.91 3344.39 3578.09 3757.35 4132.13 4197.60 4731.72 5170.99
Result Confidence
OpenBenchmarking.org ms, Fewer Is Better OpenVINO 2021.1 Model: Person Detection 0106 FP16 - Device: CPU EPYC 7F32 EPYC 7F52 EPYC 7232P EPYC 7302P EPYC 7272 EPYC 7542 EPYC 7402P EPYC 7282 EPYC 7502P EPYC 7532 EPYC 7642 EPYC 7552 EPYC 7662 EPYC 7702 900 1800 2700 3600 4500 Min: 2393.6 / Avg: 2399.19 / Max: 2408.36 Min: 2641.61 / Avg: 2643.39 / Max: 2645.95 Min: 3065.98 / Avg: 3071.91 / Max: 3076.9 Min: 3138.42 / Avg: 3145.89 / Max: 3156.77 Min: 3253.32 / Avg: 3264.49 / Max: 3282.36 Min: 3273.17 / Avg: 3276.52 / Max: 3282.04 Min: 3286.85 / Avg: 3310.91 / Max: 3337.63 Min: 3340.81 / Avg: 3344.39 / Max: 3349.89 Min: 3576.1 / Avg: 3578.09 / Max: 3581.09 Min: 3741.86 / Avg: 3757.35 / Max: 3776.73 Min: 4122.78 / Avg: 4132.13 / Max: 4139.56 Min: 4187.64 / Avg: 4197.6 / Max: 4205.86 Min: 4723.88 / Avg: 4731.72 / Max: 4743.85 Min: 5162.09 / Avg: 5170.99 / Max: 5184.28
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 7662 EPYC 7532 EPYC 7702 EPYC 7542 EPYC 7502P EPYC 7302P EPYC 7282 EPYC 7F32 EPYC 7232P EPYC 7F52 400 800 1200 1600 2000 SE +/- 11.89, N = 3 SE +/- 1.95, N = 3 SE +/- 4.04, N = 3 SE +/- 5.74, N = 3 SE +/- 3.36, N = 3 SE +/- 2.26, N = 3 SE +/- 1.26, N = 3 SE +/- 5.70, N = 3 SE +/- 2.89, N = 3 SE +/- 9.24, N = 3 2006.81 1992.76 1971.50 1885.98 1884.31 1647.78 1422.07 1277.15 1083.36 934.00 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 7302P EPYC 7282 EPYC 7232P EPYC 7542 EPYC 7502P EPYC 7F32 EPYC 7532 EPYC 7662 EPYC 7702 EPYC 7F52 5 10 15 20 25 19.55 19.39 18.48 18.15 17.73 15.36 15.32 13.49 12.90 7.29
Result Confidence
OpenBenchmarking.org Total Mop/s, More Is Better NAS Parallel Benchmarks 3.4 Test / Class: IS.D EPYC 7662 EPYC 7532 EPYC 7702 EPYC 7542 EPYC 7502P EPYC 7302P EPYC 7282 EPYC 7F32 EPYC 7232P EPYC 7F52 300 600 900 1200 1500 Min: 1983.12 / Avg: 2006.81 / Max: 2020.44 Min: 1988.95 / Avg: 1992.76 / Max: 1995.4 Min: 1965.15 / Avg: 1971.5 / Max: 1979 Min: 1876.61 / Avg: 1885.98 / Max: 1896.4 Min: 1880.37 / Avg: 1884.31 / Max: 1890.99 Min: 1643.54 / Avg: 1647.78 / Max: 1651.27 Min: 1420.09 / Avg: 1422.07 / Max: 1424.4 Min: 1269.25 / Avg: 1277.15 / Max: 1288.21 Min: 1077.67 / Avg: 1083.36 / Max: 1087.08 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 7702 EPYC 7662 EPYC 7642 EPYC 7552 EPYC 7542 EPYC 7502P EPYC 7532 EPYC 7F52 EPYC 7402P EPYC 7302P EPYC 7282 EPYC 7272 EPYC 7F32 EPYC 7232P 30 60 90 120 150 SE +/- 0.22, N = 3 SE +/- 0.09, N = 3 SE +/- 0.07, N = 3 SE +/- 0.16, N = 3 SE +/- 0.32, N = 3 SE +/- 0.07, N = 3 SE +/- 0.16, N = 3 SE +/- 0.30, N = 3 SE +/- 0.10, N = 3 SE +/- 0.14, N = 3 SE +/- 0.07, N = 3 SE +/- 0.23, N = 3 SE +/- 0.15, N = 3 SE +/- 0.29, N = 3 67.97 68.29 69.43 69.86 71.46 74.20 74.48 75.85 76.65 87.66 94.35 105.71 113.26 145.44
Result Confidence
OpenBenchmarking.org Seconds, Fewer Is Better Build2 0.13 Time To Compile EPYC 7702 EPYC 7662 EPYC 7642 EPYC 7552 EPYC 7542 EPYC 7502P EPYC 7532 EPYC 7F52 EPYC 7402P EPYC 7302P EPYC 7282 EPYC 7272 EPYC 7F32 EPYC 7232P 30 60 90 120 150 Min: 67.65 / Avg: 67.97 / Max: 68.39 Min: 68.11 / Avg: 68.29 / Max: 68.39 Min: 69.34 / Avg: 69.43 / Max: 69.57 Min: 69.58 / Avg: 69.86 / Max: 70.15 Min: 70.83 / Avg: 71.46 / Max: 71.85 Min: 74.09 / Avg: 74.2 / Max: 74.34 Min: 74.18 / Avg: 74.48 / Max: 74.74 Min: 75.26 / Avg: 75.85 / Max: 76.19 Min: 76.5 / Avg: 76.65 / Max: 76.84 Min: 87.37 / Avg: 87.66 / Max: 87.82 Min: 94.22 / Avg: 94.35 / Max: 94.43 Min: 105.37 / Avg: 105.71 / Max: 106.15 Min: 113.02 / Avg: 113.26 / Max: 113.53 Min: 145.08 / Avg: 145.44 / Max: 146.02
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 7F32 EPYC 7F52 EPYC 7232P EPYC 7302P EPYC 7272 EPYC 7542 EPYC 7402P EPYC 7282 EPYC 7502P EPYC 7532 EPYC 7642 EPYC 7552 EPYC 7662 EPYC 7702 1100 2200 3300 4400 5500 SE +/- 1.90, N = 3 SE +/- 4.58, N = 3 SE +/- 10.38, N = 3 SE +/- 5.33, N = 3 SE +/- 8.60, N = 3 SE +/- 5.09, N = 3 SE +/- 4.18, N = 3 SE +/- 1.17, N = 3 SE +/- 1.62, N = 3 SE +/- 3.83, N = 3 SE +/- 14.85, N = 3 SE +/- 8.65, N = 3 SE +/- 4.63, N = 3 SE +/- 6.37, N = 3 2409.03 2649.35 3090.58 3155.85 3265.93 3271.26 3315.63 3342.13 3582.56 3754.85 4138.69 4203.81 4732.73 5153.99
Result Confidence
OpenBenchmarking.org ms, Fewer Is Better OpenVINO 2021.1 Model: Person Detection 0106 FP32 - Device: CPU EPYC 7F32 EPYC 7F52 EPYC 7232P EPYC 7302P EPYC 7272 EPYC 7542 EPYC 7402P EPYC 7282 EPYC 7502P EPYC 7532 EPYC 7642 EPYC 7552 EPYC 7662 EPYC 7702 900 1800 2700 3600 4500 Min: 2405.41 / Avg: 2409.03 / Max: 2411.84 Min: 2640.2 / Avg: 2649.35 / Max: 2654.02 Min: 3072.59 / Avg: 3090.58 / Max: 3108.55 Min: 3145.96 / Avg: 3155.85 / Max: 3164.23 Min: 3248.92 / Avg: 3265.93 / Max: 3276.67 Min: 3264.96 / Avg: 3271.26 / Max: 3281.33 Min: 3309.61 / Avg: 3315.63 / Max: 3323.66 Min: 3339.82 / Avg: 3342.13 / Max: 3343.55 Min: 3579.4 / Avg: 3582.56 / Max: 3584.73 Min: 3748.56 / Avg: 3754.85 / Max: 3761.77 Min: 4119.13 / Avg: 4138.69 / Max: 4167.82 Min: 4186.54 / Avg: 4203.81 / Max: 4213.33 Min: 4726.94 / Avg: 4732.73 / Max: 4741.89 Min: 5142.04 / Avg: 5153.99 / Max: 5163.81
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 7642 EPYC 7532 EPYC 7702 EPYC 7662 EPYC 7302P EPYC 7552 EPYC 7F32 EPYC 7502P EPYC 7542 EPYC 7402P EPYC 7F52 EPYC 7272 EPYC 7232P EPYC 7282 10 20 30 40 50 SE +/- 0.03, N = 3 SE +/- 0.11, N = 3 SE +/- 0.07, N = 3 SE +/- 0.26, N = 5 SE +/- 0.08, N = 3 SE +/- 0.26, N = 3 SE +/- 0.03, N = 3 SE +/- 0.02, N = 3 SE +/- 0.05, N = 3 SE +/- 0.07, N = 3 SE +/- 0.03, N = 3 SE +/- 0.07, N = 3 SE +/- 0.14, N = 3 SE +/- 0.02, N = 3 21.94 22.94 23.32 23.82 24.92 26.47 27.25 27.60 27.64 29.02 35.42 42.95 45.76 46.07 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 7642 EPYC 7532 EPYC 7702 EPYC 7662 EPYC 7302P EPYC 7552 EPYC 7F32 EPYC 7502P EPYC 7542 EPYC 7402P EPYC 7F52 EPYC 7272 EPYC 7232P EPYC 7282 9 18 27 36 45 Min: 21.88 / Avg: 21.94 / Max: 21.99 Min: 22.73 / Avg: 22.94 / Max: 23.1 Min: 23.22 / Avg: 23.32 / Max: 23.46 Min: 23.2 / Avg: 23.82 / Max: 24.72 Min: 24.77 / Avg: 24.92 / Max: 25.05 Min: 26.02 / Avg: 26.47 / Max: 26.92 Min: 27.2 / Avg: 27.25 / Max: 27.28 Min: 27.55 / Avg: 27.6 / Max: 27.63 Min: 27.53 / Avg: 27.64 / Max: 27.7 Min: 28.89 / Avg: 29.02 / Max: 29.09 Min: 35.36 / Avg: 35.42 / Max: 35.47 Min: 42.88 / Avg: 42.95 / Max: 43.08 Min: 45.56 / Avg: 45.76 / Max: 46.03 Min: 46.05 / Avg: 46.07 / Max: 46.1 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 7502P EPYC 7542 EPYC 7402P EPYC 7642 EPYC 7662 EPYC 7532 EPYC 7F52 EPYC 7552 EPYC 7702 EPYC 7302P EPYC 7282 EPYC 7272 EPYC 7F32 EPYC 7232P 200 400 600 800 1000 SE +/- 0.20, N = 3 SE +/- 0.20, N = 3 SE +/- 0.25, N = 3 SE +/- 0.22, N = 3 SE +/- 0.41, N = 3 SE +/- 0.13, N = 3 SE +/- 0.50, N = 3 SE +/- 0.09, N = 3 SE +/- 2.26, N = 3 SE +/- 1.69, N = 3 SE +/- 0.30, N = 3 SE +/- 0.80, N = 3 SE +/- 0.43, N = 3 SE +/- 0.56, N = 3 467.43 467.51 467.70 473.76 474.55 474.59 475.39 481.50 481.95 562.07 580.07 680.90 778.66 954.80 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 7502P EPYC 7542 EPYC 7402P EPYC 7642 EPYC 7662 EPYC 7532 EPYC 7F52 EPYC 7552 EPYC 7702 EPYC 7302P EPYC 7282 EPYC 7272 EPYC 7F32 EPYC 7232P 200 400 600 800 1000 Min: 467.12 / Avg: 467.43 / Max: 467.79 Min: 467.15 / Avg: 467.51 / Max: 467.82 Min: 467.23 / Avg: 467.7 / Max: 468.09 Min: 473.32 / Avg: 473.76 / Max: 474.03 Min: 473.79 / Avg: 474.55 / Max: 475.18 Min: 474.43 / Avg: 474.59 / Max: 474.85 Min: 474.62 / Avg: 475.39 / Max: 476.33 Min: 481.32 / Avg: 481.5 / Max: 481.6 Min: 477.74 / Avg: 481.95 / Max: 485.47 Min: 558.73 / Avg: 562.07 / Max: 564.17 Min: 579.69 / Avg: 580.07 / Max: 580.65 Min: 679.66 / Avg: 680.9 / Max: 682.4 Min: 777.8 / Avg: 778.66 / Max: 779.18 Min: 953.7 / Avg: 954.8 / Max: 955.56 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 7542 EPYC 7502P EPYC 7402P EPYC 7642 EPYC 7702 EPYC 7662 EPYC 7552 EPYC 7F52 EPYC 7532 EPYC 7302P EPYC 7282 EPYC 7272 EPYC 7F32 EPYC 7232P 60 120 180 240 300 SE +/- 0.04, N = 3 SE +/- 0.05, N = 3 SE +/- 0.09, N = 3 SE +/- 0.03, N = 3 SE +/- 0.47, N = 3 SE +/- 0.04, N = 3 SE +/- 0.13, N = 3 SE +/- 0.46, N = 3 SE +/- 0.09, N = 3 SE +/- 1.62, N = 3 SE +/- 1.08, N = 3 SE +/- 0.65, N = 3 SE +/- 0.90, N = 3 SE +/- 0.87, N = 3 135.97 137.44 138.04 138.08 139.36 139.56 140.18 140.61 142.20 164.81 173.72 199.54 227.13 277.67 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 7542 EPYC 7502P EPYC 7402P EPYC 7642 EPYC 7702 EPYC 7662 EPYC 7552 EPYC 7F52 EPYC 7532 EPYC 7302P EPYC 7282 EPYC 7272 EPYC 7F32 EPYC 7232P 50 100 150 200 250 Min: 135.9 / Avg: 135.97 / Max: 136.04 Min: 137.39 / Avg: 137.44 / Max: 137.53 Min: 137.91 / Avg: 138.04 / Max: 138.21 Min: 138.03 / Avg: 138.08 / Max: 138.13 Min: 138.86 / Avg: 139.36 / Max: 140.29 Min: 139.49 / Avg: 139.56 / Max: 139.6 Min: 140 / Avg: 140.18 / Max: 140.43 Min: 140.07 / Avg: 140.61 / Max: 141.52 Min: 142.07 / Avg: 142.2 / Max: 142.38 Min: 161.8 / Avg: 164.81 / Max: 167.37 Min: 172.62 / Avg: 173.72 / Max: 175.87 Min: 198.32 / Avg: 199.54 / Max: 200.54 Min: 225.67 / Avg: 227.13 / Max: 228.77 Min: 275.95 / Avg: 277.67 / Max: 278.78 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 7542 EPYC 7502P EPYC 7532 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7402P EPYC 7F32 EPYC 7302P EPYC 7232P EPYC 7282 EPYC 7272 EPYC 7F52 1.3001 2.6002 3.9003 5.2004 6.5005 SE +/- 0.005, N = 15 SE +/- 0.010, N = 3 SE +/- 0.008, N = 3 SE +/- 0.004, N = 15 SE +/- 0.024, N = 3 SE +/- 0.006, N = 3 SE +/- 0.015, N = 3 SE +/- 0.012, N = 3 SE +/- 0.002, N = 14 SE +/- 0.005, N = 15 SE +/- 0.007, N = 11 SE +/- 0.060, N = 3 SE +/- 0.015, N = 4 SE +/- 0.401, N = 3 2.836 2.927 3.003 3.022 3.056 3.073 3.187 3.213 3.625 3.856 3.917 4.081 5.322 5.778 MIN: 2.77 / MAX: 4.94 MIN: 2.87 / MAX: 5.27 MIN: 2.95 / MAX: 3.25 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: 3.15 / MAX: 4.81 MIN: 3.57 / MAX: 17.34 MIN: 3.74 / MAX: 20.71 MIN: 3.79 / MAX: 19.86 MIN: 3.8 / MAX: 20.13 MIN: 5.22 / MAX: 13.18 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 7542 EPYC 7502P EPYC 7532 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7402P EPYC 7F32 EPYC 7302P EPYC 7232P EPYC 7282 EPYC 7272 EPYC 7F52 2 4 6 8 10 Min: 2.81 / Avg: 2.84 / Max: 2.88 Min: 2.92 / Avg: 2.93 / Max: 2.95 Min: 2.99 / Avg: 3 / Max: 3.02 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: 3.19 / Avg: 3.21 / Max: 3.23 Min: 3.61 / Avg: 3.62 / Max: 3.64 Min: 3.82 / Avg: 3.86 / Max: 3.88 Min: 3.86 / Avg: 3.92 / Max: 3.95 Min: 3.98 / Avg: 4.08 / Max: 4.18 Min: 5.3 / Avg: 5.32 / Max: 5.36 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 7542 EPYC 7502P EPYC 7402P EPYC 7F52 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7552 EPYC 7532 EPYC 7302P EPYC 7282 EPYC 7272 EPYC 7F32 EPYC 7232P 110 220 330 440 550 SE +/- 0.19, N = 3 SE +/- 0.13, N = 3 SE +/- 0.27, N = 3 SE +/- 1.43, N = 3 SE +/- 0.24, N = 3 SE +/- 0.17, N = 3 SE +/- 0.12, N = 3 SE +/- 0.12, N = 3 SE +/- 0.16, N = 3 SE +/- 0.98, N = 3 SE +/- 2.55, N = 3 SE +/- 2.81, N = 3 SE +/- 0.26, N = 3 SE +/- 0.90, N = 3 250.41 253.10 254.24 254.76 254.88 256.56 257.01 258.37 260.46 301.52 309.98 361.48 416.27 507.74 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 7542 EPYC 7502P EPYC 7402P EPYC 7F52 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7552 EPYC 7532 EPYC 7302P EPYC 7282 EPYC 7272 EPYC 7F32 EPYC 7232P 90 180 270 360 450 Min: 250.08 / Avg: 250.41 / Max: 250.74 Min: 252.84 / Avg: 253.1 / Max: 253.26 Min: 253.9 / Avg: 254.24 / Max: 254.77 Min: 252.29 / Avg: 254.76 / Max: 257.23 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: 258.22 / Avg: 258.37 / Max: 258.61 Min: 260.18 / Avg: 260.46 / Max: 260.72 Min: 300.37 / Avg: 301.52 / Max: 303.47 Min: 305.77 / Avg: 309.98 / Max: 314.59 Min: 356.31 / Avg: 361.48 / Max: 365.98 Min: 415.89 / Avg: 416.27 / Max: 416.76 Min: 506.68 / Avg: 507.74 / Max: 509.53 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 7532 EPYC 7662 EPYC 7702 EPYC 7552 EPYC 7F32 EPYC 7302P EPYC 7402P EPYC 7542 EPYC 7502P EPYC 7F52 EPYC 7272 EPYC 7282 EPYC 7232P 200M 400M 600M 800M 1000M SE +/- 422202.49, N = 3 SE +/- 229126.62, N = 3 SE +/- 507394.80, N = 3 SE +/- 989060.38, N = 3 SE +/- 322962.48, N = 6 SE +/- 405072.19, N = 4 SE +/- 643499.89, N = 3 SE +/- 142607.92, N = 3 SE +/- 998206.04, N = 3 SE +/- 3149876.45, N = 4 SE +/- 252656.85, N = 4 SE +/- 314598.13, N = 3 SE +/- 295157.17, N = 5 909532667 883735200 878375333 856893400 809844583 788266875 778459433 774329467 774304800 643180925 457855350 455760633 449916460 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 7F32 EPYC 7302P EPYC 7232P EPYC 7402P EPYC 7542 EPYC 7502P EPYC 7272 EPYC 7532 EPYC 7282 EPYC 7552 EPYC 7662 EPYC 7702 EPYC 7F52 2M 4M 6M 8M 10M 9577991.03 8667240.71 7366263.78 7131421.00 6697956.10 6513520.25 6485573.10 6228384.62 5939960.67 5919717.78 5265803.49 5138262.51 4682548.38
Result Confidence
OpenBenchmarking.org Figure Of Merit, More Is Better Algebraic Multi-Grid Benchmark 1.2 EPYC 7532 EPYC 7662 EPYC 7702 EPYC 7552 EPYC 7F32 EPYC 7302P EPYC 7402P EPYC 7542 EPYC 7502P EPYC 7F52 EPYC 7272 EPYC 7282 EPYC 7232P 160M 320M 480M 640M 800M Min: 908914700 / Avg: 909532666.67 / Max: 910340000 Min: 883287900 / Avg: 883735200 / Max: 884045100 Min: 877829000 / Avg: 878375333.33 / Max: 879389100 Min: 854937100 / Avg: 856893400 / Max: 858125300 Min: 808702900 / Avg: 809844583.33 / Max: 810642700 Min: 787578900 / Avg: 788266875 / Max: 789313600 Min: 777565100 / Avg: 778459433.33 / Max: 779708100 Min: 774119000 / Avg: 774329466.67 / Max: 774601400 Min: 772483400 / Avg: 774304800 / Max: 775923400 Min: 634035200 / Avg: 643180925 / Max: 647428500 Min: 457151100 / Avg: 457855350 / Max: 458299300 Min: 455133300 / Avg: 455760633.33 / Max: 456116200 Min: 448913300 / Avg: 449916460 / Max: 450629100 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 7662 EPYC 7702 EPYC 7642 EPYC 7552 EPYC 7542 EPYC 7502P EPYC 7532 EPYC 7402P EPYC 7F52 EPYC 7302P EPYC 7282 EPYC 7F32 EPYC 7272 EPYC 7232P 40 80 120 160 200 SE +/- 0.56, N = 3 SE +/- 0.31, N = 3 SE +/- 0.28, N = 3 SE +/- 0.12, N = 3 SE +/- 0.16, N = 3 SE +/- 0.08, N = 3 SE +/- 0.13, N = 3 SE +/- 0.20, N = 3 SE +/- 0.17, N = 3 SE +/- 0.09, N = 3 SE +/- 0.38, N = 3 SE +/- 0.13, N = 3 SE +/- 0.17, N = 3 SE +/- 0.13, N = 3 190.19 185.31 179.72 178.70 152.78 152.15 146.29 135.69 129.77 116.68 114.49 109.55 107.25 94.36 MIN: 126.93 / MAX: 307.7 MIN: 125.96 / MAX: 294.64 MIN: 121.84 / MAX: 276.81 MIN: 121.07 / MAX: 277.42 MIN: 98.52 / MAX: 278.09 MIN: 97.46 / MAX: 272.72 MIN: 94.75 / MAX: 256.37 MIN: 85.88 / MAX: 272.31 MIN: 84.35 / MAX: 268.95 MIN: 74.3 / MAX: 261.93 MIN: 72.02 / MAX: 259.87 MIN: 70.77 / MAX: 249.84 MIN: 67.93 / MAX: 243.83 MIN: 60.14 / MAX: 225.56 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 7552 EPYC 7542 EPYC 7502P EPYC 7662 EPYC 7642 EPYC 7282 EPYC 7402P EPYC 7702 EPYC 7272 EPYC 7302P EPYC 7232P EPYC 7532 EPYC 7F32 EPYC 7F52 0.5828 1.1656 1.7484 2.3312 2.914 2.59 2.58 2.53 2.37 2.34 2.29 2.26 2.22 2.15 2.00 1.95 1.84 1.62 1.47
Result Confidence
OpenBenchmarking.org FPS, More Is Better dav1d 0.8.1 Video Input: Chimera 1080p 10-bit EPYC 7662 EPYC 7702 EPYC 7642 EPYC 7552 EPYC 7542 EPYC 7502P EPYC 7532 EPYC 7402P EPYC 7F52 EPYC 7302P EPYC 7282 EPYC 7F32 EPYC 7272 EPYC 7232P 30 60 90 120 150 Min: 189.1 / Avg: 190.19 / Max: 190.97 Min: 184.71 / Avg: 185.31 / Max: 185.73 Min: 179.44 / Avg: 179.72 / Max: 180.27 Min: 178.47 / Avg: 178.7 / Max: 178.84 Min: 152.47 / Avg: 152.78 / Max: 153.01 Min: 152.02 / Avg: 152.15 / Max: 152.28 Min: 146.03 / Avg: 146.29 / Max: 146.46 Min: 135.36 / Avg: 135.69 / Max: 136.06 Min: 129.43 / Avg: 129.77 / Max: 129.97 Min: 116.54 / Avg: 116.68 / Max: 116.86 Min: 113.88 / Avg: 114.49 / Max: 115.2 Min: 109.41 / Avg: 109.55 / Max: 109.8 Min: 106.92 / Avg: 107.25 / Max: 107.46 Min: 94.18 / Avg: 94.36 / Max: 94.61 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 7662 EPYC 7702 EPYC 7642 EPYC 7552 EPYC 7532 EPYC 7502P EPYC 7542 EPYC 7402P EPYC 7302P EPYC 7F52 EPYC 7282 EPYC 7272 EPYC 7F32 EPYC 7232P 4 8 12 16 20 SE +/- 0.099835, N = 4 SE +/- 0.163720, N = 4 SE +/- 0.030087, N = 3 SE +/- 0.083534, N = 3 SE +/- 0.072162, N = 3 SE +/- 0.066319, N = 3 SE +/- 0.091101, N = 3 SE +/- 0.025438, N = 3 SE +/- 0.017716, N = 3 SE +/- 0.028662, N = 3 SE +/- 0.037637, N = 3 SE +/- 0.008716, N = 3 SE +/- 0.039059, N = 3 SE +/- 0.010754, N = 3 16.881168 15.614812 13.942465 12.735031 9.828871 9.326909 8.863336 7.208235 4.963715 4.897653 4.452419 3.464003 3.011595 1.583704 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 7662 EPYC 7702 EPYC 7552 EPYC 7642 EPYC 7542 EPYC 7502P EPYC 7532 EPYC 7402P EPYC 7282 EPYC 7272 EPYC 7302P EPYC 7F32 EPYC 7F52 EPYC 7232P 0.0248 0.0496 0.0744 0.0992 0.124 0.11 0.11 0.10 0.08 0.07 0.07 0.06 0.06 0.05 0.05 0.05 0.03 0.03 0.02
Result Confidence
OpenBenchmarking.org GFLOP/s, More Is Better ACES DGEMM 1.0 Sustained Floating-Point Rate EPYC 7662 EPYC 7702 EPYC 7642 EPYC 7552 EPYC 7532 EPYC 7502P EPYC 7542 EPYC 7402P EPYC 7302P EPYC 7F52 EPYC 7282 EPYC 7272 EPYC 7F32 EPYC 7232P 4 8 12 16 20 Min: 16.59 / Avg: 16.88 / Max: 17.02 Min: 15.39 / Avg: 15.61 / Max: 16.1 Min: 13.91 / Avg: 13.94 / Max: 14 Min: 12.62 / Avg: 12.74 / Max: 12.9 Min: 9.75 / Avg: 9.83 / Max: 9.97 Min: 9.25 / Avg: 9.33 / Max: 9.46 Min: 8.68 / Avg: 8.86 / Max: 8.96 Min: 7.16 / Avg: 7.21 / Max: 7.24 Min: 4.93 / Avg: 4.96 / Max: 4.99 Min: 4.85 / Avg: 4.9 / Max: 4.95 Min: 4.39 / Avg: 4.45 / Max: 4.52 Min: 3.45 / Avg: 3.46 / Max: 3.48 Min: 2.95 / Avg: 3.01 / Max: 3.08 Min: 1.57 / Avg: 1.58 / Max: 1.61 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 7542 EPYC 7502P EPYC 7402P EPYC 7532 EPYC 7282 EPYC 7F52 EPYC 7302P EPYC 7272 EPYC 7F32 EPYC 7232P EPYC 7552 EPYC 7642 EPYC 7702 EPYC 7662 200K 400K 600K 800K 1000K SE +/- 7271.02, N = 3 SE +/- 6414.70, N = 3 SE +/- 9904.69, N = 4 SE +/- 4243.12, N = 3 SE +/- 3857.18, N = 3 SE +/- 7660.92, N = 6 SE +/- 6451.00, N = 3 SE +/- 198.51, N = 3 SE +/- 3955.87, N = 3 SE +/- 6504.38, N = 3 SE +/- 6981.82, N = 3 SE +/- 1276.30, N = 3 SE +/- 1138.19, N = 3 SE +/- 1119.16, N = 3 885722 881986 838224 825374 775796 756676 756268 705855 624502 611302 536242 527541 451003 447191 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 7F32 EPYC 7502P EPYC 7402P EPYC 7542 EPYC 7532 EPYC 7F52 EPYC 7552 EPYC 7642 EPYC 7702 EPYC 7662 2K 4K 6K 8K 10K 10036.15 9067.03 8813.61 7541.24 6995.00 6049.54 5925.99 5622.62 4999.98 4243.87 3850.07 3278.22 2844.47 2634.77
Result Confidence
OpenBenchmarking.org Op/s, More Is Better Facebook RocksDB 6.3.6 Test: Sequential Fill EPYC 7542 EPYC 7502P EPYC 7402P EPYC 7532 EPYC 7282 EPYC 7F52 EPYC 7302P EPYC 7272 EPYC 7F32 EPYC 7232P EPYC 7552 EPYC 7642 EPYC 7702 EPYC 7662 150K 300K 450K 600K 750K Min: 875249 / Avg: 885722.33 / Max: 899696 Min: 872797 / Avg: 881986 / Max: 894334 Min: 809652 / Avg: 838224 / Max: 852941 Min: 820254 / Avg: 825374 / Max: 833795 Min: 771919 / Avg: 775795.67 / Max: 783510 Min: 736622 / Avg: 756676 / Max: 785060 Min: 749121 / Avg: 756268 / Max: 769144 Min: 705589 / Avg: 705854.67 / Max: 706243 Min: 617818 / Avg: 624501.67 / Max: 631510 Min: 598299 / Avg: 611302 / Max: 618139 Min: 528910 / Avg: 536242.33 / Max: 550200 Min: 525500 / Avg: 527540.67 / Max: 529889 Min: 449363 / Avg: 451002.67 / Max: 453190 Min: 445589 / Avg: 447191.33 / Max: 449346 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 7542 EPYC 7502P EPYC 7F52 EPYC 7402P EPYC 7662 EPYC 7532 EPYC 7642 EPYC 7702 EPYC 7552 EPYC 7302P EPYC 7282 EPYC 7272 EPYC 7F32 EPYC 7232P 4 8 12 16 20 SE +/- 0.015, N = 6 SE +/- 0.027, N = 6 SE +/- 0.012, N = 6 SE +/- 0.009, N = 6 SE +/- 0.009, N = 6 SE +/- 0.010, N = 6 SE +/- 0.006, N = 6 SE +/- 0.012, N = 6 SE +/- 0.013, N = 6 SE +/- 0.020, N = 5 SE +/- 0.012, N = 5 SE +/- 0.018, N = 5 SE +/- 0.031, N = 4 SE +/- 0.032, N = 4 7.949 7.972 7.973 7.974 8.052 8.055 8.074 8.125 8.162 9.354 9.654 11.131 12.788 15.547 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 7542 EPYC 7502P EPYC 7F52 EPYC 7402P EPYC 7662 EPYC 7532 EPYC 7642 EPYC 7702 EPYC 7552 EPYC 7302P EPYC 7282 EPYC 7272 EPYC 7F32 EPYC 7232P 4 8 12 16 20 Min: 7.92 / Avg: 7.95 / Max: 8.02 Min: 7.91 / Avg: 7.97 / Max: 8.08 Min: 7.94 / Avg: 7.97 / Max: 8.02 Min: 7.94 / Avg: 7.97 / Max: 8 Min: 8.04 / Avg: 8.05 / Max: 8.09 Min: 8.01 / Avg: 8.06 / Max: 8.08 Min: 8.05 / Avg: 8.07 / Max: 8.09 Min: 8.1 / Avg: 8.13 / Max: 8.17 Min: 8.12 / Avg: 8.16 / Max: 8.21 Min: 9.31 / Avg: 9.35 / Max: 9.43 Min: 9.63 / Avg: 9.65 / Max: 9.69 Min: 11.09 / Avg: 11.13 / Max: 11.19 Min: 12.74 / Avg: 12.79 / Max: 12.88 Min: 15.46 / Avg: 15.55 / Max: 15.62 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 7542 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7552 EPYC 7532 EPYC 7642 EPYC 7662 EPYC 7272 EPYC 7702 EPYC 7282 EPYC 7F32 EPYC 7232P EPYC 7F52 200 400 600 800 1000 566.99 574.77 576.98 577.65 584.61 586.67 590.56 604.15 623.78 649.31 655.45 668.99 715.21 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 7542 EPYC 7502P EPYC 7532 EPYC 7402P EPYC 7282 EPYC 7F52 EPYC 7302P EPYC 7272 EPYC 7F32 EPYC 7232P EPYC 7552 EPYC 7642 EPYC 7702 EPYC 7662 200K 400K 600K 800K 1000K SE +/- 4338.82, N = 3 SE +/- 6323.38, N = 3 SE +/- 2994.50, N = 3 SE +/- 10119.73, N = 3 SE +/- 9036.88, N = 4 SE +/- 6124.02, N = 3 SE +/- 5524.24, N = 9 SE +/- 6225.31, N = 6 SE +/- 6471.76, N = 5 SE +/- 6988.75, N = 3 SE +/- 4097.81, N = 3 SE +/- 3532.96, N = 3 SE +/- 1303.40, N = 3 SE +/- 227.93, N = 3 860225 846887 806814 805066 735381 699077 692044 656055 581407 545816 521910 518446 451547 442864 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 7282 EPYC 7272 EPYC 7302P EPYC 7F32 EPYC 7502P EPYC 7402P EPYC 7542 EPYC 7532 EPYC 7F52 EPYC 7552 EPYC 7642 EPYC 7702 EPYC 7662 2K 4K 6K 8K 10K 8529.54 8078.17 8044.80 6716.57 6147.22 5906.76 5637.77 5587.32 4922.99 3901.69 3855.32 3303.48 3013.23 2783.45
Result Confidence
OpenBenchmarking.org Op/s, More Is Better Facebook RocksDB 6.3.6 Test: Random Fill EPYC 7542 EPYC 7502P EPYC 7532 EPYC 7402P EPYC 7282 EPYC 7F52 EPYC 7302P EPYC 7272 EPYC 7F32 EPYC 7232P EPYC 7552 EPYC 7642 EPYC 7702 EPYC 7662 150K 300K 450K 600K 750K Min: 851801 / Avg: 860225.33 / Max: 866240 Min: 835350 / Avg: 846887 / Max: 857142 Min: 801674 / Avg: 806813.67 / Max: 812046 Min: 794424 / Avg: 805065.67 / Max: 825296 Min: 722999 / Avg: 735381.25 / Max: 761712 Min: 687578 / Avg: 699077 / Max: 708479 Min: 669061 / Avg: 692043.67 / Max: 723569 Min: 638259 / Avg: 656055.33 / Max: 681884 Min: 569871 / Avg: 581407 / Max: 602220 Min: 533331 / Avg: 545816.33 / Max: 557501 Min: 516355 / Avg: 521910 / Max: 529906 Min: 513881 / Avg: 518445.67 / Max: 525399 Min: 449913 / Avg: 451547 / Max: 454123 Min: 442493 / Avg: 442864.33 / Max: 443279 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 7302P EPYC 7402P EPYC 7542 EPYC 7502P EPYC 7532 EPYC 7F32 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7282 EPYC 7272 EPYC 7232P EPYC 7F52 13 26 39 52 65 SE +/- 0.12, N = 3 SE +/- 0.01, N = 3 SE +/- 0.07, N = 3 SE +/- 0.12, N = 3 SE +/- 0.15, N = 11 SE +/- 0.18, N = 3 SE +/- 0.32, N = 3 SE +/- 0.19, N = 12 SE +/- 0.27, N = 9 SE +/- 0.17, N = 9 SE +/- 0.27, N = 3 SE +/- 0.13, N = 3 SE +/- 0.05, N = 3 SE +/- 0.15, N = 3 30.84 31.46 31.48 32.04 33.27 33.81 34.20 34.90 37.35 38.51 39.42 40.01 40.67 59.81 MIN: 30.45 / MAX: 32.11 MIN: 31.24 / MAX: 33.08 MIN: 31.08 / MAX: 45.9 MIN: 31.32 / MAX: 109.6 MIN: 31.92 / MAX: 108.33 MIN: 33.39 / MAX: 80.53 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: 38.3 / MAX: 143.19 MIN: 39.54 / MAX: 41.05 MIN: 40.35 / MAX: 43.91 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 7302P EPYC 7402P EPYC 7542 EPYC 7502P EPYC 7532 EPYC 7F32 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7282 EPYC 7272 EPYC 7232P EPYC 7F52 12 24 36 48 60 Min: 30.69 / Avg: 30.84 / Max: 31.08 Min: 31.45 / Avg: 31.46 / Max: 31.48 Min: 31.34 / Avg: 31.48 / Max: 31.56 Min: 31.88 / Avg: 32.04 / Max: 32.28 Min: 32.69 / Avg: 33.27 / Max: 34.04 Min: 33.62 / Avg: 33.81 / Max: 34.17 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: 38.92 / Avg: 39.42 / Max: 39.85 Min: 39.75 / Avg: 40.01 / Max: 40.15 Min: 40.61 / Avg: 40.67 / Max: 40.77 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 7642 EPYC 7662 EPYC 7542 EPYC 7552 EPYC 7532 EPYC 7502P EPYC 7702 EPYC 7402P EPYC 7302P EPYC 7282 EPYC 7F52 EPYC 7272 EPYC 7F32 EPYC 7232P 500 1000 1500 2000 2500 2125 2122 2107 2049 2043 2022 1965 1926 1660 1538 1456 1372 1301 1112
Result
OpenBenchmarking.org ms, Fewer Is Better NCNN 20201218 Target: CPU - Model: mobilenet EPYC 7402P EPYC 7302P EPYC 7272 EPYC 7542 EPYC 7282 EPYC 7F32 EPYC 7502P EPYC 7232P EPYC 7532 EPYC 7F52 EPYC 7552 EPYC 7642 EPYC 7702 EPYC 7662 8 16 24 32 40 SE +/- 0.07, N = 3 SE +/- 0.08, N = 3 SE +/- 0.16, N = 3 SE +/- 0.03, N = 3 SE +/- 0.10, N = 3 SE +/- 0.10, N = 3 SE +/- 0.15, N = 3 SE +/- 0.10, N = 3 SE +/- 0.18, N = 11 SE +/- 0.10, N = 3 SE +/- 0.37, N = 3 SE +/- 0.64, N = 12 SE +/- 0.91, N = 9 SE +/- 0.82, N = 9 19.52 19.70 20.06 20.43 20.46 20.54 21.14 22.33 23.59 24.14 26.50 28.92 35.58 35.78 MIN: 19.11 / MAX: 21.65 MIN: 19.2 / MAX: 20.45 MIN: 19.5 / MAX: 23.62 MIN: 19.91 / MAX: 33.27 MIN: 19.72 / MAX: 77.23 MIN: 20.19 / MAX: 21.27 MIN: 20.56 / MAX: 35 MIN: 21.92 / MAX: 23.79 MIN: 22.06 / MAX: 161.6 MIN: 23.55 / MAX: 25.73 MIN: 24.55 / MAX: 33.31 MIN: 24.32 / MAX: 41.88 MIN: 29.55 / MAX: 165.69 MIN: 28.31 / MAX: 170.87 1. (CXX) g++ options: -O3 -rdynamic -lgomp -lpthread
Result Confidence
OpenBenchmarking.org ms, Fewer Is Better NCNN 20201218 Target: CPU - Model: mobilenet EPYC 7402P EPYC 7302P EPYC 7272 EPYC 7542 EPYC 7282 EPYC 7F32 EPYC 7502P EPYC 7232P EPYC 7532 EPYC 7F52 EPYC 7552 EPYC 7642 EPYC 7702 EPYC 7662 8 16 24 32 40 Min: 19.39 / Avg: 19.52 / Max: 19.6 Min: 19.56 / Avg: 19.7 / Max: 19.85 Min: 19.75 / Avg: 20.06 / Max: 20.29 Min: 20.38 / Avg: 20.43 / Max: 20.48 Min: 20.36 / Avg: 20.46 / Max: 20.66 Min: 20.4 / Avg: 20.54 / Max: 20.73 Min: 20.98 / Avg: 21.14 / Max: 21.44 Min: 22.23 / Avg: 22.33 / Max: 22.53 Min: 22.94 / Avg: 23.59 / Max: 24.92 Min: 24 / Avg: 24.14 / Max: 24.32 Min: 25.8 / Avg: 26.5 / Max: 27.04 Min: 26.74 / Avg: 28.92 / Max: 33.72 Min: 31.5 / Avg: 35.58 / Max: 39.42 Min: 31.86 / Avg: 35.78 / Max: 39.06 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 7F52 EPYC 7542 EPYC 7662 EPYC 7702 EPYC 7642 EPYC 7502P EPYC 7402P EPYC 7552 EPYC 7532 EPYC 7302P EPYC 7282 EPYC 7F32 EPYC 7272 EPYC 7232P 30 60 90 120 150 SE +/- 0.59, N = 3 SE +/- 0.80, N = 3 SE +/- 0.45, N = 3 SE +/- 0.05, N = 3 SE +/- 0.18, N = 3 SE +/- 0.60, N = 3 SE +/- 0.58, N = 3 SE +/- 1.10, N = 3 SE +/- 0.65, N = 3 SE +/- 0.45, N = 3 SE +/- 1.07, N = 3 SE +/- 0.92, N = 7 SE +/- 0.64, N = 3 SE +/- 1.44, N = 3 75.23 83.83 84.79 84.83 85.03 85.73 85.76 86.06 86.70 88.32 96.85 98.52 101.59 141.25
Result Confidence
OpenBenchmarking.org Seconds, Fewer Is Better Numenta Anomaly Benchmark 1.1 Detector: Earthgecko Skyline EPYC 7F52 EPYC 7542 EPYC 7662 EPYC 7702 EPYC 7642 EPYC 7502P EPYC 7402P EPYC 7552 EPYC 7532 EPYC 7302P EPYC 7282 EPYC 7F32 EPYC 7272 EPYC 7232P 30 60 90 120 150 Min: 74.45 / Avg: 75.23 / Max: 76.39 Min: 82.24 / Avg: 83.83 / Max: 84.72 Min: 84.12 / Avg: 84.79 / Max: 85.64 Min: 84.74 / Avg: 84.83 / Max: 84.9 Min: 84.8 / Avg: 85.03 / Max: 85.39 Min: 85.04 / Avg: 85.73 / Max: 86.93 Min: 84.6 / Avg: 85.76 / Max: 86.43 Min: 83.86 / Avg: 86.06 / Max: 87.25 Min: 85.78 / Avg: 86.7 / Max: 87.96 Min: 87.53 / Avg: 88.32 / Max: 89.11 Min: 94.95 / Avg: 96.85 / Max: 98.65 Min: 95.01 / Avg: 98.52 / Max: 100.63 Min: 100.3 / Avg: 101.59 / Max: 102.33 Min: 138.42 / Avg: 141.25 / Max: 143.09
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 7F32 EPYC 7F52 EPYC 7232P EPYC 7302P EPYC 7272 EPYC 7282 EPYC 7402P EPYC 7542 EPYC 7502P EPYC 7532 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 40 80 120 160 200 SE +/- 0.03, N = 3 SE +/- 0.08, N = 3 SE +/- 0.06, N = 3 SE +/- 0.04, N = 3 SE +/- 0.10, N = 3 SE +/- 0.05, N = 3 SE +/- 0.09, N = 3 SE +/- 0.04, N = 3 SE +/- 0.04, N = 3 SE +/- 0.08, N = 3 SE +/- 0.06, N = 3 SE +/- 0.06, N = 3 SE +/- 0.16, N = 3 SE +/- 0.18, N = 3 104.26 110.43 126.21 128.93 129.44 132.39 133.76 139.82 141.65 145.01 165.55 166.11 191.15 191.23 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 7F32 EPYC 7F52 EPYC 7232P EPYC 7302P EPYC 7272 EPYC 7282 EPYC 7402P EPYC 7542 EPYC 7502P EPYC 7532 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 40 80 120 160 200 Min: 104.21 / Avg: 104.26 / Max: 104.31 Min: 110.31 / Avg: 110.43 / Max: 110.57 Min: 126.1 / Avg: 126.21 / Max: 126.28 Min: 128.87 / Avg: 128.93 / Max: 129.01 Min: 129.26 / Avg: 129.44 / Max: 129.62 Min: 132.35 / Avg: 132.39 / Max: 132.48 Min: 133.6 / Avg: 133.76 / Max: 133.9 Min: 139.74 / Avg: 139.82 / Max: 139.89 Min: 141.6 / Avg: 141.65 / Max: 141.72 Min: 144.87 / Avg: 145.01 / Max: 145.14 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 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 7F52 EPYC 7542 EPYC 7702 EPYC 7662 EPYC 7502P EPYC 7552 EPYC 7642 EPYC 7402P EPYC 7532 EPYC 7302P EPYC 7282 EPYC 7272 EPYC 7F32 EPYC 7232P 3 6 9 12 15 SE +/- 0.016, N = 6 SE +/- 0.016, N = 6 SE +/- 0.029, N = 6 SE +/- 0.038, N = 6 SE +/- 0.020, N = 6 SE +/- 0.025, N = 6 SE +/- 0.036, N = 6 SE +/- 0.041, N = 6 SE +/- 0.044, N = 6 SE +/- 0.018, N = 6 SE +/- 0.033, N = 6 SE +/- 0.043, N = 5 SE +/- 0.034, N = 5 SE +/- 0.047, N = 4 6.586 6.900 6.930 6.971 6.989 7.033 7.063 7.121 7.220 7.645 8.105 8.798 9.790 11.912
Result Confidence
OpenBenchmarking.org Seconds, Fewer Is Better Numenta Anomaly Benchmark 1.1 Detector: Windowed Gaussian EPYC 7F52 EPYC 7542 EPYC 7702 EPYC 7662 EPYC 7502P EPYC 7552 EPYC 7642 EPYC 7402P EPYC 7532 EPYC 7302P EPYC 7282 EPYC 7272 EPYC 7F32 EPYC 7232P 3 6 9 12 15 Min: 6.53 / Avg: 6.59 / Max: 6.62 Min: 6.84 / Avg: 6.9 / Max: 6.95 Min: 6.86 / Avg: 6.93 / Max: 7.04 Min: 6.85 / Avg: 6.97 / Max: 7.12 Min: 6.93 / Avg: 6.99 / Max: 7.06 Min: 6.95 / Avg: 7.03 / Max: 7.12 Min: 6.98 / Avg: 7.06 / Max: 7.22 Min: 6.99 / Avg: 7.12 / Max: 7.23 Min: 7.06 / Avg: 7.22 / Max: 7.34 Min: 7.59 / Avg: 7.65 / Max: 7.7 Min: 8 / Avg: 8.1 / Max: 8.23 Min: 8.7 / Avg: 8.8 / Max: 8.93 Min: 9.66 / Avg: 9.79 / Max: 9.84 Min: 11.83 / Avg: 11.91 / Max: 12.03
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 7532 EPYC 7662 EPYC 7702 EPYC 7552 EPYC 7F32 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7542 EPYC 7F52 EPYC 7232P EPYC 7272 EPYC 7282 20K 40K 60K 80K 100K SE +/- 16.47, N = 5 SE +/- 21.10, N = 5 SE +/- 26.33, N = 5 SE +/- 11.91, N = 5 SE +/- 59.32, N = 5 SE +/- 5.88, N = 5 SE +/- 7.48, N = 5 SE +/- 19.43, N = 5 SE +/- 36.22, N = 5 SE +/- 194.23, N = 5 SE +/- 65.26, N = 5 SE +/- 2.27, N = 5 SE +/- 8.84, N = 5 99248.2 98343.2 98034.8 96497.1 89567.2 88105.7 87308.4 87239.8 87057.0 72315.6 56788.6 56066.6 55596.3 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 7402P EPYC 7302P EPYC 7232P 600 1200 1800 2400 3000 2788.51 2743.30 2060.05
Result Confidence
OpenBenchmarking.org MB/s, More Is Better Stream 2013-01-17 Type: Triad EPYC 7532 EPYC 7662 EPYC 7702 EPYC 7552 EPYC 7F32 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7542 EPYC 7F52 EPYC 7232P EPYC 7272 EPYC 7282 20K 40K 60K 80K 100K Min: 99194.2 / Avg: 99248.22 / Max: 99293.1 Min: 98280 / Avg: 98343.22 / Max: 98393.4 Min: 97939.6 / Avg: 98034.8 / Max: 98096.1 Min: 96474.4 / Avg: 96497.14 / Max: 96541 Min: 89468.9 / Avg: 89567.18 / Max: 89800.2 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: 86972.9 / Avg: 87057.04 / Max: 87161.9 Min: 71942.4 / Avg: 72315.56 / Max: 73068.3 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 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 7F32 EPYC 7542 EPYC 7502P EPYC 7532 EPYC 7642 EPYC 7552 EPYC 7662 EPYC 7232P EPYC 7702 EPYC 7402P EPYC 7302P EPYC 7282 EPYC 7272 EPYC 7F52 2 4 6 8 10 SE +/- 0.017, N = 14 SE +/- 0.009, N = 15 SE +/- 0.028, N = 3 SE +/- 0.022, N = 3 SE +/- 0.016, N = 3 SE +/- 0.008, N = 15 SE +/- 0.022, N = 3 SE +/- 0.030, N = 11 SE +/- 0.016, N = 3 SE +/- 0.026, N = 3 SE +/- 0.046, N = 15 SE +/- 0.033, N = 3 SE +/- 0.155, N = 4 SE +/- 0.391, N = 3 4.578 4.713 4.820 4.821 4.825 4.852 4.920 4.944 5.067 5.270 5.772 5.855 5.930 8.171 MIN: 4.43 / MAX: 10.46 MIN: 4.51 / MAX: 6.85 MIN: 4.67 / MAX: 6.92 MIN: 4.72 / MAX: 5.31 MIN: 4.71 / MAX: 5.16 MIN: 4.69 / MAX: 5.21 MIN: 4.78 / MAX: 5.1 MIN: 4.74 / MAX: 7.04 MIN: 4.95 / MAX: 5.21 MIN: 5.12 / MAX: 6.52 MIN: 5.46 / MAX: 20.47 MIN: 5.58 / MAX: 23.16 MIN: 5.53 / MAX: 20.6 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 7F32 EPYC 7542 EPYC 7502P EPYC 7532 EPYC 7642 EPYC 7552 EPYC 7662 EPYC 7232P EPYC 7702 EPYC 7402P EPYC 7302P EPYC 7282 EPYC 7272 EPYC 7F52 3 6 9 12 15 Min: 4.51 / Avg: 4.58 / Max: 4.67 Min: 4.6 / Avg: 4.71 / Max: 4.75 Min: 4.78 / Avg: 4.82 / Max: 4.87 Min: 4.8 / Avg: 4.82 / Max: 4.87 Min: 4.79 / Avg: 4.83 / Max: 4.84 Min: 4.78 / Avg: 4.85 / Max: 4.89 Min: 4.88 / Avg: 4.92 / Max: 4.96 Min: 4.81 / Avg: 4.94 / Max: 5.12 Min: 5.05 / Avg: 5.07 / Max: 5.1 Min: 5.23 / Avg: 5.27 / Max: 5.32 Min: 5.57 / Avg: 5.77 / Max: 6.19 Min: 5.81 / Avg: 5.86 / Max: 5.92 Min: 5.66 / Avg: 5.93 / Max: 6.37 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 7F32 EPYC 7F52 EPYC 7502P EPYC 7542 EPYC 7552 EPYC 7532 EPYC 7702 EPYC 7282 EPYC 7662 EPYC 7272 EPYC 7232P 50 100 150 200 250 SE +/- 1.27, N = 12 SE +/- 2.04, N = 12 SE +/- 1.66, N = 3 SE +/- 1.31, N = 12 SE +/- 1.35, N = 3 SE +/- 1.09, N = 12 SE +/- 1.19, N = 3 SE +/- 1.05, N = 3 SE +/- 1.10, N = 3 SE +/- 1.75, N = 3 SE +/- 2.36, N = 3 119.44 122.44 128.92 130.09 131.53 132.04 132.62 135.68 136.87 137.59 212.89 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 7F32 EPYC 7F52 EPYC 7502P EPYC 7542 EPYC 7552 EPYC 7532 EPYC 7702 EPYC 7282 EPYC 7662 EPYC 7272 EPYC 7232P 40 80 120 160 200 Min: 112.44 / Avg: 119.44 / Max: 126.77 Min: 113.19 / Avg: 122.44 / Max: 133.84 Min: 126.46 / Avg: 128.92 / Max: 132.08 Min: 122.93 / Avg: 130.09 / Max: 137.37 Min: 128.85 / Avg: 131.53 / Max: 133.13 Min: 125.23 / Avg: 132.04 / Max: 137.09 Min: 130.9 / Avg: 132.62 / Max: 134.89 Min: 133.59 / Avg: 135.68 / Max: 136.92 Min: 134.99 / Avg: 136.87 / Max: 138.8 Min: 134.17 / Avg: 137.59 / Max: 139.97 Min: 209.86 / Avg: 212.89 / Max: 217.53 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 7532 EPYC 7702 EPYC 7662 EPYC 7552 EPYC 7F32 EPYC 7302P EPYC 7402P EPYC 7542 EPYC 7502P EPYC 7F52 EPYC 7232P EPYC 7272 EPYC 7282 20K 40K 60K 80K 100K SE +/- 10.31, N = 5 SE +/- 31.65, N = 5 SE +/- 13.27, N = 5 SE +/- 15.41, N = 5 SE +/- 52.59, N = 5 SE +/- 8.02, N = 5 SE +/- 5.59, N = 5 SE +/- 5.66, N = 5 SE +/- 14.85, N = 5 SE +/- 330.72, N = 5 SE +/- 9.94, N = 5 SE +/- 7.06, N = 5 SE +/- 2.37, N = 5 90663.2 90511.8 90296.5 88717.2 82399.7 80140.1 79677.2 79674.1 79342.9 66901.1 52390.0 51714.4 51093.1 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 7302P EPYC 7F32 EPYC 7402P EPYC 7542 EPYC 7232P EPYC 7502P EPYC 7552 EPYC 7272 EPYC 7532 EPYC 7282 EPYC 7662 EPYC 7702 EPYC 7F52 200 400 600 800 1000 1003.43 973.24 902.05 873.56 854.90 844.44 790.62 785.09 762.36 734.63 678.70 648.19 560.85
Result Confidence
OpenBenchmarking.org MB/s, More Is Better Stream 2013-01-17 Type: Copy EPYC 7532 EPYC 7702 EPYC 7662 EPYC 7552 EPYC 7F32 EPYC 7302P EPYC 7402P EPYC 7542 EPYC 7502P EPYC 7F52 EPYC 7232P EPYC 7272 EPYC 7282 16K 32K 48K 64K 80K Min: 90631.3 / Avg: 90663.16 / Max: 90687.7 Min: 90390.8 / Avg: 90511.82 / Max: 90564 Min: 90262 / Avg: 90296.46 / Max: 90328.8 Min: 88676.8 / Avg: 88717.18 / Max: 88755.4 Min: 82189.9 / Avg: 82399.72 / Max: 82465.6 Min: 80119.5 / Avg: 80140.14 / Max: 80160.6 Min: 79657.3 / Avg: 79677.16 / Max: 79688.5 Min: 79657.3 / Avg: 79674.1 / Max: 79689.4 Min: 79306.1 / Avg: 79342.9 / Max: 79388.7 Min: 65648.8 / Avg: 66901.12 / Max: 67581.9 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 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 7702 EPYC 7662 EPYC 7642 EPYC 7552 EPYC 7542 EPYC 7502P EPYC 7532 EPYC 7F52 EPYC 7402P EPYC 7302P EPYC 7282 EPYC 7F32 EPYC 7272 EPYC 7232P 20 40 60 80 100 SE +/- 0.06, N = 3 SE +/- 0.05, N = 3 SE +/- 0.01, N = 3 SE +/- 0.03, N = 3 SE +/- 0.02, N = 3 SE +/- 0.01, N = 3 SE +/- 0.02, N = 3 SE +/- 0.21, N = 3 SE +/- 0.02, N = 3 SE +/- 0.08, N = 3 SE +/- 0.06, N = 3 SE +/- 0.01, N = 3 SE +/- 0.03, N = 3 SE +/- 0.05, N = 3 42.56 43.06 43.82 43.84 44.55 45.44 46.10 46.54 47.41 52.75 55.22 59.56 60.20 75.33
Result Confidence
OpenBenchmarking.org Seconds, Fewer Is Better Timed PHP Compilation 7.4.2 Time To Compile EPYC 7702 EPYC 7662 EPYC 7642 EPYC 7552 EPYC 7542 EPYC 7502P EPYC 7532 EPYC 7F52 EPYC 7402P EPYC 7302P EPYC 7282 EPYC 7F32 EPYC 7272 EPYC 7232P 14 28 42 56 70 Min: 42.5 / Avg: 42.56 / Max: 42.67 Min: 43 / Avg: 43.06 / Max: 43.15 Min: 43.8 / Avg: 43.82 / Max: 43.84 Min: 43.81 / Avg: 43.84 / Max: 43.91 Min: 44.52 / Avg: 44.55 / Max: 44.58 Min: 45.42 / Avg: 45.44 / Max: 45.46 Min: 46.08 / Avg: 46.1 / Max: 46.13 Min: 46.12 / Avg: 46.54 / Max: 46.75 Min: 47.38 / Avg: 47.41 / Max: 47.44 Min: 52.62 / Avg: 52.75 / Max: 52.9 Min: 55.1 / Avg: 55.22 / Max: 55.29 Min: 59.55 / Avg: 59.56 / Max: 59.58 Min: 60.16 / Avg: 60.2 / Max: 60.27 Min: 75.27 / Avg: 75.33 / Max: 75.44
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 7542 EPYC 7702 EPYC 7662 EPYC 7552 EPYC 7502P EPYC 7F52 EPYC 7532 EPYC 7402P EPYC 7302P EPYC 7282 EPYC 7272 EPYC 7F32 EPYC 7232P 8 16 24 32 40 SE +/- 0.11, N = 3 SE +/- 0.20, N = 3 SE +/- 0.05, N = 3 SE +/- 0.07, N = 3 SE +/- 0.11, N = 3 SE +/- 0.05, N = 3 SE +/- 0.01, N = 3 SE +/- 0.11, N = 3 SE +/- 0.10, N = 3 SE +/- 0.06, N = 3 SE +/- 0.05, N = 3 SE +/- 0.11, N = 3 SE +/- 0.06, N = 3 18.66 18.73 18.79 18.86 19.38 19.86 19.94 20.87 23.39 24.23 26.90 27.20 33.02
Result Confidence
OpenBenchmarking.org Seconds, Fewer Is Better OCRMyPDF 9.6.0+dfsg Processing 60 Page PDF Document EPYC 7542 EPYC 7702 EPYC 7662 EPYC 7552 EPYC 7502P EPYC 7F52 EPYC 7532 EPYC 7402P EPYC 7302P EPYC 7282 EPYC 7272 EPYC 7F32 EPYC 7232P 7 14 21 28 35 Min: 18.45 / Avg: 18.66 / Max: 18.82 Min: 18.39 / Avg: 18.73 / Max: 19.1 Min: 18.7 / Avg: 18.79 / Max: 18.88 Min: 18.73 / Avg: 18.85 / Max: 18.96 Min: 19.15 / Avg: 19.38 / Max: 19.51 Min: 19.76 / Avg: 19.86 / Max: 19.94 Min: 19.92 / Avg: 19.94 / Max: 19.97 Min: 20.74 / Avg: 20.87 / Max: 21.08 Min: 23.21 / Avg: 23.39 / Max: 23.54 Min: 24.11 / Avg: 24.23 / Max: 24.33 Min: 26.81 / Avg: 26.9 / Max: 26.96 Min: 26.98 / Avg: 27.2 / Max: 27.33 Min: 32.94 / Avg: 33.02 / Max: 33.14
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 7532 EPYC 7702 EPYC 7662 EPYC 7552 EPYC 7F32 EPYC 7302P EPYC 7402P EPYC 7542 EPYC 7502P EPYC 7F52 EPYC 7232P EPYC 7272 EPYC 7282 20K 40K 60K 80K 100K SE +/- 7.96, N = 5 SE +/- 25.81, N = 5 SE +/- 29.12, N = 5 SE +/- 16.17, N = 5 SE +/- 18.23, N = 5 SE +/- 17.97, N = 5 SE +/- 9.19, N = 5 SE +/- 16.89, N = 5 SE +/- 13.36, N = 5 SE +/- 39.00, N = 5 SE +/- 61.95, N = 5 SE +/- 9.00, N = 5 SE +/- 6.11, N = 5 97912.5 97206.3 97180.9 95807.0 89255.4 87568.8 86805.6 86737.7 86677.2 72752.2 56795.1 55911.6 55437.2 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 7532 EPYC 7702 EPYC 7662 EPYC 7552 EPYC 7F32 EPYC 7302P EPYC 7402P EPYC 7542 EPYC 7502P EPYC 7F52 EPYC 7232P EPYC 7272 EPYC 7282 20K 40K 60K 80K 100K Min: 97891 / Avg: 97912.52 / Max: 97938.6 Min: 97146.6 / Avg: 97206.28 / Max: 97299.6 Min: 97111 / Avg: 97180.94 / Max: 97268.6 Min: 95762.2 / Avg: 95807.04 / Max: 95857.9 Min: 89196.2 / Avg: 89255.38 / Max: 89299.1 Min: 87527.2 / Avg: 87568.78 / Max: 87617.1 Min: 86780.2 / Avg: 86805.64 / Max: 86837.1 Min: 86695.7 / Avg: 86737.72 / Max: 86780.2 Min: 86645.7 / Avg: 86677.24 / Max: 86711.4 Min: 72639.1 / Avg: 72752.2 / Max: 72844.7 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 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 7532 EPYC 7662 EPYC 7702 EPYC 7552 EPYC 7F32 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7542 EPYC 7F52 EPYC 7232P EPYC 7272 EPYC 7282 20K 40K 60K 80K 100K SE +/- 18.59, N = 5 SE +/- 21.55, N = 5 SE +/- 27.01, N = 5 SE +/- 32.31, N = 5 SE +/- 30.51, N = 5 SE +/- 10.74, N = 5 SE +/- 7.47, N = 5 SE +/- 12.22, N = 5 SE +/- 14.00, N = 5 SE +/- 31.64, N = 5 SE +/- 61.32, N = 5 SE +/- 4.61, N = 5 SE +/- 3.08, N = 5 89487.6 87848.1 87714.6 86805.6 81753.0 79703.5 79147.3 78638.6 78399.9 67011.9 52630.1 51978.2 51044.2 1. (CC) gcc options: -O3 -march=native -fopenmp
Result Confidence
OpenBenchmarking.org MB/s, More Is Better Stream 2013-01-17 Type: Scale EPYC 7532 EPYC 7662 EPYC 7702 EPYC 7552 EPYC 7F32 EPYC 7302P EPYC 7402P EPYC 7502P EPYC 7542 EPYC 7F52 EPYC 7232P EPYC 7272 EPYC 7282 16K 32K 48K 64K 80K Min: 89445.1 / Avg: 89487.56 / Max: 89550.1 Min: 87786 / Avg: 87848.06 / Max: 87907.9 Min: 87618.6 / Avg: 87714.62 / Max: 87786 Min: 86725.2 / Avg: 86805.6 / Max: 86880.2 Min: 81720.5 / Avg: 81753 / Max: 81875 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: 78366.2 / Avg: 78399.86 / Max: 78439.4 Min: 66926.2 / Avg: 67011.88 / Max: 67120.3 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 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 7642 EPYC 7532 EPYC 7662 EPYC 7702 EPYC 7552 EPYC 7402P EPYC 7502P EPYC 7F52 EPYC 7542 EPYC 7302P EPYC 7282 EPYC 7F32 EPYC 7272 EPYC 7232P 2K 4K 6K 8K 10K SE +/- 34.97, N = 3 SE +/- 14.29, N = 3 SE +/- 8.45, N = 3 SE +/- 33.88, N = 3 SE +/- 25.58, N = 3 SE +/- 21.24, N = 3 SE +/- 18.74, N = 3 SE +/- 20.53, N = 3 SE +/- 4.93, N = 3 SE +/- 34.67, N = 3 SE +/- 3.19, N = 3 SE +/- 4.75, N = 3 SE +/- 6.17, N = 3 SE +/- 5.69, N = 3 8499.2 8476.3 8287.7 8248.3 8172.0 8033.0 7903.6 7899.7 7885.0 7699.4 6706.2 6573.9 6498.4 5123.2 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 7402P EPYC 7302P EPYC 7282 EPYC 7272 EPYC 7542 EPYC 7502P EPYC 7552 EPYC 7642 EPYC 7232P EPYC 7532 EPYC 7662 EPYC 7F32 EPYC 7702 EPYC 7F52 30 60 90 120 150 124.95 124.18 123.70 122.04 121.69 121.39 108.55 102.10 101.96 100.70 98.16 96.70 94.05 86.38
Result Confidence
OpenBenchmarking.org MB/s, More Is Better Zstd Compression 1.4.5 Compression Level: 3 EPYC 7642 EPYC 7532 EPYC 7662 EPYC 7702 EPYC 7552 EPYC 7402P EPYC 7502P EPYC 7F52 EPYC 7542 EPYC 7302P EPYC 7282 EPYC 7F32 EPYC 7272 EPYC 7232P 1500 3000 4500 6000 7500 Min: 8460.8 / Avg: 8499.17 / Max: 8569 Min: 8449.2 / Avg: 8476.3 / Max: 8497.7 Min: 8277.2 / Avg: 8287.67 / Max: 8304.4 Min: 8204.5 / Avg: 8248.33 / Max: 8315 Min: 8129 / Avg: 8172.03 / Max: 8217.5 Min: 7990.6 / Avg: 8033.03 / Max: 8056 Min: 7870.9 / Avg: 7903.63 / Max: 7935.8 Min: 7860.7 / Avg: 7899.7 / Max: 7930.3 Min: 7875.6 / Avg: 7885 / Max: 7892.3 Min: 7651 / Avg: 7699.4 / Max: 7766.6 Min: 6700.4 / Avg: 6706.17 / Max: 6711.4 Min: 6567.3 / Avg: 6573.87 / Max: 6583.1 Min: 6486.1 / Avg: 6498.4 / Max: 6505.4 Min: 5117.2 / Avg: 5123.23 / Max: 5134.6 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 7F32 EPYC 7662 EPYC 7402P EPYC 7542 EPYC 7F52 EPYC 7532 EPYC 7552 EPYC 7642 EPYC 7502P EPYC 7702 EPYC 7302P EPYC 7282 EPYC 7272 EPYC 7232P 6K 12K 18K 24K 30K SE +/- 204.43, N = 3 SE +/- 287.13, N = 3 SE +/- 250.51, N = 6 SE +/- 218.98, N = 3 SE +/- 239.23, N = 3 SE +/- 124.32, N = 3 SE +/- 82.21, N = 3 SE +/- 82.48, N = 3 SE +/- 275.94, N = 15 SE +/- 294.57, N = 15 SE +/- 238.46, N = 3 SE +/- 144.50, N = 3 SE +/- 254.46, N = 15 SE +/- 93.54, N = 3 30037 26867 26769 26724 26636 26305 26303 26289 26186 26143 26045 25601 24876 18378 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 7282 EPYC 7272 EPYC 7F32 EPYC 7542 EPYC 7402P EPYC 7302P EPYC 7502P EPYC 7232P EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7532 EPYC 7F52 EPYC 7702 130 260 390 520 650 588.80 580.44 541.24 536.35 530.99 516.81 515.11 440.07 437.62 393.21 383.02 372.69 365.69 361.64
Result Confidence
OpenBenchmarking.org Mflops, More Is Better FFTW 3.3.6 Build: Float + SSE - Size: 2D FFT Size 2048 EPYC 7F32 EPYC 7662 EPYC 7402P EPYC 7542 EPYC 7F52 EPYC 7532 EPYC 7552 EPYC 7642 EPYC 7502P EPYC 7702 EPYC 7302P EPYC 7282 EPYC 7272 EPYC 7232P 5K 10K 15K 20K 25K Min: 29628 / Avg: 30036.67 / Max: 30252 Min: 26432 / Avg: 26866.67 / Max: 27409 Min: 26241 / Avg: 26768.83 / Max: 27891 Min: 26452 / Avg: 26723.67 / Max: 27157 Min: 26158 / Avg: 26636.33 / Max: 26885 Min: 26075 / Avg: 26304.67 / Max: 26502 Min: 26216 / Avg: 26302.67 / Max: 26467 Min: 26194 / Avg: 26288.67 / Max: 26453 Min: 23734 / Avg: 26185.6 / Max: 27586 Min: 23624 / Avg: 26142.87 / Max: 27261 Min: 25635 / Avg: 26045.33 / Max: 26461 Min: 25375 / Avg: 25601 / Max: 25870 Min: 23020 / Avg: 24876 / Max: 25801 Min: 18209 / Avg: 18378 / Max: 18532 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 7302P EPYC 7402P EPYC 7542 EPYC 7F32 EPYC 7502P EPYC 7532 EPYC 7282 EPYC 7272 EPYC 7642 EPYC 7232P EPYC 7552 EPYC 7662 EPYC 7702 EPYC 7F52 8 16 24 32 40 SE +/- 0.03, N = 3 SE +/- 0.07, N = 3 SE +/- 0.15, N = 3 SE +/- 0.09, N = 3 SE +/- 0.26, N = 3 SE +/- 0.04, N = 11 SE +/- 0.09, N = 3 SE +/- 0.33, N = 3 SE +/- 0.19, N = 12 SE +/- 0.22, N = 3 SE +/- 0.25, N = 3 SE +/- 0.12, N = 9 SE +/- 0.16, N = 9 SE +/- 0.33, N = 3 21.88 22.79 23.55 23.75 24.32 24.62 25.17 26.83 27.83 28.19 28.57 32.73 33.98 35.47 MIN: 21.64 / MAX: 23.37 MIN: 22.48 / MAX: 33.96 MIN: 23.01 / MAX: 26.62 MIN: 23.29 / MAX: 24.37 MIN: 23.62 / MAX: 27.07 MIN: 23.94 / MAX: 27.83 MIN: 24.53 / MAX: 50.53 MIN: 26.22 / MAX: 41.74 MIN: 26.6 / MAX: 234.67 MIN: 27.81 / MAX: 29.82 MIN: 27.64 / MAX: 33.13 MIN: 31.74 / MAX: 44.34 MIN: 31.83 / MAX: 59.59 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 7302P EPYC 7402P EPYC 7542 EPYC 7F32 EPYC 7502P EPYC 7532 EPYC 7282 EPYC 7272 EPYC 7642 EPYC 7232P EPYC 7552 EPYC 7662 EPYC 7702 EPYC 7F52 8 16 24 32 40 Min: 21.81 / Avg: 21.88 / Max: 21.92 Min: 22.65 / Avg: 22.79 / Max: 22.86 Min: 23.25 / Avg: 23.55 / Max: 23.73 Min: 23.57 / Avg: 23.75 / Max: 23.86 Min: 23.81 / Avg: 24.32 / Max: 24.65 Min: 24.38 / Avg: 24.62 / Max: 24.86 Min: 25.05 / Avg: 25.17 / Max: 25.35 Min: 26.36 / Avg: 26.83 / Max: 27.48 Min: 27.17 / Avg: 27.83 / Max: 29.25 Min: 27.94 / Avg: 28.19 / Max: 28.64 Min: 28.08 / Avg: 28.57 / Max: 28.9 Min: 32.29 / Avg: 32.73 / Max: 33.15 Min: 33.16 / Avg: 33.98 / Max: 34.66 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 7F52 EPYC 7542 EPYC 7502P EPYC 7642 EPYC 7702 EPYC 7662 EPYC 7552 EPYC 7402P EPYC 7532 EPYC 7302P EPYC 7282 EPYC 7F32 EPYC 7272 EPYC 7232P 6 12 18 24 30 SE +/- 0.08, N = 4 SE +/- 0.06, N = 4 SE +/- 0.15, N = 4 SE +/- 0.13, N = 4 SE +/- 0.03, N = 4 SE +/- 0.10, N = 4 SE +/- 0.08, N = 4 SE +/- 0.05, N = 4 SE +/- 0.08, N = 4 SE +/- 0.17, N = 3 SE +/- 0.10, N = 3 SE +/- 0.09, N = 3 SE +/- 0.17, N = 3 SE +/- 0.17, N = 3 14.60 15.72 15.85 15.89 15.94 15.97 15.97 16.12 16.33 17.18 18.10 18.88 19.11 23.56
Result Confidence
OpenBenchmarking.org Seconds, Fewer Is Better Numenta Anomaly Benchmark 1.1 Detector: Relative Entropy EPYC 7F52 EPYC 7542 EPYC 7502P EPYC 7642 EPYC 7702 EPYC 7662 EPYC 7552 EPYC 7402P EPYC 7532 EPYC 7302P EPYC 7282 EPYC 7F32 EPYC 7272 EPYC 7232P 6 12 18 24 30 Min: 14.38 / Avg: 14.6 / Max: 14.74 Min: 15.6 / Avg: 15.72 / Max: 15.88 Min: 15.61 / Avg: 15.85 / Max: 16.23 Min: 15.65 / Avg: 15.89 / Max: 16.17 Min: 15.88 / Avg: 15.94 / Max: 16.04 Min: 15.81 / Avg: 15.97 / Max: 16.23 Min: 15.82 / Avg: 15.97 / Max: 16.13 Min: 16.01 / Avg: 16.12 / Max: 16.23 Min: 16.13 / Avg: 16.33 / Max: 16.51 Min: 17 / Avg: 17.18 / Max: 17.52 Min: 17.96 / Avg: 18.1 / Max: 18.29 Min: 18.71 / Avg: 18.88 / Max: 19.01 Min: 18.77 / Avg: 19.11 / Max: 19.31 Min: 23.35 / Avg: 23.56 / Max: 23.91
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 7702 EPYC 7662 EPYC 7552 EPYC 7542 EPYC 7F52 EPYC 7502P EPYC 7532 EPYC 7402P EPYC 7302P EPYC 7282 EPYC 7F32 EPYC 7272 3 6 9 12 15 SE +/- 0.00, 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 = 6 SE +/- 0.02, N = 5 SE +/- 0.01, N = 5 SE +/- 0.00, N = 5 5.82 6.68 6.78 6.93 7.02 7.10 7.17 7.33 7.47 8.30 8.63 9.04 9.38 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 7702 EPYC 7662 EPYC 7552 EPYC 7542 EPYC 7F52 EPYC 7502P EPYC 7532 EPYC 7402P EPYC 7302P EPYC 7282 EPYC 7F32 EPYC 7272 3 6 9 12 15 Min: 5.81 / Avg: 5.82 / Max: 5.83 Min: 6.64 / Avg: 6.68 / Max: 6.71 Min: 6.76 / Avg: 6.78 / Max: 6.8 Min: 6.89 / Avg: 6.93 / Max: 6.96 Min: 7.01 / Avg: 7.02 / Max: 7.04 Min: 7.07 / Avg: 7.1 / Max: 7.13 Min: 7.15 / Avg: 7.17 / Max: 7.18 Min: 7.31 / Avg: 7.33 / Max: 7.35 Min: 7.43 / Avg: 7.47 / Max: 7.49 Min: 8.25 / Avg: 8.3 / Max: 8.34 Min: 8.59 / Avg: 8.63 / Max: 8.68 Min: 9.02 / Avg: 9.04 / Max: 9.06 Min: 9.37 / Avg: 9.38 / Max: 9.39 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 7F52 EPYC 7642 EPYC 7702 EPYC 7662 EPYC 7532 EPYC 7542 EPYC 7402P EPYC 7502P EPYC 7552 EPYC 7302P EPYC 7282 EPYC 7272 EPYC 7F32 EPYC 7232P 8 16 24 32 40 SE +/- 0.11, N = 3 SE +/- 0.08, N = 3 SE +/- 0.12, N = 3 SE +/- 0.05, N = 3 SE +/- 0.06, N = 3 SE +/- 0.07, N = 3 SE +/- 0.07, N = 3 SE +/- 0.09, N = 3 SE +/- 0.05, N = 3 SE +/- 0.19, N = 9 SE +/- 0.08, N = 3 SE +/- 0.07, N = 3 SE +/- 0.07, N = 3 SE +/- 0.02, N = 3 21.43 22.01 22.05 22.05 22.09 22.30 22.40 22.42 22.54 23.15 24.90 25.66 29.61 34.51 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 7F52 EPYC 7642 EPYC 7702 EPYC 7662 EPYC 7532 EPYC 7542 EPYC 7402P EPYC 7502P EPYC 7552 EPYC 7302P EPYC 7282 EPYC 7272 EPYC 7F32 EPYC 7232P 7 14 21 28 35 Min: 21.32 / Avg: 21.43 / Max: 21.65 Min: 21.89 / Avg: 22.01 / Max: 22.17 Min: 21.86 / Avg: 22.05 / Max: 22.28 Min: 22 / Avg: 22.05 / Max: 22.15 Min: 22.03 / Avg: 22.09 / Max: 22.22 Min: 22.23 / Avg: 22.3 / Max: 22.43 Min: 22.31 / Avg: 22.4 / Max: 22.53 Min: 22.33 / Avg: 22.42 / Max: 22.59 Min: 22.49 / Avg: 22.54 / Max: 22.64 Min: 22.45 / Avg: 23.15 / Max: 23.78 Min: 24.75 / Avg: 24.9 / Max: 25.01 Min: 25.58 / Avg: 25.66 / Max: 25.79 Min: 29.47 / Avg: 29.61 / Max: 29.69 Min: 34.46 / Avg: 34.51 / Max: 34.53 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 7402P EPYC 7542 EPYC 7502P EPYC 7282 EPYC 7552 EPYC 7642 EPYC 7532 EPYC 7662 EPYC 7702 EPYC 7302P EPYC 7F52 EPYC 7272 EPYC 7F32 EPYC 7232P 60 120 180 240 300 173.05 173.16 173.53 177.85 182.38 185.01 186.27 187.07 188.84 191.51 192.28 210.16 247.66 278.32
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 7F52 EPYC 7F32 EPYC 7302P EPYC 7402P EPYC 7542 EPYC 7272 EPYC 7232P EPYC 7282 EPYC 7502P EPYC 7532 EPYC 7642 EPYC 7552 EPYC 7702 EPYC 7662 30 60 90 120 150 SE +/- 0.24, N = 3 SE +/- 0.18, N = 3 SE +/- 0.21, N = 3 SE +/- 0.29, N = 3 SE +/- 0.07, N = 3 SE +/- 0.05, N = 3 SE +/- 0.07, N = 3 SE +/- 0.16, N = 3 SE +/- 0.21, N = 3 SE +/- 0.34, N = 3 SE +/- 0.17, N = 3 SE +/- 1.17, N = 4 SE +/- 0.25, N = 3 SE +/- 1.02, N = 3 72.43 72.89 85.93 86.00 86.72 87.60 88.67 89.20 94.26 96.81 102.45 104.52 115.27 116.15 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 7F52 EPYC 7F32 EPYC 7302P EPYC 7402P EPYC 7542 EPYC 7272 EPYC 7232P EPYC 7282 EPYC 7502P EPYC 7532 EPYC 7642 EPYC 7552 EPYC 7702 EPYC 7662 20 40 60 80 100 Min: 72.17 / Avg: 72.43 / Max: 72.9 Min: 72.56 / Avg: 72.89 / Max: 73.16 Min: 85.7 / Avg: 85.93 / Max: 86.35 Min: 85.64 / Avg: 86 / Max: 86.58 Min: 86.61 / Avg: 86.72 / Max: 86.86 Min: 87.51 / Avg: 87.6 / Max: 87.67 Min: 88.6 / Avg: 88.67 / Max: 88.81 Min: 88.88 / Avg: 89.2 / Max: 89.39 Min: 93.87 / Avg: 94.26 / Max: 94.59 Min: 96.44 / Avg: 96.81 / Max: 97.49 Min: 102.2 / Avg: 102.45 / Max: 102.77 Min: 103.18 / Avg: 104.52 / Max: 108.01 Min: 114.96 / Avg: 115.27 / Max: 115.77 Min: 115.11 / Avg: 116.15 / Max: 118.18 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 7542 EPYC 7F32 EPYC 7F52 EPYC 7282 EPYC 7302P EPYC 7502P EPYC 7272 EPYC 7402P EPYC 7532 EPYC 7232P EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 0.2745 0.549 0.8235 1.098 1.3725 SE +/- 0.00, N = 3 SE +/- 0.00, N = 3 SE +/- 0.00, N = 3 SE +/- 0.01, N = 4 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 +/- 0.01, N = 4 SE +/- 0.00, N = 3 SE +/- 0.00, N = 3 SE +/- 0.00, N = 3 SE +/- 0.00, N = 3 0.77 0.78 0.79 0.79 0.84 0.84 0.87 0.88 0.95 0.96 0.99 1.02 1.07 1.22
Result Confidence
OpenBenchmarking.org ms, Fewer Is Better OpenVINO 2021.1 Model: Age Gender Recognition Retail 0013 FP32 - Device: CPU EPYC 7542 EPYC 7F32 EPYC 7F52 EPYC 7282 EPYC 7302P EPYC 7502P EPYC 7272 EPYC 7402P EPYC 7532 EPYC 7232P EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 2 4 6 8 10 Min: 0.77 / Avg: 0.77 / Max: 0.78 Min: 0.78 / Avg: 0.78 / Max: 0.79 Min: 0.78 / Avg: 0.79 / Max: 0.79 Min: 0.77 / Avg: 0.79 / Max: 0.81 Min: 0.83 / Avg: 0.84 / Max: 0.84 Min: 0.83 / Avg: 0.84 / Max: 0.84 Min: 0.87 / Avg: 0.87 / Max: 0.87 Min: 0.87 / Avg: 0.88 / Max: 0.91 Min: 0.95 / Avg: 0.95 / Max: 0.95 Min: 0.94 / Avg: 0.96 / Max: 0.99 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
Result
OpenBenchmarking.org ms, Fewer Is Better OpenVINO 2021.1 Model: Age Gender Recognition Retail 0013 FP16 - Device: CPU EPYC 7542 EPYC 7282 EPYC 7F32 EPYC 7F52 EPYC 7302P EPYC 7502P EPYC 7272 EPYC 7402P EPYC 7532 EPYC 7232P EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 0.2723 0.5446 0.8169 1.0892 1.3615 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 SE +/- 0.01, N = 3 SE +/- 0.01, N = 3 SE +/- 0.00, N = 3 SE +/- 0.01, N = 15 SE +/- 0.00, N = 3 SE +/- 0.00, N = 3 SE +/- 0.00, N = 3 SE +/- 0.00, N = 3 0.77 0.78 0.79 0.81 0.84 0.84 0.89 0.92 0.95 0.98 0.99 1.02 1.06 1.21
Result Confidence
OpenBenchmarking.org ms, Fewer Is Better OpenVINO 2021.1 Model: Age Gender Recognition Retail 0013 FP16 - Device: CPU EPYC 7542 EPYC 7282 EPYC 7F32 EPYC 7F52 EPYC 7302P EPYC 7502P EPYC 7272 EPYC 7402P EPYC 7532 EPYC 7232P EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 2 4 6 8 10 Min: 0.77 / Avg: 0.77 / Max: 0.78 Min: 0.77 / Avg: 0.78 / Max: 0.79 Min: 0.78 / Avg: 0.79 / Max: 0.81 Min: 0.8 / Avg: 0.81 / Max: 0.82 Min: 0.83 / Avg: 0.84 / Max: 0.84 Min: 0.83 / Avg: 0.84 / Max: 0.84 Min: 0.87 / Avg: 0.89 / Max: 0.91 Min: 0.91 / Avg: 0.92 / Max: 0.93 Min: 0.95 / Avg: 0.95 / Max: 0.95 Min: 0.91 / Avg: 0.98 / Max: 1.03 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
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 7542 EPYC 7642 EPYC 7502P EPYC 7662 EPYC 7532 EPYC 7552 EPYC 7702 EPYC 7F32 EPYC 7402P EPYC 7232P EPYC 7302P EPYC 7F52 EPYC 7282 EPYC 7272 9 18 27 36 45 SE +/- 0.05, N = 15 SE +/- 0.03, N = 3 SE +/- 0.12, N = 3 SE +/- 0.10, N = 3 SE +/- 0.05, N = 3 SE +/- 0.05, N = 15 SE +/- 0.07, N = 3 SE +/- 0.01, N = 14 SE +/- 0.97, N = 3 SE +/- 0.12, N = 11 SE +/- 0.09, N = 15 SE +/- 0.19, N = 3 SE +/- 0.12, N = 3 SE +/- 0.11, N = 4 24.30 24.78 25.06 25.22 25.27 25.44 26.92 27.45 29.02 31.44 31.54 33.50 33.59 38.10 MIN: 23.72 / MAX: 27.28 MIN: 24.46 / MAX: 25.37 MIN: 24.51 / MAX: 27.82 MIN: 24.73 / MAX: 27.24 MIN: 24.96 / MAX: 28.42 MIN: 24.73 / MAX: 28.58 MIN: 26.49 / MAX: 27.67 MIN: 27.01 / MAX: 58.07 MIN: 27.23 / MAX: 33.12 MIN: 30.44 / MAX: 49.82 MIN: 30.05 / MAX: 48.95 MIN: 32.85 / MAX: 46.41 MIN: 32.54 / MAX: 48.77 MIN: 36.85 / MAX: 55.75 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 7542 EPYC 7642 EPYC 7502P EPYC 7662 EPYC 7532 EPYC 7552 EPYC 7702 EPYC 7F32 EPYC 7402P EPYC 7232P EPYC 7302P EPYC 7F52 EPYC 7282 EPYC 7272 8 16 24 32 40 Min: 23.9 / Avg: 24.3 / Max: 24.57 Min: 24.73 / Avg: 24.78 / Max: 24.82 Min: 24.81 / Avg: 25.06 / Max: 25.18 Min: 25.03 / Avg: 25.22 / Max: 25.35 Min: 25.2 / Avg: 25.27 / Max: 25.36 Min: 25.04 / Avg: 25.44 / Max: 25.64 Min: 26.83 / Avg: 26.92 / Max: 27.06 Min: 27.35 / Avg: 27.44 / Max: 27.53 Min: 27.93 / Avg: 29.02 / Max: 30.96 Min: 30.9 / Avg: 31.44 / Max: 32.5 Min: 30.84 / Avg: 31.54 / Max: 32 Min: 33.28 / Avg: 33.5 / Max: 33.89 Min: 33.39 / Avg: 33.59 / Max: 33.8 Min: 37.9 / Avg: 38.1 / Max: 38.42 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 7702 EPYC 7662 EPYC 7642 EPYC 7542 EPYC 7552 EPYC 7502P EPYC 7532 EPYC 7402P EPYC 7F52 EPYC 7302P EPYC 7282 EPYC 7F32 EPYC 7272 EPYC 7232P 8 16 24 32 40 SE +/- 0.02, N = 3 SE +/- 0.02, N = 3 SE +/- 0.04, N = 3 SE +/- 0.05, N = 3 SE +/- 0.03, N = 3 SE +/- 0.03, N = 3 SE +/- 0.01, N = 3 SE +/- 0.03, N = 3 SE +/- 0.07, N = 3 SE +/- 0.04, N = 3 SE +/- 0.03, N = 3 SE +/- 0.22, N = 3 SE +/- 0.25, N = 3 SE +/- 0.41, N = 3 21.97 22.13 22.55 22.64 22.65 23.11 23.55 23.87 24.42 26.02 26.79 28.10 29.95 33.92 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 7702 EPYC 7662 EPYC 7642 EPYC 7542 EPYC 7552 EPYC 7502P EPYC 7532 EPYC 7402P EPYC 7F52 EPYC 7302P EPYC 7282 EPYC 7F32 EPYC 7272 EPYC 7232P 7 14 21 28 35 Min: 21.94 / Avg: 21.97 / Max: 21.99 Min: 22.09 / Avg: 22.13 / Max: 22.15 Min: 22.48 / Avg: 22.55 / Max: 22.63 Min: 22.58 / Avg: 22.64 / Max: 22.73 Min: 22.58 / Avg: 22.65 / Max: 22.7 Min: 23.07 / Avg: 23.11 / Max: 23.16 Min: 23.54 / Avg: 23.55 / Max: 23.58 Min: 23.81 / Avg: 23.87 / Max: 23.93 Min: 24.31 / Avg: 24.42 / Max: 24.54 Min: 25.95 / Avg: 26.02 / Max: 26.08 Min: 26.76 / Avg: 26.79 / Max: 26.84 Min: 27.88 / Avg: 28.1 / Max: 28.53 Min: 29.5 / Avg: 29.95 / Max: 30.34 Min: 33.49 / Avg: 33.92 / Max: 34.73 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 7F52 EPYC 7502P EPYC 7542 EPYC 7702 EPYC 7662 EPYC 7532 EPYC 7642 EPYC 7552 EPYC 7402P EPYC 7302P EPYC 7F32 EPYC 7282 EPYC 7272 EPYC 7232P 10 20 30 40 50 SE +/- 0.20, N = 3 SE +/- 0.27, N = 3 SE +/- 0.20, N = 3 SE +/- 0.26, N = 3 SE +/- 0.35, N = 3 SE +/- 0.11, N = 3 SE +/- 0.24, N = 3 SE +/- 0.14, N = 3 SE +/- 0.24, N = 3 SE +/- 0.10, N = 3 SE +/- 0.22, N = 3 SE +/- 0.48, N = 3 SE +/- 0.13, N = 3 SE +/- 0.11, N = 3 29.45 32.65 32.87 33.27 33.41 33.43 33.60 33.96 34.31 34.84 35.67 36.35 38.07 45.21
Result Confidence
OpenBenchmarking.org Seconds, Fewer Is Better Numenta Anomaly Benchmark 1.1 Detector: Bayesian Changepoint EPYC 7F52 EPYC 7502P EPYC 7542 EPYC 7702 EPYC 7662 EPYC 7532 EPYC 7642 EPYC 7552 EPYC 7402P EPYC 7302P EPYC 7F32 EPYC 7282 EPYC 7272 EPYC 7232P 9 18 27 36 45 Min: 29.13 / Avg: 29.45 / Max: 29.83 Min: 32.15 / Avg: 32.64 / Max: 33.08 Min: 32.54 / Avg: 32.87 / Max: 33.22 Min: 32.84 / Avg: 33.27 / Max: 33.73 Min: 32.9 / Avg: 33.41 / Max: 34.08 Min: 33.26 / Avg: 33.43 / Max: 33.62 Min: 33.36 / Avg: 33.6 / Max: 34.09 Min: 33.82 / Avg: 33.96 / Max: 34.23 Min: 33.83 / Avg: 34.31 / Max: 34.61 Min: 34.65 / Avg: 34.84 / Max: 35.01 Min: 35.42 / Avg: 35.67 / Max: 36.1 Min: 35.71 / Avg: 36.35 / Max: 37.28 Min: 37.91 / Avg: 38.07 / Max: 38.32 Min: 45 / Avg: 45.21 / Max: 45.37
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 7F52 EPYC 7542 EPYC 7402P EPYC 7502P EPYC 7282 EPYC 7532 EPYC 7302P EPYC 7552 EPYC 7662 EPYC 7702 EPYC 7272 EPYC 7F32 EPYC 7232P 1100 2200 3300 4400 5500 SE +/- 17.61, N = 4 SE +/- 30.98, N = 5 SE +/- 36.08, N = 5 SE +/- 31.58, N = 20 SE +/- 23.50, N = 13 SE +/- 38.48, N = 5 SE +/- 23.38, N = 5 SE +/- 25.46, N = 5 SE +/- 22.90, N = 5 SE +/- 23.53, N = 20 SE +/- 35.80, N = 6 SE +/- 13.18, N = 4 SE +/- 47.23, N = 4 3288 3304 3310 3358 3492 3497 3526 3550 3624 3626 3757 4095 5021
Result Confidence
OpenBenchmarking.org msec, Fewer Is Better DaCapo Benchmark 9.12-MR1 Java Test: Tradesoap EPYC 7F52 EPYC 7542 EPYC 7402P EPYC 7502P EPYC 7282 EPYC 7532 EPYC 7302P EPYC 7552 EPYC 7662 EPYC 7702 EPYC 7272 EPYC 7F32 EPYC 7232P 900 1800 2700 3600 4500 Min: 3254 / Avg: 3287.75 / Max: 3330 Min: 3195 / Avg: 3303.6 / Max: 3360 Min: 3228 / Avg: 3310.2 / Max: 3400 Min: 3220 / Avg: 3358.3 / Max: 3805 Min: 3310 / Avg: 3491.92 / Max: 3632 Min: 3410 / Avg: 3496.6 / Max: 3597 Min: 3448 / Avg: 3526.2 / Max: 3591 Min: 3490 / Avg: 3550 / Max: 3631 Min: 3562 / Avg: 3624.4 / Max: 3691 Min: 3427 / Avg: 3625.95 / Max: 3913 Min: 3621 / Avg: 3757.17 / Max: 3836 Min: 4078 / Avg: 4095 / Max: 4134 Min: 4937 / Avg: 5020.5 / Max: 5136
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 7F32 EPYC 7F52 EPYC 7302P EPYC 7232P EPYC 7402P EPYC 7272 EPYC 7542 EPYC 7282 EPYC 7502P EPYC 7532 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 2K 4K 6K 8K 10K SE +/- 45.76, N = 3 SE +/- 112.30, N = 4 SE +/- 1.83, N = 3 SE +/- 15.37, N = 3 SE +/- 18.32, N = 3 SE +/- 2.92, N = 3 SE +/- 29.60, N = 3 SE +/- 45.05, N = 3 SE +/- 63.96, N = 12 SE +/- 105.59, N = 12 SE +/- 70.17, N = 12 SE +/- 73.86, N = 12 SE +/- 46.88, N = 3 SE +/- 53.19, N = 12 9823 9348 8975 8836 8810 8721 8698 8611 8421 8070 7373 7221 6686 6478 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 7F32 EPYC 7302P EPYC 7402P EPYC 7542 EPYC 7502P EPYC 7F52 EPYC 7532 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 40 80 120 160 200 172.02 154.91 142.11 135.13 129.62 108.45 101.89 96.92 82.09 74.72 68.55 59.42 50.67 46.15
Result Confidence
OpenBenchmarking.org Inferences Per Minute, More Is Better ONNX Runtime 1.6 Model: shufflenet-v2-10 - Device: OpenMP CPU EPYC 7F32 EPYC 7F52 EPYC 7302P EPYC 7232P EPYC 7402P EPYC 7272 EPYC 7542 EPYC 7282 EPYC 7502P EPYC 7532 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 2K 4K 6K 8K 10K Min: 9743 / Avg: 9822.67 / Max: 9901.5 Min: 9037.5 / Avg: 9348.13 / Max: 9565.5 Min: 8973 / Avg: 8974.83 / Max: 8978.5 Min: 8814.5 / Avg: 8836.33 / Max: 8866 Min: 8780.5 / Avg: 8809.83 / Max: 8843.5 Min: 8717.5 / Avg: 8720.67 / Max: 8726.5 Min: 8644 / Avg: 8698 / Max: 8746 Min: 8522 / Avg: 8611.17 / Max: 8667 Min: 7942 / Avg: 8421.42 / Max: 8675.5 Min: 7492 / Avg: 8070 / Max: 8524 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 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 7302P EPYC 7272 EPYC 7282 EPYC 7402P EPYC 7502P EPYC 7542 EPYC 7F52 EPYC 7F32 EPYC 7532 EPYC 7232P EPYC 7642 EPYC 7552 EPYC 7662 EPYC 7702 8 16 24 32 40 SE +/- 0.08, N = 3 SE +/- 0.09, N = 3 SE +/- 0.08, N = 3 SE +/- 0.05, N = 3 SE +/- 0.14, N = 3 SE +/- 0.07, N = 3 SE +/- 0.15, N = 3 SE +/- 0.05, N = 3 SE +/- 0.05, N = 11 SE +/- 0.01, N = 3 SE +/- 0.09, N = 12 SE +/- 0.03, N = 3 SE +/- 0.15, N = 9 SE +/- 0.19, N = 9 22.45 22.62 22.85 23.02 23.73 24.52 25.20 25.76 25.94 27.97 28.68 28.94 32.09 33.16 MIN: 21.7 / MAX: 24.03 MIN: 22.05 / MAX: 23.63 MIN: 21.95 / MAX: 99.38 MIN: 22.47 / MAX: 24.28 MIN: 22.99 / MAX: 25.94 MIN: 24.07 / MAX: 27.01 MIN: 24.28 / MAX: 26.66 MIN: 24.63 / MAX: 28.33 MIN: 25.15 / MAX: 38.37 MIN: 27.46 / MAX: 42.1 MIN: 27.54 / MAX: 42.27 MIN: 28.1 / MAX: 41.11 MIN: 30.51 / MAX: 174.53 MIN: 31.64 / MAX: 127 1. (CXX) g++ options: -O3 -rdynamic -lgomp -lpthread
Result Confidence
OpenBenchmarking.org ms, Fewer Is Better NCNN 20201218 Target: CPU - Model: squeezenet_ssd EPYC 7302P EPYC 7272 EPYC 7282 EPYC 7402P EPYC 7502P EPYC 7542 EPYC 7F52 EPYC 7F32 EPYC 7532 EPYC 7232P EPYC 7642 EPYC 7552 EPYC 7662 EPYC 7702 7 14 21 28 35 Min: 22.32 / Avg: 22.45 / Max: 22.58 Min: 22.44 / Avg: 22.62 / Max: 22.74 Min: 22.7 / Avg: 22.85 / Max: 22.98 Min: 22.92 / Avg: 23.02 / Max: 23.09 Min: 23.45 / Avg: 23.73 / Max: 23.93 Min: 24.41 / Avg: 24.52 / Max: 24.65 Min: 24.91 / Avg: 25.2 / Max: 25.41 Min: 25.69 / Avg: 25.76 / Max: 25.86 Min: 25.63 / Avg: 25.94 / Max: 26.21 Min: 27.95 / Avg: 27.97 / Max: 27.99 Min: 28.28 / Avg: 28.68 / Max: 29.56 Min: 28.89 / Avg: 28.94 / Max: 28.98 Min: 31.56 / Avg: 32.09 / Max: 32.7 Min: 32.47 / Avg: 33.16 / Max: 34.44 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 7282 EPYC 7272 EPYC 7402P EPYC 7502P EPYC 7232P EPYC 7542 EPYC 7302P EPYC 7F32 EPYC 7552 EPYC 7F52 EPYC 7532 EPYC 7642 EPYC 7662 EPYC 7702 400K 800K 1200K 1600K 2000K SE +/- 12175.94, N = 3 SE +/- 20232.46, N = 3 SE +/- 7805.03, N = 3 SE +/- 7760.40, N = 3 SE +/- 16960.13, N = 3 SE +/- 7106.01, N = 3 SE +/- 7235.14, N = 3 SE +/- 14389.61, N = 3 SE +/- 4883.16, N = 3 SE +/- 13461.20, N = 3 SE +/- 13194.50, N = 3 SE +/- 14031.09, N = 3 SE +/- 9874.65, N = 3 SE +/- 10548.76, N = 3 2043037 2023180 1959615 1950080 1944496 1923368 1898428 1772037 1771624 1676516 1636092 1583350 1397475 1372955 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 7542 EPYC 7502P EPYC 7F32 EPYC 7552 EPYC 7532 EPYC 7F52 EPYC 7642 EPYC 7662 EPYC 7702 6K 12K 18K 24K 30K 29655.38 28304.98 27647.84 22851.81 21034.07 20274.62 20067.14 19861.21 15592.36 14192.86 12966.29 12835.03 10885.37 10196.91
Result Confidence
OpenBenchmarking.org Final Score, More Is Better BlogBench 1.1 Test: Read EPYC 7282 EPYC 7272 EPYC 7402P EPYC 7502P EPYC 7232P EPYC 7542 EPYC 7302P EPYC 7F32 EPYC 7552 EPYC 7F52 EPYC 7532 EPYC 7642 EPYC 7662 EPYC 7702 400K 800K 1200K 1600K 2000K Min: 2022967 / Avg: 2043037.33 / Max: 2065016 Min: 1992185 / Avg: 2023179.67 / Max: 2061206 Min: 1944836 / Avg: 1959614.67 / Max: 1971357 Min: 1935120 / Avg: 1950080.33 / Max: 1961140 Min: 1916141 / Avg: 1944496.33 / Max: 1974796 Min: 1909275 / Avg: 1923368 / Max: 1932004 Min: 1890301 / Avg: 1898428 / Max: 1912860 Min: 1743950 / Avg: 1772037 / Max: 1791514 Min: 1764285 / Avg: 1771624.33 / Max: 1780874 Min: 1650220 / Avg: 1676515.67 / Max: 1694665 Min: 1610844 / Avg: 1636092.33 / Max: 1655363 Min: 1565457 / Avg: 1583350 / Max: 1611018 Min: 1384215 / Avg: 1397475 / Max: 1416780 Min: 1360224 / Avg: 1372955 / Max: 1393890 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 7F32 EPYC 7F52 EPYC 7272 EPYC 7302P EPYC 7282 EPYC 7402P EPYC 7232P EPYC 7542 EPYC 7502P EPYC 7532 EPYC 7552 EPYC 7702 EPYC 7662 1000 2000 3000 4000 5000 SE +/- 31.43, N = 6 SE +/- 31.15, N = 7 SE +/- 22.48, N = 6 SE +/- 38.29, N = 5 SE +/- 31.79, N = 5 SE +/- 13.74, N = 5 SE +/- 29.37, N = 5 SE +/- 15.11, N = 5 SE +/- 22.77, N = 5 SE +/- 44.06, N = 5 SE +/- 34.34, N = 5 SE +/- 47.69, N = 5 SE +/- 39.23, N = 5 3316 3323 3552 3633 3671 3778 3793 3861 3917 4026 4463 4686 4773
Result Confidence
OpenBenchmarking.org msec, Fewer Is Better DaCapo Benchmark 9.12-MR1 Java Test: H2 EPYC 7F32 EPYC 7F52 EPYC 7272 EPYC 7302P EPYC 7282 EPYC 7402P EPYC 7232P EPYC 7542 EPYC 7502P EPYC 7532 EPYC 7552 EPYC 7702 EPYC 7662 800 1600 2400 3200 4000 Min: 3220 / Avg: 3315.5 / Max: 3444 Min: 3208 / Avg: 3323.43 / Max: 3442 Min: 3511 / Avg: 3551.67 / Max: 3657 Min: 3534 / Avg: 3633.2 / Max: 3722 Min: 3564 / Avg: 3671.2 / Max: 3763 Min: 3743 / Avg: 3778.2 / Max: 3810 Min: 3701 / Avg: 3792.8 / Max: 3886 Min: 3817 / Avg: 3860.6 / Max: 3906 Min: 3832 / Avg: 3917.4 / Max: 3957 Min: 3901 / Avg: 4025.6 / Max: 4157 Min: 4370 / Avg: 4463.2 / Max: 4566 Min: 4536 / Avg: 4686 / Max: 4799 Min: 4691 / Avg: 4773.4 / Max: 4896
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 7F32 EPYC 7F52 EPYC 7272 EPYC 7232P EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7542 EPYC 7502P EPYC 7532 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 6K 12K 18K 24K 30K SE +/- 296.05, N = 4 SE +/- 205.94, N = 13 SE +/- 251.88, N = 3 SE +/- 130.62, N = 3 SE +/- 162.08, N = 13 SE +/- 278.67, N = 4 SE +/- 228.79, N = 5 SE +/- 300.22, N = 3 SE +/- 303.68, N = 3 SE +/- 233.41, N = 5 SE +/- 149.83, N = 11 SE +/- 208.12, N = 5 SE +/- 203.19, N = 6 SE +/- 189.69, N = 6 27135.63 24205.54 23807.67 23230.19 22574.80 22339.85 21653.91 21442.00 21272.04 20967.48 20634.20 20036.19 19915.00 19062.92 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 7F32 EPYC 7302P EPYC 7402P EPYC 7542 EPYC 7502P EPYC 7F52 EPYC 7552 EPYC 7532 EPYC 7642 EPYC 7662 EPYC 7702 110 220 330 440 550 531.57 527.48 475.56 446.35 405.87 372.78 365.15 356.46 283.96 278.09 261.72 242.20 231.24 211.71
Result Confidence
OpenBenchmarking.org Test Cases Per Minute, More Is Better Darmstadt Automotive Parallel Heterogeneous Suite Backend: OpenMP - Kernel: Points2Image EPYC 7F32 EPYC 7F52 EPYC 7272 EPYC 7232P EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7542 EPYC 7502P EPYC 7532 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 5K 10K 15K 20K 25K Min: 26266.6 / Avg: 27135.63 / Max: 27598.01 Min: 22569.97 / Avg: 24205.54 / Max: 25313.47 Min: 23305.32 / Avg: 23807.67 / Max: 24091.45 Min: 22989.39 / Avg: 23230.19 / Max: 23438.32 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: 20857.09 / Avg: 21442 / Max: 21851.95 Min: 20665.78 / Avg: 21272.04 / Max: 21606.83 Min: 20100.44 / Avg: 20967.48 / Max: 21472.74 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 1. (CXX) g++ options: -O3 -std=c++11 -fopenmp
Result
OpenBenchmarking.org ms, Fewer Is Better NCNN 20201218 Target: CPU - Model: resnet18 EPYC 7F32 EPYC 7302P EPYC 7402P EPYC 7542 EPYC 7532 EPYC 7502P EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7552 EPYC 7642 EPYC 7F52 EPYC 7662 EPYC 7702 4 8 12 16 20 SE +/- 0.06, N = 3 SE +/- 0.02, N = 3 SE +/- 0.02, N = 3 SE +/- 0.09, N = 3 SE +/- 0.03, N = 11 SE +/- 0.22, N = 3 SE +/- 0.01, N = 3 SE +/- 0.16, N = 3 SE +/- 0.23, N = 3 SE +/- 0.09, N = 3 SE +/- 0.50, N = 12 SE +/- 0.02, N = 3 SE +/- 0.08, N = 9 SE +/- 0.13, N = 9 11.88 12.02 12.53 13.01 13.09 13.17 14.14 14.50 14.52 14.95 15.35 15.83 16.19 16.80 MIN: 11.62 / MAX: 12.46 MIN: 11.87 / MAX: 12.25 MIN: 12.29 / MAX: 14.54 MIN: 12.71 / MAX: 16.73 MIN: 12.54 / MAX: 15.91 MIN: 12.72 / MAX: 15.99 MIN: 14.02 / MAX: 14.84 MIN: 14.03 / MAX: 30.23 MIN: 14.04 / MAX: 90.85 MIN: 14.44 / MAX: 17.51 MIN: 13.83 / MAX: 1062.41 MIN: 15.56 / MAX: 17.09 MIN: 14.96 / MAX: 24.1 MIN: 15.34 / MAX: 148.17 1. (CXX) g++ options: -O3 -rdynamic -lgomp -lpthread
Result Confidence
OpenBenchmarking.org ms, Fewer Is Better NCNN 20201218 Target: CPU - Model: resnet18 EPYC 7F32 EPYC 7302P EPYC 7402P EPYC 7542 EPYC 7532 EPYC 7502P EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7552 EPYC 7642 EPYC 7F52 EPYC 7662 EPYC 7702 4 8 12 16 20 Min: 11.76 / Avg: 11.88 / Max: 11.97 Min: 11.98 / Avg: 12.02 / Max: 12.05 Min: 12.49 / Avg: 12.53 / Max: 12.57 Min: 12.88 / Avg: 13.01 / Max: 13.19 Min: 12.94 / Avg: 13.09 / Max: 13.29 Min: 12.85 / Avg: 13.17 / Max: 13.59 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: 14.77 / Avg: 14.95 / Max: 15.05 Min: 14.54 / Avg: 15.35 / Max: 20.77 Min: 15.79 / Avg: 15.83 / Max: 15.87 Min: 15.8 / Avg: 16.19 / Max: 16.66 Min: 16.19 / Avg: 16.8 / Max: 17.25 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 7402P EPYC 7542 EPYC 7502P EPYC 7532 EPYC 7302P EPYC 7642 EPYC 7282 EPYC 7552 EPYC 7272 EPYC 7662 EPYC 7F32 EPYC 7F52 EPYC 7702 EPYC 7232P 300 600 900 1200 1500 1546 1534 1488 1475 1459 1403 1384 1348 1307 1219 1173 1159 1124 1094
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 7F52 EPYC 7F32 EPYC 7542 EPYC 7552 EPYC 7662 EPYC 7502P EPYC 7272 EPYC 7532 EPYC 7702 EPYC 7282 EPYC 7232P 50 100 150 200 250 SE +/- 2.33, N = 9 SE +/- 1.05, N = 3 SE +/- 1.90, N = 3 SE +/- 1.89, N = 3 SE +/- 1.33, N = 3 SE +/- 1.93, N = 5 SE +/- 1.59, N = 3 SE +/- 1.85, N = 3 SE +/- 1.88, N = 4 SE +/- 1.23, N = 3 SE +/- 2.54, N = 3 151.46 158.79 165.66 170.22 172.37 173.90 174.20 175.85 177.62 183.22 211.49 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 7F52 EPYC 7F32 EPYC 7542 EPYC 7552 EPYC 7662 EPYC 7502P EPYC 7272 EPYC 7532 EPYC 7702 EPYC 7282 EPYC 7232P 40 80 120 160 200 Min: 142 / Avg: 151.46 / Max: 162.3 Min: 157.45 / Avg: 158.79 / Max: 160.86 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: 168.11 / Avg: 173.89 / Max: 179.12 Min: 171.02 / Avg: 174.2 / Max: 175.94 Min: 172.42 / Avg: 175.85 / Max: 178.76 Min: 172.48 / Avg: 177.62 / Max: 181.39 Min: 181.83 / Avg: 183.22 / Max: 185.67 Min: 206.5 / Avg: 211.49 / Max: 214.78 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 7532 EPYC 7642 EPYC 7502P EPYC 7662 EPYC 7542 EPYC 7552 EPYC 7702 EPYC 7402P EPYC 7F32 EPYC 7302P EPYC 7282 EPYC 7232P EPYC 7272 EPYC 7F52 3 6 9 12 15 SE +/- 0.016, N = 3 SE +/- 0.003, N = 3 SE +/- 0.048, N = 3 SE +/- 0.018, N = 3 SE +/- 0.252, N = 15 SE +/- 0.271, N = 15 SE +/- 0.014, N = 3 SE +/- 0.114, N = 3 SE +/- 0.062, N = 14 SE +/- 0.061, N = 15 SE +/- 0.027, N = 3 SE +/- 0.071, N = 11 SE +/- 0.115, N = 4 SE +/- 0.064, N = 3 7.338 7.479 7.493 7.542 7.625 8.142 8.375 8.978 9.357 9.504 9.610 9.650 9.768 10.209 MIN: 7.23 / MAX: 7.87 MIN: 7.34 / MAX: 8.04 MIN: 7.29 / MAX: 9.78 MIN: 7.38 / MAX: 8.01 MIN: 7.08 / MAX: 14.04 MIN: 7.43 / MAX: 13.26 MIN: 8.25 / MAX: 8.55 MIN: 8.7 / MAX: 10.42 MIN: 8.98 / MAX: 23.95 MIN: 9.01 / MAX: 25.56 MIN: 9.28 / MAX: 25.71 MIN: 9.16 / MAX: 25.96 MIN: 9.3 / MAX: 12.44 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 7532 EPYC 7642 EPYC 7502P EPYC 7662 EPYC 7542 EPYC 7552 EPYC 7702 EPYC 7402P EPYC 7F32 EPYC 7302P EPYC 7282 EPYC 7232P EPYC 7272 EPYC 7F52 3 6 9 12 15 Min: 7.32 / Avg: 7.34 / Max: 7.37 Min: 7.47 / Avg: 7.48 / Max: 7.48 Min: 7.44 / Avg: 7.49 / Max: 7.59 Min: 7.51 / Avg: 7.54 / Max: 7.56 Min: 7.17 / Avg: 7.63 / Max: 10.86 Min: 7.63 / Avg: 8.14 / Max: 11.51 Min: 8.35 / Avg: 8.37 / Max: 8.4 Min: 8.84 / Avg: 8.98 / Max: 9.2 Min: 9.16 / Avg: 9.36 / Max: 10 Min: 9.26 / Avg: 9.5 / Max: 10.27 Min: 9.58 / Avg: 9.61 / Max: 9.66 Min: 9.3 / Avg: 9.65 / Max: 10.14 Min: 9.49 / Avg: 9.77 / Max: 10.05 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 7542 EPYC 7502P EPYC 7F52 EPYC 7402P EPYC 7552 EPYC 7532 EPYC 7662 EPYC 7702 EPYC 7302P EPYC 7282 EPYC 7F32 EPYC 7272 EPYC 7232P 16 32 48 64 80 SE +/- 0.04, N = 3 SE +/- 0.03, N = 3 SE +/- 0.12, N = 3 SE +/- 0.04, N = 3 SE +/- 0.08, N = 3 SE +/- 0.06, N = 3 SE +/- 0.01, N = 3 SE +/- 0.04, N = 3 SE +/- 0.01, N = 3 SE +/- 0.59, N = 3 SE +/- 0.08, N = 3 SE +/- 0.05, N = 3 SE +/- 0.02, N = 3 52.13 52.74 53.15 53.93 54.49 54.77 55.04 56.03 58.51 61.54 62.24 62.76 72.47 1. RawTherapee, version 5.8, command line.
Result Confidence
OpenBenchmarking.org Seconds, Fewer Is Better RawTherapee Total Benchmark Time EPYC 7542 EPYC 7502P EPYC 7F52 EPYC 7402P EPYC 7552 EPYC 7532 EPYC 7662 EPYC 7702 EPYC 7302P EPYC 7282 EPYC 7F32 EPYC 7272 EPYC 7232P 14 28 42 56 70 Min: 52.04 / Avg: 52.12 / Max: 52.19 Min: 52.69 / Avg: 52.74 / Max: 52.79 Min: 52.9 / Avg: 53.15 / Max: 53.28 Min: 53.88 / Avg: 53.93 / Max: 54 Min: 54.34 / Avg: 54.49 / Max: 54.59 Min: 54.71 / Avg: 54.77 / Max: 54.89 Min: 55.03 / Avg: 55.04 / Max: 55.06 Min: 55.95 / Avg: 56.03 / Max: 56.09 Min: 58.49 / Avg: 58.51 / Max: 58.52 Min: 60.92 / Avg: 61.54 / Max: 62.73 Min: 62.13 / Avg: 62.24 / Max: 62.4 Min: 62.66 / Avg: 62.76 / Max: 62.82 Min: 72.44 / Avg: 72.47 / Max: 72.51 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 7F52 EPYC 7702 EPYC 7662 EPYC 7542 EPYC 7552 EPYC 7502P EPYC 7532 EPYC 7402P EPYC 7F32 EPYC 7302P EPYC 7282 EPYC 7272 EPYC 7232P 2 4 6 8 10 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 SE +/- 0.01, N = 7 SE +/- 0.00, N = 7 SE +/- 0.01, N = 7 SE +/- 0.01, N = 6 SE +/- 0.00, N = 6 SE +/- 0.01, N = 6 SE +/- 0.01, N = 6 5.51 5.76 5.83 5.83 5.89 5.93 6.05 6.06 6.28 6.47 6.68 6.97 7.65 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 7F52 EPYC 7702 EPYC 7662 EPYC 7542 EPYC 7552 EPYC 7502P EPYC 7532 EPYC 7402P EPYC 7F32 EPYC 7302P EPYC 7282 EPYC 7272 EPYC 7232P 3 6 9 12 15 Min: 5.49 / Avg: 5.51 / Max: 5.54 Min: 5.75 / Avg: 5.76 / Max: 5.8 Min: 5.82 / Avg: 5.83 / Max: 5.84 Min: 5.81 / Avg: 5.83 / Max: 5.86 Min: 5.87 / Avg: 5.89 / Max: 5.91 Min: 5.92 / Avg: 5.93 / Max: 5.96 Min: 6.01 / Avg: 6.05 / Max: 6.07 Min: 6.04 / Avg: 6.06 / Max: 6.07 Min: 6.24 / Avg: 6.28 / Max: 6.31 Min: 6.45 / Avg: 6.47 / Max: 6.5 Min: 6.66 / Avg: 6.68 / Max: 6.69 Min: 6.93 / Avg: 6.97 / Max: 7.01 Min: 7.6 / Avg: 7.65 / Max: 7.69 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 7F52 EPYC 7542 EPYC 7502P EPYC 7702 EPYC 7552 EPYC 7402P EPYC 7662 EPYC 7642 EPYC 7532 EPYC 7302P EPYC 7F32 EPYC 7282 EPYC 7272 EPYC 7232P 30 60 90 120 150 SE +/- 0.08, N = 3 SE +/- 0.07, N = 3 SE +/- 0.03, N = 3 SE +/- 0.07, N = 3 SE +/- 0.01, N = 3 SE +/- 0.03, N = 3 SE +/- 0.04, N = 3 SE +/- 0.01, N = 3 SE +/- 0.11, N = 3 SE +/- 0.09, N = 3 SE +/- 0.08, N = 3 SE +/- 0.05, N = 3 SE +/- 0.06, N = 3 SE +/- 0.11, N = 3 82.92 84.83 85.96 86.37 86.95 86.97 87.02 87.21 88.42 92.26 94.01 94.48 99.22 114.83
Result Confidence
OpenBenchmarking.org Seconds, Fewer Is Better Timed GDB GNU Debugger Compilation 9.1 Time To Compile EPYC 7F52 EPYC 7542 EPYC 7502P EPYC 7702 EPYC 7552 EPYC 7402P EPYC 7662 EPYC 7642 EPYC 7532 EPYC 7302P EPYC 7F32 EPYC 7282 EPYC 7272 EPYC 7232P 20 40 60 80 100 Min: 82.8 / Avg: 82.92 / Max: 83.07 Min: 84.74 / Avg: 84.83 / Max: 84.97 Min: 85.93 / Avg: 85.96 / Max: 86.02 Min: 86.23 / Avg: 86.37 / Max: 86.48 Min: 86.95 / Avg: 86.95 / Max: 86.96 Min: 86.94 / Avg: 86.97 / Max: 87.03 Min: 86.98 / Avg: 87.02 / Max: 87.09 Min: 87.2 / Avg: 87.21 / Max: 87.22 Min: 88.21 / Avg: 88.42 / Max: 88.6 Min: 92.07 / Avg: 92.26 / Max: 92.37 Min: 93.84 / Avg: 94.01 / Max: 94.13 Min: 94.41 / Avg: 94.48 / Max: 94.59 Min: 99.11 / Avg: 99.22 / Max: 99.3 Min: 114.63 / Avg: 114.83 / Max: 115
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 7702 EPYC 7662 EPYC 7542 EPYC 7552 EPYC 7402P EPYC 7F32 EPYC 7F52 EPYC 7642 EPYC 7502P EPYC 7302P EPYC 7532 EPYC 7282 EPYC 7272 EPYC 7232P 400 800 1200 1600 2000 SE +/- 1.52, N = 3 SE +/- 1.64, N = 3 SE +/- 3.48, N = 3 SE +/- 16.58, N = 4 SE +/- 1.29, N = 3 SE +/- 0.33, N = 3 SE +/- 11.50, N = 3 SE +/- 22.87, N = 9 SE +/- 5.50, N = 3 SE +/- 5.19, N = 3 SE +/- 6.34, N = 3 SE +/- 4.40, N = 3 SE +/- 1.18, N = 3 SE +/- 0.83, N = 3 1208.31 1216.50 1317.27 1329.90 1342.14 1356.26 1357.30 1372.73 1386.78 1403.52 1403.87 1456.82 1520.43 1656.88 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 7702 EPYC 7662 EPYC 7542 EPYC 7552 EPYC 7402P EPYC 7F32 EPYC 7F52 EPYC 7642 EPYC 7502P EPYC 7302P EPYC 7532 EPYC 7282 EPYC 7272 EPYC 7232P 300 600 900 1200 1500 Min: 1205.82 / Avg: 1208.31 / Max: 1211.05 Min: 1214.11 / Avg: 1216.5 / Max: 1219.63 Min: 1313.6 / Avg: 1317.27 / Max: 1324.22 Min: 1306.89 / Avg: 1329.9 / Max: 1377.55 Min: 1339.87 / Avg: 1342.14 / Max: 1344.32 Min: 1355.84 / Avg: 1356.26 / Max: 1356.92 Min: 1338.99 / Avg: 1357.3 / Max: 1378.5 Min: 1251.31 / Avg: 1372.73 / Max: 1438.64 Min: 1377.07 / Avg: 1386.78 / Max: 1396.11 Min: 1394.1 / Avg: 1403.52 / Max: 1411.99 Min: 1396.5 / Avg: 1403.87 / Max: 1416.5 Min: 1450.92 / Avg: 1456.82 / Max: 1465.43 Min: 1518.1 / Avg: 1520.43 / Max: 1521.97 Min: 1655.62 / Avg: 1656.88 / Max: 1658.44 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 7302P EPYC 7F32 EPYC 7402P EPYC 7532 EPYC 7542 EPYC 7502P EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7552 EPYC 7232P EPYC 7272 EPYC 7F52 EPYC 7282 3 6 9 12 15 SE +/- 0.01, N = 2 SE +/- 0.00, N = 3 SE +/- 0.01, N = 3 SE +/- 0.06, N = 11 SE +/- 0.16, N = 3 SE +/- 0.16, N = 3 SE +/- 0.07, N = 12 SE +/- 0.08, N = 9 SE +/- 0.05, N = 9 SE +/- 0.32, N = 3 SE +/- 0.02, N = 3 SE +/- 0.02, N = 3 SE +/- 0.14, N = 3 SE +/- 0.08, N = 3 7.44 7.60 7.80 7.81 8.28 8.55 8.56 8.81 9.01 9.49 9.86 9.86 9.87 10.16 MIN: 7.34 / MAX: 8.53 MIN: 7.51 / MAX: 8.13 MIN: 7.66 / MAX: 9.41 MIN: 7.55 / MAX: 10.47 MIN: 8 / MAX: 10.85 MIN: 8.18 / MAX: 10.72 MIN: 8.22 / MAX: 24.11 MIN: 8.44 / MAX: 32.96 MIN: 8.61 / MAX: 17.39 MIN: 8.54 / MAX: 13.63 MIN: 9.77 / MAX: 25.65 MIN: 9.77 / MAX: 10.66 MIN: 9.45 / MAX: 10.5 MIN: 9.88 / MAX: 21.62 1. (CXX) g++ options: -O3 -rdynamic -lgomp -lpthread
Result Confidence
OpenBenchmarking.org ms, Fewer Is Better NCNN 20201218 Target: CPU - Model: alexnet EPYC 7302P EPYC 7F32 EPYC 7402P EPYC 7532 EPYC 7542 EPYC 7502P EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7552 EPYC 7232P EPYC 7272 EPYC 7F52 EPYC 7282 3 6 9 12 15 Min: 7.43 / Avg: 7.44 / Max: 7.45 Min: 7.6 / Avg: 7.6 / Max: 7.61 Min: 7.78 / Avg: 7.8 / Max: 7.82 Min: 7.65 / Avg: 7.81 / Max: 8.24 Min: 8.12 / Avg: 8.28 / Max: 8.6 Min: 8.38 / Avg: 8.55 / Max: 8.86 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: 8.86 / Avg: 9.49 / Max: 9.82 Min: 9.84 / Avg: 9.86 / Max: 9.9 Min: 9.82 / Avg: 9.86 / Max: 9.89 Min: 9.7 / Avg: 9.87 / Max: 10.15 Min: 10.05 / Avg: 10.16 / Max: 10.31 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 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 EPYC 7232P EPYC 7302P EPYC 7402P EPYC 7272 EPYC 7282 EPYC 7542 EPYC 7502P EPYC 7552 EPYC 7532 EPYC 7642 40K 80K 120K 160K 200K SE +/- 146.69, N = 3 SE +/- 182.06, N = 3 SE +/- 101.93, N = 3 SE +/- 1333.26, N = 3 SE +/- 139.37, N = 3 SE +/- 37.21, N = 3 SE +/- 92.46, N = 3 SE +/- 272.29, N = 3 SE +/- 76.96, N = 3 SE +/- 120.93, N = 3 SE +/- 187.42, N = 3 SE +/- 1549.72, N = 7 SE +/- 106.86, N = 3 SE +/- 114.49, N = 3 127699 128965 140558 151327 151559 152539 154693 154871 155763 162544 168728 171885 172508 173812 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 7662 EPYC 7702 EPYC 7F32 EPYC 7F52 EPYC 7232P EPYC 7302P EPYC 7402P EPYC 7272 EPYC 7282 EPYC 7542 EPYC 7502P EPYC 7552 EPYC 7532 EPYC 7642 30K 60K 90K 120K 150K 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 Min: 151334 / Avg: 151559 / Max: 151814 Min: 152490 / Avg: 152539 / Max: 152612 Min: 154545 / Avg: 154693 / Max: 154863 Min: 154328 / Avg: 154871.33 / Max: 155175 Min: 155611 / Avg: 155763 / Max: 155860 Min: 162302 / Avg: 162543.67 / Max: 162673 Min: 168512 / Avg: 168727.67 / Max: 169101 Min: 162598 / Avg: 171885 / Max: 173740 Min: 172364 / Avg: 172508.33 / Max: 172717 Min: 173597 / Avg: 173811.67 / Max: 173988 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 7542 EPYC 7532 EPYC 7642 EPYC 7502P EPYC 7662 EPYC 7F32 EPYC 7552 EPYC 7402P EPYC 7702 EPYC 7232P EPYC 7272 EPYC 7302P EPYC 7282 EPYC 7F52 10 20 30 40 50 SE +/- 0.05, N = 15 SE +/- 0.06, N = 3 SE +/- 0.12, N = 3 SE +/- 0.14, N = 3 SE +/- 0.01, N = 3 SE +/- 0.02, N = 14 SE +/- 0.05, N = 15 SE +/- 0.70, N = 3 SE +/- 0.04, N = 3 SE +/- 0.12, N = 11 SE +/- 0.09, N = 4 SE +/- 0.09, N = 15 SE +/- 0.09, N = 3 SE +/- 0.27, N = 3 31.87 32.47 32.86 32.92 33.58 34.91 35.47 36.88 38.00 38.33 38.62 41.12 43.13 43.36 MIN: 30.79 / MAX: 34.77 MIN: 32.03 / MAX: 34.7 MIN: 32.05 / MAX: 34.89 MIN: 32.02 / MAX: 35.9 MIN: 32.98 / MAX: 34.68 MIN: 33.81 / MAX: 50.1 MIN: 34.49 / MAX: 38.11 MIN: 35.1 / MAX: 40.26 MIN: 36.26 / MAX: 38.93 MIN: 37.06 / MAX: 55.19 MIN: 38.09 / MAX: 52.97 MIN: 39.63 / MAX: 81.35 MIN: 42.07 / MAX: 59.48 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 7542 EPYC 7532 EPYC 7642 EPYC 7502P EPYC 7662 EPYC 7F32 EPYC 7552 EPYC 7402P EPYC 7702 EPYC 7232P EPYC 7272 EPYC 7302P EPYC 7282 EPYC 7F52 9 18 27 36 45 Min: 31.52 / Avg: 31.87 / Max: 32.13 Min: 32.35 / Avg: 32.47 / Max: 32.57 Min: 32.62 / Avg: 32.86 / Max: 33.02 Min: 32.64 / Avg: 32.92 / Max: 33.11 Min: 33.57 / Avg: 33.58 / Max: 33.59 Min: 34.79 / Avg: 34.91 / Max: 35.08 Min: 34.98 / Avg: 35.47 / Max: 35.68 Min: 35.66 / Avg: 36.88 / Max: 38.08 Min: 37.92 / Avg: 38 / Max: 38.08 Min: 37.94 / Avg: 38.33 / Max: 39.34 Min: 38.45 / Avg: 38.62 / Max: 38.79 Min: 40.41 / Avg: 41.12 / Max: 41.65 Min: 43 / Avg: 43.13 / Max: 43.3 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 7642 EPYC 7532 EPYC 7662 EPYC 7552 EPYC 7282 EPYC 7702 EPYC 7402P EPYC 7272 EPYC 7542 EPYC 7F52 EPYC 7302P EPYC 7502P EPYC 7F32 EPYC 7232P 20 40 60 80 100 SE +/- 0.17, N = 3 SE +/- 0.67, N = 3 SE +/- 0.33, N = 3 SE +/- 1.04, N = 3 SE +/- 0.29, N = 3 SE +/- 0.44, N = 3 SE +/- 0.29, N = 3 SE +/- 0.17, N = 3 SE +/- 0.58, N = 3 SE +/- 0.60, N = 3 SE +/- 0.67, N = 3 SE +/- 0.53, N = 12 SE +/- 0.67, N = 3 SE +/- 0.00, N = 3 80 79 79 79 77 74 72 70 69 69 69 64 59 59 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 7282 EPYC 7272 EPYC 7232P EPYC 7552 EPYC 7302P EPYC 7402P EPYC 7542 EPYC 7642 EPYC 7502P EPYC 7702 EPYC 7532 EPYC 7662 EPYC 7F32 EPYC 7F52 0.1845 0.369 0.5535 0.738 0.9225 0.82 0.76 0.68 0.67 0.66 0.61 0.60 0.58 0.58 0.57 0.55 0.55 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 7642 EPYC 7532 EPYC 7662 EPYC 7552 EPYC 7282 EPYC 7702 EPYC 7402P EPYC 7272 EPYC 7542 EPYC 7F52 EPYC 7302P EPYC 7502P EPYC 7F32 EPYC 7232P 15 30 45 60 75 Min: 80 / Avg: 80.17 / Max: 80.5 Min: 78.5 / Avg: 79.17 / Max: 80.5 Min: 78.5 / Avg: 79.17 / Max: 79.5 Min: 77 / Avg: 79 / Max: 80.5 Min: 76.5 / Avg: 77 / Max: 77.5 Min: 73.5 / Avg: 74.33 / Max: 75 Min: 71 / Avg: 71.5 / Max: 72 Min: 69.5 / Avg: 69.83 / Max: 70 Min: 68 / Avg: 69 / Max: 70 Min: 68 / Avg: 69.17 / Max: 70 Min: 68 / Avg: 69.33 / Max: 70 Min: 61 / Avg: 64 / Max: 67.5 Min: 58 / Avg: 59.33 / Max: 60 Min: 58.5 / Avg: 58.5 / Max: 58.5 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 7F32 EPYC 7F52 EPYC 7302P EPYC 7532 EPYC 7402P EPYC 7542 EPYC 7502P EPYC 7272 EPYC 7282 EPYC 7232P EPYC 7642 EPYC 7552 EPYC 7702 EPYC 7662 2K 4K 6K 8K 10K SE +/- 15.51, N = 3 SE +/- 27.57, N = 3 SE +/- 5.79, N = 3 SE +/- 8.53, N = 3 SE +/- 4.79, N = 3 SE +/- 0.44, N = 3 SE +/- 6.00, N = 3 SE +/- 6.54, N = 3 SE +/- 21.69, N = 3 SE +/- 13.17, N = 3 SE +/- 9.12, N = 3 SE +/- 22.60, N = 3 SE +/- 20.77, N = 3 SE +/- 18.47, N = 3 11206.8 10910.1 10476.8 10253.3 10178.3 9878.0 9808.0 9442.9 9400.7 9386.8 9301.0 9155.0 8372.7 8328.2 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 7F32 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7542 EPYC 7502P EPYC 7F52 EPYC 7532 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 40 80 120 160 200 182.90 173.90 165.32 165.18 160.12 145.89 138.76 135.67 109.47 106.55 104.37 93.88 83.21 77.37
Result Confidence
OpenBenchmarking.org MB/s, More Is Better C-Blosc 2.0 Beta 5 Compressor: blosclz EPYC 7F32 EPYC 7F52 EPYC 7302P EPYC 7532 EPYC 7402P EPYC 7542 EPYC 7502P EPYC 7272 EPYC 7282 EPYC 7232P EPYC 7642 EPYC 7552 EPYC 7702 EPYC 7662 2K 4K 6K 8K 10K Min: 11190.3 / Avg: 11206.8 / Max: 11237.8 Min: 10869.2 / Avg: 10910.13 / Max: 10962.6 Min: 10468.4 / Avg: 10476.8 / Max: 10487.9 Min: 10242.8 / Avg: 10253.3 / Max: 10270.2 Min: 10170 / Avg: 10178.27 / Max: 10186.6 Min: 9877.3 / Avg: 9878 / Max: 9878.8 Min: 9796 / Avg: 9808 / Max: 9814.1 Min: 9434.1 / Avg: 9442.93 / Max: 9455.7 Min: 9370.8 / Avg: 9400.73 / Max: 9442.9 Min: 9360.9 / Avg: 9386.83 / Max: 9403.8 Min: 9282.8 / Avg: 9301 / Max: 9311.2 Min: 9132 / Avg: 9155 / Max: 9200.2 Min: 8331.9 / Avg: 8372.7 / Max: 8399.9 Min: 8294.6 / Avg: 8328.2 / Max: 8358.3 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 7402P EPYC 7F32 EPYC 7542 EPYC 7532 EPYC 7502P EPYC 7302P EPYC 7552 EPYC 7642 EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7662 EPYC 7702 EPYC 7F52 110 220 330 440 550 SE +/- 4.15, N = 9 SE +/- 0.50, N = 3 SE +/- 1.15, N = 3 SE +/- 0.44, N = 3 SE +/- 4.69, N = 12 SE +/- 5.01, N = 3 SE +/- 0.60, N = 3 SE +/- 3.97, N = 3 SE +/- 0.50, N = 3 SE +/- 1.26, N = 3 SE +/- 0.29, N = 3 SE +/- 6.16, N = 12 SE +/- 7.16, N = 12 SE +/- 6.13, N = 12 500 480 475 466 459 456 440 431 409 403 400 395 390 372 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 7F32 EPYC 7542 EPYC 7502P EPYC 7532 EPYC 7552 EPYC 7642 EPYC 7F52 EPYC 7662 EPYC 7702 1.179 2.358 3.537 4.716 5.895 5.24 4.79 4.71 4.50 4.25 4.10 4.08 3.86 3.27 3.22 2.84 2.50 2.50 2.39
Result Confidence
OpenBenchmarking.org Inferences Per Minute, More Is Better ONNX Runtime 1.6 Model: bertsquad-10 - Device: OpenMP CPU EPYC 7402P EPYC 7F32 EPYC 7542 EPYC 7532 EPYC 7502P EPYC 7302P EPYC 7552 EPYC 7642 EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7662 EPYC 7702 EPYC 7F52 90 180 270 360 450 Min: 468 / Avg: 500.22 / Max: 507 Min: 479.5 / Avg: 480 / Max: 481 Min: 472.5 / Avg: 474.5 / Max: 476.5 Min: 465.5 / Avg: 466.33 / Max: 467 Min: 425.5 / Avg: 459.13 / Max: 469.5 Min: 450.5 / Avg: 456 / Max: 466 Min: 439.5 / Avg: 440.33 / Max: 441.5 Min: 424.5 / Avg: 430.5 / Max: 438 Min: 408 / Avg: 409 / Max: 409.5 Min: 401.5 / Avg: 403 / Max: 405.5 Min: 399.5 / Avg: 400 / Max: 400.5 Min: 343.5 / Avg: 395 / Max: 412.5 Min: 335.5 / Avg: 389.54 / Max: 410.5 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 7F52 EPYC 7542 EPYC 7402P EPYC 7532 EPYC 7502P EPYC 7552 EPYC 7302P EPYC 7F32 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7282 EPYC 7272 EPYC 7232P 1100 2200 3300 4400 5500 SE +/- 88.35, N = 12 SE +/- 67.46, N = 11 SE +/- 71.97, N = 12 SE +/- 35.49, N = 11 SE +/- 62.74, N = 3 SE +/- 27.98, N = 3 SE +/- 73.62, N = 12 SE +/- 5.63, N = 3 SE +/- 52.31, N = 12 SE +/- 95.52, N = 12 SE +/- 84.35, N = 9 SE +/- 24.57, N = 3 SE +/- 16.48, N = 3 SE +/- 3.69, N = 3 5212 4986 4946 4864 4755 4642 4522 4518 4506 4175 4087 4044 3943 3941 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 7282 EPYC 7272 EPYC 7302P EPYC 7542 EPYC 7402P EPYC 7502P EPYC 7F32 EPYC 7552 EPYC 7532 EPYC 7F52 EPYC 7642 EPYC 7702 EPYC 7662 11 22 33 44 55 47.91 45.86 44.61 43.67 40.89 39.90 38.41 36.02 33.35 32.78 28.68 28.36 25.73 25.67
Result Confidence
OpenBenchmarking.org Inferences Per Minute, More Is Better ONNX Runtime 1.6 Model: super-resolution-10 - Device: OpenMP CPU EPYC 7F52 EPYC 7542 EPYC 7402P EPYC 7532 EPYC 7502P EPYC 7552 EPYC 7302P EPYC 7F32 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7282 EPYC 7272 EPYC 7232P 900 1800 2700 3600 4500 Min: 4665 / Avg: 5211.92 / Max: 5596 Min: 4318 / Avg: 4986.05 / Max: 5084 Min: 4494.5 / Avg: 4946.25 / Max: 5164.5 Min: 4539 / Avg: 4864.36 / Max: 4940.5 Min: 4633.5 / Avg: 4754.67 / Max: 4843.5 Min: 4586 / Avg: 4641.67 / Max: 4674.5 Min: 4171 / Avg: 4521.92 / Max: 5107 Min: 4508 / Avg: 4517.67 / Max: 4527.5 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: 3996 / Avg: 4043.83 / Max: 4077.5 Min: 3922 / Avg: 3943 / Max: 3975.5 Min: 3934 / Avg: 3941 / Max: 3946.5 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 7F52 EPYC 7542 EPYC 7502P EPYC 7552 EPYC 7662 EPYC 7402P EPYC 7642 EPYC 7532 EPYC 7702 EPYC 7282 EPYC 7F32 EPYC 7302P EPYC 7272 EPYC 7232P 5 10 15 20 25 SE +/- 0.01, N = 4 SE +/- 0.01, N = 4 SE +/- 0.03, N = 4 SE +/- 0.08, N = 3 SE +/- 0.05, N = 3 SE +/- 0.01, N = 3 SE +/- 0.16, N = 3 SE +/- 0.00, N = 3 SE +/- 0.15, 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 16.20 16.37 16.55 16.67 16.89 16.92 17.03 17.21 17.37 17.39 17.44 17.75 18.10 21.35 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 7F52 EPYC 7542 EPYC 7502P EPYC 7552 EPYC 7662 EPYC 7402P EPYC 7642 EPYC 7532 EPYC 7702 EPYC 7282 EPYC 7F32 EPYC 7302P EPYC 7272 EPYC 7232P 5 10 15 20 25 Min: 16.19 / Avg: 16.2 / Max: 16.23 Min: 16.34 / Avg: 16.37 / Max: 16.39 Min: 16.49 / Avg: 16.55 / Max: 16.65 Min: 16.52 / Avg: 16.67 / Max: 16.78 Min: 16.79 / Avg: 16.89 / Max: 16.96 Min: 16.91 / Avg: 16.92 / Max: 16.93 Min: 16.72 / Avg: 17.03 / Max: 17.24 Min: 17.21 / Avg: 17.21 / Max: 17.22 Min: 17.08 / Avg: 17.37 / Max: 17.52 Min: 17.38 / Avg: 17.39 / Max: 17.4 Min: 17.42 / Avg: 17.43 / Max: 17.46 Min: 17.73 / Avg: 17.75 / Max: 17.77 Min: 18.08 / Avg: 18.1 / Max: 18.11 Min: 21.31 / Avg: 21.35 / Max: 21.39 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 7F52 EPYC 7F32 EPYC 7542 EPYC 7702 EPYC 7502P EPYC 7662 EPYC 7552 EPYC 7402P EPYC 7532 EPYC 7302P EPYC 7282 EPYC 7272 EPYC 7232P 14 28 42 56 70 SE +/- 0.03, N = 3 SE +/- 0.23, N = 3 SE +/- 0.05, N = 3 SE +/- 0.06, N = 3 SE +/- 0.07, N = 3 SE +/- 0.03, N = 3 SE +/- 0.02, N = 3 SE +/- 0.01, N = 3 SE +/- 0.05, N = 3 SE +/- 0.04, N = 3 SE +/- 0.01, N = 3 SE +/- 0.04, N = 3 SE +/- 0.13, N = 3 49.34 53.65 53.93 54.10 54.57 54.82 54.98 55.14 55.59 57.18 58.64 60.10 64.83 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 7F52 EPYC 7F32 EPYC 7542 EPYC 7702 EPYC 7502P EPYC 7662 EPYC 7552 EPYC 7402P EPYC 7532 EPYC 7302P EPYC 7282 EPYC 7272 EPYC 7232P 13 26 39 52 65 Min: 49.28 / Avg: 49.34 / Max: 49.38 Min: 53.23 / Avg: 53.65 / Max: 54.01 Min: 53.83 / Avg: 53.93 / Max: 54.01 Min: 54.02 / Avg: 54.1 / Max: 54.23 Min: 54.42 / Avg: 54.57 / Max: 54.65 Min: 54.77 / Avg: 54.82 / Max: 54.86 Min: 54.94 / Avg: 54.98 / Max: 55.01 Min: 55.12 / Avg: 55.14 / Max: 55.16 Min: 55.5 / Avg: 55.59 / Max: 55.67 Min: 57.13 / Avg: 57.18 / Max: 57.25 Min: 58.62 / Avg: 58.64 / Max: 58.66 Min: 60.03 / Avg: 60.1 / Max: 60.17 Min: 64.68 / Avg: 64.83 / Max: 65.09 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 7F52 EPYC 7542 EPYC 7F32 EPYC 7702 EPYC 7662 EPYC 7502P EPYC 7552 EPYC 7402P EPYC 7532 EPYC 7302P EPYC 7282 EPYC 7272 EPYC 7232P 3 6 9 12 15 SE +/- 0.005, N = 6 SE +/- 0.005, N = 6 SE +/- 0.002, N = 6 SE +/- 0.006, N = 6 SE +/- 0.002, N = 6 SE +/- 0.002, N = 6 SE +/- 0.003, N = 6 SE +/- 0.009, N = 6 SE +/- 0.003, N = 5 SE +/- 0.005, N = 5 SE +/- 0.007, N = 5 SE +/- 0.002, N = 5 SE +/- 0.005, N = 5 7.453 8.038 8.077 8.095 8.132 8.149 8.198 8.267 8.357 8.660 8.923 9.190 9.756 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 7F52 EPYC 7542 EPYC 7F32 EPYC 7702 EPYC 7662 EPYC 7502P EPYC 7552 EPYC 7402P EPYC 7532 EPYC 7302P EPYC 7282 EPYC 7272 EPYC 7232P 3 6 9 12 15 Min: 7.44 / Avg: 7.45 / Max: 7.48 Min: 8.02 / Avg: 8.04 / Max: 8.05 Min: 8.07 / Avg: 8.08 / Max: 8.08 Min: 8.06 / Avg: 8.09 / Max: 8.11 Min: 8.13 / Avg: 8.13 / Max: 8.14 Min: 8.14 / Avg: 8.15 / Max: 8.16 Min: 8.19 / Avg: 8.2 / Max: 8.21 Min: 8.24 / Avg: 8.27 / Max: 8.3 Min: 8.35 / Avg: 8.36 / Max: 8.37 Min: 8.65 / Avg: 8.66 / Max: 8.67 Min: 8.9 / Avg: 8.92 / Max: 8.94 Min: 9.18 / Avg: 9.19 / Max: 9.19 Min: 9.74 / Avg: 9.76 / Max: 9.77 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 7F32 EPYC 7662 EPYC 7702 EPYC 7232P EPYC 7272 EPYC 7F52 EPYC 7302P EPYC 7282 EPYC 7402P EPYC 7552 EPYC 7542 EPYC 7502P EPYC 7642 EPYC 7532 90K 180K 270K 360K 450K SE +/- 95.91, N = 3 SE +/- 1226.45, N = 3 SE +/- 730.51, N = 3 SE +/- 533.40, N = 3 SE +/- 226.68, N = 3 SE +/- 1699.46, N = 3 SE +/- 60.14, N = 3 SE +/- 456.29, N = 3 SE +/- 338.07, N = 3 SE +/- 18239.03, N = 9 SE +/- 147.16, N = 3 SE +/- 440.86, N = 3 SE +/- 10886.13, N = 9 SE +/- 422.64, N = 3 340168 345626 347484 369027 378367 382020 387173 388699 391015 399610 411681 427967 429875 441978 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 7F32 EPYC 7662 EPYC 7702 EPYC 7232P EPYC 7272 EPYC 7F52 EPYC 7302P EPYC 7282 EPYC 7402P EPYC 7552 EPYC 7542 EPYC 7502P EPYC 7642 EPYC 7532 80K 160K 240K 320K 400K Min: 339980 / Avg: 340168 / Max: 340295 Min: 344068 / Avg: 345626.33 / Max: 348046 Min: 346044 / Avg: 347483.67 / Max: 348419 Min: 367965 / Avg: 369027.33 / Max: 369643 Min: 378044 / Avg: 378367 / Max: 378804 Min: 379249 / Avg: 382019.67 / Max: 385110 Min: 387058 / Avg: 387173 / Max: 387261 Min: 387821 / Avg: 388699.33 / Max: 389353 Min: 390425 / Avg: 391015.33 / Max: 391596 Min: 331340 / Avg: 399610.44 / Max: 446964 Min: 411435 / Avg: 411681.33 / Max: 411944 Min: 427345 / Avg: 427966.67 / Max: 428819 Min: 364614 / Avg: 429875.11 / Max: 446994 Min: 441242 / Avg: 441977.67 / Max: 442706 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 7F52 EPYC 7F32 EPYC 7542 EPYC 7502P EPYC 7402P EPYC 7702 EPYC 7552 EPYC 7662 EPYC 7642 EPYC 7532 EPYC 7302P EPYC 7282 EPYC 7272 EPYC 7232P 7 14 21 28 35 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 +/- 0.02, N = 3 SE +/- 0.01, N = 3 SE +/- 0.02, N = 3 SE +/- 0.03, N = 3 SE +/- 0.02, N = 3 SE +/- 0.01, N = 3 SE +/- 0.02, N = 3 21.62 23.00 24.20 24.43 24.53 24.56 24.89 24.92 24.93 25.02 25.02 25.65 26.02 28.08
Result Confidence
OpenBenchmarking.org Seconds, Fewer Is Better Timed Apache Compilation 2.4.41 Time To Compile EPYC 7F52 EPYC 7F32 EPYC 7542 EPYC 7502P EPYC 7402P EPYC 7702 EPYC 7552 EPYC 7662 EPYC 7642 EPYC 7532 EPYC 7302P EPYC 7282 EPYC 7272 EPYC 7232P 6 12 18 24 30 Min: 21.59 / Avg: 21.62 / Max: 21.66 Min: 22.98 / Avg: 23 / Max: 23.04 Min: 24.17 / Avg: 24.2 / Max: 24.23 Min: 24.41 / Avg: 24.43 / Max: 24.46 Min: 24.51 / Avg: 24.53 / Max: 24.56 Min: 24.54 / Avg: 24.56 / Max: 24.58 Min: 24.85 / Avg: 24.89 / Max: 24.92 Min: 24.89 / Avg: 24.92 / Max: 24.95 Min: 24.92 / Avg: 24.93 / Max: 24.95 Min: 25 / Avg: 25.02 / Max: 25.06 Min: 24.97 / Avg: 25.02 / Max: 25.06 Min: 25.6 / Avg: 25.65 / Max: 25.68 Min: 26.01 / Avg: 26.02 / Max: 26.03 Min: 28.05 / Avg: 28.08 / Max: 28.12
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 7F52 EPYC 7F32 EPYC 7542 EPYC 7702 EPYC 7662 EPYC 7502P EPYC 7402P EPYC 7642 EPYC 7302P EPYC 7282 EPYC 7532 EPYC 7552 EPYC 7272 EPYC 7232P 4K 8K 12K 16K 20K SE +/- 146.33, N = 3 SE +/- 233.09, N = 3 SE +/- 37.78, N = 3 SE +/- 52.30, N = 3 SE +/- 32.36, N = 3 SE +/- 33.50, N = 3 SE +/- 31.25, N = 3 SE +/- 142.34, N = 3 SE +/- 28.18, N = 3 SE +/- 49.84, N = 3 SE +/- 135.81, N = 9 SE +/- 159.60, N = 7 SE +/- 167.66, N = 3 SE +/- 181.85, N = 3 19037 19036 18047 17793 17681 17664 17644 17609 17600 17559 17308 17090 16820 14713 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 7282 EPYC 7272 EPYC 7542 EPYC 7402P EPYC 7502P EPYC 7232P EPYC 7302P EPYC 7F32 EPYC 7552 EPYC 7642 EPYC 7F52 EPYC 7662 EPYC 7702 EPYC 7532 90 180 270 360 450 395.06 387.92 350.90 344.76 339.99 338.94 337.27 332.96 277.86 257.05 250.92 246.91 241.00 239.28
Result Confidence
OpenBenchmarking.org Mflops, More Is Better FFTW 3.3.6 Build: Float + SSE - Size: 2D FFT Size 4096 EPYC 7F52 EPYC 7F32 EPYC 7542 EPYC 7702 EPYC 7662 EPYC 7502P EPYC 7402P EPYC 7642 EPYC 7302P EPYC 7282 EPYC 7532 EPYC 7552 EPYC 7272 EPYC 7232P 3K 6K 9K 12K 15K Min: 18745 / Avg: 19037 / Max: 19200 Min: 18580 / Avg: 19036.33 / Max: 19347 Min: 18004 / Avg: 18046.67 / Max: 18122 Min: 17693 / Avg: 17792.67 / Max: 17870 Min: 17626 / Avg: 17680.67 / Max: 17738 Min: 17611 / Avg: 17664 / Max: 17726 Min: 17597 / Avg: 17643.67 / Max: 17703 Min: 17324 / Avg: 17608.67 / Max: 17754 Min: 17559 / Avg: 17600 / Max: 17654 Min: 17469 / Avg: 17559.33 / Max: 17641 Min: 16389 / Avg: 17308.33 / Max: 17615 Min: 16499 / Avg: 17090.14 / Max: 17664 Min: 16499 / Avg: 16820.33 / Max: 17064 Min: 14527 / Avg: 14713.33 / Max: 15077 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 7F32 EPYC 7F52 EPYC 7542 EPYC 7402P EPYC 7502P EPYC 7302P EPYC 7552 EPYC 7532 EPYC 7662 EPYC 7642 EPYC 7702 EPYC 7282 EPYC 7272 EPYC 7232P 3 6 9 12 15 SE +/- 0.030, N = 5 SE +/- 0.037, N = 5 SE +/- 0.014, N = 5 SE +/- 0.027, N = 5 SE +/- 0.030, N = 5 SE +/- 0.004, N = 5 SE +/- 0.033, N = 5 SE +/- 0.021, N = 5 SE +/- 0.024, N = 5 SE +/- 0.037, N = 5 SE +/- 0.027, N = 5 SE +/- 0.028, N = 5 SE +/- 0.023, N = 5 SE +/- 0.035, N = 5 8.598 8.868 9.602 9.725 9.735 9.892 9.925 9.938 9.989 10.040 10.097 10.221 10.236 11.112 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 7F32 EPYC 7F52 EPYC 7542 EPYC 7402P EPYC 7502P EPYC 7302P EPYC 7552 EPYC 7532 EPYC 7662 EPYC 7642 EPYC 7702 EPYC 7282 EPYC 7272 EPYC 7232P 3 6 9 12 15 Min: 8.55 / Avg: 8.6 / Max: 8.69 Min: 8.78 / Avg: 8.87 / Max: 8.95 Min: 9.57 / Avg: 9.6 / Max: 9.64 Min: 9.65 / Avg: 9.73 / Max: 9.8 Min: 9.66 / Avg: 9.74 / Max: 9.84 Min: 9.88 / Avg: 9.89 / Max: 9.9 Min: 9.82 / Avg: 9.92 / Max: 10 Min: 9.89 / Avg: 9.94 / Max: 10.01 Min: 9.92 / Avg: 9.99 / Max: 10.06 Min: 9.91 / Avg: 10.04 / Max: 10.12 Min: 10.02 / Avg: 10.1 / Max: 10.18 Min: 10.15 / Avg: 10.22 / Max: 10.32 Min: 10.16 / Avg: 10.24 / Max: 10.3 Min: 11.04 / Avg: 11.11 / Max: 11.22 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 7F32 EPYC 7402P EPYC 7302P EPYC 7542 EPYC 7502P EPYC 7272 EPYC 7532 EPYC 7232P EPYC 7282 EPYC 7642 EPYC 7552 EPYC 7662 EPYC 7702 EPYC 7F52 8 16 24 32 40 SE +/- 0.29, N = 3 SE +/- 0.02, N = 3 SE +/- 0.17, N = 3 SE +/- 0.04, N = 3 SE +/- 0.33, N = 3 SE +/- 0.61, N = 3 SE +/- 0.17, N = 11 SE +/- 0.50, N = 3 SE +/- 0.45, N = 3 SE +/- 0.06, N = 12 SE +/- 0.10, N = 3 SE +/- 0.12, N = 9 SE +/- 0.21, N = 9 SE +/- 0.28, N = 3 27.61 27.78 27.87 28.27 29.11 29.23 29.66 29.67 29.78 30.63 31.61 34.15 35.12 35.38 MIN: 26.76 / MAX: 28.5 MIN: 27.43 / MAX: 29.51 MIN: 27.31 / MAX: 41.48 MIN: 27.87 / MAX: 31.14 MIN: 28.33 / MAX: 32.38 MIN: 28.35 / MAX: 32.28 MIN: 28.65 / MAX: 167.51 MIN: 28.72 / MAX: 42.97 MIN: 28.36 / MAX: 108.17 MIN: 29.81 / MAX: 126.09 MIN: 30.9 / MAX: 36.86 MIN: 32.54 / MAX: 132.52 MIN: 33.13 / MAX: 169.41 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 7F32 EPYC 7402P EPYC 7302P EPYC 7542 EPYC 7502P EPYC 7272 EPYC 7532 EPYC 7232P EPYC 7282 EPYC 7642 EPYC 7552 EPYC 7662 EPYC 7702 EPYC 7F52 8 16 24 32 40 Min: 27.05 / Avg: 27.61 / Max: 28 Min: 27.74 / Avg: 27.78 / Max: 27.82 Min: 27.62 / Avg: 27.87 / Max: 28.19 Min: 28.2 / Avg: 28.27 / Max: 28.34 Min: 28.7 / Avg: 29.11 / Max: 29.76 Min: 28.56 / Avg: 29.23 / Max: 30.45 Min: 29.28 / Avg: 29.66 / Max: 31.16 Min: 29 / Avg: 29.67 / Max: 30.66 Min: 28.88 / Avg: 29.78 / Max: 30.25 Min: 30.33 / Avg: 30.63 / Max: 30.98 Min: 31.41 / Avg: 31.61 / Max: 31.75 Min: 33.31 / Avg: 34.15 / Max: 34.59 Min: 33.91 / Avg: 35.12 / Max: 35.94 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 7F52 EPYC 7702 EPYC 7502P EPYC 7642 EPYC 7662 EPYC 7402P EPYC 7552 EPYC 7532 EPYC 7F32 EPYC 7302P EPYC 7282 EPYC 7542 EPYC 7272 EPYC 7232P 300K 600K 900K 1200K 1500K SE +/- 2686.24, N = 3 SE +/- 628.66, N = 3 SE +/- 702.94, N = 3 SE +/- 1733.41, N = 3 SE +/- 762.66, N = 3 SE +/- 2008.07, N = 3 SE +/- 686.09, N = 3 SE +/- 759.90, N = 3 SE +/- 1176.92, N = 3 SE +/- 1121.87, N = 3 SE +/- 1061.91, N = 3 SE +/- 295.02, N = 3 SE +/- 1242.45, N = 3 SE +/- 1442.60, N = 3 1438050.4 1308517.2 1303437.6 1295588.8 1294664.5 1290897.8 1288738.6 1281490.5 1279851.8 1249264.6 1211354.3 1206497.8 1185857.8 1113861.3
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 7502P EPYC 7402P EPYC 7542 EPYC 7F32 EPYC 7552 EPYC 7532 EPYC 7662 EPYC 7642 EPYC 7F52 EPYC 7702 4K 8K 12K 16K 20K 19958.05 19817.67 19723.37 18467.75 17835.71 17743.64 17199.25 16288.24 15448.09 13818.71 13662.86 13661.39 13202.43 12919.70
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 7F52 EPYC 7702 EPYC 7502P EPYC 7642 EPYC 7662 EPYC 7402P EPYC 7552 EPYC 7532 EPYC 7F32 EPYC 7302P EPYC 7282 EPYC 7542 EPYC 7272 EPYC 7232P 200K 400K 600K 800K 1000K Min: 1433192.9 / Avg: 1438050.37 / Max: 1442466.9 Min: 1307504.2 / Avg: 1308517.23 / Max: 1309668.7 Min: 1302037.7 / Avg: 1303437.6 / Max: 1304249.7 Min: 1293258.5 / Avg: 1295588.83 / Max: 1298976.9 Min: 1293775.5 / Avg: 1294664.5 / Max: 1296182.4 Min: 1287374.1 / Avg: 1290897.83 / Max: 1294328.4 Min: 1287797.7 / Avg: 1288738.57 / Max: 1290074 Min: 1279979.8 / Avg: 1281490.47 / Max: 1282389.9 Min: 1277678.1 / Avg: 1279851.77 / Max: 1281720.8 Min: 1247865.2 / Avg: 1249264.6 / Max: 1251483.2 Min: 1209909.6 / Avg: 1211354.27 / Max: 1213424.8 Min: 1205942.3 / Avg: 1206497.83 / Max: 1206947.8 Min: 1183868.7 / Avg: 1185857.83 / Max: 1188142.2 Min: 1110976.3 / Avg: 1113861.27 / Max: 1115334.9
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 7F52 EPYC 7F32 EPYC 7542 EPYC 7502P EPYC 7402P EPYC 7702 EPYC 7642 EPYC 7552 EPYC 7532 EPYC 7662 EPYC 7302P EPYC 7272 EPYC 7282 EPYC 7232P 80 160 240 320 400 SE +/- 0.20, N = 3 SE +/- 0.65, N = 3 SE +/- 0.40, N = 3 SE +/- 0.31, N = 3 SE +/- 0.30, N = 3 SE +/- 0.70, N = 3 SE +/- 0.24, N = 3 SE +/- 0.35, N = 3 SE +/- 0.48, N = 3 SE +/- 0.41, N = 3 SE +/- 1.35, N = 3 SE +/- 0.30, N = 3 SE +/- 0.76, N = 3 SE +/- 0.53, N = 3 348.66 345.36 311.97 309.10 307.47 306.50 303.75 303.45 303.33 303.21 301.28 298.27 296.96 270.83
Score Per Watt
OpenBenchmarking.org Score Per Watt, More Is Better Numpy Benchmark EPYC 7272 EPYC 7282 EPYC 7232P EPYC 7542 EPYC 7F32 EPYC 7402P EPYC 7502P EPYC 7302P EPYC 7552 EPYC 7F52 EPYC 7642 EPYC 7532 EPYC 7662 EPYC 7702 2 4 6 8 10 6.82 6.72 6.25 6.05 6.03 5.98 5.96 5.85 4.97 4.56 4.46 4.23 4.22 4.18
Result Confidence
OpenBenchmarking.org Score, More Is Better Numpy Benchmark EPYC 7F52 EPYC 7F32 EPYC 7542 EPYC 7502P EPYC 7402P EPYC 7702 EPYC 7642 EPYC 7552 EPYC 7532 EPYC 7662 EPYC 7302P EPYC 7272 EPYC 7282 EPYC 7232P 60 120 180 240 300 Min: 348.4 / Avg: 348.66 / Max: 349.06 Min: 344.12 / Avg: 345.36 / Max: 346.34 Min: 311.24 / Avg: 311.97 / Max: 312.62 Min: 308.57 / Avg: 309.1 / Max: 309.64 Min: 307 / Avg: 307.47 / Max: 308.03 Min: 305.69 / Avg: 306.5 / Max: 307.9 Min: 303.29 / Avg: 303.75 / Max: 304.08 Min: 302.78 / Avg: 303.45 / Max: 303.96 Min: 302.7 / Avg: 303.33 / Max: 304.28 Min: 302.77 / Avg: 303.21 / Max: 304.03 Min: 298.67 / Avg: 301.28 / Max: 303.16 Min: 297.91 / Avg: 298.27 / Max: 298.86 Min: 295.48 / Avg: 296.96 / Max: 298.01 Min: 269.87 / Avg: 270.83 / Max: 271.69
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 7F52 EPYC 7502P EPYC 7542 EPYC 7402P EPYC 7282 EPYC 7302P EPYC 7532 EPYC 7642 EPYC 7272 EPYC 7552 EPYC 7F32 EPYC 7662 EPYC 7702 EPYC 7232P 20 40 60 80 100 SE +/- 0.45, N = 3 SE +/- 1.14, N = 3 SE +/- 0.45, N = 3 SE +/- 0.52, N = 3 SE +/- 0.89, N = 3 SE +/- 0.51, N = 3 SE +/- 0.64, N = 3 SE +/- 0.03, N = 3 SE +/- 1.02, N = 4 SE +/- 0.35, N = 3 SE +/- 0.48, N = 3 SE +/- 0.34, N = 3 SE +/- 0.55, N = 3 SE +/- 0.41, N = 3 83.28 86.23 86.57 86.68 87.94 89.43 91.32 91.51 92.35 92.59 93.79 97.30 97.95 107.01 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 7F52 EPYC 7502P EPYC 7542 EPYC 7402P EPYC 7282 EPYC 7302P EPYC 7532 EPYC 7642 EPYC 7272 EPYC 7552 EPYC 7F32 EPYC 7662 EPYC 7702 EPYC 7232P 20 40 60 80 100 Min: 82.43 / Avg: 83.28 / Max: 83.97 Min: 84.36 / Avg: 86.23 / Max: 88.29 Min: 86.01 / Avg: 86.57 / Max: 87.47 Min: 85.65 / Avg: 86.68 / Max: 87.25 Min: 86.34 / Avg: 87.94 / Max: 89.41 Min: 88.41 / Avg: 89.43 / Max: 89.96 Min: 90.24 / Avg: 91.31 / Max: 92.46 Min: 91.47 / Avg: 91.51 / Max: 91.55 Min: 90.47 / Avg: 92.35 / Max: 94.9 Min: 91.9 / Avg: 92.59 / Max: 93.05 Min: 92.83 / Avg: 93.79 / Max: 94.31 Min: 96.62 / Avg: 97.29 / Max: 97.72 Min: 96.92 / Avg: 97.95 / Max: 98.78 Min: 106.25 / Avg: 107.01 / Max: 107.66 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 7F52 EPYC 7F32 EPYC 7502P EPYC 7542 EPYC 7702 EPYC 7662 EPYC 7402P EPYC 7532 EPYC 7552 EPYC 7302P EPYC 7282 EPYC 7272 EPYC 7232P 1200 2400 3600 4800 6000 SE +/- 11.37, N = 7 SE +/- 22.07, N = 7 SE +/- 12.59, N = 6 SE +/- 17.79, N = 6 SE +/- 22.61, N = 6 SE +/- 12.22, N = 6 SE +/- 17.40, N = 6 SE +/- 21.30, N = 6 SE +/- 9.85, N = 6 SE +/- 20.02, N = 6 SE +/- 22.94, N = 6 SE +/- 17.45, N = 6 SE +/- 49.86, N = 6 4375 4544 4916 4935 5012 5021 5053 5070 5112 5145 5280 5353 5580
Result Confidence
OpenBenchmarking.org msec, Fewer Is Better DaCapo Benchmark 9.12-MR1 Java Test: Jython EPYC 7F52 EPYC 7F32 EPYC 7502P EPYC 7542 EPYC 7702 EPYC 7662 EPYC 7402P EPYC 7532 EPYC 7552 EPYC 7302P EPYC 7282 EPYC 7272 EPYC 7232P 1000 2000 3000 4000 5000 Min: 4328 / Avg: 4374.57 / Max: 4420 Min: 4475 / Avg: 4544.29 / Max: 4659 Min: 4883 / Avg: 4916 / Max: 4959 Min: 4891 / Avg: 4934.83 / Max: 4996 Min: 4957 / Avg: 5011.67 / Max: 5119 Min: 4981 / Avg: 5020.83 / Max: 5072 Min: 5000 / Avg: 5053.33 / Max: 5104 Min: 5014 / Avg: 5070.17 / Max: 5141 Min: 5077 / Avg: 5112 / Max: 5138 Min: 5069 / Avg: 5145.33 / Max: 5205 Min: 5219 / Avg: 5279.5 / Max: 5358 Min: 5275 / Avg: 5352.5 / Max: 5392 Min: 5502 / Avg: 5579.5 / Max: 5827
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 7F52 EPYC 7F32 EPYC 7542 EPYC 7502P EPYC 7702 EPYC 7402P EPYC 7552 EPYC 7532 EPYC 7642 EPYC 7302P EPYC 7662 EPYC 7272 EPYC 7282 EPYC 7232P 5 10 15 20 25 SE +/- 0.14, N = 3 SE +/- 0.10, N = 3 SE +/- 0.17, N = 3 SE +/- 0.13, N = 3 SE +/- 0.10, N = 3 SE +/- 0.09, N = 3 SE +/- 0.09, N = 3 SE +/- 0.09, N = 3 SE +/- 0.06, N = 3 SE +/- 0.20, N = 3 SE +/- 0.09, N = 3 SE +/- 0.15, N = 3 SE +/- 0.20, N = 3 SE +/- 0.03, N = 3 17.67 17.70 20.10 20.29 20.39 20.50 20.85 20.86 20.86 20.87 20.90 21.27 21.38 22.45 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 7F52 EPYC 7F32 EPYC 7542 EPYC 7502P EPYC 7702 EPYC 7402P EPYC 7552 EPYC 7532 EPYC 7642 EPYC 7302P EPYC 7662 EPYC 7272 EPYC 7282 EPYC 7232P 5 10 15 20 25 Min: 17.4 / Avg: 17.67 / Max: 17.81 Min: 17.51 / Avg: 17.7 / Max: 17.84 Min: 19.77 / Avg: 20.1 / Max: 20.29 Min: 20.1 / Avg: 20.29 / Max: 20.55 Min: 20.19 / Avg: 20.39 / Max: 20.52 Min: 20.34 / Avg: 20.5 / Max: 20.64 Min: 20.67 / Avg: 20.85 / Max: 20.97 Min: 20.71 / Avg: 20.86 / Max: 21.01 Min: 20.76 / Avg: 20.86 / Max: 20.97 Min: 20.48 / Avg: 20.87 / Max: 21.12 Min: 20.76 / Avg: 20.9 / Max: 21.07 Min: 21.11 / Avg: 21.27 / Max: 21.58 Min: 21.02 / Avg: 21.38 / Max: 21.69 Min: 22.41 / Avg: 22.45 / Max: 22.5 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 7F32 EPYC 7F52 EPYC 7542 EPYC 7502P EPYC 7702 EPYC 7402P EPYC 7532 EPYC 7662 EPYC 7302P EPYC 7552 EPYC 7642 EPYC 7272 EPYC 7282 EPYC 7232P 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 +/- 0.00, 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 7.47 7.54 8.57 8.62 8.71 8.72 8.79 8.80 8.82 8.83 8.84 9.06 9.13 9.49
Result Confidence
OpenBenchmarking.org Milliseconds, Fewer Is Better PyPerformance 1.0.0 Benchmark: python_startup EPYC 7F32 EPYC 7F52 EPYC 7542 EPYC 7502P EPYC 7702 EPYC 7402P EPYC 7532 EPYC 7662 EPYC 7302P EPYC 7552 EPYC 7642 EPYC 7272 EPYC 7282 EPYC 7232P 3 6 9 12 15 Min: 7.47 / Avg: 7.47 / Max: 7.48 Min: 7.54 / Avg: 7.54 / Max: 7.55 Min: 8.57 / Avg: 8.57 / Max: 8.57 Min: 8.61 / Avg: 8.62 / Max: 8.62 Min: 8.71 / Avg: 8.71 / Max: 8.71 Min: 8.72 / Avg: 8.72 / Max: 8.73 Min: 8.78 / Avg: 8.79 / Max: 8.79 Min: 8.8 / Avg: 8.8 / Max: 8.8 Min: 8.81 / Avg: 8.82 / Max: 8.82 Min: 8.81 / Avg: 8.83 / Max: 8.84 Min: 8.83 / Avg: 8.84 / Max: 8.85 Min: 9.05 / Avg: 9.06 / Max: 9.06 Min: 9.12 / Avg: 9.13 / Max: 9.13 Min: 9.49 / Avg: 9.49 / Max: 9.49
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 7F52 EPYC 7F32 EPYC 7542 EPYC 7702 EPYC 7402P EPYC 7502P EPYC 7552 EPYC 7302P EPYC 7532 EPYC 7642 EPYC 7662 EPYC 7272 EPYC 7282 EPYC 7232P 10 20 30 40 50 SE +/- 0.07, N = 3 SE +/- 0.02, N = 3 SE +/- 0.02, N = 3 SE +/- 0.01, N = 3 SE +/- 0.18, N = 3 SE +/- 0.04, N = 3 SE +/- 0.09, N = 3 SE +/- 0.07, N = 3 SE +/- 0.04, N = 3 SE +/- 0.09, N = 3 SE +/- 0.12, N = 3 SE +/- 0.06, N = 3 SE +/- 0.08, N = 3 SE +/- 0.08, N = 3 36.44 36.49 41.66 42.29 42.30 42.31 42.86 42.88 42.90 42.96 43.14 44.27 44.37 46.30 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 7F52 EPYC 7F32 EPYC 7542 EPYC 7702 EPYC 7402P EPYC 7502P EPYC 7552 EPYC 7302P EPYC 7532 EPYC 7642 EPYC 7662 EPYC 7272 EPYC 7282 EPYC 7232P 9 18 27 36 45 Min: 36.33 / Avg: 36.44 / Max: 36.56 Min: 36.45 / Avg: 36.49 / Max: 36.52 Min: 41.62 / Avg: 41.66 / Max: 41.7 Min: 42.26 / Avg: 42.29 / Max: 42.3 Min: 42.03 / Avg: 42.3 / Max: 42.64 Min: 42.23 / Avg: 42.31 / Max: 42.35 Min: 42.71 / Avg: 42.86 / Max: 43.03 Min: 42.75 / Avg: 42.88 / Max: 42.95 Min: 42.83 / Avg: 42.9 / Max: 42.94 Min: 42.78 / Avg: 42.96 / Max: 43.08 Min: 43 / Avg: 43.13 / Max: 43.38 Min: 44.18 / Avg: 44.27 / Max: 44.39 Min: 44.26 / Avg: 44.37 / Max: 44.53 Min: 46.14 / Avg: 46.3 / Max: 46.42 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 7F52 EPYC 7F32 EPYC 7542 EPYC 7502P EPYC 7402P EPYC 7702 EPYC 7662 EPYC 7552 EPYC 7532 EPYC 7302P EPYC 7642 EPYC 7282 EPYC 7272 EPYC 7232P 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 +/- 0.00, 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 2.51 2.38 2.22 2.20 2.19 2.17 2.16 2.16 2.15 2.14 2.12 2.08 2.05 1.98 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 7F32 EPYC 7282 EPYC 7542 EPYC 7502P EPYC 7272 EPYC 7232P EPYC 7302P EPYC 7402P EPYC 7642 EPYC 7532 EPYC 7F52 EPYC 7662 EPYC 7552 EPYC 7702 0.009 0.018 0.027 0.036 0.045 0.04 0.04 0.04 0.04 0.04 0.04 0.04 0.04 0.03 0.03 0.03 0.03 0.03 0.03
Result Confidence
OpenBenchmarking.org Frames Per Second, More Is Better AOM AV1 2.0 Encoder Mode: Speed 4 Two-Pass EPYC 7F52 EPYC 7F32 EPYC 7542 EPYC 7502P EPYC 7402P EPYC 7702 EPYC 7662 EPYC 7552 EPYC 7532 EPYC 7302P EPYC 7642 EPYC 7282 EPYC 7272 EPYC 7232P 2 4 6 8 10 Min: 2.5 / Avg: 2.51 / Max: 2.51 Min: 2.37 / Avg: 2.38 / Max: 2.39 Min: 2.21 / Avg: 2.22 / Max: 2.23 Min: 2.2 / Avg: 2.2 / Max: 2.2 Min: 2.19 / Avg: 2.19 / Max: 2.19 Min: 2.17 / Avg: 2.17 / Max: 2.17 Min: 2.15 / Avg: 2.16 / Max: 2.16 Min: 2.15 / Avg: 2.16 / Max: 2.16 Min: 2.14 / Avg: 2.15 / Max: 2.15 Min: 2.14 / Avg: 2.14 / Max: 2.15 Min: 2.12 / Avg: 2.12 / Max: 2.13 Min: 2.07 / Avg: 2.08 / Max: 2.09 Min: 2.04 / Avg: 2.05 / Max: 2.06 Min: 1.97 / Avg: 1.98 / Max: 1.98 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 7F52 EPYC 7F32 EPYC 7542 EPYC 7502P EPYC 7402P EPYC 7702 EPYC 7532 EPYC 7552 EPYC 7662 EPYC 7302P EPYC 7642 EPYC 7282 EPYC 7272 EPYC 7232P 0.8775 1.755 2.6325 3.51 4.3875 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 +/- 0.00, 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 +/- 0.02, N = 3 SE +/- 0.01, N = 3 SE +/- 0.01, N = 3 3.90 3.73 3.48 3.42 3.42 3.38 3.37 3.37 3.36 3.36 3.33 3.23 3.19 3.08 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 7282 EPYC 7272 EPYC 7232P EPYC 7F32 EPYC 7542 EPYC 7502P EPYC 7302P EPYC 7402P EPYC 7642 EPYC 7532 EPYC 7F52 EPYC 7662 EPYC 7552 EPYC 7702 0.0158 0.0316 0.0474 0.0632 0.079 0.07 0.07 0.07 0.06 0.06 0.06 0.06 0.06 0.05 0.05 0.05 0.05 0.05 0.04
Result Confidence
OpenBenchmarking.org Frames Per Second, More Is Better AOM AV1 2.0 Encoder Mode: Speed 6 Two-Pass EPYC 7F52 EPYC 7F32 EPYC 7542 EPYC 7502P EPYC 7402P EPYC 7702 EPYC 7532 EPYC 7552 EPYC 7662 EPYC 7302P EPYC 7642 EPYC 7282 EPYC 7272 EPYC 7232P 2 4 6 8 10 Min: 3.89 / Avg: 3.9 / Max: 3.91 Min: 3.73 / Avg: 3.73 / Max: 3.74 Min: 3.48 / Avg: 3.48 / Max: 3.48 Min: 3.41 / Avg: 3.42 / Max: 3.43 Min: 3.42 / Avg: 3.42 / Max: 3.43 Min: 3.38 / Avg: 3.38 / Max: 3.39 Min: 3.36 / Avg: 3.37 / Max: 3.37 Min: 3.37 / Avg: 3.37 / Max: 3.38 Min: 3.36 / Avg: 3.36 / Max: 3.36 Min: 3.33 / Avg: 3.36 / Max: 3.37 Min: 3.32 / Avg: 3.33 / Max: 3.35 Min: 3.21 / Avg: 3.23 / Max: 3.27 Min: 3.18 / Avg: 3.19 / Max: 3.21 Min: 3.07 / Avg: 3.08 / Max: 3.1 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 7F52 EPYC 7F32 EPYC 7542 EPYC 7502P EPYC 7402P EPYC 7702 EPYC 7552 EPYC 7662 EPYC 7532 EPYC 7642 EPYC 7302P EPYC 7282 EPYC 7272 EPYC 7232P 5 10 15 20 25 SE +/- 0.02, N = 3 SE +/- 0.03, N = 3 SE +/- 0.02, N = 3 SE +/- 0.04, N = 3 SE +/- 0.07, 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 = 3 SE +/- 0.16, N = 3 SE +/- 0.07, N = 3 SE +/- 0.05, N = 3 SE +/- 0.05, N = 3 21.76 20.22 20.19 19.97 19.88 19.84 19.63 19.59 19.51 19.48 19.11 18.92 17.83 17.30 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 7282 EPYC 7272 EPYC 7232P EPYC 7542 EPYC 7502P EPYC 7302P EPYC 7402P EPYC 7F32 EPYC 7552 EPYC 7642 EPYC 7532 EPYC 7662 EPYC 7702 EPYC 7F52 0.072 0.144 0.216 0.288 0.36 0.32 0.31 0.31 0.30 0.30 0.29 0.29 0.26 0.26 0.23 0.23 0.23 0.22 0.21
Result Confidence
OpenBenchmarking.org Frames Per Second, More Is Better AOM AV1 2.0 Encoder Mode: Speed 6 Realtime EPYC 7F52 EPYC 7F32 EPYC 7542 EPYC 7502P EPYC 7402P EPYC 7702 EPYC 7552 EPYC 7662 EPYC 7532 EPYC 7642 EPYC 7302P EPYC 7282 EPYC 7272 EPYC 7232P 5 10 15 20 25 Min: 21.73 / Avg: 21.76 / Max: 21.79 Min: 20.16 / Avg: 20.22 / Max: 20.28 Min: 20.17 / Avg: 20.19 / Max: 20.22 Min: 19.9 / Avg: 19.97 / Max: 20.03 Min: 19.75 / Avg: 19.88 / Max: 19.97 Min: 19.82 / Avg: 19.84 / Max: 19.86 Min: 19.61 / Avg: 19.63 / Max: 19.66 Min: 19.58 / Avg: 19.59 / Max: 19.6 Min: 19.46 / Avg: 19.51 / Max: 19.57 Min: 19.45 / Avg: 19.48 / Max: 19.52 Min: 18.83 / Avg: 19.11 / Max: 19.38 Min: 18.8 / Avg: 18.92 / Max: 19.03 Min: 17.77 / Avg: 17.83 / Max: 17.92 Min: 17.21 / Avg: 17.3 / Max: 17.37 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 7F52 EPYC 7F32 EPYC 7402P EPYC 7542 EPYC 7502P EPYC 7702 EPYC 7302P EPYC 7552 EPYC 7532 EPYC 7662 EPYC 7642 EPYC 7272 EPYC 7282 EPYC 7232P 20 40 60 80 100 SE +/- 0.02, N = 3 SE +/- 0.02, N = 3 SE +/- 0.05, N = 3 SE +/- 0.03, N = 3 SE +/- 0.01, N = 3 SE +/- 0.05, N = 3 SE +/- 0.03, N = 3 SE +/- 0.01, N = 3 SE +/- 0.00, N = 3 SE +/- 0.02, N = 3 SE +/- 0.03, N = 3 SE +/- 0.04, N = 3 SE +/- 0.02, N = 3 SE +/- 0.03, N = 3 83.02 83.50 94.84 94.97 95.81 96.09 97.20 97.22 97.37 97.55 97.99 99.84 99.92 103.98
Result Confidence
OpenBenchmarking.org Seconds, Fewer Is Better Timed Eigen Compilation 3.3.9 Time To Compile EPYC 7F52 EPYC 7F32 EPYC 7402P EPYC 7542 EPYC 7502P EPYC 7702 EPYC 7302P EPYC 7552 EPYC 7532 EPYC 7662 EPYC 7642 EPYC 7272 EPYC 7282 EPYC 7232P 20 40 60 80 100 Min: 82.99 / Avg: 83.02 / Max: 83.06 Min: 83.48 / Avg: 83.5 / Max: 83.55 Min: 94.73 / Avg: 94.83 / Max: 94.91 Min: 94.92 / Avg: 94.97 / Max: 95.02 Min: 95.78 / Avg: 95.81 / Max: 95.83 Min: 96 / Avg: 96.09 / Max: 96.18 Min: 97.15 / Avg: 97.2 / Max: 97.27 Min: 97.2 / Avg: 97.22 / Max: 97.24 Min: 97.37 / Avg: 97.37 / Max: 97.38 Min: 97.52 / Avg: 97.55 / Max: 97.6 Min: 97.94 / Avg: 97.99 / Max: 98.06 Min: 99.78 / Avg: 99.84 / Max: 99.91 Min: 99.9 / Avg: 99.92 / Max: 99.96 Min: 103.94 / Avg: 103.98 / Max: 104.04
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 7F32 EPYC 7542 EPYC 7642 EPYC 7402P EPYC 7502P EPYC 7302P EPYC 7662 EPYC 7552 EPYC 7532 EPYC 7272 EPYC 7702 EPYC 7232P EPYC 7282 EPYC 7F52 200 400 600 800 1000 SE +/- 2.91, N = 3 SE +/- 3.23, N = 3 SE +/- 1.66, N = 3 SE +/- 2.49, N = 3 SE +/- 3.41, N = 3 SE +/- 1.97, N = 3 SE +/- 7.17, N = 3 SE +/- 3.34, N = 3 SE +/- 1.89, N = 3 SE +/- 3.25, N = 3 SE +/- 3.26, N = 3 SE +/- 1.85, N = 3 SE +/- 3.07, N = 3 SE +/- 5.28, N = 3 967.37 908.46 903.30 899.45 898.84 898.21 897.59 895.52 895.33 864.62 861.35 861.07 858.54 773.86 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 7F32 EPYC 7542 EPYC 7402P EPYC 7502P EPYC 7552 EPYC 7642 EPYC 7532 EPYC 7662 EPYC 7702 EPYC 7F52 5 10 15 20 25 19.69 19.36 18.48 16.79 16.68 16.61 16.53 16.03 13.37 12.13 11.94 11.61 10.75 9.53
Result Confidence
OpenBenchmarking.org Test Cases Per Minute, More Is Better Darmstadt Automotive Parallel Heterogeneous Suite Backend: OpenMP - Kernel: NDT Mapping EPYC 7F32 EPYC 7542 EPYC 7642 EPYC 7402P EPYC 7502P EPYC 7302P EPYC 7662 EPYC 7552 EPYC 7532 EPYC 7272 EPYC 7702 EPYC 7232P EPYC 7282 EPYC 7F52 200 400 600 800 1000 Min: 961.58 / Avg: 967.37 / Max: 970.7 Min: 902.91 / Avg: 908.46 / Max: 914.1 Min: 900.01 / Avg: 903.3 / Max: 905.33 Min: 895.16 / Avg: 899.45 / Max: 903.77 Min: 892.02 / Avg: 898.84 / Max: 902.4 Min: 894.42 / Avg: 898.21 / Max: 901.07 Min: 885.88 / Avg: 897.59 / Max: 910.61 Min: 888.84 / Avg: 895.52 / Max: 899.09 Min: 892.13 / Avg: 895.33 / Max: 898.66 Min: 858.29 / Avg: 864.62 / Max: 869.06 Min: 854.83 / Avg: 861.35 / Max: 864.7 Min: 857.36 / Avg: 861.07 / Max: 863.04 Min: 852.55 / Avg: 858.54 / Max: 862.73 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 7F32 EPYC 7F52 EPYC 7542 EPYC 7502P EPYC 7402P EPYC 7302P EPYC 7272 EPYC 7532 EPYC 7702 EPYC 7282 EPYC 7552 EPYC 7662 EPYC 7232P 6 12 18 24 30 SE +/- 0.04, N = 3 SE +/- 0.05, N = 3 SE +/- 0.07, N = 3 SE +/- 0.06, N = 3 SE +/- 0.09, N = 3 SE +/- 0.07, N = 3 SE +/- 0.09, N = 3 SE +/- 0.06, N = 3 SE +/- 0.03, N = 3 SE +/- 0.04, N = 3 SE +/- 0.05, N = 3 SE +/- 0.06, N = 3 SE +/- 0.04, N = 3 20.03 20.48 23.35 23.65 23.66 23.78 24.09 24.09 24.34 24.46 24.53 24.73 25.02 1. rsvg-convert version 2.48.9
Result Confidence
OpenBenchmarking.org Seconds, Fewer Is Better librsvg Operation: SVG Files To PNG EPYC 7F32 EPYC 7F52 EPYC 7542 EPYC 7502P EPYC 7402P EPYC 7302P EPYC 7272 EPYC 7532 EPYC 7702 EPYC 7282 EPYC 7552 EPYC 7662 EPYC 7232P 6 12 18 24 30 Min: 19.96 / Avg: 20.03 / Max: 20.1 Min: 20.42 / Avg: 20.48 / Max: 20.58 Min: 23.26 / Avg: 23.35 / Max: 23.49 Min: 23.57 / Avg: 23.65 / Max: 23.77 Min: 23.49 / Avg: 23.66 / Max: 23.78 Min: 23.65 / Avg: 23.78 / Max: 23.89 Min: 23.94 / Avg: 24.09 / Max: 24.24 Min: 24 / Avg: 24.09 / Max: 24.2 Min: 24.29 / Avg: 24.34 / Max: 24.4 Min: 24.41 / Avg: 24.46 / Max: 24.53 Min: 24.43 / Avg: 24.53 / Max: 24.6 Min: 24.63 / Avg: 24.73 / Max: 24.84 Min: 24.97 / Avg: 25.02 / Max: 25.1 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 7F32 EPYC 7F52 EPYC 7542 EPYC 7402P EPYC 7642 EPYC 7502P EPYC 7662 EPYC 7552 EPYC 7302P EPYC 7702 EPYC 7532 EPYC 7282 EPYC 7272 EPYC 7232P 0.1395 0.279 0.4185 0.558 0.6975 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 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 0.62 0.61 0.53 0.53 0.52 0.52 0.52 0.52 0.52 0.52 0.51 0.50 0.50 0.50 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 7642 EPYC 7532 EPYC 7F32 EPYC 7282 EPYC 7542 EPYC 7F52 EPYC 7502P EPYC 7662 EPYC 7272 EPYC 7552 EPYC 7232P EPYC 7302P EPYC 7402P EPYC 7702 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 7F32 EPYC 7F52 EPYC 7542 EPYC 7402P EPYC 7642 EPYC 7502P EPYC 7662 EPYC 7552 EPYC 7302P EPYC 7702 EPYC 7532 EPYC 7282 EPYC 7272 EPYC 7232P 2 4 6 8 10 Min: 0.62 / Avg: 0.62 / Max: 0.62 Min: 0.61 / Avg: 0.61 / Max: 0.62 Min: 0.52 / Avg: 0.53 / Max: 0.54 Min: 0.52 / Avg: 0.53 / Max: 0.53 Min: 0.51 / Avg: 0.52 / Max: 0.52 Min: 0.52 / Avg: 0.52 / Max: 0.53 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: 0.52 Min: 0.52 / Avg: 0.52 / Max: 0.53 Min: 0.51 / Avg: 0.51 / Max: 0.52 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 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 7F32 EPYC 7F52 EPYC 7502P EPYC 7542 EPYC 7702 EPYC 7402P EPYC 7302P EPYC 7532 EPYC 7552 EPYC 7662 EPYC 7642 EPYC 7272 EPYC 7232P EPYC 7282 5 10 15 20 25 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 +/- 0.03, N = 3 SE +/- 0.03, N = 3 SE +/- 0.03, N = 3 SE +/- 0.00, N = 3 SE +/- 0.03, N = 3 SE +/- 0.00, N = 3 SE +/- 0.03, N = 3 SE +/- 0.00, N = 3 SE +/- 0.03, N = 3 17.2 17.5 19.9 19.9 20.2 20.2 20.4 20.4 20.5 20.5 20.5 21.0 21.1 21.3
Result Confidence
OpenBenchmarking.org Milliseconds, Fewer Is Better PyPerformance 1.0.0 Benchmark: pathlib EPYC 7F32 EPYC 7F52 EPYC 7502P EPYC 7542 EPYC 7702 EPYC 7402P EPYC 7302P EPYC 7532 EPYC 7552 EPYC 7662 EPYC 7642 EPYC 7272 EPYC 7232P EPYC 7282 5 10 15 20 25 Min: 17.2 / Avg: 17.2 / Max: 17.2 Min: 17.5 / Avg: 17.5 / Max: 17.5 Min: 19.9 / Avg: 19.9 / Max: 19.9 Min: 19.8 / Avg: 19.87 / Max: 19.9 Min: 20.2 / Avg: 20.2 / Max: 20.2 Min: 20.2 / Avg: 20.23 / Max: 20.3 Min: 20.4 / Avg: 20.43 / Max: 20.5 Min: 20.4 / Avg: 20.43 / Max: 20.5 Min: 20.5 / Avg: 20.5 / Max: 20.5 Min: 20.5 / Avg: 20.53 / Max: 20.6 Min: 20.5 / Avg: 20.5 / Max: 20.5 Min: 20.9 / Avg: 20.97 / Max: 21 Min: 21.1 / Avg: 21.1 / Max: 21.1 Min: 21.2 / Avg: 21.27 / Max: 21.3
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 7F52 EPYC 7F32 EPYC 7542 EPYC 7702 EPYC 7402P EPYC 7502P EPYC 7302P EPYC 7662 EPYC 7552 EPYC 7272 EPYC 7282 EPYC 7532 EPYC 7232P 2M 4M 6M 8M 10M SE +/- 3201.01, N = 3 SE +/- 9056.97, N = 3 SE +/- 15198.80, N = 3 SE +/- 4763.31, N = 3 SE +/- 5954.89, N = 3 SE +/- 2921.91, N = 3 SE +/- 16881.14, N = 3 SE +/- 6430.53, N = 3 SE +/- 15133.11, N = 3 SE +/- 4235.69, N = 3 SE +/- 18409.69, N = 3 SE +/- 8887.25, N = 3 SE +/- 8448.82, N = 3 7940047 7939883 6983945 6899948 6880760 6804305 6787692 6753902 6674881 6551351 6547690 6545211 6414609 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 7272 EPYC 7232P EPYC 7282 EPYC 7F32 EPYC 7542 EPYC 7402P EPYC 7502P EPYC 7302P EPYC 7552 EPYC 7F52 EPYC 7662 EPYC 7702 EPYC 7532 30K 60K 90K 120K 150K 159454.66 158031.23 156016.10 150336.84 144587.96 142769.17 139718.79 139072.47 116329.09 114628.80 100655.93 99938.47 97701.58
Result Confidence
OpenBenchmarking.org Nodes Per Second, More Is Better Crafty 25.2 Elapsed Time EPYC 7F52 EPYC 7F32 EPYC 7542 EPYC 7702 EPYC 7402P EPYC 7502P EPYC 7302P EPYC 7662 EPYC 7552 EPYC 7272 EPYC 7282 EPYC 7532 EPYC 7232P 1.4M 2.8M 4.2M 5.6M 7M Min: 7934298 / Avg: 7940047 / Max: 7945361 Min: 7924088 / Avg: 7939883 / Max: 7955460 Min: 6962515 / Avg: 6983944.67 / Max: 7013330 Min: 6892591 / Avg: 6899948 / Max: 6908868 Min: 6872751 / Avg: 6880759.67 / Max: 6892398 Min: 6798906 / Avg: 6804305.33 / Max: 6808941 Min: 6763111 / Avg: 6787691.67 / Max: 6820026 Min: 6743220 / Avg: 6753902.33 / Max: 6765446 Min: 6646698 / Avg: 6674880.67 / Max: 6698529 Min: 6543694 / Avg: 6551351.33 / Max: 6558318 Min: 6524614 / Avg: 6547690 / Max: 6584075 Min: 6532471 / Avg: 6545211 / Max: 6562315 Min: 6399116 / Avg: 6414609 / Max: 6428197 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 7F32 EPYC 7F52 EPYC 7542 EPYC 7702 EPYC 7502P EPYC 7662 EPYC 7302P EPYC 7402P EPYC 7642 EPYC 7532 EPYC 7552 EPYC 7232P EPYC 7282 EPYC 7272 0.1418 0.2836 0.4254 0.5672 0.709 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 SE +/- 0.00, N = 3 SE +/- 0.00, N = 3 SE +/- 0.00, N = 3 0.63 0.62 0.54 0.54 0.53 0.53 0.53 0.53 0.52 0.52 0.52 0.52 0.51 0.51 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 7642 EPYC 7532 EPYC 7F32 EPYC 7282 EPYC 7542 EPYC 7F52 EPYC 7502P EPYC 7662 EPYC 7272 EPYC 7552 EPYC 7232P EPYC 7302P EPYC 7402P EPYC 7702 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 7F32 EPYC 7F52 EPYC 7542 EPYC 7702 EPYC 7502P EPYC 7662 EPYC 7302P EPYC 7402P EPYC 7642 EPYC 7532 EPYC 7552 EPYC 7232P EPYC 7282 EPYC 7272 2 4 6 8 10 Min: 0.62 / Avg: 0.63 / Max: 0.63 Min: 0.61 / Avg: 0.62 / Max: 0.63 Min: 0.54 / Avg: 0.54 / Max: 0.55 Min: 0.53 / Avg: 0.54 / Max: 0.54 Min: 0.53 / Avg: 0.53 / Max: 0.54 Min: 0.52 / Avg: 0.53 / Max: 0.53 Min: 0.53 / Avg: 0.53 / Max: 0.53 Min: 0.53 / Avg: 0.53 / Max: 0.54 Min: 0.52 / Avg: 0.52 / Max: 0.53 Min: 0.52 / Avg: 0.52 / Max: 0.53 Min: 0.52 / Avg: 0.52 / Max: 0.53 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 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 7F52 EPYC 7F32 EPYC 7542 EPYC 7402P EPYC 7662 EPYC 7502P EPYC 7702 EPYC 7552 EPYC 7302P EPYC 7532 EPYC 7232P EPYC 7272 EPYC 7282 12 24 36 48 60 SE +/- 0.42, N = 3 SE +/- 0.36, N = 15 SE +/- 0.28, N = 3 SE +/- 0.34, N = 3 SE +/- 0.42, N = 3 SE +/- 0.39, N = 3 SE +/- 0.30, N = 14 SE +/- 0.48, N = 5 SE +/- 0.42, N = 3 SE +/- 0.02, N = 3 SE +/- 0.44, N = 5 SE +/- 0.61, N = 3 SE +/- 0.13, N = 3 52.02 51.95 45.13 45.09 44.80 44.68 44.54 44.49 43.98 43.69 43.17 42.94 42.25 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 7F52 EPYC 7F32 EPYC 7542 EPYC 7402P EPYC 7662 EPYC 7502P EPYC 7702 EPYC 7552 EPYC 7302P EPYC 7532 EPYC 7232P EPYC 7272 EPYC 7282 10 20 30 40 50 Min: 51.53 / Avg: 52.02 / Max: 52.86 Min: 49.68 / Avg: 51.95 / Max: 54.03 Min: 44.77 / Avg: 45.13 / Max: 45.69 Min: 44.42 / Avg: 45.09 / Max: 45.46 Min: 44.34 / Avg: 44.8 / Max: 45.63 Min: 44.24 / Avg: 44.68 / Max: 45.45 Min: 42.74 / Avg: 44.54 / Max: 46.27 Min: 43.45 / Avg: 44.49 / Max: 45.67 Min: 43.51 / Avg: 43.98 / Max: 44.82 Min: 43.65 / Avg: 43.69 / Max: 43.71 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 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 7F52 EPYC 7F32 EPYC 7542 EPYC 7702 EPYC 7502P EPYC 7532 EPYC 7402P EPYC 7552 EPYC 7302P EPYC 7642 EPYC 7662 EPYC 7272 EPYC 7282 EPYC 7232P 50 100 150 200 250 184.49 184.74 214.26 214.77 215.16 217.33 217.55 217.90 218.14 218.42 219.26 223.38 224.52 226.64
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 7F52 EPYC 7F32 EPYC 7542 EPYC 7402P EPYC 7502P EPYC 7702 EPYC 7302P EPYC 7662 EPYC 7532 EPYC 7642 EPYC 7552 EPYC 7272 EPYC 7282 EPYC 7232P 12 24 36 48 60 SE +/- 0.06, N = 3 SE +/- 0.07, N = 3 SE +/- 0.06, N = 3 SE +/- 0.00, N = 3 SE +/- 0.12, N = 3 SE +/- 0.04, N = 3 SE +/- 0.02, N = 3 SE +/- 0.07, N = 3 SE +/- 0.06, N = 3 SE +/- 0.06, N = 3 SE +/- 0.11, N = 3 SE +/- 0.12, N = 3 SE +/- 0.08, N = 3 SE +/- 0.06, N = 3 44.84 44.92 51.62 52.30 52.34 52.35 52.93 53.07 53.18 53.20 53.29 54.63 54.76 55.08 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 7F52 EPYC 7F32 EPYC 7542 EPYC 7402P EPYC 7502P EPYC 7702 EPYC 7302P EPYC 7662 EPYC 7532 EPYC 7642 EPYC 7552 EPYC 7272 EPYC 7282 EPYC 7232P 11 22 33 44 55 Min: 44.76 / Avg: 44.84 / Max: 44.96 Min: 44.81 / Avg: 44.92 / Max: 45.04 Min: 51.51 / Avg: 51.62 / Max: 51.69 Min: 52.29 / Avg: 52.3 / Max: 52.3 Min: 52.19 / Avg: 52.34 / Max: 52.57 Min: 52.3 / Avg: 52.35 / Max: 52.43 Min: 52.9 / Avg: 52.93 / Max: 52.97 Min: 52.97 / Avg: 53.07 / Max: 53.19 Min: 53.07 / Avg: 53.18 / Max: 53.26 Min: 53.13 / Avg: 53.2 / Max: 53.31 Min: 53.08 / Avg: 53.29 / Max: 53.44 Min: 54.4 / Avg: 54.63 / Max: 54.76 Min: 54.61 / Avg: 54.76 / Max: 54.89 Min: 54.97 / Avg: 55.08 / Max: 55.19 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 7F32 EPYC 7F52 EPYC 7542 EPYC 7402P EPYC 7702 EPYC 7502P EPYC 7642 EPYC 7662 EPYC 7532 EPYC 7302P EPYC 7552 EPYC 7272 EPYC 7282 EPYC 7232P 5 10 15 20 25 SE +/- 0.02, N = 3 SE +/- 0.04, N = 3 SE +/- 0.02, N = 3 SE +/- 0.01, N = 3 SE +/- 0.02, N = 3 SE +/- 0.00, N = 3 SE +/- 0.01, N = 3 SE +/- 0.01, N = 3 SE +/- 0.04, N = 3 SE +/- 0.07, N = 3 SE +/- 0.01, N = 3 SE +/- 0.01, N = 3 SE +/- 0.05, N = 3 SE +/- 0.03, N = 3 17.56 17.60 20.11 20.48 20.56 20.69 20.74 20.78 20.79 20.79 20.81 21.39 21.42 21.55
Result Confidence
OpenBenchmarking.org Seconds, Fewer Is Better Dolfyn 0.527 Computational Fluid Dynamics EPYC 7F32 EPYC 7F52 EPYC 7542 EPYC 7402P EPYC 7702 EPYC 7502P EPYC 7642 EPYC 7662 EPYC 7532 EPYC 7302P EPYC 7552 EPYC 7272 EPYC 7282 EPYC 7232P 5 10 15 20 25 Min: 17.53 / Avg: 17.56 / Max: 17.6 Min: 17.53 / Avg: 17.6 / Max: 17.67 Min: 20.1 / Avg: 20.11 / Max: 20.15 Min: 20.46 / Avg: 20.48 / Max: 20.5 Min: 20.54 / Avg: 20.56 / Max: 20.59 Min: 20.68 / Avg: 20.69 / Max: 20.7 Min: 20.73 / Avg: 20.74 / Max: 20.77 Min: 20.77 / Avg: 20.78 / Max: 20.8 Min: 20.71 / Avg: 20.79 / Max: 20.84 Min: 20.67 / Avg: 20.79 / Max: 20.9 Min: 20.79 / Avg: 20.81 / Max: 20.83 Min: 21.37 / Avg: 21.39 / Max: 21.42 Min: 21.35 / Avg: 21.42 / Max: 21.51 Min: 21.5 / Avg: 21.55 / Max: 21.61
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 7F32 EPYC 7F52 EPYC 7542 EPYC 7702 EPYC 7502P EPYC 7402P EPYC 7532 EPYC 7552 EPYC 7662 EPYC 7642 EPYC 7302P EPYC 7232P EPYC 7272 EPYC 7282 60 120 180 240 300 SE +/- 0.09, N = 3 SE +/- 0.11, N = 3 SE +/- 0.52, N = 3 SE +/- 0.70, N = 3 SE +/- 1.03, N = 3 SE +/- 1.43, N = 3 SE +/- 0.48, N = 3 SE +/- 0.57, N = 3 SE +/- 0.81, N = 3 SE +/- 1.00, N = 3 SE +/- 0.38, N = 3 SE +/- 0.64, N = 3 SE +/- 0.37, N = 3 SE +/- 0.34, N = 3 223.71 223.75 257.57 261.45 262.12 262.91 264.68 264.99 265.19 265.92 268.68 273.02 273.20 274.30 1. (CC) gcc options: -O2 -fvisibility=hidden
Result Confidence
OpenBenchmarking.org Seconds, Fewer Is Better Gcrypt Library 1.9 EPYC 7F32 EPYC 7F52 EPYC 7542 EPYC 7702 EPYC 7502P EPYC 7402P EPYC 7532 EPYC 7552 EPYC 7662 EPYC 7642 EPYC 7302P EPYC 7232P EPYC 7272 EPYC 7282 50 100 150 200 250 Min: 223.61 / Avg: 223.71 / Max: 223.89 Min: 223.6 / Avg: 223.75 / Max: 223.97 Min: 256.94 / Avg: 257.57 / Max: 258.61 Min: 260.68 / Avg: 261.45 / Max: 262.85 Min: 260.44 / Avg: 262.12 / Max: 264 Min: 261.48 / Avg: 262.91 / Max: 265.77 Min: 263.89 / Avg: 264.68 / Max: 265.54 Min: 264.26 / Avg: 264.98 / Max: 266.12 Min: 263.73 / Avg: 265.19 / Max: 266.52 Min: 264.29 / Avg: 265.92 / Max: 267.74 Min: 267.92 / Avg: 268.68 / Max: 269.11 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 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 7F52 EPYC 7F32 EPYC 7542 EPYC 7502P EPYC 7662 EPYC 7702 EPYC 7402P EPYC 7302P EPYC 7532 EPYC 7642 EPYC 7552 EPYC 7282 EPYC 7272 EPYC 7232P 3 6 9 12 15 SE +/- 0.031, N = 5 SE +/- 0.004, N = 5 SE +/- 0.158, N = 15 SE +/- 0.003, N = 5 SE +/- 0.006, N = 5 SE +/- 0.051, N = 5 SE +/- 0.006, N = 5 SE +/- 0.012, N = 5 SE +/- 0.004, N = 5 SE +/- 0.016, N = 5 SE +/- 0.009, N = 5 SE +/- 0.010, N = 5 SE +/- 0.007, N = 5 SE +/- 0.168, N = 15 9.240 9.293 10.074 10.083 10.130 10.131 10.154 10.281 10.325 10.337 10.358 10.539 10.746 11.327
Result Confidence
OpenBenchmarking.org Seconds, Fewer Is Better Scikit-Learn 0.22.1 EPYC 7F52 EPYC 7F32 EPYC 7542 EPYC 7502P EPYC 7662 EPYC 7702 EPYC 7402P EPYC 7302P EPYC 7532 EPYC 7642 EPYC 7552 EPYC 7282 EPYC 7272 EPYC 7232P 3 6 9 12 15 Min: 9.14 / Avg: 9.24 / Max: 9.33 Min: 9.28 / Avg: 9.29 / Max: 9.3 Min: 9.88 / Avg: 10.07 / Max: 12.28 Min: 10.08 / Avg: 10.08 / Max: 10.09 Min: 10.11 / Avg: 10.13 / Max: 10.14 Min: 10.04 / Avg: 10.13 / Max: 10.33 Min: 10.13 / Avg: 10.15 / Max: 10.17 Min: 10.25 / Avg: 10.28 / Max: 10.32 Min: 10.32 / Avg: 10.33 / Max: 10.34 Min: 10.28 / Avg: 10.34 / Max: 10.37 Min: 10.34 / Avg: 10.36 / Max: 10.39 Min: 10.52 / Avg: 10.54 / Max: 10.57 Min: 10.72 / Avg: 10.75 / Max: 10.76 Min: 11.13 / Avg: 11.33 / Max: 13.67
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 7F32 EPYC 7F52 EPYC 7542 EPYC 7502P EPYC 7302P EPYC 7402P EPYC 7702 EPYC 7642 EPYC 7532 EPYC 7282 EPYC 7662 EPYC 7272 EPYC 7552 EPYC 7232P 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 0.38 0.38 0.33 0.33 0.33 0.33 0.33 0.32 0.32 0.32 0.32 0.32 0.32 0.31 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 7F32 EPYC 7282 EPYC 7542 EPYC 7F52 EPYC 7502P EPYC 7272 EPYC 7552 EPYC 7232P EPYC 7302P EPYC 7402P EPYC 7642 EPYC 7532 EPYC 7662 EPYC 7702 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 7F32 EPYC 7F52 EPYC 7542 EPYC 7502P EPYC 7302P EPYC 7402P EPYC 7702 EPYC 7642 EPYC 7532 EPYC 7282 EPYC 7662 EPYC 7272 EPYC 7552 EPYC 7232P 1 2 3 4 5 Min: 0.38 / Avg: 0.38 / Max: 0.39 Min: 0.38 / Avg: 0.38 / Max: 0.38 Min: 0.33 / Avg: 0.33 / Max: 0.34 Min: 0.33 / Avg: 0.33 / Max: 0.33 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: 0.33 Min: 0.32 / Avg: 0.32 / Max: 0.32 Min: 0.31 / Avg: 0.32 / Max: 0.32 Min: 0.32 / Avg: 0.32 / Max: 0.33 Min: 0.31 / Avg: 0.32 / Max: 0.32 Min: 0.32 / Avg: 0.32 / Max: 0.33 Min: 0.31 / Avg: 0.31 / Max: 0.31 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 7F52 EPYC 7F32 EPYC 7402P EPYC 7542 EPYC 7502P EPYC 7702 EPYC 7302P EPYC 7662 EPYC 7532 EPYC 7642 EPYC 7552 EPYC 7282 EPYC 7272 EPYC 7232P 20 40 60 80 100 SE +/- 0.10, N = 3 SE +/- 0.06, N = 3 SE +/- 0.54, N = 3 SE +/- 0.19, N = 3 SE +/- 0.36, N = 3 SE +/- 0.04, N = 3 SE +/- 0.05, N = 3 SE +/- 0.11, N = 3 SE +/- 0.27, N = 3 SE +/- 0.11, N = 3 SE +/- 0.06, N = 3 SE +/- 0.18, N = 3 SE +/- 0.06, N = 3 SE +/- 0.25, N = 3 66.52 67.30 75.91 76.16 77.19 77.61 77.74 77.94 78.07 78.23 78.26 80.05 80.19 81.51 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 7F52 EPYC 7F32 EPYC 7402P EPYC 7542 EPYC 7502P EPYC 7702 EPYC 7302P EPYC 7662 EPYC 7532 EPYC 7642 EPYC 7552 EPYC 7282 EPYC 7272 EPYC 7232P 16 32 48 64 80 Min: 66.35 / Avg: 66.52 / Max: 66.7 Min: 67.2 / Avg: 67.3 / Max: 67.4 Min: 74.83 / Avg: 75.9 / Max: 76.53 Min: 75.89 / Avg: 76.16 / Max: 76.52 Min: 76.8 / Avg: 77.18 / Max: 77.9 Min: 77.55 / Avg: 77.61 / Max: 77.67 Min: 77.69 / Avg: 77.74 / Max: 77.85 Min: 77.74 / Avg: 77.94 / Max: 78.1 Min: 77.69 / Avg: 78.06 / Max: 78.59 Min: 78.09 / Avg: 78.23 / Max: 78.45 Min: 78.14 / Avg: 78.26 / Max: 78.37 Min: 79.76 / Avg: 80.05 / Max: 80.38 Min: 80.11 / Avg: 80.19 / Max: 80.3 Min: 81.25 / Avg: 81.51 / Max: 82.01 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 7F52 EPYC 7F32 EPYC 7542 EPYC 7702 EPYC 7402P EPYC 7502P EPYC 7552 EPYC 7532 EPYC 7642 EPYC 7302P EPYC 7662 EPYC 7232P EPYC 7272 EPYC 7282 3 6 9 12 15 SE +/- 0.003, N = 6 SE +/- 0.010, N = 6 SE +/- 0.004, N = 5 SE +/- 0.005, N = 5 SE +/- 0.014, N = 5 SE +/- 0.025, N = 5 SE +/- 0.001, N = 5 SE +/- 0.005, N = 5 SE +/- 0.009, N = 5 SE +/- 0.009, N = 5 SE +/- 0.025, N = 5 SE +/- 0.004, N = 5 SE +/- 0.009, N = 5 SE +/- 0.025, N = 5 7.739 7.745 8.861 9.003 9.014 9.014 9.126 9.140 9.145 9.151 9.154 9.414 9.419 9.481 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 7F52 EPYC 7F32 EPYC 7542 EPYC 7702 EPYC 7402P EPYC 7502P EPYC 7552 EPYC 7532 EPYC 7642 EPYC 7302P EPYC 7662 EPYC 7232P EPYC 7272 EPYC 7282 3 6 9 12 15 Min: 7.73 / Avg: 7.74 / Max: 7.75 Min: 7.72 / Avg: 7.74 / Max: 7.79 Min: 8.85 / Avg: 8.86 / Max: 8.87 Min: 8.99 / Avg: 9 / Max: 9.02 Min: 8.99 / Avg: 9.01 / Max: 9.06 Min: 8.98 / Avg: 9.01 / Max: 9.12 Min: 9.12 / Avg: 9.13 / Max: 9.13 Min: 9.13 / Avg: 9.14 / Max: 9.15 Min: 9.13 / Avg: 9.14 / Max: 9.17 Min: 9.12 / Avg: 9.15 / Max: 9.17 Min: 9.12 / Avg: 9.15 / Max: 9.25 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 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 7F32 EPYC 7F52 EPYC 7542 EPYC 7702 EPYC 7402P EPYC 7502P EPYC 7302P EPYC 7642 EPYC 7662 EPYC 7532 EPYC 7552 EPYC 7232P EPYC 7272 EPYC 7282 80 160 240 320 400 SE +/- 0.35, N = 3 SE +/- 0.41, N = 3 SE +/- 0.10, N = 3 SE +/- 0.62, N = 3 SE +/- 0.03, N = 3 SE +/- 0.72, N = 3 SE +/- 0.94, N = 3 SE +/- 0.40, N = 3 SE +/- 0.29, N = 3 SE +/- 0.88, N = 3 SE +/- 0.46, N = 3 SE +/- 0.14, N = 3 SE +/- 0.22, N = 3 SE +/- 0.21, N = 3 286.43 288.47 333.28 333.30 336.66 336.89 339.05 341.93 342.47 344.25 344.33 347.18 347.77 350.76 MIN: 283.81 / MAX: 294.29 MIN: 285.34 / MAX: 304.15 MIN: 329.87 / MAX: 349.8 MIN: 330.49 / MAX: 343.73 MIN: 333.97 / MAX: 348.51 MIN: 332.6 / MAX: 347.08 MIN: 335.68 / MAX: 355.89 MIN: 337.09 / MAX: 359.76 MIN: 338.7 / MAX: 360.58 MIN: 339.59 / MAX: 367.05 MIN: 340.96 / MAX: 358.42 MIN: 343.85 / MAX: 356.42 MIN: 345.44 / MAX: 366.04 MIN: 346.27 / MAX: 363.67 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 7F32 EPYC 7F52 EPYC 7542 EPYC 7702 EPYC 7402P EPYC 7502P EPYC 7302P EPYC 7642 EPYC 7662 EPYC 7532 EPYC 7552 EPYC 7232P EPYC 7272 EPYC 7282 60 120 180 240 300 Min: 285.73 / Avg: 286.43 / Max: 286.81 Min: 287.8 / Avg: 288.47 / Max: 289.23 Min: 333.14 / Avg: 333.28 / Max: 333.46 Min: 332.62 / Avg: 333.3 / Max: 334.54 Min: 336.61 / Avg: 336.66 / Max: 336.68 Min: 335.5 / Avg: 336.89 / Max: 337.88 Min: 337.77 / Avg: 339.05 / Max: 340.89 Min: 341.17 / Avg: 341.93 / Max: 342.54 Min: 342 / Avg: 342.47 / Max: 343.01 Min: 342.92 / Avg: 344.25 / Max: 345.93 Min: 343.4 / Avg: 344.33 / Max: 344.79 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 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 7F32 EPYC 7F52 EPYC 7542 EPYC 7702 EPYC 7402P EPYC 7502P EPYC 7662 EPYC 7532 EPYC 7302P EPYC 7552 EPYC 7642 EPYC 7272 EPYC 7232P EPYC 7282 1000 2000 3000 4000 5000 SE +/- 2.49, N = 3 SE +/- 3.14, N = 3 SE +/- 5.67, N = 3 SE +/- 5.35, N = 3 SE +/- 2.96, N = 3 SE +/- 4.11, N = 3 SE +/- 2.07, N = 3 SE +/- 3.97, N = 3 SE +/- 1.09, N = 3 SE +/- 2.54, N = 3 SE +/- 3.12, N = 3 SE +/- 1.24, N = 3 SE +/- 5.48, N = 3 SE +/- 2.72, N = 3 4835.02 4834.05 4207.91 4152.60 4151.29 4139.98 4091.78 4089.12 4086.08 4085.53 4072.76 3965.03 3949.44 3949.00 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 7F32 EPYC 7542 EPYC 7402P EPYC 7502P EPYC 7302P EPYC 7552 EPYC 7F52 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7532 20 40 60 80 100 94.07 93.36 91.59 87.24 83.94 82.69 81.90 81.20 68.50 64.14 61.08 58.12 57.63 57.18
Result Confidence
OpenBenchmarking.org MiB/second, More Is Better Crypto++ 8.2 Test: Integer + Elliptic Curve Public Key Algorithms EPYC 7F32 EPYC 7F52 EPYC 7542 EPYC 7702 EPYC 7402P EPYC 7502P EPYC 7662 EPYC 7532 EPYC 7302P EPYC 7552 EPYC 7642 EPYC 7272 EPYC 7232P EPYC 7282 800 1600 2400 3200 4000 Min: 4830.71 / Avg: 4835.02 / Max: 4839.34 Min: 4828.11 / Avg: 4834.05 / Max: 4838.82 Min: 4199.27 / Avg: 4207.91 / Max: 4218.6 Min: 4142.26 / Avg: 4152.6 / Max: 4160.14 Min: 4145.43 / Avg: 4151.29 / Max: 4154.96 Min: 4132.23 / Avg: 4139.98 / Max: 4146.24 Min: 4087.91 / Avg: 4091.78 / Max: 4095.01 Min: 4081.58 / Avg: 4089.12 / Max: 4095.03 Min: 4084.12 / Avg: 4086.08 / Max: 4087.91 Min: 4080.99 / Avg: 4085.53 / Max: 4089.76 Min: 4068.43 / Avg: 4072.76 / Max: 4078.81 Min: 3963.31 / Avg: 3965.03 / Max: 3967.43 Min: 3939.83 / Avg: 3949.44 / Max: 3958.81 Min: 3943.6 / Avg: 3949 / Max: 3952.3 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 7F32 EPYC 7F52 EPYC 7542 EPYC 7402P EPYC 7702 EPYC 7302P EPYC 7502P EPYC 7552 EPYC 7532 EPYC 7662 EPYC 7642 EPYC 7272 EPYC 7232P EPYC 7282 300 600 900 1200 1500 SE +/- 8.33, N = 3 SE +/- 5.46, N = 3 SE +/- 1.20, N = 3 SE +/- 1.20, N = 3 SE +/- 6.84, N = 3 SE +/- 1.86, N = 3 SE +/- 10.82, N = 3 SE +/- 9.35, N = 3 SE +/- 7.33, N = 3 SE +/- 9.54, N = 3 SE +/- 7.55, N = 3 SE +/- 9.68, N = 3 SE +/- 8.01, N = 3 998 999 1137 1159 1166 1172 1173 1178 1180 1184 1184 1208 1213 1221
Result Confidence
OpenBenchmarking.org Milliseconds, Fewer Is Better PyBench 2018-02-16 Total For Average Test Times EPYC 7F32 EPYC 7F52 EPYC 7542 EPYC 7402P EPYC 7702 EPYC 7302P EPYC 7502P EPYC 7552 EPYC 7532 EPYC 7662 EPYC 7642 EPYC 7272 EPYC 7232P EPYC 7282 200 400 600 800 1000 Min: 990 / Avg: 998.33 / Max: 1015 Min: 992 / Avg: 999.33 / Max: 1010 Min: 1135 / Avg: 1137.33 / Max: 1139 Min: 1157 / Avg: 1159.33 / Max: 1161 Min: 1159 / Avg: 1166.33 / Max: 1180 Min: 1168 / Avg: 1171.67 / Max: 1174 Min: 1152 / Avg: 1173 / Max: 1188 Min: 1168 / Avg: 1178.33 / Max: 1197 Min: 1173 / Avg: 1180.33 / Max: 1195 Min: 1165 / Avg: 1184 / Max: 1195 Min: 1175 / Avg: 1184 / Max: 1199 Min: 1202 / Avg: 1212.67 / Max: 1232 Min: 1209 / Avg: 1220.67 / Max: 1236
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 7F52 EPYC 7F32 EPYC 7542 EPYC 7702 EPYC 7502P EPYC 7402P EPYC 7532 EPYC 7552 EPYC 7302P EPYC 7662 EPYC 7642 EPYC 7272 EPYC 7232P EPYC 7282 140 280 420 560 700 SE +/- 0.14, N = 3 SE +/- 0.29, N = 3 SE +/- 0.77, N = 3 SE +/- 0.06, N = 3 SE +/- 0.31, N = 3 SE +/- 0.56, N = 3 SE +/- 0.27, N = 3 SE +/- 0.13, N = 3 SE +/- 0.13, N = 3 SE +/- 0.63, N = 3 SE +/- 0.31, N = 3 SE +/- 0.07, N = 3 SE +/- 0.59, N = 3 SE +/- 0.21, N = 3 628.21 627.44 546.72 539.45 539.17 538.09 531.14 530.80 530.36 529.62 529.60 514.85 513.65 513.60 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 7F32 EPYC 7542 EPYC 7402P EPYC 7502P EPYC 7302P EPYC 7552 EPYC 7F52 EPYC 7642 EPYC 7662 EPYC 7532 EPYC 7702 3 6 9 12 15 12.39 12.28 12.03 11.44 11.01 10.84 10.78 10.63 9.00 8.43 7.98 7.58 7.57 7.54
Result Confidence
OpenBenchmarking.org MiB/second, More Is Better Crypto++ 8.2 Test: Keyed Algorithms EPYC 7F52 EPYC 7F32 EPYC 7542 EPYC 7702 EPYC 7502P EPYC 7402P EPYC 7532 EPYC 7552 EPYC 7302P EPYC 7662 EPYC 7642 EPYC 7272 EPYC 7232P EPYC 7282 110 220 330 440 550 Min: 628.01 / Avg: 628.21 / Max: 628.49 Min: 627.02 / Avg: 627.44 / Max: 627.99 Min: 545.3 / Avg: 546.72 / Max: 547.95 Min: 539.37 / Avg: 539.45 / Max: 539.56 Min: 538.79 / Avg: 539.17 / Max: 539.79 Min: 537.38 / Avg: 538.09 / Max: 539.19 Min: 530.69 / Avg: 531.14 / Max: 531.61 Min: 530.54 / Avg: 530.8 / Max: 530.93 Min: 530.22 / Avg: 530.36 / Max: 530.61 Min: 528.75 / Avg: 529.62 / Max: 530.84 Min: 528.99 / Avg: 529.6 / Max: 530.03 Min: 514.7 / Avg: 514.85 / Max: 514.94 Min: 512.6 / Avg: 513.65 / Max: 514.65 Min: 513.18 / Avg: 513.6 / Max: 513.82 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 7F52 EPYC 7F32 EPYC 7542 EPYC 7402P EPYC 7502P EPYC 7702 EPYC 7532 EPYC 7662 EPYC 7302P EPYC 7552 EPYC 7272 EPYC 7282 EPYC 7232P 11K 22K 33K 44K 55K SE +/- 174.69, N = 3 SE +/- 107.65, N = 3 SE +/- 84.26, N = 3 SE +/- 17.38, N = 3 SE +/- 71.59, N = 3 SE +/- 45.54, N = 3 SE +/- 133.22, N = 3 SE +/- 71.36, N = 3 SE +/- 383.79, N = 3 SE +/- 241.95, N = 3 SE +/- 108.67, N = 3 SE +/- 109.50, N = 3 SE +/- 275.73, N = 3 43527.28 43548.63 50076.27 50474.70 50609.04 51015.87 51428.89 51437.79 51629.10 51630.50 52936.98 52977.60 53237.68 1. (CXX) g++ options: -O3 -march=native -fopenmp
Result Confidence
OpenBenchmarking.org ms, Fewer Is Better FinanceBench 2016-07-25 Benchmark: Repo OpenMP EPYC 7F52 EPYC 7F32 EPYC 7542 EPYC 7402P EPYC 7502P EPYC 7702 EPYC 7532 EPYC 7662 EPYC 7302P EPYC 7552 EPYC 7272 EPYC 7282 EPYC 7232P 9K 18K 27K 36K 45K Min: 43324.05 / Avg: 43527.28 / Max: 43875.02 Min: 43343.38 / Avg: 43548.63 / Max: 43707.56 Min: 49985.34 / Avg: 50076.27 / Max: 50244.61 Min: 50450.23 / Avg: 50474.7 / Max: 50508.32 Min: 50528.84 / Avg: 50609.04 / Max: 50751.85 Min: 50939.99 / Avg: 51015.87 / Max: 51097.43 Min: 51271.63 / Avg: 51428.89 / Max: 51693.79 Min: 51363.7 / Avg: 51437.79 / Max: 51580.48 Min: 51241.3 / Avg: 51629.1 / Max: 52396.66 Min: 51347.45 / Avg: 51630.5 / Max: 52111.92 Min: 52784.59 / Avg: 52936.98 / Max: 53147.39 Min: 52852.14 / Avg: 52977.6 / Max: 53195.79 Min: 52860.58 / Avg: 53237.68 / Max: 53774.7 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 7F52 EPYC 7F32 EPYC 7542 EPYC 7502P EPYC 7402P EPYC 7702 EPYC 7642 EPYC 7532 EPYC 7662 EPYC 7552 EPYC 7302P EPYC 7282 EPYC 7272 EPYC 7232P 30 60 90 120 150 SE +/- 0.12, N = 3 SE +/- 0.39, N = 3 SE +/- 0.55, N = 3 SE +/- 0.46, N = 3 SE +/- 0.44, N = 3 SE +/- 0.49, N = 3 SE +/- 0.18, N = 3 SE +/- 0.37, N = 3 SE +/- 0.28, N = 3 SE +/- 0.31, N = 3 SE +/- 0.37, N = 3 SE +/- 0.80, N = 3 SE +/- 0.38, N = 3 SE +/- 0.50, N = 3 114.91 114.95 132.23 133.23 133.73 134.93 135.09 135.33 135.90 136.07 136.52 140.13 140.43 140.53 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 7F52 EPYC 7F32 EPYC 7542 EPYC 7502P EPYC 7402P EPYC 7702 EPYC 7642 EPYC 7532 EPYC 7662 EPYC 7552 EPYC 7302P EPYC 7282 EPYC 7272 EPYC 7232P 30 60 90 120 150 Min: 114.67 / Avg: 114.91 / Max: 115.06 Min: 114.45 / Avg: 114.95 / Max: 115.72 Min: 131.17 / Avg: 132.23 / Max: 133 Min: 132.34 / Avg: 133.23 / Max: 133.85 Min: 133.03 / Avg: 133.73 / Max: 134.55 Min: 133.97 / Avg: 134.93 / Max: 135.63 Min: 134.86 / Avg: 135.09 / Max: 135.44 Min: 134.6 / Avg: 135.33 / Max: 135.75 Min: 135.39 / Avg: 135.9 / Max: 136.37 Min: 135.55 / Avg: 136.07 / Max: 136.63 Min: 135.79 / Avg: 136.52 / Max: 136.95 Min: 138.59 / Avg: 140.13 / Max: 141.26 Min: 139.94 / Avg: 140.43 / Max: 141.19 Min: 139.78 / Avg: 140.53 / Max: 141.47 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 7F32 EPYC 7F52 EPYC 7542 EPYC 7702 EPYC 7502P EPYC 7402P EPYC 7552 EPYC 7532 EPYC 7662 EPYC 7302P EPYC 7642 EPYC 7232P EPYC 7272 EPYC 7282 90 180 270 360 450 SE +/- 0.15, N = 3 SE +/- 0.07, N = 3 SE +/- 0.10, N = 3 SE +/- 0.16, N = 3 SE +/- 0.14, N = 3 SE +/- 0.40, N = 3 SE +/- 0.10, N = 3 SE +/- 0.13, N = 3 SE +/- 0.16, N = 3 SE +/- 0.15, N = 3 SE +/- 0.20, N = 3 SE +/- 0.13, N = 3 SE +/- 0.16, N = 3 SE +/- 0.25, N = 3 429.41 429.14 374.52 368.93 368.69 368.38 363.50 363.10 362.99 362.20 361.80 352.29 352.07 351.14 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 7F32 EPYC 7542 EPYC 7402P EPYC 7502P EPYC 7302P EPYC 7552 EPYC 7F52 EPYC 7642 EPYC 7532 EPYC 7662 EPYC 7702 3 6 9 12 15 8.96 8.88 8.62 8.25 8.01 7.92 7.85 7.70 6.50 6.21 5.83 5.52 5.51 5.49
Result Confidence
OpenBenchmarking.org MiB/s, More Is Better Botan 2.13.0 Test: Blowfish EPYC 7F32 EPYC 7F52 EPYC 7542 EPYC 7702 EPYC 7502P EPYC 7402P EPYC 7552 EPYC 7532 EPYC 7662 EPYC 7302P EPYC 7642 EPYC 7232P EPYC 7272 EPYC 7282 80 160 240 320 400 Min: 429.18 / Avg: 429.41 / Max: 429.7 Min: 429.06 / Avg: 429.14 / Max: 429.27 Min: 374.32 / Avg: 374.52 / Max: 374.67 Min: 368.71 / Avg: 368.93 / Max: 369.25 Min: 368.54 / Avg: 368.69 / Max: 368.97 Min: 367.96 / Avg: 368.38 / Max: 369.17 Min: 363.36 / Avg: 363.5 / Max: 363.69 Min: 362.85 / Avg: 363.1 / Max: 363.25 Min: 362.68 / Avg: 362.99 / Max: 363.15 Min: 362.03 / Avg: 362.2 / Max: 362.49 Min: 361.43 / Avg: 361.8 / Max: 362.1 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 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 7F52 EPYC 7F32 EPYC 7542 EPYC 7502P EPYC 7402P EPYC 7702 EPYC 7642 EPYC 7532 EPYC 7662 EPYC 7552 EPYC 7302P EPYC 7272 EPYC 7282 EPYC 7232P 20 40 60 80 100 SE +/- 0.11, N = 3 SE +/- 0.23, N = 3 SE +/- 0.07, N = 3 SE +/- 0.02, N = 3 SE +/- 0.10, N = 3 SE +/- 0.14, N = 3 SE +/- 0.32, N = 3 SE +/- 0.17, N = 3 SE +/- 0.07, N = 3 SE +/- 0.09, N = 3 SE +/- 0.11, N = 3 SE +/- 0.19, N = 3 SE +/- 0.33, N = 3 SE +/- 0.13, N = 3 67.74 67.80 77.80 79.00 79.03 79.39 79.72 79.85 80.12 80.15 80.33 81.97 82.15 82.84 1. (CXX) g++ options: -std=gnu++11 -O3 -fomit-frame-pointer -rdynamic
Result Confidence
OpenBenchmarking.org Seconds, Fewer Is Better Minion 1.8 Benchmark: Solitaire EPYC 7F52 EPYC 7F32 EPYC 7542 EPYC 7502P EPYC 7402P EPYC 7702 EPYC 7642 EPYC 7532 EPYC 7662 EPYC 7552 EPYC 7302P EPYC 7272 EPYC 7282 EPYC 7232P 16 32 48 64 80 Min: 67.63 / Avg: 67.74 / Max: 67.95 Min: 67.36 / Avg: 67.8 / Max: 68.07 Min: 77.68 / Avg: 77.8 / Max: 77.93 Min: 78.98 / Avg: 79 / Max: 79.03 Min: 78.84 / Avg: 79.03 / Max: 79.18 Min: 79.2 / Avg: 79.39 / Max: 79.66 Min: 79.1 / Avg: 79.72 / Max: 80.13 Min: 79.51 / Avg: 79.85 / Max: 80.03 Min: 80.05 / Avg: 80.12 / Max: 80.26 Min: 80.03 / Avg: 80.15 / Max: 80.32 Min: 80.18 / Avg: 80.33 / Max: 80.55 Min: 81.59 / Avg: 81.97 / Max: 82.16 Min: 81.53 / Avg: 82.15 / Max: 82.68 Min: 82.61 / Avg: 82.84 / Max: 83.06 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 7F32 EPYC 7F52 EPYC 7542 EPYC 7402P EPYC 7502P EPYC 7702 EPYC 7532 EPYC 7552 EPYC 7662 EPYC 7302P EPYC 7272 EPYC 7232P EPYC 7282 70M 140M 210M 280M 350M SE +/- 60046.42, N = 3 SE +/- 33906.80, N = 3 SE +/- 40543.01, N = 3 SE +/- 465752.47, N = 3 SE +/- 131222.60, N = 3 SE +/- 320354.97, N = 3 SE +/- 12833.10, N = 3 SE +/- 234513.76, N = 3 SE +/- 136985.64, N = 3 SE +/- 206566.86, N = 3 SE +/- 380619.49, N = 3 SE +/- 333820.85, N = 3 SE +/- 38644.36, N = 3 346733990.00 346505619.64 302406827.18 297827555.09 297816529.28 297478250.43 293437386.11 293216264.80 293169027.15 292597759.78 284710986.66 284332324.15 283588722.34 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 7F32 EPYC 7542 EPYC 7402P EPYC 7502P EPYC 7302P EPYC 7552 EPYC 7F52 EPYC 7532 EPYC 7662 EPYC 7702 1.5M 3M 4.5M 6M 7.5M 6962207.10 6892716.30 6710210.44 6400547.89 6161220.61 6095028.20 6028009.87 5937216.36 5029503.05 4710525.85 4210427.87 4208867.42 4189997.27
Result Confidence
OpenBenchmarking.org QUIPs, More Is Better Hierarchical INTegration 1.0 Test: FLOAT EPYC 7F32 EPYC 7F52 EPYC 7542 EPYC 7402P EPYC 7502P EPYC 7702 EPYC 7532 EPYC 7552 EPYC 7662 EPYC 7302P EPYC 7272 EPYC 7232P EPYC 7282 60M 120M 180M 240M 300M Min: 346619184.22 / Avg: 346733990 / Max: 346821912.43 Min: 346439918.8 / Avg: 346505619.64 / Max: 346553015.3 Min: 302325902.16 / Avg: 302406827.18 / Max: 302451712.79 Min: 297325728.53 / Avg: 297827555.09 / Max: 298758103.32 Min: 297554997.89 / Avg: 297816529.28 / Max: 297966245.2 Min: 296837585.98 / Avg: 297478250.43 / Max: 297805193.98 Min: 293416576.95 / Avg: 293437386.11 / Max: 293460802.19 Min: 292759126.74 / Avg: 293216264.8 / Max: 293535711.28 Min: 292897063.96 / Avg: 293169027.15 / Max: 293333683.01 Min: 292233343.29 / Avg: 292597759.78 / Max: 292948520.88 Min: 284060087.32 / Avg: 284710986.66 / Max: 285378285.89 Min: 283664869.62 / Avg: 284332324.15 / Max: 284679741.15 Min: 283512887.38 / Avg: 283588722.34 / Max: 283639560.88 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 7F32 EPYC 7F52 EPYC 7542 EPYC 7502P EPYC 7702 EPYC 7402P EPYC 7662 EPYC 7532 EPYC 7302P EPYC 7552 EPYC 7642 EPYC 7232P EPYC 7272 EPYC 7282 80 160 240 320 400 SE +/- 0.08, N = 3 SE +/- 0.04, N = 3 SE +/- 0.37, N = 3 SE +/- 0.04, N = 3 SE +/- 0.04, N = 3 SE +/- 0.18, N = 3 SE +/- 0.08, N = 3 SE +/- 0.03, N = 3 SE +/- 0.11, N = 3 SE +/- 0.05, N = 3 SE +/- 0.05, N = 3 SE +/- 0.10, N = 3 SE +/- 0.07, N = 3 SE +/- 0.10, N = 3 351.99 351.63 306.62 302.25 302.14 302.12 297.81 297.71 297.65 297.10 296.91 288.70 288.62 287.93 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 7F32 EPYC 7542 EPYC 7402P EPYC 7502P EPYC 7302P EPYC 7552 EPYC 7F52 EPYC 7642 EPYC 7532 EPYC 7662 EPYC 7702 2 4 6 8 10 7.37 7.30 7.11 6.82 6.60 6.50 6.42 6.28 5.41 5.10 4.77 4.57 4.53 4.50
Result Confidence
OpenBenchmarking.org MiB/s, More Is Better Botan 2.13.0 Test: Twofish EPYC 7F32 EPYC 7F52 EPYC 7542 EPYC 7502P EPYC 7702 EPYC 7402P EPYC 7662 EPYC 7532 EPYC 7302P EPYC 7552 EPYC 7642 EPYC 7232P EPYC 7272 EPYC 7282 60 120 180 240 300 Min: 351.85 / Avg: 351.99 / Max: 352.11 Min: 351.56 / Avg: 351.63 / Max: 351.71 Min: 305.88 / Avg: 306.62 / Max: 307 Min: 302.19 / Avg: 302.25 / Max: 302.32 Min: 302.1 / Avg: 302.14 / Max: 302.21 Min: 301.76 / Avg: 302.12 / Max: 302.35 Min: 297.64 / Avg: 297.81 / Max: 297.92 Min: 297.66 / Avg: 297.7 / Max: 297.77 Min: 297.5 / Avg: 297.65 / Max: 297.86 Min: 297.02 / Avg: 297.1 / Max: 297.2 Min: 296.81 / Avg: 296.91 / Max: 296.96 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 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 7F32 EPYC 7F52 EPYC 7542 EPYC 7502P EPYC 7402P EPYC 7702 EPYC 7302P EPYC 7532 EPYC 7552 EPYC 7662 EPYC 7232P EPYC 7272 EPYC 7282 160 320 480 640 800 SE +/- 0.17, N = 3 SE +/- 0.59, N = 3 SE +/- 0.70, N = 3 SE +/- 0.11, N = 3 SE +/- 0.32, N = 3 SE +/- 0.57, N = 3 SE +/- 0.13, N = 3 SE +/- 0.46, N = 3 SE +/- 0.70, N = 3 SE +/- 0.57, N = 3 SE +/- 0.27, N = 3 SE +/- 0.12, N = 3 SE +/- 0.36, N = 3 740.58 739.72 645.87 637.38 636.43 635.92 627.74 627.06 626.57 624.73 608.61 608.05 605.83 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 7F32 EPYC 7542 EPYC 7402P EPYC 7502P EPYC 7302P EPYC 7552 EPYC 7F52 EPYC 7532 EPYC 7702 EPYC 7662 4 8 12 16 20 15.47 15.33 14.84 14.59 13.83 13.61 13.51 13.11 11.25 10.89 9.49 9.49 9.48
Result Confidence
OpenBenchmarking.org Voices, More Is Better Google SynthMark 20201109 Test: VoiceMark_100 EPYC 7F32 EPYC 7F52 EPYC 7542 EPYC 7502P EPYC 7402P EPYC 7702 EPYC 7302P EPYC 7532 EPYC 7552 EPYC 7662 EPYC 7232P EPYC 7272 EPYC 7282 130 260 390 520 650 Min: 740.39 / Avg: 740.58 / Max: 740.92 Min: 738.56 / Avg: 739.72 / Max: 740.43 Min: 644.48 / Avg: 645.87 / Max: 646.66 Min: 637.17 / Avg: 637.38 / Max: 637.55 Min: 635.86 / Avg: 636.43 / Max: 636.98 Min: 634.78 / Avg: 635.92 / Max: 636.53 Min: 627.49 / Avg: 627.74 / Max: 627.91 Min: 626.15 / Avg: 627.06 / Max: 627.62 Min: 625.29 / Avg: 626.57 / Max: 627.72 Min: 623.79 / Avg: 624.73 / Max: 625.77 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 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 7F52 EPYC 7F32 EPYC 7702 EPYC 7542 EPYC 7502P EPYC 7402P EPYC 7552 EPYC 7532 EPYC 7642 EPYC 7302P EPYC 7662 EPYC 7282 EPYC 7272 EPYC 7232P 11K 22K 33K 44K 55K SE +/- 131.48, N = 6 SE +/- 204.79, N = 6 SE +/- 126.64, N = 6 SE +/- 307.98, N = 6 SE +/- 288.40, N = 6 SE +/- 343.41, N = 6 SE +/- 152.42, N = 6 SE +/- 312.60, N = 6 SE +/- 392.71, N = 6 SE +/- 385.00, N = 7 SE +/- 399.17, N = 6 SE +/- 244.70, N = 6 SE +/- 304.76, N = 6 SE +/- 369.07, N = 6 50969 50675 44328 43936 43903 43414 43404 43275 42836 42761 42730 42375 41912 41704 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 7F32 EPYC 7542 EPYC 7402P EPYC 7502P EPYC 7302P EPYC 7552 EPYC 7F52 EPYC 7642 EPYC 7532 EPYC 7702 EPYC 7662 200 400 600 800 1000 1123.76 1109.61 1101.31 1037.75 1000.27 988.44 984.98 963.62 820.23 775.34 736.70 709.62 696.81 683.14
Result Confidence
OpenBenchmarking.org Mflops, More Is Better FFTW 3.3.6 Build: Float + SSE - Size: 1D FFT Size 4096 EPYC 7F52 EPYC 7F32 EPYC 7702 EPYC 7542 EPYC 7502P EPYC 7402P EPYC 7552 EPYC 7532 EPYC 7642 EPYC 7302P EPYC 7662 EPYC 7282 EPYC 7272 EPYC 7232P 9K 18K 27K 36K 45K Min: 50577 / Avg: 50968.83 / Max: 51456 Min: 49987 / Avg: 50674.5 / Max: 51435 Min: 43820 / Avg: 44328.17 / Max: 44688 Min: 43041 / Avg: 43936.17 / Max: 44903 Min: 42938 / Avg: 43902.83 / Max: 44700 Min: 42288 / Avg: 43414 / Max: 44416 Min: 42872 / Avg: 43404.33 / Max: 43831 Min: 41954 / Avg: 43274.83 / Max: 44008 Min: 41412 / Avg: 42836.17 / Max: 44004 Min: 40864 / Avg: 42761.14 / Max: 44031 Min: 40860 / Avg: 42729.67 / Max: 43619 Min: 41289 / Avg: 42374.5 / Max: 42923 Min: 40544 / Avg: 41912 / Max: 42672 Min: 40672 / Avg: 41703.5 / Max: 42890 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 7F32 EPYC 7F52 EPYC 7542 EPYC 7502P EPYC 7402P EPYC 7702 EPYC 7302P EPYC 7552 EPYC 7532 EPYC 7642 EPYC 7662 EPYC 7282 EPYC 7232P EPYC 7272 13 26 39 52 65 SE +/- 0.45, N = 3 SE +/- 0.23, N = 3 SE +/- 0.22, N = 3 SE +/- 0.37, N = 3 SE +/- 0.03, N = 3 SE +/- 0.09, N = 3 SE +/- 0.44, N = 3 SE +/- 0.52, N = 3 SE +/- 0.26, N = 3 SE +/- 0.37, N = 3 SE +/- 0.19, N = 3 SE +/- 0.27, N = 3 SE +/- 0.40, N = 3 SE +/- 0.15, N = 3 49.1 50.4 56.7 56.9 57.2 57.5 57.6 58.1 58.3 58.4 58.6 59.1 59.5 60.0
Result Confidence
OpenBenchmarking.org Milliseconds, Fewer Is Better PyPerformance 1.0.0 Benchmark: django_template EPYC 7F32 EPYC 7F52 EPYC 7542 EPYC 7502P EPYC 7402P EPYC 7702 EPYC 7302P EPYC 7552 EPYC 7532 EPYC 7642 EPYC 7662 EPYC 7282 EPYC 7232P EPYC 7272 12 24 36 48 60 Min: 48.2 / Avg: 49.07 / Max: 49.7 Min: 50.2 / Avg: 50.43 / Max: 50.9 Min: 56.4 / Avg: 56.67 / Max: 57.1 Min: 56.2 / Avg: 56.93 / Max: 57.4 Min: 57.2 / Avg: 57.23 / Max: 57.3 Min: 57.3 / Avg: 57.47 / Max: 57.6 Min: 56.8 / Avg: 57.63 / Max: 58.3 Min: 57.2 / Avg: 58.1 / Max: 59 Min: 57.8 / Avg: 58.27 / Max: 58.7 Min: 57.9 / Avg: 58.37 / Max: 59.1 Min: 58.2 / Avg: 58.57 / Max: 58.8 Min: 58.6 / Avg: 59.13 / Max: 59.4 Min: 58.7 / Avg: 59.5 / Max: 59.9 Min: 59.8 / Avg: 60.03 / Max: 60.3
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 7F32 EPYC 7F52 EPYC 7542 EPYC 7502P EPYC 7702 EPYC 7402P EPYC 7302P EPYC 7532 EPYC 7552 EPYC 7662 EPYC 7272 EPYC 7232P EPYC 7282 20K 40K 60K 80K 100K SE +/- 185.79, N = 3 SE +/- 395.61, N = 3 SE +/- 26.41, N = 3 SE +/- 294.03, N = 3 SE +/- 232.73, N = 3 SE +/- 397.99, N = 3 SE +/- 461.99, N = 3 SE +/- 287.97, N = 3 SE +/- 75.52, N = 3 SE +/- 966.88, N = 3 SE +/- 203.38, N = 3 SE +/- 200.17, N = 3 SE +/- 402.31, N = 3 76027.98 76410.11 86946.61 88487.57 88553.78 88634.31 89863.26 90157.28 90310.90 90672.45 92387.25 92426.49 92896.62 1. (CXX) g++ options: -O3 -march=native -fopenmp
Result Confidence
OpenBenchmarking.org ms, Fewer Is Better FinanceBench 2016-07-25 Benchmark: Bonds OpenMP EPYC 7F32 EPYC 7F52 EPYC 7542 EPYC 7502P EPYC 7702 EPYC 7402P EPYC 7302P EPYC 7532 EPYC 7552 EPYC 7662 EPYC 7272 EPYC 7232P EPYC 7282 16K 32K 48K 64K 80K Min: 75656.88 / Avg: 76027.98 / Max: 76230.05 Min: 75619.2 / Avg: 76410.11 / Max: 76824.91 Min: 86896.07 / Avg: 86946.61 / Max: 86985.19 Min: 88176.03 / Avg: 88487.57 / Max: 89075.27 Min: 88306.55 / Avg: 88553.78 / Max: 89018.95 Min: 88093.03 / Avg: 88634.31 / Max: 89410.36 Min: 89400.2 / Avg: 89863.26 / Max: 90787.24 Min: 89581.38 / Avg: 90157.28 / Max: 90451.57 Min: 90159.87 / Avg: 90310.9 / Max: 90387.48 Min: 89694.92 / Avg: 90672.45 / Max: 92606.17 Min: 92154.74 / Avg: 92387.25 / Max: 92792.54 Min: 92207.57 / Avg: 92426.49 / Max: 92826.23 Min: 92266.52 / Avg: 92896.62 / Max: 93645.02 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 7F52 EPYC 7F32 EPYC 7402P EPYC 7542 EPYC 7502P EPYC 7702 EPYC 7552 EPYC 7662 EPYC 7232P EPYC 7532 EPYC 7302P EPYC 7282 EPYC 7272 12 24 36 48 60 SE +/- 0.01, N = 3 SE +/- 0.35, N = 3 SE +/- 0.55, N = 4 SE +/- 0.04, N = 3 SE +/- 0.29, N = 3 SE +/- 0.42, N = 7 SE +/- 0.65, N = 3 SE +/- 0.31, N = 3 SE +/- 0.43, N = 3 SE +/- 0.37, N = 3 SE +/- 0.53, N = 3 SE +/- 0.15, N = 3 SE +/- 0.15, N = 3 52.82 52.79 45.98 45.90 45.77 45.69 45.38 45.19 44.93 44.69 44.53 44.38 43.23 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 7F52 EPYC 7F32 EPYC 7402P EPYC 7542 EPYC 7502P EPYC 7702 EPYC 7552 EPYC 7662 EPYC 7232P EPYC 7532 EPYC 7302P EPYC 7282 EPYC 7272 11 22 33 44 55 Min: 52.79 / Avg: 52.82 / Max: 52.84 Min: 52.36 / Avg: 52.79 / Max: 53.48 Min: 45.35 / Avg: 45.98 / Max: 47.62 Min: 45.84 / Avg: 45.9 / Max: 45.97 Min: 45.44 / Avg: 45.77 / Max: 46.36 Min: 44.72 / Avg: 45.69 / Max: 47.44 Min: 44.32 / Avg: 45.38 / Max: 46.55 Min: 44.56 / Avg: 45.19 / Max: 45.52 Min: 44.07 / Avg: 44.93 / Max: 45.44 Min: 44.12 / Avg: 44.69 / Max: 45.37 Min: 44 / Avg: 44.53 / Max: 45.58 Min: 44.15 / Avg: 44.38 / Max: 44.66 Min: 42.93 / Avg: 43.23 / Max: 43.4 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 7F32 EPYC 7F52 EPYC 7542 EPYC 7552 EPYC 7702 EPYC 7662 EPYC 7402P EPYC 7302P EPYC 7502P EPYC 7532 EPYC 7272 EPYC 7282 EPYC 7232P 150M 300M 450M 600M 750M SE +/- 2325206.90, N = 3 SE +/- 2209414.80, N = 3 SE +/- 8506660.76, N = 3 SE +/- 807930.96, N = 3 SE +/- 2469610.76, N = 3 SE +/- 5706451.14, N = 3 SE +/- 2164773.96, N = 3 SE +/- 3828695.03, N = 3 SE +/- 4052005.46, N = 3 SE +/- 1400113.05, N = 3 SE +/- 2920022.24, N = 3 SE +/- 5177314.46, N = 3 SE +/- 6957648.38, N = 3 686395419 685188810 612218425 605644364 602434885 602203842 600065572 598589228 597361197 582684333 581194588 571825580 561816772 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 7272 EPYC 7232P EPYC 7282 EPYC 7F32 EPYC 7542 EPYC 7402P EPYC 7502P EPYC 7302P EPYC 7552 EPYC 7F52 EPYC 7662 EPYC 7702 EPYC 7532 3M 6M 9M 12M 15M 14898341.79 14546659.15 14256393.92 13794532.24 13255560.12 13079157.08 12873172.87 12821906.80 11032151.74 10268451.78 9228207.39 9098672.56 9008595.44
Result Confidence
OpenBenchmarking.org Operations Per Second, More Is Better Swet 1.5.16 Average EPYC 7F32 EPYC 7F52 EPYC 7542 EPYC 7552 EPYC 7702 EPYC 7662 EPYC 7402P EPYC 7302P EPYC 7502P EPYC 7532 EPYC 7272 EPYC 7282 EPYC 7232P 120M 240M 360M 480M 600M Min: 682854921 / Avg: 686395419.33 / Max: 690776878 Min: 680933266 / Avg: 685188809.67 / Max: 688347262 Min: 596416785 / Avg: 612218425.33 / Max: 625580102 Min: 604227306 / Avg: 605644364.33 / Max: 607025364 Min: 597611652 / Avg: 602434885.33 / Max: 605768048 Min: 590802604 / Avg: 602203842.33 / Max: 608351202 Min: 595836568 / Avg: 600065571.67 / Max: 602983432 Min: 593041731 / Avg: 598589227.67 / Max: 605934155 Min: 589487365 / Avg: 597361197.33 / Max: 602958932 Min: 579892857 / Avg: 582684332.67 / Max: 584271636 Min: 575619977 / Avg: 581194588 / Max: 585489333 Min: 566389680 / Avg: 571825580.33 / Max: 582175830 Min: 547924209 / Avg: 561816771.67 / Max: 569451631 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 7F32 EPYC 7F52 EPYC 7542 EPYC 7502P EPYC 7702 EPYC 7402P EPYC 7552 EPYC 7532 EPYC 7662 EPYC 7642 EPYC 7302P EPYC 7272 EPYC 7232P EPYC 7282 30 60 90 120 150 SE +/- 0.02, N = 3 SE +/- 0.04, N = 3 SE +/- 0.02, N = 3 SE +/- 0.05, N = 3 SE +/- 0.01, N = 3 SE +/- 0.03, N = 3 SE +/- 0.02, N = 3 SE +/- 0.04, N = 3 SE +/- 0.09, N = 3 SE +/- 0.11, N = 3 SE +/- 0.28, N = 3 SE +/- 0.06, N = 3 SE +/- 0.04, N = 3 SE +/- 0.09, N = 3 139.83 139.71 121.92 120.06 120.00 119.99 118.32 118.29 118.23 117.99 117.88 114.69 114.59 114.47 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 7F32 EPYC 7542 EPYC 7402P EPYC 7502P EPYC 7302P EPYC 7552 EPYC 7F52 EPYC 7642 EPYC 7532 EPYC 7702 EPYC 7662 0.675 1.35 2.025 2.7 3.375 3.00 2.98 2.88 2.83 2.67 2.65 2.61 2.56 2.16 2.09 1.93 1.83 1.83 1.82
Result Confidence
OpenBenchmarking.org MiB/s, More Is Better Botan 2.13.0 Test: CAST-256 EPYC 7F32 EPYC 7F52 EPYC 7542 EPYC 7502P EPYC 7702 EPYC 7402P EPYC 7552 EPYC 7532 EPYC 7662 EPYC 7642 EPYC 7302P EPYC 7272 EPYC 7232P EPYC 7282 30 60 90 120 150 Min: 139.8 / Avg: 139.83 / Max: 139.86 Min: 139.63 / Avg: 139.71 / Max: 139.74 Min: 121.89 / Avg: 121.92 / Max: 121.94 Min: 119.97 / Avg: 120.06 / Max: 120.12 Min: 119.99 / Avg: 119.99 / Max: 120.01 Min: 119.95 / Avg: 119.99 / Max: 120.04 Min: 118.29 / Avg: 118.32 / Max: 118.36 Min: 118.22 / Avg: 118.29 / Max: 118.36 Min: 118.06 / Avg: 118.23 / Max: 118.33 Min: 117.81 / Avg: 117.99 / Max: 118.19 Min: 117.32 / Avg: 117.88 / Max: 118.21 Min: 114.63 / Avg: 114.69 / Max: 114.8 Min: 114.51 / Avg: 114.59 / Max: 114.64 Min: 114.34 / Avg: 114.47 / Max: 114.63 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 7F32 EPYC 7F52 EPYC 7542 EPYC 7702 EPYC 7502P EPYC 7402P EPYC 7552 EPYC 7662 EPYC 7532 EPYC 7302P EPYC 7642 EPYC 7232P EPYC 7272 EPYC 7282 20 40 60 80 100 SE +/- 0.00, 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 +/- 0.00, N = 3 SE +/- 0.00, N = 3 SE +/- 0.06, N = 3 SE +/- 0.01, N = 3 SE +/- 0.05, N = 3 SE +/- 0.02, N = 3 SE +/- 0.01, N = 3 SE +/- 0.07, N = 3 90.46 90.42 78.88 77.70 77.69 77.57 76.58 76.55 76.53 76.51 76.22 74.27 74.21 74.06 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 7F32 EPYC 7542 EPYC 7402P EPYC 7502P EPYC 7302P EPYC 7552 EPYC 7F52 EPYC 7642 EPYC 7532 EPYC 7662 EPYC 7702 0.4365 0.873 1.3095 1.746 2.1825 1.94 1.92 1.86 1.82 1.73 1.70 1.69 1.66 1.40 1.33 1.25 1.18 1.18 1.18
Result Confidence
OpenBenchmarking.org MiB/s, More Is Better Botan 2.13.0 Test: KASUMI EPYC 7F32 EPYC 7F52 EPYC 7542 EPYC 7702 EPYC 7502P EPYC 7402P EPYC 7552 EPYC 7662 EPYC 7532 EPYC 7302P EPYC 7642 EPYC 7232P EPYC 7272 EPYC 7282 20 40 60 80 100 Min: 90.45 / Avg: 90.46 / Max: 90.47 Min: 90.37 / Avg: 90.42 / Max: 90.45 Min: 78.84 / Avg: 78.88 / Max: 78.91 Min: 77.66 / Avg: 77.7 / Max: 77.77 Min: 77.68 / Avg: 77.69 / Max: 77.7 Min: 77.5 / Avg: 77.57 / Max: 77.66 Min: 76.57 / Avg: 76.57 / Max: 76.58 Min: 76.54 / Avg: 76.55 / Max: 76.55 Min: 76.42 / Avg: 76.53 / Max: 76.6 Min: 76.49 / Avg: 76.51 / Max: 76.52 Min: 76.12 / Avg: 76.22 / Max: 76.31 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 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 7F52 EPYC 7F32 EPYC 7542 EPYC 7702 EPYC 7402P EPYC 7502P EPYC 7662 EPYC 7532 EPYC 7302P EPYC 7642 EPYC 7552 EPYC 7282 EPYC 7272 EPYC 7232P 160 320 480 640 800 612.89 613.55 705.16 713.56 714.24 721.79 723.32 724.56 724.99 725.23 727.34 746.18 746.72 748.59
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 7F52 EPYC 7F32 EPYC 7542 EPYC 7402P EPYC 7502P EPYC 7702 EPYC 7662 EPYC 7532 EPYC 7642 EPYC 7302P EPYC 7552 EPYC 7232P EPYC 7272 EPYC 7282 9 18 27 36 45 SE +/- 0.08, N = 4 SE +/- 0.07, N = 4 SE +/- 0.04, N = 4 SE +/- 0.07, N = 4 SE +/- 0.08, N = 4 SE +/- 0.12, N = 4 SE +/- 0.09, N = 4 SE +/- 0.07, N = 4 SE +/- 0.06, N = 4 SE +/- 0.12, N = 4 SE +/- 0.11, N = 4 SE +/- 0.11, N = 4 SE +/- 0.08, N = 4 SE +/- 0.10, N = 4 30.75 30.84 35.27 35.69 35.73 35.93 36.20 36.24 36.28 36.36 36.40 37.40 37.40 37.55 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 7F52 EPYC 7F32 EPYC 7542 EPYC 7402P EPYC 7502P EPYC 7702 EPYC 7662 EPYC 7532 EPYC 7642 EPYC 7302P EPYC 7552 EPYC 7232P EPYC 7272 EPYC 7282 8 16 24 32 40 Min: 30.52 / Avg: 30.75 / Max: 30.86 Min: 30.64 / Avg: 30.84 / Max: 30.96 Min: 35.16 / Avg: 35.27 / Max: 35.37 Min: 35.55 / Avg: 35.69 / Max: 35.87 Min: 35.5 / Avg: 35.73 / Max: 35.85 Min: 35.63 / Avg: 35.93 / Max: 36.21 Min: 35.97 / Avg: 36.2 / Max: 36.42 Min: 36.12 / Avg: 36.24 / Max: 36.4 Min: 36.17 / Avg: 36.28 / Max: 36.45 Min: 36.06 / Avg: 36.36 / Max: 36.65 Min: 36.11 / Avg: 36.4 / Max: 36.59 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 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 7F32 EPYC 7F52 EPYC 7402P EPYC 7542 EPYC 7502P EPYC 7642 EPYC 7702 EPYC 7662 EPYC 7302P EPYC 7532 EPYC 7552 EPYC 7282 EPYC 7272 EPYC 7232P 0.0352 0.0704 0.1056 0.1408 0.176 SE +/- 0.00007037, N = 3 SE +/- 0.00013172, N = 3 SE +/- 0.00052181, N = 3 SE +/- 0.00010921, N = 3 SE +/- 0.00050264, N = 3 SE +/- 0.00113052, N = 3 SE +/- 0.00022828, N = 3 SE +/- 0.00009609, N = 3 SE +/- 0.00104595, N = 3 SE +/- 0.00097851, N = 3 SE +/- 0.00076232, N = 3 SE +/- 0.00047942, N = 3 SE +/- 0.00070595, N = 3 SE +/- 0.00101629, N = 3 0.12819545 0.12924285 0.14573597 0.14850812 0.14859273 0.14868253 0.14954339 0.14976795 0.14978489 0.14988293 0.15124976 0.15341705 0.15457890 0.15653208
Result Confidence
OpenBenchmarking.org Seconds, Fewer Is Better Perl Benchmarks Test: Pod2html EPYC 7F32 EPYC 7F52 EPYC 7402P EPYC 7542 EPYC 7502P EPYC 7642 EPYC 7702 EPYC 7662 EPYC 7302P EPYC 7532 EPYC 7552 EPYC 7282 EPYC 7272 EPYC 7232P 1 2 3 4 5 Min: 0.13 / Avg: 0.13 / Max: 0.13 Min: 0.13 / Avg: 0.13 / Max: 0.13 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: 0.15 / Avg: 0.15 / Max: 0.15 Min: 0.15 / Avg: 0.15 / Max: 0.15 Min: 0.15 / Avg: 0.15 / Max: 0.16 Min: 0.16 / Avg: 0.16 / Max: 0.16
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 7F32 EPYC 7F52 EPYC 7542 EPYC 7702 EPYC 7502P EPYC 7402P EPYC 7302P EPYC 7532 EPYC 7662 EPYC 7642 EPYC 7552 EPYC 7232P EPYC 7282 EPYC 7272 1100 2200 3300 4400 5500 SE +/- 1.69, N = 3 SE +/- 1.30, N = 3 SE +/- 2.98, N = 3 SE +/- 1.00, N = 3 SE +/- 3.31, N = 3 SE +/- 0.83, N = 3 SE +/- 0.26, N = 3 SE +/- 1.33, N = 3 SE +/- 0.85, N = 3 SE +/- 3.58, N = 3 SE +/- 3.88, N = 3 SE +/- 13.87, N = 3 SE +/- 0.80, N = 3 SE +/- 7.02, N = 3 5238.76 5226.75 4561.19 4499.50 4497.77 4487.90 4430.72 4429.47 4429.19 4425.92 4421.41 4311.06 4293.87 4290.85 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 7F32 EPYC 7542 EPYC 7402P EPYC 7502P EPYC 7302P EPYC 7552 EPYC 7F52 EPYC 7642 EPYC 7532 EPYC 7662 EPYC 7702 20 40 60 80 100 109.56 108.21 105.14 101.50 97.57 96.36 95.12 94.08 79.86 76.11 70.28 67.57 67.17 66.83
Result Confidence
OpenBenchmarking.org MiB/s, More Is Better Botan 2.13.0 Test: AES-256 EPYC 7F32 EPYC 7F52 EPYC 7542 EPYC 7702 EPYC 7502P EPYC 7402P EPYC 7302P EPYC 7532 EPYC 7662 EPYC 7642 EPYC 7552 EPYC 7232P EPYC 7282 EPYC 7272 900 1800 2700 3600 4500 Min: 5235.4 / Avg: 5238.76 / Max: 5240.69 Min: 5224.38 / Avg: 5226.75 / Max: 5228.88 Min: 4555.36 / Avg: 4561.19 / Max: 4565.19 Min: 4497.86 / Avg: 4499.5 / Max: 4501.3 Min: 4492.53 / Avg: 4497.77 / Max: 4503.89 Min: 4486.88 / Avg: 4487.9 / Max: 4489.54 Min: 4430.21 / Avg: 4430.72 / Max: 4431.05 Min: 4426.94 / Avg: 4429.47 / Max: 4431.46 Min: 4427.63 / Avg: 4429.19 / Max: 4430.55 Min: 4421.28 / Avg: 4425.91 / Max: 4432.96 Min: 4413.66 / Avg: 4421.41 / Max: 4425.33 Min: 4293.42 / Avg: 4311.06 / Max: 4338.43 Min: 4292.82 / Avg: 4293.87 / Max: 4295.45 Min: 4276.91 / Avg: 4290.85 / Max: 4299.27 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 7F32 EPYC 7F52 EPYC 7542 EPYC 7502P EPYC 7702 EPYC 7402P EPYC 7662 EPYC 7302P EPYC 7552 EPYC 7532 EPYC 7232P EPYC 7272 EPYC 7282 40 80 120 160 200 SE +/- 0.01, N = 3 SE +/- 0.03, N = 3 SE +/- 0.11, N = 3 SE +/- 0.00, N = 3 SE +/- 0.01, N = 3 SE +/- 0.10, N = 3 SE +/- 0.02, N = 3 SE +/- 0.03, N = 3 SE +/- 0.03, N = 3 SE +/- 0.08, N = 3 SE +/- 0.02, N = 3 SE +/- 0.02, N = 3 SE +/- 0.09, N = 3 159.79 159.60 139.25 137.34 137.28 137.09 135.24 135.18 135.14 135.01 131.18 131.15 130.88 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 7F32 EPYC 7542 EPYC 7402P EPYC 7502P EPYC 7302P EPYC 7552 EPYC 7F52 EPYC 7532 EPYC 7662 EPYC 7702 0.7358 1.4716 2.2074 2.9432 3.679 3.27 3.24 3.16 3.07 2.91 2.87 2.86 2.79 2.39 2.29 2.02 2.00 2.00
Result Confidence
OpenBenchmarking.org Mpx/s, More Is Better Etcpak 0.7 Configuration: ETC2 EPYC 7F32 EPYC 7F52 EPYC 7542 EPYC 7502P EPYC 7702 EPYC 7402P EPYC 7662 EPYC 7302P EPYC 7552 EPYC 7532 EPYC 7232P EPYC 7272 EPYC 7282 30 60 90 120 150 Min: 159.77 / Avg: 159.79 / Max: 159.8 Min: 159.56 / Avg: 159.6 / Max: 159.65 Min: 139.03 / Avg: 139.25 / Max: 139.39 Min: 137.34 / Avg: 137.34 / Max: 137.35 Min: 137.26 / Avg: 137.28 / Max: 137.3 Min: 136.98 / Avg: 137.09 / Max: 137.3 Min: 135.2 / Avg: 135.23 / Max: 135.25 Min: 135.12 / Avg: 135.18 / Max: 135.24 Min: 135.11 / Avg: 135.14 / Max: 135.2 Min: 134.91 / Avg: 135.01 / Max: 135.17 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 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 7F52 EPYC 7F32 EPYC 7542 EPYC 7502P EPYC 7402P EPYC 7702 EPYC 7302P EPYC 7662 EPYC 7552 EPYC 7642 EPYC 7532 EPYC 7232P EPYC 7272 EPYC 7282 40 80 120 160 200 SE +/- 0.04, N = 7 SE +/- 0.02, N = 7 SE +/- 0.07, N = 7 SE +/- 0.05, N = 7 SE +/- 0.44, N = 7 SE +/- 0.04, N = 7 SE +/- 0.04, N = 7 SE +/- 0.04, N = 7 SE +/- 0.02, N = 7 SE +/- 0.03, N = 7 SE +/- 0.07, N = 7 SE +/- 0.03, N = 7 SE +/- 0.26, N = 7 SE +/- 0.10, N = 7 197.79 197.77 172.55 170.11 169.70 169.54 167.63 167.62 167.61 167.57 167.52 162.56 162.37 162.07 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 7F32 EPYC 7542 EPYC 7502P EPYC 7402P EPYC 7302P EPYC 7552 EPYC 7F52 EPYC 7642 EPYC 7532 EPYC 7662 EPYC 7702 1.0148 2.0296 3.0444 4.0592 5.074 4.51 4.45 4.30 4.25 4.03 3.96 3.95 3.87 3.31 3.16 2.88 2.85 2.80 2.78
Result Confidence
OpenBenchmarking.org Megapixels/sec, More Is Better libjpeg-turbo tjbench 2.0.2 Test: Decompression Throughput EPYC 7F52 EPYC 7F32 EPYC 7542 EPYC 7502P EPYC 7402P EPYC 7702 EPYC 7302P EPYC 7662 EPYC 7552 EPYC 7642 EPYC 7532 EPYC 7232P EPYC 7272 EPYC 7282 40 80 120 160 200 Min: 197.62 / Avg: 197.79 / Max: 197.87 Min: 197.66 / Avg: 197.77 / Max: 197.86 Min: 172.16 / Avg: 172.55 / Max: 172.69 Min: 169.86 / Avg: 170.11 / Max: 170.26 Min: 167.04 / Avg: 169.7 / Max: 170.26 Min: 169.39 / Avg: 169.54 / Max: 169.69 Min: 167.45 / Avg: 167.63 / Max: 167.79 Min: 167.5 / Avg: 167.62 / Max: 167.77 Min: 167.49 / Avg: 167.61 / Max: 167.66 Min: 167.44 / Avg: 167.57 / Max: 167.69 Min: 167.15 / Avg: 167.52 / Max: 167.68 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 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 7F32 EPYC 7F52 EPYC 7542 EPYC 7502P EPYC 7402P EPYC 7702 EPYC 7662 EPYC 7532 EPYC 7302P EPYC 7552 EPYC 7232P EPYC 7272 EPYC 7282 60 120 180 240 300 SE +/- 0.19, N = 3 SE +/- 0.18, N = 3 SE +/- 0.18, N = 3 SE +/- 0.11, N = 3 SE +/- 0.16, N = 3 SE +/- 0.12, N = 3 SE +/- 0.16, N = 3 SE +/- 0.10, N = 3 SE +/- 0.08, N = 3 SE +/- 0.00, N = 3 SE +/- 0.14, N = 3 SE +/- 0.03, N = 3 SE +/- 0.21, N = 3 271.32 271.07 236.91 233.51 233.39 233.35 229.86 229.73 229.56 229.46 223.03 222.62 222.36 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 7F32 EPYC 7542 EPYC 7502P EPYC 7402P EPYC 7302P EPYC 7552 EPYC 7F52 EPYC 7532 EPYC 7702 EPYC 7662 1.2713 2.5426 3.8139 5.0852 6.3565 5.65 5.60 5.44 5.29 5.04 4.95 4.94 4.81 4.14 3.89 3.48 3.48 3.46
Result Confidence
OpenBenchmarking.org Mpx/s, More Is Better Etcpak 0.7 Configuration: ETC1 EPYC 7F32 EPYC 7F52 EPYC 7542 EPYC 7502P EPYC 7402P EPYC 7702 EPYC 7662 EPYC 7532 EPYC 7302P EPYC 7552 EPYC 7232P EPYC 7272 EPYC 7282 50 100 150 200 250 Min: 271.12 / Avg: 271.32 / Max: 271.69 Min: 270.72 / Avg: 271.07 / Max: 271.3 Min: 236.57 / Avg: 236.91 / Max: 237.18 Min: 233.3 / Avg: 233.51 / Max: 233.66 Min: 233.07 / Avg: 233.39 / Max: 233.6 Min: 233.22 / Avg: 233.35 / Max: 233.6 Min: 229.54 / Avg: 229.86 / Max: 230.03 Min: 229.59 / Avg: 229.73 / Max: 229.93 Min: 229.4 / Avg: 229.56 / Max: 229.64 Min: 229.45 / Avg: 229.46 / Max: 229.47 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 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 7F52 EPYC 7F32 EPYC 7542 EPYC 7502P EPYC 7402P EPYC 7302P EPYC 7702 EPYC 7552 EPYC 7642 EPYC 7532 EPYC 7662 EPYC 7282 EPYC 7232P EPYC 7272 10 20 30 40 50 SE +/- 0.02, N = 3 SE +/- 0.02, N = 3 SE +/- 0.01, N = 3 SE +/- 0.02, N = 3 SE +/- 0.00, N = 3 SE +/- 0.18, N = 3 SE +/- 0.51, 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 +/- 0.01, N = 3 SE +/- 0.05, N = 3 34.81 34.84 39.92 40.53 40.59 40.98 41.15 41.17 41.17 41.19 41.26 42.44 42.44 42.48 1. (CC) gcc options: -lm -O3
Result Confidence
OpenBenchmarking.org Seconds, Fewer Is Better AOBench Size: 2048 x 2048 - Total Time EPYC 7F52 EPYC 7F32 EPYC 7542 EPYC 7502P EPYC 7402P EPYC 7302P EPYC 7702 EPYC 7552 EPYC 7642 EPYC 7532 EPYC 7662 EPYC 7282 EPYC 7232P EPYC 7272 9 18 27 36 45 Min: 34.79 / Avg: 34.81 / Max: 34.85 Min: 34.8 / Avg: 34.83 / Max: 34.87 Min: 39.91 / Avg: 39.92 / Max: 39.94 Min: 40.51 / Avg: 40.53 / Max: 40.58 Min: 40.58 / Avg: 40.59 / Max: 40.6 Min: 40.63 / Avg: 40.98 / Max: 41.17 Min: 40.64 / Avg: 41.15 / Max: 42.18 Min: 41.14 / Avg: 41.16 / Max: 41.18 Min: 41.14 / Avg: 41.17 / Max: 41.18 Min: 41.18 / Avg: 41.19 / Max: 41.2 Min: 41.23 / Avg: 41.26 / Max: 41.3 Min: 42.4 / Avg: 42.43 / Max: 42.45 Min: 42.43 / Avg: 42.44 / Max: 42.45 Min: 42.42 / Avg: 42.48 / Max: 42.58 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 7F32 EPYC 7F52 EPYC 7542 EPYC 7702 EPYC 7502P EPYC 7402P EPYC 7552 EPYC 7302P EPYC 7662 EPYC 7532 EPYC 7272 EPYC 7232P EPYC 7282 60 120 180 240 300 SE +/- 0.01, N = 3 SE +/- 0.04, N = 3 SE +/- 0.05, N = 3 SE +/- 0.08, N = 3 SE +/- 0.07, N = 3 SE +/- 0.02, 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 SE +/- 0.09, N = 3 SE +/- 0.12, N = 3 257.01 256.42 223.49 220.80 220.76 220.71 217.50 217.50 217.45 216.79 211.03 210.93 210.72 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 7F32 EPYC 7542 EPYC 7402P EPYC 7502P EPYC 7302P EPYC 7552 EPYC 7F52 EPYC 7532 EPYC 7662 EPYC 7702 1.2038 2.4076 3.6114 4.8152 6.019 5.35 5.28 5.14 5.05 4.78 4.70 4.65 4.57 3.92 3.74 3.32 3.28 3.28
Result Confidence
OpenBenchmarking.org Mpx/s, More Is Better Etcpak 0.7 Configuration: ETC1 + Dithering EPYC 7F32 EPYC 7F52 EPYC 7542 EPYC 7702 EPYC 7502P EPYC 7402P EPYC 7552 EPYC 7302P EPYC 7662 EPYC 7532 EPYC 7272 EPYC 7232P EPYC 7282 50 100 150 200 250 Min: 257 / Avg: 257.01 / Max: 257.02 Min: 256.36 / Avg: 256.42 / Max: 256.5 Min: 223.43 / Avg: 223.49 / Max: 223.58 Min: 220.64 / Avg: 220.8 / Max: 220.91 Min: 220.68 / Avg: 220.76 / Max: 220.9 Min: 220.68 / Avg: 220.71 / Max: 220.76 Min: 217.48 / Avg: 217.5 / Max: 217.52 Min: 217.45 / Avg: 217.5 / Max: 217.57 Min: 217.36 / Avg: 217.45 / Max: 217.6 Min: 216.67 / Avg: 216.79 / Max: 216.93 Min: 210.87 / Avg: 211.03 / Max: 211.13 Min: 210.74 / Avg: 210.93 / Max: 211.03 Min: 210.52 / Avg: 210.72 / Max: 210.94 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 7F32 EPYC 7F52 EPYC 7542 EPYC 7702 EPYC 7502P EPYC 7402P EPYC 7532 EPYC 7662 EPYC 7552 EPYC 7302P EPYC 7232P EPYC 7272 EPYC 7282 300K 600K 900K 1200K 1500K SE +/- 1531.45, N = 12 SE +/- 791.31, N = 12 SE +/- 372.53, N = 12 SE +/- 658.02, N = 11 SE +/- 1366.07, N = 11 SE +/- 1181.68, N = 11 SE +/- 986.25, N = 11 SE +/- 1511.23, N = 11 SE +/- 587.46, N = 11 SE +/- 609.53, N = 11 SE +/- 504.67, N = 11 SE +/- 863.61, N = 11 SE +/- 1355.09, N = 11 1180682 1178140 1030295 1015858 1014342 1013320 999442 997809 997461 997133 969371 969066 968149 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 7F32 EPYC 7232P EPYC 7272 EPYC 7282 EPYC 7542 EPYC 7402P EPYC 7502P EPYC 7302P EPYC 7F52 EPYC 7552 EPYC 7532 EPYC 7702 EPYC 7662 7K 14K 21K 28K 35K 31397.39 30915.01 30478.57 29161.11 28093.43 27950.92 27717.32 26682.94 23615.12 23213.22 20016.67 19805.30 19457.25
Result Confidence
OpenBenchmarking.org Nodes Per Second, More Is Better TSCP 1.81 AI Chess Performance EPYC 7F32 EPYC 7F52 EPYC 7542 EPYC 7702 EPYC 7502P EPYC 7402P EPYC 7532 EPYC 7662 EPYC 7552 EPYC 7302P EPYC 7232P EPYC 7272 EPYC 7282 200K 400K 600K 800K 1000K Min: 1166902 / Avg: 1180681.92 / Max: 1187021 Min: 1174366 / Avg: 1178140.42 / Max: 1181927 Min: 1029491 / Avg: 1030294.92 / Max: 1033354 Min: 1010601 / Avg: 1015858.45 / Max: 1018073 Min: 1001414 / Avg: 1014342.27 / Max: 1018073 Min: 1003238 / Avg: 1013319.55 / Max: 1016195 Min: 990607 / Avg: 999441.64 / Max: 1003238 Min: 987057 / Avg: 997809 / Max: 1001414 Min: 994184 / Avg: 997460.73 / Max: 999597 Min: 994184 / Avg: 997132.73 / Max: 999597 Min: 966277 / Avg: 969371.36 / Max: 971389 Min: 961218 / Avg: 969066.36 / Max: 971389 Min: 956211 / Avg: 968148.55 / Max: 971389 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 7F52 EPYC 7F32 EPYC 7542 EPYC 7502P EPYC 7402P EPYC 7702 EPYC 7662 EPYC 7302P EPYC 7552 EPYC 7532 EPYC 7272 EPYC 7232P EPYC 7282 500 1000 1500 2000 2500 SE +/- 10.66, N = 3 SE +/- 13.33, N = 3 SE +/- 11.83, N = 3 SE +/- 9.97, N = 3 SE +/- 12.22, N = 3 SE +/- 11.47, N = 3 SE +/- 10.12, N = 3 SE +/- 10.13, N = 3 SE +/- 13.45, N = 3 SE +/- 10.26, N = 3 SE +/- 12.91, N = 3 SE +/- 10.95, N = 3 SE +/- 8.78, N = 3 2300.7 2285.2 2016.4 1984.5 1977.3 1970.1 1955.3 1952.5 1945.3 1922.3 1893.2 1892.0 1887.0 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 7F32 EPYC 7542 EPYC 7402P EPYC 7502P EPYC 7302P EPYC 7552 EPYC 7F52 EPYC 7662 EPYC 7532 EPYC 7702 10 20 30 40 50 46.01 45.42 44.47 42.47 41.04 40.44 40.27 39.68 33.75 31.99 28.49 28.32 28.04
Result Confidence
OpenBenchmarking.org MFLOPS, More Is Better QuantLib 1.21 EPYC 7F52 EPYC 7F32 EPYC 7542 EPYC 7502P EPYC 7402P EPYC 7702 EPYC 7662 EPYC 7302P EPYC 7552 EPYC 7532 EPYC 7272 EPYC 7232P EPYC 7282 400 800 1200 1600 2000 Min: 2279.8 / Avg: 2300.73 / Max: 2314.7 Min: 2258.5 / Avg: 2285.17 / Max: 2298.8 Min: 1993.3 / Avg: 2016.43 / Max: 2032.3 Min: 1964.7 / Avg: 1984.5 / Max: 1996.4 Min: 1953.5 / Avg: 1977.33 / Max: 1993.9 Min: 1947.7 / Avg: 1970.13 / Max: 1985.5 Min: 1935.1 / Avg: 1955.3 / Max: 1966.5 Min: 1932.3 / Avg: 1952.53 / Max: 1963.6 Min: 1918.7 / Avg: 1945.33 / Max: 1961.9 Min: 1902.5 / Avg: 1922.27 / Max: 1936.9 Min: 1867.5 / Avg: 1893.2 / Max: 1908.2 Min: 1870.4 / Avg: 1892 / Max: 1905.9 Min: 1869.4 / Avg: 1886.97 / Max: 1895.9 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 7F32 EPYC 7F52 EPYC 7542 EPYC 7502P EPYC 7702 EPYC 7402P EPYC 7662 EPYC 7302P EPYC 7532 EPYC 7642 EPYC 7552 EPYC 7232P EPYC 7272 EPYC 7282 70 140 210 280 350 SE +/- 0.36, N = 3 SE +/- 0.12, N = 3 SE +/- 0.29, N = 3 SE +/- 0.71, N = 3 SE +/- 0.80, N = 3 SE +/- 0.19, N = 3 SE +/- 0.83, N = 3 SE +/- 0.82, N = 3 SE +/- 0.26, N = 3 SE +/- 1.03, N = 3 SE +/- 1.22, N = 3 SE +/- 0.77, N = 3 SE +/- 0.11, N = 3 SE +/- 1.44, N = 3 269.64 269.92 308.94 312.89 313.01 314.31 317.55 318.37 318.58 318.67 318.67 327.99 328.36 328.64 MIN: 267.19 / MAX: 279.76 MIN: 267.18 / MAX: 272.47 MIN: 306.29 / MAX: 322.41 MIN: 310.9 / MAX: 315.08 MIN: 310.72 / MAX: 314.66 MIN: 311.3 / MAX: 317.52 MIN: 315.59 / MAX: 319.4 MIN: 315.66 / MAX: 323.53 MIN: 315.09 / MAX: 320.21 MIN: 315.68 / MAX: 321.91 MIN: 315.63 / MAX: 323.01 MIN: 325.21 / MAX: 329.77 MIN: 325.02 / MAX: 339.93 MIN: 325.19 / MAX: 342.8 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 7F32 EPYC 7F52 EPYC 7542 EPYC 7502P EPYC 7702 EPYC 7402P EPYC 7662 EPYC 7302P EPYC 7532 EPYC 7642 EPYC 7552 EPYC 7232P EPYC 7272 EPYC 7282 60 120 180 240 300 Min: 269.01 / Avg: 269.64 / Max: 270.25 Min: 269.68 / Avg: 269.92 / Max: 270.07 Min: 308.42 / Avg: 308.94 / Max: 309.44 Min: 311.52 / Avg: 312.89 / Max: 313.94 Min: 311.43 / Avg: 313.01 / Max: 313.95 Min: 313.92 / Avg: 314.31 / Max: 314.52 Min: 316.01 / Avg: 317.55 / Max: 318.87 Min: 317.19 / Avg: 318.37 / Max: 319.96 Min: 318.08 / Avg: 318.58 / Max: 318.92 Min: 316.65 / Avg: 318.67 / Max: 319.98 Min: 316.23 / Avg: 318.67 / Max: 320.01 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 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 7F52 EPYC 7F32 EPYC 7302P EPYC 7542 EPYC 7402P EPYC 7502P EPYC 7552 EPYC 7642 EPYC 7532 EPYC 7702 EPYC 7662 EPYC 7272 EPYC 7282 EPYC 7232P 0.0002 0.0004 0.0006 0.0008 0.001 SE +/- 0.00000483, N = 3 SE +/- 0.00001015, N = 3 SE +/- 0.00000413, N = 3 SE +/- 0.00000879, N = 3 SE +/- 0.00000962, N = 3 SE +/- 0.00000724, N = 3 SE +/- 0.00000921, N = 3 SE +/- 0.00000264, N = 3 SE +/- 0.00000252, N = 3 SE +/- 0.00000621, N = 3 SE +/- 0.00000365, N = 3 SE +/- 0.00001257, N = 3 SE +/- 0.00000497, N = 3 SE +/- 0.00000737, N = 3 0.00082570 0.00083563 0.00095478 0.00095485 0.00095586 0.00096082 0.00096153 0.00096579 0.00096753 0.00097084 0.00097455 0.00098074 0.00099210 0.00100608
Result Confidence
OpenBenchmarking.org Seconds, Fewer Is Better Perl Benchmarks Test: Interpreter EPYC 7F52 EPYC 7F32 EPYC 7302P EPYC 7542 EPYC 7402P EPYC 7502P EPYC 7552 EPYC 7642 EPYC 7532 EPYC 7702 EPYC 7662 EPYC 7272 EPYC 7282 EPYC 7232P 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 7F32 EPYC 7F52 EPYC 7542 EPYC 7502P EPYC 7402P EPYC 7702 EPYC 7642 EPYC 7302P EPYC 7532 EPYC 7552 EPYC 7662 EPYC 7282 EPYC 7272 EPYC 7232P 20 40 60 80 100 SE +/- 0.05, N = 3 SE +/- 0.14, N = 3 SE +/- 0.31, N = 3 SE +/- 0.17, N = 3 SE +/- 0.09, N = 3 SE +/- 0.11, N = 3 SE +/- 0.19, N = 3 SE +/- 0.09, N = 3 SE +/- 0.08, N = 3 SE +/- 0.28, N = 3 SE +/- 0.12, N = 3 SE +/- 0.12, N = 3 SE +/- 0.04, N = 3 SE +/- 0.16, N = 3 80.85 80.94 92.77 93.86 93.92 94.76 95.39 95.45 95.48 95.53 95.56 98.24 98.31 98.41 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 7F32 EPYC 7F52 EPYC 7542 EPYC 7502P EPYC 7402P EPYC 7702 EPYC 7642 EPYC 7302P EPYC 7532 EPYC 7552 EPYC 7662 EPYC 7282 EPYC 7272 EPYC 7232P 20 40 60 80 100 Min: 80.76 / Avg: 80.85 / Max: 80.91 Min: 80.67 / Avg: 80.94 / Max: 81.13 Min: 92.29 / Avg: 92.77 / Max: 93.36 Min: 93.53 / Avg: 93.86 / Max: 94.1 Min: 93.8 / Avg: 93.92 / Max: 94.11 Min: 94.65 / Avg: 94.76 / Max: 94.97 Min: 95.12 / Avg: 95.39 / Max: 95.75 Min: 95.27 / Avg: 95.45 / Max: 95.58 Min: 95.35 / Avg: 95.48 / Max: 95.62 Min: 95.11 / Avg: 95.53 / Max: 96.06 Min: 95.43 / Avg: 95.56 / Max: 95.8 Min: 98.08 / Avg: 98.24 / Max: 98.48 Min: 98.25 / Avg: 98.31 / Max: 98.39 Min: 98.12 / Avg: 98.41 / Max: 98.67 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 7F32 EPYC 7F52 EPYC 7542 EPYC 7502P EPYC 7402P EPYC 7702 EPYC 7302P EPYC 7552 EPYC 7532 EPYC 7662 EPYC 7642 EPYC 7272 EPYC 7232P EPYC 7282 0.6833 1.3666 2.0499 2.7332 3.4165 SE +/- 0.001, N = 10 SE +/- 0.002, N = 10 SE +/- 0.001, N = 9 SE +/- 0.003, N = 9 SE +/- 0.002, N = 9 SE +/- 0.003, N = 9 SE +/- 0.002, N = 9 SE +/- 0.002, N = 9 SE +/- 0.001, N = 9 SE +/- 0.003, N = 9 SE +/- 0.003, N = 9 SE +/- 0.001, N = 9 SE +/- 0.002, N = 9 SE +/- 0.002, N = 9 2.495 2.500 2.858 2.899 2.901 2.905 2.945 2.945 2.945 2.946 2.952 3.029 3.035 3.037 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 7F32 EPYC 7F52 EPYC 7542 EPYC 7502P EPYC 7402P EPYC 7702 EPYC 7302P EPYC 7552 EPYC 7532 EPYC 7662 EPYC 7642 EPYC 7272 EPYC 7232P EPYC 7282 2 4 6 8 10 Min: 2.49 / Avg: 2.49 / Max: 2.5 Min: 2.49 / Avg: 2.5 / Max: 2.51 Min: 2.85 / Avg: 2.86 / Max: 2.87 Min: 2.89 / Avg: 2.9 / Max: 2.92 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: 2.94 / Avg: 2.94 / Max: 2.95 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: 3.02 / Avg: 3.03 / Max: 3.03 Min: 3.03 / Avg: 3.04 / Max: 3.05 Min: 3.03 / Avg: 3.04 / Max: 3.05 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 7F52 EPYC 7F32 EPYC 7542 EPYC 7502P EPYC 7662 EPYC 7532 EPYC 7642 EPYC 7552 EPYC 7302P EPYC 7402P EPYC 7702 EPYC 7282 EPYC 7272 EPYC 7232P 900 1800 2700 3600 4500 SE +/- 38.21, N = 3 SE +/- 33.69, N = 3 SE +/- 9.42, N = 3 SE +/- 43.10, N = 4 SE +/- 47.38, N = 4 SE +/- 42.46, N = 3 SE +/- 44.49, N = 4 SE +/- 31.29, N = 9 SE +/- 46.66, N = 4 SE +/- 37.84, N = 3 SE +/- 36.48, N = 3 SE +/- 17.87, N = 3 SE +/- 37.21, N = 3 SE +/- 25.83, N = 3 4367.12 4336.41 3988.94 3853.50 3837.56 3830.20 3816.08 3793.17 3792.81 3765.85 3762.49 3756.96 3634.17 3589.93 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 7282 EPYC 7232P EPYC 7272 EPYC 7542 EPYC 7F32 EPYC 7502P EPYC 7402P EPYC 7302P EPYC 7552 EPYC 7F52 EPYC 7642 EPYC 7532 EPYC 7662 EPYC 7702 20 40 60 80 100 84.36 83.09 82.98 77.43 75.95 75.05 73.50 73.24 62.42 57.55 56.78 53.96 53.85 51.62
Result Confidence
OpenBenchmarking.org MFLOPS, More Is Better Himeno Benchmark 3.0 Poisson Pressure Solver EPYC 7F52 EPYC 7F32 EPYC 7542 EPYC 7502P EPYC 7662 EPYC 7532 EPYC 7642 EPYC 7552 EPYC 7302P EPYC 7402P EPYC 7702 EPYC 7282 EPYC 7272 EPYC 7232P 800 1600 2400 3200 4000 Min: 4297.85 / Avg: 4367.12 / Max: 4429.7 Min: 4277.41 / Avg: 4336.41 / Max: 4394.1 Min: 3976.02 / Avg: 3988.94 / Max: 4007.28 Min: 3731.7 / Avg: 3853.5 / Max: 3929.87 Min: 3701.86 / Avg: 3837.56 / Max: 3910.17 Min: 3768.21 / Avg: 3830.2 / Max: 3911.46 Min: 3692 / Avg: 3816.08 / Max: 3902.55 Min: 3632 / Avg: 3793.17 / Max: 3925.79 Min: 3699.39 / Avg: 3792.81 / Max: 3917.69 Min: 3719.42 / Avg: 3765.85 / Max: 3840.83 Min: 3718.35 / Avg: 3762.49 / Max: 3834.86 Min: 3721.38 / Avg: 3756.96 / Max: 3777.75 Min: 3590.61 / Avg: 3634.17 / Max: 3708.22 Min: 3541.75 / Avg: 3589.93 / Max: 3630.15 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 7F32 EPYC 7F52 EPYC 7402P EPYC 7542 EPYC 7532 EPYC 7502P EPYC 7702 EPYC 7662 EPYC 7302P EPYC 7552 EPYC 7642 EPYC 7272 EPYC 7232P EPYC 7282 130K 260K 390K 520K 650K SE +/- 7086.33, N = 3 SE +/- 1476.72, N = 3 SE +/- 4035.67, N = 3 SE +/- 741.11, N = 3 SE +/- 4131.15, N = 3 SE +/- 948.15, N = 3 SE +/- 1921.47, N = 3 SE +/- 1174.39, N = 3 SE +/- 957.34, N = 3 SE +/- 142.64, N = 3 SE +/- 215.70, N = 3 SE +/- 2157.92, N = 3 SE +/- 569.07, N = 3 SE +/- 973.54, N = 3 621672 614039 542521 539060 532957 531740 529609 524751 524189 523575 521572 513356 511906 511228
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 7F32 EPYC 7402P EPYC 7542 EPYC 7502P EPYC 7302P EPYC 7552 EPYC 7F52 EPYC 7642 EPYC 7532 EPYC 7662 EPYC 7702 3K 6K 9K 12K 15K 12522.00 12418.02 12087.81 11604.83 11170.88 11143.99 10842.61 10676.05 9050.74 8583.59 8074.56 7829.14 7697.43 7643.25
Result Confidence
OpenBenchmarking.org Score, More Is Better PHPBench 0.8.1 PHP Benchmark Suite EPYC 7F32 EPYC 7F52 EPYC 7402P EPYC 7542 EPYC 7532 EPYC 7502P EPYC 7702 EPYC 7662 EPYC 7302P EPYC 7552 EPYC 7642 EPYC 7272 EPYC 7232P EPYC 7282 110K 220K 330K 440K 550K Min: 613060 / Avg: 621672 / Max: 635726 Min: 611253 / Avg: 614039 / Max: 616281 Min: 534521 / Avg: 542520.67 / Max: 547450 Min: 538010 / Avg: 539060 / Max: 540491 Min: 524902 / Avg: 532956.67 / Max: 538578 Min: 530354 / Avg: 531740.33 / Max: 533554 Min: 525962 / Avg: 529608.67 / Max: 532482 Min: 523197 / Avg: 524750.67 / Max: 527053 Min: 522517 / Avg: 524188.67 / Max: 525833 Min: 523393 / Avg: 523574.67 / Max: 523856 Min: 521324 / Avg: 521572.33 / Max: 522002 Min: 510924 / Avg: 513356.33 / Max: 517660 Min: 511300 / Avg: 511905.67 / Max: 513043 Min: 510027 / Avg: 511228.33 / Max: 513156
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 7F32 EPYC 7F52 EPYC 7542 EPYC 7402P EPYC 7502P EPYC 7702 EPYC 7662 EPYC 7532 EPYC 7302P EPYC 7642 EPYC 7552 EPYC 7272 EPYC 7232P EPYC 7282 20 40 60 80 100 SE +/- 0.36, N = 3 SE +/- 0.29, N = 3 SE +/- 0.30, N = 3 SE +/- 0.84, N = 3 SE +/- 0.75, N = 3 SE +/- 0.76, N = 3 SE +/- 0.88, N = 3 SE +/- 0.48, N = 3 SE +/- 0.95, N = 3 SE +/- 0.80, N = 3 SE +/- 0.71, N = 3 SE +/- 0.94, N = 3 SE +/- 0.53, N = 3 SE +/- 0.25, N = 3 73.75 73.85 83.90 84.43 85.02 85.24 85.73 85.79 85.82 86.36 86.37 88.44 88.44 89.68 1. (CC) gcc options: -O2
Result Confidence
OpenBenchmarking.org Seconds, Fewer Is Better GnuPG 2.2.27 2.7GB Sample File Encryption EPYC 7F32 EPYC 7F52 EPYC 7542 EPYC 7402P EPYC 7502P EPYC 7702 EPYC 7662 EPYC 7532 EPYC 7302P EPYC 7642 EPYC 7552 EPYC 7272 EPYC 7232P EPYC 7282 20 40 60 80 100 Min: 73.34 / Avg: 73.75 / Max: 74.47 Min: 73.37 / Avg: 73.85 / Max: 74.37 Min: 83.3 / Avg: 83.9 / Max: 84.23 Min: 83.56 / Avg: 84.43 / Max: 86.11 Min: 83.6 / Avg: 85.02 / Max: 86.12 Min: 83.83 / Avg: 85.24 / Max: 86.45 Min: 84.82 / Avg: 85.73 / Max: 87.48 Min: 85.06 / Avg: 85.79 / Max: 86.69 Min: 84.82 / Avg: 85.82 / Max: 87.72 Min: 84.87 / Avg: 86.36 / Max: 87.6 Min: 85.07 / Avg: 86.37 / Max: 87.5 Min: 87.5 / Avg: 88.44 / Max: 90.31 Min: 87.54 / Avg: 88.44 / Max: 89.39 Min: 89.26 / Avg: 89.68 / Max: 90.12 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 7F52 EPYC 7F32 EPYC 7542 EPYC 7502P EPYC 7662 EPYC 7642 EPYC 7402P EPYC 7552 EPYC 7702 EPYC 7532 EPYC 7302P EPYC 7282 EPYC 7272 EPYC 7232P 200 400 600 800 1000 SE +/- 0.51, N = 3 SE +/- 1.50, N = 3 SE +/- 0.71, N = 3 SE +/- 0.42, N = 3 SE +/- 0.53, N = 3 SE +/- 1.18, N = 3 SE +/- 0.40, N = 3 SE +/- 0.82, N = 3 SE +/- 1.46, N = 3 SE +/- 0.79, N = 3 SE +/- 0.19, N = 3 SE +/- 1.22, N = 3 SE +/- 0.49, N = 3 SE +/- 0.40, N = 3 1062.32 1039.60 983.45 974.40 966.04 963.00 962.88 956.82 954.20 949.15 943.29 928.43 919.01 876.45 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 7272 EPYC 7232P EPYC 7282 EPYC 7F32 EPYC 7302P EPYC 7542 EPYC 7402P EPYC 7502P EPYC 7552 EPYC 7F52 EPYC 7532 EPYC 7642 EPYC 7662 EPYC 7702 5 10 15 20 25 18.67 18.67 18.12 16.03 16.01 15.32 15.18 15.04 12.12 11.43 11.25 10.78 10.48 9.72
Result Confidence
OpenBenchmarking.org Test Cases Per Minute, More Is Better Darmstadt Automotive Parallel Heterogeneous Suite Backend: OpenMP - Kernel: Euclidean Cluster EPYC 7F52 EPYC 7F32 EPYC 7542 EPYC 7502P EPYC 7662 EPYC 7642 EPYC 7402P EPYC 7552 EPYC 7702 EPYC 7532 EPYC 7302P EPYC 7282 EPYC 7272 EPYC 7232P 200 400 600 800 1000 Min: 1061.29 / Avg: 1062.32 / Max: 1062.84 Min: 1037.63 / Avg: 1039.6 / Max: 1042.55 Min: 982.72 / Avg: 983.45 / Max: 984.87 Min: 973.64 / Avg: 974.4 / Max: 975.08 Min: 965.08 / Avg: 966.04 / Max: 966.9 Min: 961.75 / Avg: 963 / Max: 965.37 Min: 962.13 / Avg: 962.88 / Max: 963.5 Min: 955.86 / Avg: 956.82 / Max: 958.45 Min: 951.37 / Avg: 954.2 / Max: 956.21 Min: 947.85 / Avg: 949.15 / Max: 950.57 Min: 942.97 / Avg: 943.29 / Max: 943.63 Min: 926.64 / Avg: 928.43 / Max: 930.77 Min: 918.04 / Avg: 919.01 / Max: 919.66 Min: 876.05 / Avg: 876.45 / Max: 877.26 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 7502P EPYC 7402P EPYC 7F52 EPYC 7642 EPYC 7702 EPYC 7662 EPYC 7552 EPYC 7532 EPYC 7302P EPYC 7282 EPYC 7542 EPYC 7F32 EPYC 7272 EPYC 7232P 300K 600K 900K 1200K 1500K SE +/- 1998.87, N = 3 SE +/- 607.09, N = 3 SE +/- 771.81, N = 3 SE +/- 472.72, N = 3 SE +/- 1936.89, N = 3 SE +/- 2041.67, N = 3 SE +/- 2507.53, N = 3 SE +/- 2350.83, N = 3 SE +/- 842.53, N = 3 SE +/- 1258.02, N = 3 SE +/- 577.19, N = 3 SE +/- 2229.96, N = 3 SE +/- 1165.03, N = 3 SE +/- 1045.78, N = 3 1262530.4 1248284.1 1247037.6 1215056.1 1212918.2 1209698.0 1208480.8 1197778.9 1188387.2 1172021.1 1162690.9 1155871.8 1143360.5 1041996.8
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 7272 EPYC 7282 EPYC 7232P EPYC 7302P EPYC 7502P EPYC 7402P EPYC 7542 EPYC 7F32 EPYC 7552 EPYC 7532 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7F52 4K 8K 12K 16K 20K 19247.10 19191.04 19005.43 17671.85 17421.85 17298.69 16668.21 15038.78 14523.73 12972.75 12867.29 12804.70 12097.16 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 7502P EPYC 7402P EPYC 7F52 EPYC 7642 EPYC 7702 EPYC 7662 EPYC 7552 EPYC 7532 EPYC 7302P EPYC 7282 EPYC 7542 EPYC 7F32 EPYC 7272 EPYC 7232P 200K 400K 600K 800K 1000K Min: 1259246.9 / Avg: 1262530.43 / Max: 1266147.1 Min: 1247624.2 / Avg: 1248284.1 / Max: 1249496.7 Min: 1245534.1 / Avg: 1247037.63 / Max: 1248092.1 Min: 1214294.3 / Avg: 1215056.1 / Max: 1215921.9 Min: 1209097.9 / Avg: 1212918.2 / Max: 1215383.9 Min: 1206399.7 / Avg: 1209698.03 / Max: 1213431.9 Min: 1203466.2 / Avg: 1208480.8 / Max: 1211047.5 Min: 1194820.8 / Avg: 1197778.87 / Max: 1202422.8 Min: 1187003 / Avg: 1188387.17 / Max: 1189911.5 Min: 1169540.4 / Avg: 1172021.13 / Max: 1173625.2 Min: 1161606.1 / Avg: 1162690.93 / Max: 1163575.1 Min: 1152601.1 / Avg: 1155871.8 / Max: 1160133 Min: 1141134.6 / Avg: 1143360.47 / Max: 1145070.1 Min: 1040104.9 / Avg: 1041996.77 / Max: 1043715.1
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 7F32 EPYC 7F52 EPYC 7542 EPYC 7502P EPYC 7702 EPYC 7402P EPYC 7552 EPYC 7302P EPYC 7662 EPYC 7532 EPYC 7272 EPYC 7232P EPYC 7282 300 600 900 1200 1500 SE +/- 0.24, N = 8 SE +/- 2.05, N = 8 SE +/- 1.94, N = 7 SE +/- 1.96, N = 7 SE +/- 1.34, N = 7 SE +/- 1.99, N = 7 SE +/- 1.97, N = 7 SE +/- 1.74, N = 7 SE +/- 2.20, N = 7 SE +/- 2.27, N = 7 SE +/- 1.94, N = 7 SE +/- 1.98, N = 7 SE +/- 2.23, N = 7 1179.30 1179.02 1035.23 1022.48 1019.21 1018.97 1008.24 1007.95 1007.22 1006.92 978.85 976.59 975.22 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 7F32 EPYC 7282 EPYC 7542 EPYC 7402P EPYC 7502P EPYC 7302P EPYC 7552 EPYC 7F52 EPYC 7532 EPYC 7702 EPYC 7662 6 12 18 24 30 27.45 27.10 26.64 26.39 24.75 24.45 24.28 23.75 20.49 19.82 17.36 17.07 17.06
Result Confidence
OpenBenchmarking.org Mpx/s, More Is Better Etcpak 0.7 Configuration: DXT1 EPYC 7F32 EPYC 7F52 EPYC 7542 EPYC 7502P EPYC 7702 EPYC 7402P EPYC 7552 EPYC 7302P EPYC 7662 EPYC 7532 EPYC 7272 EPYC 7232P EPYC 7282 200 400 600 800 1000 Min: 1178.67 / Avg: 1179.3 / Max: 1180.64 Min: 1173.37 / Avg: 1179.02 / Max: 1186.77 Min: 1031.59 / Avg: 1035.22 / Max: 1042.84 Min: 1017.68 / Avg: 1022.48 / Max: 1028.23 Min: 1017.42 / Avg: 1019.21 / Max: 1027.18 Min: 1012.27 / Avg: 1018.97 / Max: 1026.96 Min: 1002.46 / Avg: 1008.24 / Max: 1013.3 Min: 1001.21 / Avg: 1007.95 / Max: 1011.76 Min: 1002.3 / Avg: 1007.22 / Max: 1013.81 Min: 999.92 / Avg: 1006.92 / Max: 1013.6 Min: 972.88 / Avg: 978.85 / Max: 983.32 Min: 970.13 / Avg: 976.59 / Max: 981.11 Min: 970.09 / Avg: 975.22 / Max: 983.12 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 7F32 EPYC 7F52 EPYC 7542 EPYC 7702 EPYC 7402P EPYC 7532 EPYC 7502P EPYC 7552 EPYC 7662 EPYC 7302P EPYC 7642 EPYC 7272 EPYC 7282 EPYC 7232P 0.767 1.534 2.301 3.068 3.835 SE +/- 0.010, N = 3 SE +/- 0.017, N = 3 SE +/- 0.009, N = 3 SE +/- 0.009, N = 3 SE +/- 0.004, N = 3 SE +/- 0.006, N = 3 SE +/- 0.005, N = 3 SE +/- 0.005, N = 3 SE +/- 0.009, N = 3 SE +/- 0.009, N = 3 SE +/- 0.008, N = 3 SE +/- 0.008, N = 3 SE +/- 0.008, N = 3 SE +/- 0.006, N = 3 3.409 3.365 3.004 2.970 2.967 2.937 2.929 2.929 2.926 2.926 2.894 2.861 2.838 2.822
Frames Per Second Per Watt
OpenBenchmarking.org Frames Per Second Per Watt, More Is Better rav1e 0.4 Speed: 10 EPYC 7F32 EPYC 7282 EPYC 7542 EPYC 7272 EPYC 7232P EPYC 7402P EPYC 7502P EPYC 7552 EPYC 7302P EPYC 7642 EPYC 7532 EPYC 7F52 EPYC 7662 EPYC 7702 0.0135 0.027 0.0405 0.054 0.0675 0.06 0.06 0.06 0.06 0.06 0.06 0.05 0.05 0.05 0.04 0.04 0.04 0.04 0.04
Result Confidence
OpenBenchmarking.org Frames Per Second, More Is Better rav1e 0.4 Speed: 10 EPYC 7F32 EPYC 7F52 EPYC 7542 EPYC 7702 EPYC 7402P EPYC 7532 EPYC 7502P EPYC 7552 EPYC 7662 EPYC 7302P EPYC 7642 EPYC 7272 EPYC 7282 EPYC 7232P 2 4 6 8 10 Min: 3.39 / Avg: 3.41 / Max: 3.42 Min: 3.35 / Avg: 3.36 / Max: 3.4 Min: 2.99 / Avg: 3 / Max: 3.02 Min: 2.95 / Avg: 2.97 / Max: 2.98 Min: 2.96 / Avg: 2.97 / Max: 2.97 Min: 2.93 / Avg: 2.94 / Max: 2.94 Min: 2.92 / Avg: 2.93 / Max: 2.94 Min: 2.92 / Avg: 2.93 / Max: 2.94 Min: 2.91 / Avg: 2.93 / Max: 2.94 Min: 2.92 / Avg: 2.93 / Max: 2.94 Min: 2.88 / Avg: 2.89 / Max: 2.9 Min: 2.85 / Avg: 2.86 / Max: 2.87 Min: 2.82 / Avg: 2.84 / Max: 2.85 Min: 2.81 / Avg: 2.82 / Max: 2.83
Result
OpenBenchmarking.org Frames Per Second, More Is Better rav1e 0.4 Speed: 6 EPYC 7F32 EPYC 7F52 EPYC 7542 EPYC 7402P EPYC 7702 EPYC 7502P EPYC 7532 EPYC 7662 EPYC 7552 EPYC 7302P EPYC 7642 EPYC 7272 EPYC 7282 EPYC 7232P 0.3499 0.6998 1.0497 1.3996 1.7495 SE +/- 0.001, N = 3 SE +/- 0.001, N = 3 SE +/- 0.002, N = 3 SE +/- 0.001, N = 3 SE +/- 0.001, N = 3 SE +/- 0.002, N = 3 SE +/- 0.000, N = 3 SE +/- 0.001, N = 3 SE +/- 0.001, N = 3 SE +/- 0.000, N = 3 SE +/- 0.003, N = 3 SE +/- 0.002, N = 3 SE +/- 0.002, N = 3 SE +/- 0.001, N = 3 1.555 1.542 1.368 1.351 1.342 1.338 1.336 1.333 1.331 1.329 1.320 1.296 1.293 1.289
Frames Per Second Per Watt
OpenBenchmarking.org Frames Per Second Per Watt, More Is Better rav1e 0.4 Speed: 6 EPYC 7282 EPYC 7272 EPYC 7232P EPYC 7642 EPYC 7532 EPYC 7F32 EPYC 7542 EPYC 7F52 EPYC 7502P EPYC 7662 EPYC 7552 EPYC 7302P EPYC 7402P EPYC 7702 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 7F32 EPYC 7F52 EPYC 7542 EPYC 7402P EPYC 7702 EPYC 7502P EPYC 7532 EPYC 7662 EPYC 7552 EPYC 7302P EPYC 7642 EPYC 7272 EPYC 7282 EPYC 7232P 2 4 6 8 10 Min: 1.55 / Avg: 1.55 / Max: 1.56 Min: 1.54 / Avg: 1.54 / Max: 1.54 Min: 1.36 / Avg: 1.37 / Max: 1.37 Min: 1.35 / Avg: 1.35 / Max: 1.35 Min: 1.34 / Avg: 1.34 / Max: 1.34 Min: 1.33 / Avg: 1.34 / Max: 1.34 Min: 1.34 / Avg: 1.34 / Max: 1.34 Min: 1.33 / Avg: 1.33 / Max: 1.34 Min: 1.33 / Avg: 1.33 / Max: 1.33 Min: 1.33 / Avg: 1.33 / Max: 1.33 Min: 1.32 / Avg: 1.32 / Max: 1.32 Min: 1.29 / Avg: 1.3 / Max: 1.3 Min: 1.29 / Avg: 1.29 / Max: 1.3 Min: 1.29 / Avg: 1.29 / Max: 1.29
Result
OpenBenchmarking.org Frames Per Second, More Is Better rav1e 0.4 Speed: 5 EPYC 7F32 EPYC 7F52 EPYC 7542 EPYC 7402P EPYC 7502P EPYC 7702 EPYC 7532 EPYC 7302P EPYC 7662 EPYC 7552 EPYC 7642 EPYC 7272 EPYC 7282 EPYC 7232P 0.2619 0.5238 0.7857 1.0476 1.3095 SE +/- 0.001, 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 SE +/- 0.001, N = 3 SE +/- 0.001, N = 3 SE +/- 0.003, N = 3 SE +/- 0.001, N = 3 SE +/- 0.001, N = 3 SE +/- 0.000, N = 3 SE +/- 0.001, N = 3 1.164 1.156 1.024 1.009 1.006 1.005 0.999 0.997 0.993 0.992 0.989 0.972 0.969 0.965
Frames Per Second Per Watt
OpenBenchmarking.org Frames Per Second Per Watt, More Is Better rav1e 0.4 Speed: 5 EPYC 7F32 EPYC 7282 EPYC 7542 EPYC 7502P EPYC 7272 EPYC 7552 EPYC 7232P EPYC 7302P EPYC 7402P EPYC 7642 EPYC 7532 EPYC 7F52 EPYC 7662 EPYC 7702 0.0045 0.009 0.0135 0.018 0.0225 0.02 0.02 0.02 0.02 0.02 0.02 0.02 0.02 0.02 0.01 0.01 0.01 0.01 0.01
Result Confidence
OpenBenchmarking.org Frames Per Second, More Is Better rav1e 0.4 Speed: 5 EPYC 7F32 EPYC 7F52 EPYC 7542 EPYC 7402P EPYC 7502P EPYC 7702 EPYC 7532 EPYC 7302P EPYC 7662 EPYC 7552 EPYC 7642 EPYC 7272 EPYC 7282 EPYC 7232P 2 4 6 8 10 Min: 1.16 / Avg: 1.16 / Max: 1.17 Min: 1.15 / Avg: 1.16 / Max: 1.16 Min: 1.02 / Avg: 1.02 / Max: 1.03 Min: 1.01 / Avg: 1.01 / Max: 1.01 Min: 1 / Avg: 1.01 / Max: 1.01 Min: 1 / Avg: 1.01 / Max: 1.01 Min: 1 / Avg: 1 / Max: 1 Min: 0.99 / Avg: 1 / Max: 1 Min: 0.99 / Avg: 0.99 / Max: 0.99 Min: 0.99 / Avg: 0.99 / Max: 1 Min: 0.99 / Avg: 0.99 / Max: 0.99 Min: 0.97 / Avg: 0.97 / Max: 0.97 Min: 0.97 / Avg: 0.97 / Max: 0.97 Min: 0.96 / Avg: 0.96 / Max: 0.97
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 7F32 EPYC 7F52 EPYC 7542 EPYC 7702 EPYC 7502P EPYC 7402P EPYC 7302P EPYC 7532 EPYC 7552 EPYC 7662 EPYC 7642 EPYC 7232P EPYC 7272 EPYC 7282 70 140 210 280 350 SE +/- 0.04, N = 3 SE +/- 0.17, N = 3 SE +/- 0.11, N = 3 SE +/- 0.01, N = 3 SE +/- 0.11, N = 3 SE +/- 0.11, N = 3 SE +/- 0.12, N = 3 SE +/- 0.11, N = 3 SE +/- 0.10, N = 3 SE +/- 0.18, N = 3 SE +/- 0.93, N = 3 SE +/- 0.14, N = 3 SE +/- 0.17, N = 3 SE +/- 0.25, N = 3 343.61 342.93 302.93 298.73 298.71 298.49 294.44 294.27 293.88 293.81 292.60 286.19 286.18 285.25 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 7F32 EPYC 7542 EPYC 7402P EPYC 7502P EPYC 7302P EPYC 7552 EPYC 7F52 EPYC 7642 EPYC 7662 EPYC 7702 EPYC 7532 2 4 6 8 10 7.09 7.01 6.83 6.50 6.26 6.18 6.13 5.98 5.14 4.76 4.52 4.31 4.29 4.26
Result Confidence
OpenBenchmarking.org MiB/second, More Is Better Crypto++ 8.2 Test: Unkeyed Algorithms EPYC 7F32 EPYC 7F52 EPYC 7542 EPYC 7702 EPYC 7502P EPYC 7402P EPYC 7302P EPYC 7532 EPYC 7552 EPYC 7662 EPYC 7642 EPYC 7232P EPYC 7272 EPYC 7282 60 120 180 240 300 Min: 343.56 / Avg: 343.61 / Max: 343.68 Min: 342.6 / Avg: 342.93 / Max: 343.11 Min: 302.75 / Avg: 302.93 / Max: 303.14 Min: 298.7 / Avg: 298.73 / Max: 298.75 Min: 298.57 / Avg: 298.71 / Max: 298.93 Min: 298.33 / Avg: 298.49 / Max: 298.7 Min: 294.21 / Avg: 294.44 / Max: 294.59 Min: 294.13 / Avg: 294.27 / Max: 294.49 Min: 293.7 / Avg: 293.88 / Max: 294.04 Min: 293.61 / Avg: 293.81 / Max: 294.16 Min: 290.74 / Avg: 292.6 / Max: 293.53 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 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 7F32 EPYC 7F52 EPYC 7542 EPYC 7502P EPYC 7402P EPYC 7702 EPYC 7642 EPYC 7532 EPYC 7662 EPYC 7552 EPYC 7302P EPYC 7282 EPYC 7272 EPYC 7232P 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 0.53 0.53 0.46 0.46 0.46 0.46 0.45 0.45 0.45 0.45 0.45 0.44 0.44 0.44 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 7642 EPYC 7532 EPYC 7F32 EPYC 7282 EPYC 7542 EPYC 7F52 EPYC 7502P EPYC 7662 EPYC 7272 EPYC 7552 EPYC 7232P EPYC 7302P EPYC 7402P EPYC 7702 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 7F32 EPYC 7F52 EPYC 7542 EPYC 7502P EPYC 7402P EPYC 7702 EPYC 7642 EPYC 7532 EPYC 7662 EPYC 7552 EPYC 7302P EPYC 7282 EPYC 7272 EPYC 7232P 2 4 6 8 10 Min: 0.53 / Avg: 0.53 / Max: 0.53 Min: 0.53 / Avg: 0.53 / Max: 0.53 Min: 0.46 / Avg: 0.46 / Max: 0.46 Min: 0.46 / Avg: 0.46 / Max: 0.46 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: 0.45 / 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: 0.45 / Avg: 0.45 / Max: 0.45 Min: 0.44 / Avg: 0.44 / Max: 0.44 Min: 0.44 / Avg: 0.44 / Max: 0.44 Min: 0.43 / Avg: 0.44 / Max: 0.44 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 7F32 EPYC 7F52 EPYC 7542 EPYC 7502P EPYC 7302P EPYC 7402P EPYC 7532 EPYC 7642 EPYC 7552 EPYC 7662 EPYC 7282 EPYC 7702 EPYC 7272 EPYC 7232P 10 20 30 40 50 36.98 40.55 40.89 41.04 41.15 41.33 41.52 41.85 41.91 42.35 42.78 43.16 43.38 44.49
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 7F52 EPYC 7F32 EPYC 7542 EPYC 7502P EPYC 7402P EPYC 7702 EPYC 7302P EPYC 7532 EPYC 7642 EPYC 7662 EPYC 7552 EPYC 7282 EPYC 7272 EPYC 7232P 20 40 60 80 100 SE +/- 0.58, N = 3 SE +/- 0.07, N = 3 SE +/- 0.18, N = 3 SE +/- 0.50, N = 3 SE +/- 0.65, N = 3 SE +/- 0.46, N = 3 SE +/- 0.56, N = 3 SE +/- 0.36, N = 3 SE +/- 0.98, N = 3 SE +/- 0.11, N = 3 SE +/- 0.05, N = 3 SE +/- 0.58, N = 3 SE +/- 0.54, N = 3 SE +/- 1.23, N = 5 92.08 93.08 103.80 105.24 105.28 106.58 106.77 107.48 107.70 107.88 108.25 108.86 109.60 110.50 1. (CXX) g++ options: -O2 -lOpenCL
Result Confidence
OpenBenchmarking.org Seconds, Fewer Is Better Rodinia 3.1 Test: OpenMP HotSpot3D EPYC 7F52 EPYC 7F32 EPYC 7542 EPYC 7502P EPYC 7402P EPYC 7702 EPYC 7302P EPYC 7532 EPYC 7642 EPYC 7662 EPYC 7552 EPYC 7282 EPYC 7272 EPYC 7232P 20 40 60 80 100 Min: 91.23 / Avg: 92.08 / Max: 93.18 Min: 92.93 / Avg: 93.08 / Max: 93.17 Min: 103.43 / Avg: 103.8 / Max: 104 Min: 104.53 / Avg: 105.24 / Max: 106.2 Min: 104.57 / Avg: 105.28 / Max: 106.58 Min: 105.66 / Avg: 106.58 / Max: 107.16 Min: 106.14 / Avg: 106.77 / Max: 107.88 Min: 106.77 / Avg: 107.48 / Max: 107.96 Min: 105.86 / Avg: 107.7 / Max: 109.21 Min: 107.69 / Avg: 107.88 / Max: 108.06 Min: 108.18 / Avg: 108.25 / Max: 108.34 Min: 108.23 / Avg: 108.86 / Max: 110.01 Min: 108.57 / Avg: 109.6 / Max: 110.38 Min: 108.22 / Avg: 110.5 / Max: 115.08 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 7F32 EPYC 7282 EPYC 7542 EPYC 7232P EPYC 7502P EPYC 7272 EPYC 7402P EPYC 7F52 EPYC 7302P EPYC 7552 EPYC 7532 EPYC 7702 EPYC 7662 1000 2000 3000 4000 5000 SE +/- 35.92, N = 5 SE +/- 32.99, N = 5 SE +/- 12.58, N = 5 SE +/- 22.80, N = 5 SE +/- 28.80, N = 5 SE +/- 33.20, N = 5 SE +/- 9.28, N = 5 SE +/- 35.77, N = 5 SE +/- 20.03, N = 5 SE +/- 22.36, N = 5 SE +/- 15.90, N = 5 SE +/- 33.26, N = 5 SE +/- 25.14, N = 5 3724 3881 3886 3894 3912 3971 3993 4085 4138 4218 4303 4407 4457
Result Confidence
OpenBenchmarking.org msec, Fewer Is Better DaCapo Benchmark 9.12-MR1 Java Test: Tradebeans EPYC 7F32 EPYC 7282 EPYC 7542 EPYC 7232P EPYC 7502P EPYC 7272 EPYC 7402P EPYC 7F52 EPYC 7302P EPYC 7552 EPYC 7532 EPYC 7702 EPYC 7662 800 1600 2400 3200 4000 Min: 3653 / Avg: 3723.6 / Max: 3860 Min: 3765 / Avg: 3881.4 / Max: 3963 Min: 3845 / Avg: 3886.4 / Max: 3916 Min: 3832 / Avg: 3893.8 / Max: 3948 Min: 3827 / Avg: 3912.2 / Max: 3971 Min: 3886 / Avg: 3970.6 / Max: 4055 Min: 3975 / Avg: 3993.2 / Max: 4028 Min: 3969 / Avg: 4084.8 / Max: 4158 Min: 4074 / Avg: 4138.2 / Max: 4180 Min: 4158 / Avg: 4217.6 / Max: 4273 Min: 4246 / Avg: 4302.6 / Max: 4341 Min: 4330 / Avg: 4406.6 / Max: 4494 Min: 4392 / Avg: 4456.8 / Max: 4536
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 7F52 EPYC 7F32 EPYC 7542 EPYC 7702 EPYC 7532 EPYC 7402P EPYC 7552 EPYC 7302P EPYC 7642 EPYC 7232P EPYC 7502P EPYC 7662 EPYC 7282 EPYC 7272 400K 800K 1200K 1600K 2000K SE +/- 17849.12, N = 5 SE +/- 19118.80, N = 4 SE +/- 13573.21, N = 15 SE +/- 18256.32, N = 3 SE +/- 21214.43, N = 3 SE +/- 13170.58, N = 15 SE +/- 8071.25, N = 3 SE +/- 13583.32, N = 6 SE +/- 11135.64, N = 15 SE +/- 18495.33, N = 15 SE +/- 18437.40, N = 3 SE +/- 13883.40, N = 3 SE +/- 14367.89, N = 15 SE +/- 12289.67, N = 3 1635794.57 1601070.50 1508082.41 1482738.92 1481804.00 1466557.03 1450496.71 1438157.73 1437534.23 1421564.35 1419600.13 1417246.67 1414840.41 1372468.88 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 7402P EPYC 7542 EPYC 7F32 EPYC 7302P EPYC 7502P EPYC 7552 EPYC 7F52 EPYC 7702 EPYC 7532 EPYC 7642 EPYC 7662 9K 18K 27K 36K 45K 42939.75 40587.49 39449.14 39042.93 38176.82 37914.84 36649.44 35995.93 31741.99 29783.14 27989.20 27229.69 27083.65 25840.00
Result Confidence
OpenBenchmarking.org Requests Per Second, More Is Better Redis 6.0.9 Test: GET EPYC 7F52 EPYC 7F32 EPYC 7542 EPYC 7702 EPYC 7532 EPYC 7402P EPYC 7552 EPYC 7302P EPYC 7642 EPYC 7232P EPYC 7502P EPYC 7662 EPYC 7282 EPYC 7272 300K 600K 900K 1200K 1500K Min: 1586048 / Avg: 1635794.57 / Max: 1671133.62 Min: 1561051.5 / Avg: 1601070.5 / Max: 1650709.75 Min: 1433897.38 / Avg: 1508082.41 / Max: 1604899.38 Min: 1456664.25 / Avg: 1482738.92 / Max: 1517911.38 Min: 1456461.38 / Avg: 1481804 / Max: 1523945.12 Min: 1388893.38 / Avg: 1466557.03 / Max: 1567157.5 Min: 1439056 / Avg: 1450496.71 / Max: 1466079.5 Min: 1387351.75 / Avg: 1438157.73 / Max: 1487252.88 Min: 1363529.88 / Avg: 1437534.23 / Max: 1507163.75 Min: 1340662.25 / Avg: 1421564.35 / Max: 1628409.75 Min: 1387942.88 / Avg: 1419600.13 / Max: 1451804.88 Min: 1397042.75 / Avg: 1417246.67 / Max: 1443844 Min: 1349900.62 / Avg: 1414840.41 / Max: 1535877.12 Min: 1350621.38 / Avg: 1372468.88 / Max: 1393145.75 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 7702 EPYC 7552 EPYC 7F32 EPYC 7542 EPYC 7662 EPYC 7F52 EPYC 7502P EPYC 7402P EPYC 7282 EPYC 7302P EPYC 7532 EPYC 7272 EPYC 7232P 4K 8K 12K 16K 20K SE +/- 217.98, N = 3 SE +/- 217.68, N = 3 SE +/- 28.30, N = 3 SE +/- 39.21, N = 3 SE +/- 52.61, N = 3 SE +/- 39.37, N = 3 SE +/- 13.93, N = 3 SE +/- 46.42, N = 3 SE +/- 18.80, N = 3 SE +/- 20.90, N = 3 SE +/- 27.08, N = 3 SE +/- 37.39, N = 3 SE +/- 21.61, N = 3 17329.8 16494.4 16357.2 15872.0 15640.1 15585.7 15097.1 14961.4 14921.3 14820.3 14786.9 14776.4 14571.7 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 7272 EPYC 7282 EPYC 7232P EPYC 7542 EPYC 7502P EPYC 7F32 EPYC 7402P EPYC 7302P EPYC 7552 EPYC 7702 EPYC 7662 EPYC 7F52 EPYC 7532 70 140 210 280 350 334.79 333.88 332.00 303.95 289.31 286.11 284.81 279.72 268.71 236.78 215.62 209.76 202.28
Result Confidence
OpenBenchmarking.org MB/s, More Is Better Tinymembench 2018-05-28 Standard Memset EPYC 7702 EPYC 7552 EPYC 7F32 EPYC 7542 EPYC 7662 EPYC 7F52 EPYC 7502P EPYC 7402P EPYC 7282 EPYC 7302P EPYC 7532 EPYC 7272 EPYC 7232P 3K 6K 9K 12K 15K Min: 16900.6 / Avg: 17329.83 / Max: 17610.5 Min: 16092.5 / Avg: 16494.43 / Max: 16840.3 Min: 16301.7 / Avg: 16357.2 / Max: 16394.6 Min: 15794.6 / Avg: 15872.03 / Max: 15921.5 Min: 15534.9 / Avg: 15640.1 / Max: 15694.5 Min: 15512.6 / Avg: 15585.7 / Max: 15647.6 Min: 15074.8 / Avg: 15097.07 / Max: 15122.7 Min: 14876.5 / Avg: 14961.37 / Max: 15036.4 Min: 14884.6 / Avg: 14921.27 / Max: 14946.8 Min: 14781.5 / Avg: 14820.27 / Max: 14853.2 Min: 14734.2 / Avg: 14786.93 / Max: 14824 Min: 14704.8 / Avg: 14776.4 / Max: 14830.9 Min: 14546.4 / Avg: 14571.7 / Max: 14614.7 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 7F32 EPYC 7F52 EPYC 7702 EPYC 7542 EPYC 7502P EPYC 7402P EPYC 7662 EPYC 7302P EPYC 7552 EPYC 7272 EPYC 7282 EPYC 7532 EPYC 7232P 9 18 27 36 45 SE +/- 0.01, N = 3 SE +/- 0.03, N = 3 SE +/- 0.09, N = 3 SE +/- 0.05, N = 3 SE +/- 0.09, N = 3 SE +/- 0.07, N = 3 SE +/- 0.17, N = 3 SE +/- 0.02, N = 3 SE +/- 0.23, N = 3 SE +/- 0.05, N = 3 SE +/- 0.10, N = 3 SE +/- 0.07, N = 3 SE +/- 0.02, N = 3 38.59 38.01 34.50 34.38 34.11 34.03 34.01 33.71 33.64 33.12 33.08 33.06 32.48 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 7272 EPYC 7232P EPYC 7282 EPYC 7542 EPYC 7502P EPYC 7302P EPYC 7402P EPYC 7F32 EPYC 7552 EPYC 7532 EPYC 7662 EPYC 7F52 EPYC 7702 0.1395 0.279 0.4185 0.558 0.6975 0.62 0.62 0.61 0.55 0.55 0.55 0.55 0.53 0.47 0.41 0.41 0.40 0.40
Result Confidence
OpenBenchmarking.org Mpix/sec, More Is Better LibRaw 0.20 Post-Processing Benchmark EPYC 7F32 EPYC 7F52 EPYC 7702 EPYC 7542 EPYC 7502P EPYC 7402P EPYC 7662 EPYC 7302P EPYC 7552 EPYC 7272 EPYC 7282 EPYC 7532 EPYC 7232P 8 16 24 32 40 Min: 38.57 / Avg: 38.59 / Max: 38.62 Min: 37.96 / Avg: 38.01 / Max: 38.06 Min: 34.32 / Avg: 34.5 / Max: 34.63 Min: 34.31 / Avg: 34.38 / Max: 34.48 Min: 33.96 / Avg: 34.11 / Max: 34.27 Min: 33.89 / Avg: 34.03 / Max: 34.12 Min: 33.71 / Avg: 34.01 / Max: 34.31 Min: 33.67 / Avg: 33.71 / Max: 33.74 Min: 33.2 / Avg: 33.64 / Max: 34 Min: 33.04 / Avg: 33.12 / Max: 33.21 Min: 32.96 / Avg: 33.08 / Max: 33.27 Min: 32.93 / Avg: 33.06 / Max: 33.13 Min: 32.44 / Avg: 32.48 / Max: 32.51 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 7542 EPYC 7402P EPYC 7502P EPYC 7302P EPYC 7532 EPYC 7282 EPYC 7552 EPYC 7642 EPYC 7F32 EPYC 7272 EPYC 7F52 EPYC 7662 EPYC 7232P EPYC 7702 60 120 180 240 300 SE +/- 0.67, N = 3 SE +/- 0.17, N = 3 SE +/- 0.88, N = 3 SE +/- 0.29, N = 3 SE +/- 0.17, N = 3 SE +/- 0.33, N = 3 SE +/- 0.50, N = 3 SE +/- 1.01, N = 3 SE +/- 1.00, N = 3 SE +/- 0.29, N = 3 SE +/- 0.93, N = 3 SE +/- 0.60, N = 3 SE +/- 1.30, N = 3 285 280 277 277 271 267 264 263 262 259 248 243 243 240 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 7282 EPYC 7272 EPYC 7302P EPYC 7402P EPYC 7542 EPYC 7F32 EPYC 7502P EPYC 7552 EPYC 7532 EPYC 7642 EPYC 7F52 EPYC 7662 EPYC 7702 0.7695 1.539 2.3085 3.078 3.8475 3.42 3.28 3.26 2.95 2.60 2.57 2.55 2.49 2.01 1.98 1.75 1.71 1.58 1.55
Result Confidence
OpenBenchmarking.org Inferences Per Minute, More Is Better ONNX Runtime 1.6 Model: yolov4 - Device: OpenMP CPU EPYC 7542 EPYC 7402P EPYC 7502P EPYC 7302P EPYC 7532 EPYC 7282 EPYC 7552 EPYC 7642 EPYC 7F32 EPYC 7272 EPYC 7F52 EPYC 7662 EPYC 7232P EPYC 7702 50 100 150 200 250 Min: 284.5 / Avg: 285.17 / Max: 286.5 Min: 279.5 / Avg: 279.67 / Max: 280 Min: 275.5 / Avg: 276.83 / Max: 278.5 Min: 276.5 / Avg: 277 / Max: 277.5 Min: 270.5 / Avg: 270.67 / Max: 271 Min: 266.5 / Avg: 267.17 / Max: 267.5 Min: 263 / Avg: 263.5 / Max: 264.5 Min: 261 / Avg: 262.83 / Max: 264.5 Min: 260 / Avg: 262 / Max: 263 Min: 258.5 / Avg: 259 / Max: 259.5 Min: 242 / Avg: 243.17 / Max: 245 Min: 242.5 / Avg: 243.33 / Max: 244.5 Min: 238 / Avg: 240.33 / Max: 242.5 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 7F52 EPYC 7F32 EPYC 7702 EPYC 7662 EPYC 7542 EPYC 7532 EPYC 7642 EPYC 7502P EPYC 7302P EPYC 7552 EPYC 7272 EPYC 7402P EPYC 7282 EPYC 7232P 300K 600K 900K 1200K 1500K SE +/- 8091.69, N = 3 SE +/- 13442.74, N = 3 SE +/- 22602.36, N = 12 SE +/- 18435.82, N = 15 SE +/- 15275.38, N = 3 SE +/- 15826.22, N = 15 SE +/- 16083.41, N = 14 SE +/- 14615.10, N = 4 SE +/- 12613.83, N = 5 SE +/- 14106.76, N = 3 SE +/- 17229.52, N = 15 SE +/- 4313.29, N = 3 SE +/- 15930.17, N = 3 SE +/- 11537.36, N = 4 1336546.21 1315900.46 1228831.79 1200527.31 1189270.87 1186674.32 1183717.45 1180459.91 1173570.00 1170719.46 1156241.74 1147451.38 1143594.63 1126925.50 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 7272 EPYC 7232P EPYC 7282 EPYC 7F32 EPYC 7402P EPYC 7542 EPYC 7302P EPYC 7502P EPYC 7552 EPYC 7F52 EPYC 7702 EPYC 7642 EPYC 7662 EPYC 7532 7K 14K 21K 28K 35K 33520.26 33238.20 31275.55 30367.37 29418.44 29411.07 29192.78 29043.85 24980.53 23705.79 22530.98 21774.45 21301.37 21182.66
Result Confidence
OpenBenchmarking.org Requests Per Second, More Is Better Redis 6.0.9 Test: SET EPYC 7F52 EPYC 7F32 EPYC 7702 EPYC 7662 EPYC 7542 EPYC 7532 EPYC 7642 EPYC 7502P EPYC 7302P EPYC 7552 EPYC 7272 EPYC 7402P EPYC 7282 EPYC 7232P 200K 400K 600K 800K 1000K Min: 1320510.25 / Avg: 1336546.21 / Max: 1346451.62 Min: 1289503 / Avg: 1315900.46 / Max: 1333515.38 Min: 1142730.12 / Avg: 1228831.79 / Max: 1378956.5 Min: 1107542.38 / Avg: 1200527.31 / Max: 1349007.38 Min: 1161717.5 / Avg: 1189270.87 / Max: 1214476.5 Min: 1117600.38 / Avg: 1186674.32 / Max: 1295341 Min: 1125387.38 / Avg: 1183717.45 / Max: 1363145 Min: 1147582.38 / Avg: 1180459.91 / Max: 1209351.5 Min: 1141950.88 / Avg: 1173570 / Max: 1208467 Min: 1151024 / Avg: 1170719.46 / Max: 1198062 Min: 1088613.12 / Avg: 1156241.74 / Max: 1310666.25 Min: 1143020.75 / Avg: 1147451.38 / Max: 1156076.88 Min: 1112121 / Avg: 1143594.63 / Max: 1163617.38 Min: 1105957.12 / Avg: 1126925.5 / Max: 1159285.88 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 7F32 EPYC 7F52 EPYC 7542 EPYC 7532 EPYC 7402P EPYC 7502P EPYC 7662 EPYC 7272 EPYC 7702 EPYC 7302P EPYC 7642 EPYC 7552 EPYC 7282 EPYC 7232P 300K 600K 900K 1200K 1500K SE +/- 6374.74, N = 3 SE +/- 8000.25, N = 3 SE +/- 11205.82, N = 5 SE +/- 10288.34, N = 15 SE +/- 11072.90, N = 15 SE +/- 9569.43, N = 3 SE +/- 5890.12, N = 3 SE +/- 15424.51, N = 15 SE +/- 7054.62, N = 13 SE +/- 8436.86, N = 3 SE +/- 4227.00, N = 3 SE +/- 7701.66, N = 3 SE +/- 3774.33, N = 3 SE +/- 6585.32, N = 3 1174520.46 1174427.00 1067438.77 1059976.32 1045821.59 1045486.81 1039389.17 1037523.56 1031876.33 1030785.79 1018402.69 1013049.13 997652.46 991962.08 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 7272 EPYC 7232P EPYC 7282 EPYC 7F32 EPYC 7402P EPYC 7542 EPYC 7502P EPYC 7302P EPYC 7552 EPYC 7F52 EPYC 7532 EPYC 7642 EPYC 7662 EPYC 7702 6K 12K 18K 24K 30K 29596.02 28993.77 27079.37 26954.89 26554.24 26166.33 25519.76 25453.57 21454.67 20551.40 18680.49 18554.91 18391.09 18361.54
Result Confidence
OpenBenchmarking.org Requests Per Second, More Is Better Redis 6.0.9 Test: LPUSH EPYC 7F32 EPYC 7F52 EPYC 7542 EPYC 7532 EPYC 7402P EPYC 7502P EPYC 7662 EPYC 7272 EPYC 7702 EPYC 7302P EPYC 7642 EPYC 7552 EPYC 7282 EPYC 7232P 200K 400K 600K 800K 1000K Min: 1167284.62 / Avg: 1174520.46 / Max: 1187229.25 Min: 1165101.25 / Avg: 1174427 / Max: 1190349.75 Min: 1044932.12 / Avg: 1067438.77 / Max: 1106467.75 Min: 1006359.25 / Avg: 1059976.32 / Max: 1149564.75 Min: 987478.25 / Avg: 1045821.59 / Max: 1105957.12 Min: 1029134.12 / Avg: 1045486.81 / Max: 1062275 Min: 1027854.88 / Avg: 1039389.17 / Max: 1047230.12 Min: 976187.38 / Avg: 1037523.56 / Max: 1152915 Min: 1004120.12 / Avg: 1031876.33 / Max: 1093254.62 Min: 1014202.06 / Avg: 1030785.79 / Max: 1041775.19 Min: 1013376.56 / Avg: 1018402.69 / Max: 1026802.69 Min: 1004120.12 / Avg: 1013049.13 / Max: 1028383.38 Min: 990504 / Avg: 997652.46 / Max: 1003327 Min: 978965.06 / Avg: 991962.08 / Max: 1000306.5 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 7F52 EPYC 7F32 EPYC 7402P EPYC 7542 EPYC 7502P EPYC 7642 EPYC 7552 EPYC 7702 EPYC 7302P EPYC 7662 EPYC 7282 EPYC 7532 EPYC 7232P EPYC 7272 300K 600K 900K 1200K 1500K SE +/- 8827.27, N = 3 SE +/- 11422.05, N = 10 SE +/- 20897.40, N = 15 SE +/- 17960.88, N = 3 SE +/- 16125.60, N = 15 SE +/- 16607.14, N = 15 SE +/- 17355.22, N = 15 SE +/- 13671.93, N = 15 SE +/- 8695.76, N = 3 SE +/- 12423.96, N = 3 SE +/- 16958.48, N = 15 SE +/- 3475.48, N = 3 SE +/- 8933.33, N = 3 SE +/- 13873.03, N = 3 1514902.30 1510395.93 1393300.08 1388206.16 1387616.13 1360852.66 1349388.24 1347163.14 1345235.04 1328786.50 1325778.66 1319402.58 1302498.71 1285763.37 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 7402P EPYC 7F32 EPYC 7542 EPYC 7502P EPYC 7302P EPYC 7552 EPYC 7F52 EPYC 7642 EPYC 7702 EPYC 7662 EPYC 7532 8K 16K 24K 32K 40K 39084.39 37338.23 36856.97 36325.60 35697.64 34766.37 34715.91 34516.59 29367.10 27216.48 25475.97 25016.28 24141.05 23687.13
Result Confidence
OpenBenchmarking.org Requests Per Second, More Is Better Redis 6.0.9 Test: SADD EPYC 7F52 EPYC 7F32 EPYC 7402P EPYC 7542 EPYC 7502P EPYC 7642 EPYC 7552 EPYC 7702 EPYC 7302P EPYC 7662 EPYC 7282 EPYC 7532 EPYC 7232P EPYC 7272 300K 600K 900K 1200K 1500K Min: 1500849.5 / Avg: 1514902.33 / Max: 1531183.5 Min: 1461584.38 / Avg: 1510395.93 / Max: 1591637.12 Min: 1309088.62 / Avg: 1393300.08 / Max: 1560067.38 Min: 1357040.62 / Avg: 1388206.16 / Max: 1419258.62 Min: 1293828.38 / Avg: 1387616.13 / Max: 1488321.5 Min: 1297029.25 / Avg: 1360852.66 / Max: 1498136.88 Min: 1255650.38 / Avg: 1349388.24 / Max: 1542049.62 Min: 1270656.12 / Avg: 1347163.14 / Max: 1487873.75 Min: 1327844.88 / Avg: 1345235.04 / Max: 1354117.75 Min: 1314595.5 / Avg: 1328786.5 / Max: 1353546.25 Min: 1238091.38 / Avg: 1325778.66 / Max: 1481061.62 Min: 1313197.62 / Avg: 1319402.58 / Max: 1325218.12 Min: 1285520.5 / Avg: 1302498.71 / Max: 1315806.38 Min: 1260088.75 / Avg: 1285763.37 / Max: 1307710.75 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 7F52 EPYC 7542 EPYC 7F32 EPYC 7402P EPYC 7502P EPYC 7552 EPYC 7532 EPYC 7702 EPYC 7302P EPYC 7662 EPYC 7282 EPYC 7272 EPYC 7232P 13 26 39 52 65 SE +/- 0.24, N = 3 SE +/- 0.30, N = 3 SE +/- 0.33, N = 3 SE +/- 0.41, N = 3 SE +/- 0.42, N = 3 SE +/- 0.28, N = 3 SE +/- 0.36, N = 3 SE +/- 0.32, N = 3 SE +/- 0.45, N = 3 SE +/- 0.23, N = 3 SE +/- 0.50, N = 3 SE +/- 0.07, N = 3 SE +/- 0.80, N = 3 50.59 52.99 52.99 53.36 53.72 55.42 55.57 55.68 55.77 55.95 56.10 57.24 59.31
Result Confidence
OpenBenchmarking.org Seconds, Fewer Is Better Hugin Panorama Photo Assistant + Stitching Time EPYC 7F52 EPYC 7542 EPYC 7F32 EPYC 7402P EPYC 7502P EPYC 7552 EPYC 7532 EPYC 7702 EPYC 7302P EPYC 7662 EPYC 7282 EPYC 7272 EPYC 7232P 12 24 36 48 60 Min: 50.13 / Avg: 50.59 / Max: 50.91 Min: 52.43 / Avg: 52.99 / Max: 53.44 Min: 52.38 / Avg: 52.99 / Max: 53.51 Min: 52.68 / Avg: 53.36 / Max: 54.09 Min: 52.98 / Avg: 53.72 / Max: 54.43 Min: 54.86 / Avg: 55.42 / Max: 55.71 Min: 55.11 / Avg: 55.57 / Max: 56.28 Min: 55.04 / Avg: 55.68 / Max: 56.12 Min: 54.93 / Avg: 55.77 / Max: 56.46 Min: 55.51 / Avg: 55.95 / Max: 56.27 Min: 55.21 / Avg: 56.1 / Max: 56.93 Min: 57.12 / Avg: 57.24 / Max: 57.34 Min: 57.78 / Avg: 59.31 / Max: 60.47
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 7F52 EPYC 7F32 EPYC 7542 EPYC 7282 EPYC 7272 EPYC 7402P EPYC 7502P EPYC 7302P EPYC 7532 EPYC 7232P EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 90K 180K 270K 360K 450K SE +/- 428.23, N = 3 SE +/- 183.84, N = 3 SE +/- 3270.77, N = 3 SE +/- 1079.81, N = 3 SE +/- 1365.59, N = 3 SE +/- 3460.73, N = 3 SE +/- 430.27, N = 3 SE +/- 639.41, N = 3 SE +/- 2791.26, N = 3 SE +/- 533.37, N = 3 SE +/- 5135.26, N = 3 SE +/- 4280.31, N = 3 SE +/- 4382.81, N = 3 SE +/- 4507.61, N = 3 433091.73 424600.07 422944.46 420324.96 418080.47 415583.96 413354.59 405905.78 404313.15 399110.88 394639.23 386824.54 376241.11 371448.21 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 7542 EPYC 7402P EPYC 7502P EPYC 7F32 EPYC 7552 EPYC 7532 EPYC 7642 EPYC 7F52 EPYC 7662 EPYC 7702 1600 3200 4800 6400 8000 7415.88 7232.18 7158.88 6206.07 6102.85 5903.16 5856.34 5640.60 4838.07 4517.76 4228.11 4143.95 4095.78 3833.65
Result Confidence
OpenBenchmarking.org Ops/sec, More Is Better KeyDB 6.0.16 EPYC 7F52 EPYC 7F32 EPYC 7542 EPYC 7282 EPYC 7272 EPYC 7402P EPYC 7502P EPYC 7302P EPYC 7532 EPYC 7232P EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 80K 160K 240K 320K 400K Min: 432304.57 / Avg: 433091.73 / Max: 433777.59 Min: 424252.48 / Avg: 424600.07 / Max: 424877.7 Min: 416505.35 / Avg: 422944.46 / Max: 427162.66 Min: 419061.55 / Avg: 420324.96 / Max: 422473.5 Min: 416043.78 / Avg: 418080.47 / Max: 420674.69 Min: 412054.17 / Avg: 415583.96 / Max: 422504.97 Min: 412498.94 / Avg: 413354.59 / Max: 413861.79 Min: 404993.42 / Avg: 405905.78 / Max: 407138 Min: 399536.5 / Avg: 404313.15 / Max: 409203.69 Min: 398044.81 / Avg: 399110.88 / Max: 399676.81 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 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 7F52 EPYC 7F32 EPYC 7542 EPYC 7502P EPYC 7662 EPYC 7642 EPYC 7532 EPYC 7402P EPYC 7552 EPYC 7302P EPYC 7282 EPYC 7702 EPYC 7272 EPYC 7232P 1.3478 2.6956 4.0434 5.3912 6.739 SE +/- 0.05, 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 +/- 0.02, N = 3 SE +/- 0.03, N = 3 SE +/- 0.01, N = 3 SE +/- 0.01, N = 3 SE +/- 0.01, N = 3 SE +/- 0.01, N = 3 SE +/- 0.04, N = 3 SE +/- 0.02, N = 3 5.99 5.96 5.84 5.76 5.76 5.72 5.71 5.68 5.67 5.67 5.57 5.56 5.53 5.17
FPS Per Watt
OpenBenchmarking.org FPS Per Watt, More Is Better PlaidML FP16: No - Mode: Inference - Network: ResNet 50 - Device: CPU EPYC 7282 EPYC 7272 EPYC 7542 EPYC 7232P EPYC 7F32 EPYC 7502P EPYC 7302P EPYC 7402P EPYC 7552 EPYC 7642 EPYC 7532 EPYC 7F52 EPYC 7662 EPYC 7702 0.0248 0.0496 0.0744 0.0992 0.124 0.11 0.11 0.10 0.10 0.09 0.09 0.09 0.09 0.08 0.07 0.07 0.07 0.07 0.06
Result Confidence
OpenBenchmarking.org FPS, More Is Better PlaidML FP16: No - Mode: Inference - Network: ResNet 50 - Device: CPU EPYC 7F52 EPYC 7F32 EPYC 7542 EPYC 7502P EPYC 7662 EPYC 7642 EPYC 7532 EPYC 7402P EPYC 7552 EPYC 7302P EPYC 7282 EPYC 7702 EPYC 7272 EPYC 7232P 2 4 6 8 10 Min: 5.9 / Avg: 5.99 / Max: 6.05 Min: 5.9 / Avg: 5.96 / Max: 6.02 Min: 5.82 / Avg: 5.84 / Max: 5.86 Min: 5.73 / Avg: 5.76 / Max: 5.78 Min: 5.73 / Avg: 5.76 / Max: 5.79 Min: 5.7 / Avg: 5.72 / Max: 5.73 Min: 5.68 / Avg: 5.71 / Max: 5.73 Min: 5.62 / Avg: 5.68 / Max: 5.72 Min: 5.64 / Avg: 5.67 / Max: 5.69 Min: 5.65 / Avg: 5.67 / Max: 5.68 Min: 5.55 / Avg: 5.57 / Max: 5.59 Min: 5.54 / Avg: 5.56 / Max: 5.58 Min: 5.46 / Avg: 5.53 / Max: 5.61 Min: 5.14 / Avg: 5.17 / Max: 5.2
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 7F52 EPYC 7F32 EPYC 7542 EPYC 7402P EPYC 7502P EPYC 7702 EPYC 7302P EPYC 7552 EPYC 7662 EPYC 7532 EPYC 7642 EPYC 7282 EPYC 7272 EPYC 7232P 8 16 24 32 40 SE +/- 0.03, N = 3 SE +/- 0.06, N = 3 SE +/- 0.06, N = 3 SE +/- 0.07, N = 3 SE +/- 0.34, N = 5 SE +/- 0.03, N = 3 SE +/- 0.11, N = 3 SE +/- 0.02, N = 3 SE +/- 0.00, N = 3 SE +/- 0.03, N = 3 SE +/- 0.03, N = 3 SE +/- 0.04, N = 3 SE +/- 0.03, N = 3 SE +/- 0.03, N = 3 35.56 35.48 33.51 32.99 32.86 32.78 32.62 32.60 32.54 32.35 32.31 32.03 31.63 31.08 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 7272 EPYC 7232P EPYC 7282 EPYC 7542 EPYC 7502P EPYC 7302P EPYC 7402P EPYC 7F32 EPYC 7552 EPYC 7532 EPYC 7642 EPYC 7662 EPYC 7F52 EPYC 7702 0.1508 0.3016 0.4524 0.6032 0.754 0.67 0.67 0.66 0.60 0.59 0.59 0.59 0.58 0.51 0.45 0.44 0.44 0.42 0.42
Result Confidence
OpenBenchmarking.org Frames Per Second, More Is Better AOM AV1 2.0 Encoder Mode: Speed 8 Realtime EPYC 7F52 EPYC 7F32 EPYC 7542 EPYC 7402P EPYC 7502P EPYC 7702 EPYC 7302P EPYC 7552 EPYC 7662 EPYC 7532 EPYC 7642 EPYC 7282 EPYC 7272 EPYC 7232P 8 16 24 32 40 Min: 35.51 / Avg: 35.56 / Max: 35.62 Min: 35.37 / Avg: 35.48 / Max: 35.54 Min: 33.4 / Avg: 33.51 / Max: 33.6 Min: 32.85 / Avg: 32.99 / Max: 33.06 Min: 31.51 / Avg: 32.86 / Max: 33.21 Min: 32.72 / Avg: 32.78 / Max: 32.82 Min: 32.42 / Avg: 32.62 / Max: 32.79 Min: 32.57 / Avg: 32.6 / Max: 32.62 Min: 32.54 / Avg: 32.54 / Max: 32.55 Min: 32.3 / Avg: 32.35 / Max: 32.38 Min: 32.25 / Avg: 32.31 / Max: 32.36 Min: 31.98 / Avg: 32.03 / Max: 32.11 Min: 31.58 / Avg: 31.63 / Max: 31.69 Min: 31.04 / Avg: 31.08 / Max: 31.13 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 7542 EPYC 7502P EPYC 7282 EPYC 7402P EPYC 7F52 EPYC 7552 EPYC 7662 EPYC 7F32 EPYC 7532 EPYC 7272 EPYC 7702 EPYC 7302P EPYC 7232P 70 140 210 280 350 SE +/- 0.63, N = 3 SE +/- 1.08, N = 3 SE +/- 0.25, N = 3 SE +/- 1.52, N = 3 SE +/- 0.12, N = 3 SE +/- 0.75, N = 3 SE +/- 1.82, N = 3 SE +/- 0.79, N = 3 SE +/- 0.79, N = 3 SE +/- 0.55, N = 3 SE +/- 1.60, N = 3 SE +/- 0.22, N = 3 SE +/- 0.07, N = 3 291.08 292.42 296.16 297.53 299.33 302.11 302.42 302.70 305.06 305.22 307.85 308.49 326.23
Result Confidence
OpenBenchmarking.org Seconds, Fewer Is Better WireGuard + Linux Networking Stack Stress Test EPYC 7542 EPYC 7502P EPYC 7282 EPYC 7402P EPYC 7F52 EPYC 7552 EPYC 7662 EPYC 7F32 EPYC 7532 EPYC 7272 EPYC 7702 EPYC 7302P EPYC 7232P 60 120 180 240 300 Min: 290.32 / Avg: 291.08 / Max: 292.34 Min: 291.12 / Avg: 292.42 / Max: 294.56 Min: 295.71 / Avg: 296.16 / Max: 296.59 Min: 295.48 / Avg: 297.53 / Max: 300.5 Min: 299.09 / Avg: 299.33 / Max: 299.49 Min: 301.02 / Avg: 302.11 / Max: 303.55 Min: 299.36 / Avg: 302.42 / Max: 305.67 Min: 301.87 / Avg: 302.7 / Max: 304.28 Min: 303.92 / Avg: 305.06 / Max: 306.58 Min: 304.14 / Avg: 305.22 / Max: 305.91 Min: 305.74 / Avg: 307.85 / Max: 310.98 Min: 308.17 / Avg: 308.49 / Max: 308.9 Min: 326.14 / Avg: 326.23 / Max: 326.37
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 7282 EPYC 7542 EPYC 7272 EPYC 7402P EPYC 7502P EPYC 7302P EPYC 7F32 EPYC 7232P EPYC 7532 EPYC 7F52 EPYC 7552 EPYC 7662 EPYC 7642 EPYC 7702 200 400 600 800 1000 736.22 739.71 748.54 749.67 755.01 763.80 775.67 783.24 783.25 785.07 788.52 789.56 792.74 817.66
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 7F32 EPYC 7702 EPYC 7642 EPYC 7662 EPYC 7552 EPYC 7532 EPYC 7F52 EPYC 7542 EPYC 7502P EPYC 7402P EPYC 7232P EPYC 7302P EPYC 7272 EPYC 7282 20 40 60 80 100 SE +/- 0.14, N = 3 SE +/- 0.28, N = 3 SE +/- 0.58, N = 3 SE +/- 0.10, N = 3 SE +/- 0.13, N = 3 SE +/- 0.09, N = 3 SE +/- 0.45, N = 3 SE +/- 0.14, N = 3 SE +/- 0.52, N = 3 SE +/- 0.20, N = 3 SE +/- 0.15, N = 3 SE +/- 0.22, N = 3 SE +/- 0.20, N = 3 SE +/- 0.07, N = 3 69.51 70.11 70.17 70.67 70.72 71.56 71.67 72.13 72.21 72.68 72.99 73.17 73.79 74.99
Result Confidence
OpenBenchmarking.org Seconds, Fewer Is Better DeepSpeech 0.6 Acceleration: CPU EPYC 7F32 EPYC 7702 EPYC 7642 EPYC 7662 EPYC 7552 EPYC 7532 EPYC 7F52 EPYC 7542 EPYC 7502P EPYC 7402P EPYC 7232P EPYC 7302P EPYC 7272 EPYC 7282 14 28 42 56 70 Min: 69.32 / Avg: 69.51 / Max: 69.77 Min: 69.57 / Avg: 70.11 / Max: 70.51 Min: 69.04 / Avg: 70.17 / Max: 70.95 Min: 70.52 / Avg: 70.67 / Max: 70.87 Min: 70.48 / Avg: 70.72 / Max: 70.91 Min: 71.46 / Avg: 71.56 / Max: 71.73 Min: 70.79 / Avg: 71.67 / Max: 72.23 Min: 71.89 / Avg: 72.13 / Max: 72.38 Min: 71.26 / Avg: 72.21 / Max: 73.03 Min: 72.4 / Avg: 72.68 / Max: 73.08 Min: 72.82 / Avg: 72.99 / Max: 73.3 Min: 72.74 / Avg: 73.17 / Max: 73.46 Min: 73.4 / Avg: 73.79 / Max: 74.01 Min: 74.85 / Avg: 74.99 / Max: 75.07
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 7702 EPYC 7552 EPYC 7F52 EPYC 7F32 EPYC 7542 EPYC 7402P EPYC 7502P EPYC 7662 EPYC 7282 EPYC 7302P EPYC 7532 EPYC 7272 EPYC 7232P 2K 4K 6K 8K 10K SE +/- 44.65, N = 3 SE +/- 35.12, N = 3 SE +/- 1.52, N = 3 SE +/- 2.03, N = 3 SE +/- 17.46, N = 3 SE +/- 19.03, N = 3 SE +/- 2.05, N = 3 SE +/- 14.82, N = 3 SE +/- 7.90, N = 3 SE +/- 2.29, N = 3 SE +/- 2.22, N = 3 SE +/- 22.30, N = 3 SE +/- 2.95, N = 3 9314.0 9087.1 9055.1 9025.4 8907.7 8902.8 8854.2 8852.0 8850.6 8842.7 8829.9 8825.7 8805.9 1. (CC) gcc options: -O2 -lm
Result Confidence
OpenBenchmarking.org MB/s, More Is Better Tinymembench 2018-05-28 Standard Memcpy EPYC 7702 EPYC 7552 EPYC 7F52 EPYC 7F32 EPYC 7542 EPYC 7402P EPYC 7502P EPYC 7662 EPYC 7282 EPYC 7302P EPYC 7532 EPYC 7272 EPYC 7232P 1600 3200 4800 6400 8000 Min: 9224.8 / Avg: 9313.97 / Max: 9362.9 Min: 9051.6 / Avg: 9087.07 / Max: 9157.3 Min: 9052.3 / Avg: 9055.13 / Max: 9057.5 Min: 9023.3 / Avg: 9025.43 / Max: 9029.5 Min: 8873.4 / Avg: 8907.73 / Max: 8930.4 Min: 8864.9 / Avg: 8902.83 / Max: 8924.5 Min: 8851 / Avg: 8854.17 / Max: 8858 Min: 8829.6 / Avg: 8851.97 / Max: 8880 Min: 8835.2 / Avg: 8850.57 / Max: 8861.4 Min: 8838.4 / Avg: 8842.73 / Max: 8846.2 Min: 8825.5 / Avg: 8829.87 / Max: 8832.7 Min: 8781.6 / Avg: 8825.67 / Max: 8853.7 Min: 8800 / Avg: 8805.9 / Max: 8809 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 7F32 EPYC 7542 EPYC 7402P EPYC 7662 EPYC 7702 EPYC 7532 EPYC 7502P EPYC 7552 EPYC 7302P EPYC 7282 EPYC 7272 EPYC 7F52 EPYC 7232P 2K 4K 6K 8K 10K SE +/- 12.37, N = 15 SE +/- 71.90, N = 3 SE +/- 36.49, N = 3 SE +/- 42.91, N = 3 SE +/- 25.22, N = 14 SE +/- 51.28, N = 3 SE +/- 31.02, N = 3 SE +/- 28.28, N = 5 SE +/- 35.59, N = 3 SE +/- 51.98, N = 3 SE +/- 37.27, N = 3 SE +/- 33.96, N = 3 SE +/- 28.32, N = 5 10561.9 10292.5 10256.3 10249.3 10219.5 10188.6 10184.5 10156.5 10132.1 10110.9 10070.2 10068.5 10057.8 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 7542 EPYC 7402P EPYC 7302P EPYC 7502P EPYC 7F32 EPYC 7552 EPYC 7662 EPYC 7532 EPYC 7702 EPYC 7F52 50 100 150 200 250 234.32 231.30 228.69 201.45 201.08 197.87 197.68 183.94 166.46 144.64 142.36 139.63 134.54
Result Confidence
OpenBenchmarking.org MB/s, More Is Better LZ4 Compression 1.9.3 Compression Level: 9 - Decompression Speed EPYC 7F32 EPYC 7542 EPYC 7402P EPYC 7662 EPYC 7702 EPYC 7532 EPYC 7502P EPYC 7552 EPYC 7302P EPYC 7282 EPYC 7272 EPYC 7F52 EPYC 7232P 2K 4K 6K 8K 10K Min: 10508.8 / Avg: 10561.89 / Max: 10609.7 Min: 10179.5 / Avg: 10292.47 / Max: 10426 Min: 10188.2 / Avg: 10256.27 / Max: 10313.1 Min: 10163.9 / Avg: 10249.27 / Max: 10299.5 Min: 10124.1 / Avg: 10219.52 / Max: 10411.5 Min: 10089.5 / Avg: 10188.6 / Max: 10261 Min: 10134.8 / Avg: 10184.5 / Max: 10241.5 Min: 10088.8 / Avg: 10156.48 / Max: 10226.8 Min: 10093.6 / Avg: 10132.1 / Max: 10203.2 Min: 10010.1 / Avg: 10110.87 / Max: 10183.4 Min: 10010.8 / Avg: 10070.17 / Max: 10138.9 Min: 10031 / Avg: 10068.5 / Max: 10136.3 Min: 10025.8 / Avg: 10057.76 / Max: 10170.9 1. (CC) gcc options: -O3
Result
OpenBenchmarking.org MB/s, More Is Better LZ4 Compression 1.9.3 Compression Level: 3 - Decompression Speed EPYC 7F32 EPYC 7502P EPYC 7542 EPYC 7402P EPYC 7302P EPYC 7662 EPYC 7702 EPYC 7552 EPYC 7532 EPYC 7282 EPYC 7272 EPYC 7F52 EPYC 7232P 2K 4K 6K 8K 10K SE +/- 34.53, N = 3 SE +/- 14.46, N = 3 SE +/- 29.33, N = 3 SE +/- 36.01, N = 4 SE +/- 93.14, N = 3 SE +/- 44.06, N = 3 SE +/- 18.64, N = 7 SE +/- 54.81, N = 3 SE +/- 43.54, N = 3 SE +/- 66.67, N = 3 SE +/- 29.05, N = 3 SE +/- 89.78, N = 3 SE +/- 44.49, N = 3 10567.2 10232.8 10222.4 10209.3 10172.7 10170.7 10162.0 10159.7 10118.0 10112.2 10101.0 10099.6 10063.0 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 7402P EPYC 7542 EPYC 7502P EPYC 7302P EPYC 7F32 EPYC 7552 EPYC 7662 EPYC 7532 EPYC 7702 EPYC 7F52 50 100 150 200 250 233.97 232.15 227.31 199.84 199.63 198.84 198.83 188.33 166.50 143.59 141.26 139.07 134.23
Result Confidence
OpenBenchmarking.org MB/s, More Is Better LZ4 Compression 1.9.3 Compression Level: 3 - Decompression Speed EPYC 7F32 EPYC 7502P EPYC 7542 EPYC 7402P EPYC 7302P EPYC 7662 EPYC 7702 EPYC 7552 EPYC 7532 EPYC 7282 EPYC 7272 EPYC 7F52 EPYC 7232P 2K 4K 6K 8K 10K Min: 10498.8 / Avg: 10567.23 / Max: 10609.5 Min: 10214 / Avg: 10232.77 / Max: 10261.2 Min: 10167.9 / Avg: 10222.43 / Max: 10268.4 Min: 10125 / Avg: 10209.25 / Max: 10270.7 Min: 10073 / Avg: 10172.67 / Max: 10358.8 Min: 10082.6 / Avg: 10170.7 / Max: 10215.9 Min: 10103.5 / Avg: 10162.01 / Max: 10237.8 Min: 10076.5 / Avg: 10159.67 / Max: 10263.1 Min: 10073.2 / Avg: 10118.03 / Max: 10205.1 Min: 9978.9 / Avg: 10112.23 / Max: 10180.1 Min: 10050 / Avg: 10101 / Max: 10150.6 Min: 9990.9 / Avg: 10099.57 / Max: 10277.7 Min: 10013.3 / Avg: 10063.03 / Max: 10151.8 1. (CC) gcc options: -O3
Result
OpenBenchmarking.org MB/s, More Is Better LZ4 Compression 1.9.3 Compression Level: 1 - Decompression Speed EPYC 7F32 EPYC 7302P EPYC 7702 EPYC 7542 EPYC 7502P EPYC 7402P EPYC 7232P EPYC 7532 EPYC 7272 EPYC 7662 EPYC 7552 EPYC 7282 EPYC 7F52 2K 4K 6K 8K 10K SE +/- 42.46, N = 3 SE +/- 18.80, N = 3 SE +/- 36.93, N = 3 SE +/- 47.44, N = 3 SE +/- 5.92, N = 3 SE +/- 43.01, N = 3 SE +/- 37.22, N = 3 SE +/- 41.47, N = 3 SE +/- 27.35, N = 3 SE +/- 27.42, N = 3 SE +/- 23.29, N = 3 SE +/- 7.93, N = 3 SE +/- 24.26, N = 3 11210.0 11006.6 10996.1 10993.2 10968.6 10951.0 10936.6 10931.6 10929.9 10926.3 10920.5 10898.3 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 7402P EPYC 7542 EPYC 7302P EPYC 7502P EPYC 7F32 EPYC 7552 EPYC 7662 EPYC 7532 EPYC 7702 EPYC 7F52 50 100 150 200 250 237.48 234.75 227.91 202.51 202.37 201.84 200.00 189.50 172.19 147.64 146.91 142.24 139.96
Result Confidence
OpenBenchmarking.org MB/s, More Is Better LZ4 Compression 1.9.3 Compression Level: 1 - Decompression Speed EPYC 7F32 EPYC 7302P EPYC 7702 EPYC 7542 EPYC 7502P EPYC 7402P EPYC 7232P EPYC 7532 EPYC 7272 EPYC 7662 EPYC 7552 EPYC 7282 EPYC 7F52 2K 4K 6K 8K 10K Min: 11129.3 / Avg: 11209.97 / Max: 11273.3 Min: 10976.1 / Avg: 11006.63 / Max: 11040.9 Min: 10957.3 / Avg: 10996.07 / Max: 11069.9 Min: 10916.9 / Avg: 10993.2 / Max: 11080.2 Min: 10961.1 / Avg: 10968.63 / Max: 10980.3 Min: 10899.4 / Avg: 10951 / Max: 11036.4 Min: 10862.2 / Avg: 10936.63 / Max: 10975.1 Min: 10851.3 / Avg: 10931.63 / Max: 10989.7 Min: 10878.3 / Avg: 10929.9 / Max: 10971.4 Min: 10874.5 / Avg: 10926.3 / Max: 10967.8 Min: 10874.2 / Avg: 10920.47 / Max: 10948.2 Min: 10885.6 / Avg: 10898.33 / Max: 10912.9 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 7F32 EPYC 7542 EPYC 7502P EPYC 7662 EPYC 7702 EPYC 7232P EPYC 7402P EPYC 7532 EPYC 7282 EPYC 7272 EPYC 7302P EPYC 7552 EPYC 7F52 3K 6K 9K 12K 15K SE +/- 4.94, N = 3 SE +/- 24.53, N = 3 SE +/- 83.23, N = 3 SE +/- 2.47, N = 3 SE +/- 67.71, N = 3 SE +/- 33.58, N = 3 SE +/- 93.82, N = 3 SE +/- 36.28, N = 3 SE +/- 87.56, N = 3 SE +/- 85.10, N = 3 SE +/- 60.36, N = 3 SE +/- 23.45, N = 3 SE +/- 1.29, N = 3 15666.70 15641.09 15621.64 15616.90 15599.90 15523.14 15510.92 15503.05 15482.74 15482.71 15480.29 15459.16 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 7542 EPYC 7502P EPYC 7402P EPYC 7302P EPYC 7F32 EPYC 7552 EPYC 7662 EPYC 7532 EPYC 7702 EPYC 7F52 70 140 210 280 350 315.08 311.47 306.50 272.57 269.18 268.62 266.51 248.71 230.35 201.36 194.18 192.02 182.44
Result Confidence
OpenBenchmarking.org MiB/s, More Is Better MBW 2018-09-08 Test: Memory Copy - Array Size: 8192 MiB EPYC 7F32 EPYC 7542 EPYC 7502P EPYC 7662 EPYC 7702 EPYC 7232P EPYC 7402P EPYC 7532 EPYC 7282 EPYC 7272 EPYC 7302P EPYC 7552 EPYC 7F52 3K 6K 9K 12K 15K Min: 15657.32 / Avg: 15666.7 / Max: 15674.1 Min: 15608.52 / Avg: 15641.09 / Max: 15689.15 Min: 15473.05 / Avg: 15621.64 / Max: 15760.91 Min: 15613.31 / Avg: 15616.9 / Max: 15621.62 Min: 15488.47 / Avg: 15599.9 / Max: 15722.26 Min: 15473.92 / Avg: 15523.14 / Max: 15587.31 Min: 15344.4 / Avg: 15510.92 / Max: 15669.08 Min: 15458.28 / Avg: 15503.05 / Max: 15574.89 Min: 15323.81 / Avg: 15482.73 / Max: 15625.9 Min: 15312.58 / Avg: 15482.71 / Max: 15571.59 Min: 15391.63 / Avg: 15480.29 / Max: 15595.56 Min: 15413.52 / Avg: 15459.16 / Max: 15491.31 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 7F32 EPYC 7702 EPYC 7402P EPYC 7542 EPYC 7502P EPYC 7F52 EPYC 7532 EPYC 7302P EPYC 7232P EPYC 7662 EPYC 7552 EPYC 7272 EPYC 7282 2K 4K 6K 8K 10K SE +/- 52.96, N = 3 SE +/- 50.78, N = 3 SE +/- 57.96, N = 3 SE +/- 14.87, N = 3 SE +/- 5.54, N = 3 SE +/- 19.46, N = 3 SE +/- 55.86, N = 3 SE +/- 29.02, N = 3 SE +/- 52.82, N = 3 SE +/- 19.08, N = 3 SE +/- 18.08, N = 3 SE +/- 18.11, N = 3 SE +/- 8.54, N = 3 9802.81 9496.00 9472.86 9468.59 9464.00 9461.09 9434.31 9428.77 9421.69 9376.86 9369.35 9365.44 9360.35 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 7F32 EPYC 7702 EPYC 7402P EPYC 7542 EPYC 7502P EPYC 7F52 EPYC 7532 EPYC 7302P EPYC 7232P EPYC 7662 EPYC 7552 EPYC 7272 EPYC 7282 2K 4K 6K 8K 10K Min: 9744.32 / Avg: 9802.81 / Max: 9908.52 Min: 9444.69 / Avg: 9496 / Max: 9597.56 Min: 9413.59 / Avg: 9472.86 / Max: 9588.77 Min: 9438.88 / Avg: 9468.59 / Max: 9484.45 Min: 9454.4 / Avg: 9464 / Max: 9473.6 Min: 9423.06 / Avg: 9461.09 / Max: 9487.27 Min: 9377.21 / Avg: 9434.31 / Max: 9546.03 Min: 9379.2 / Avg: 9428.77 / Max: 9479.71 Min: 9316.16 / Avg: 9421.69 / Max: 9478.74 Min: 9351.87 / Avg: 9376.86 / Max: 9414.33 Min: 9339.76 / Avg: 9369.35 / Max: 9402.14 Min: 9344.67 / Avg: 9365.44 / Max: 9401.53 Min: 9345.51 / Avg: 9360.35 / Max: 9375.08 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 7F32 EPYC 7542 EPYC 7502P EPYC 7662 EPYC 7702 EPYC 7552 EPYC 7402P EPYC 7302P EPYC 7232P EPYC 7272 EPYC 7532 EPYC 7282 EPYC 7F52 2K 4K 6K 8K 10K SE +/- 5.81, N = 3 SE +/- 2.76, N = 3 SE +/- 16.71, N = 3 SE +/- 4.98, N = 3 SE +/- 18.50, N = 3 SE +/- 10.51, N = 3 SE +/- 18.97, N = 3 SE +/- 19.18, N = 3 SE +/- 7.74, N = 3 SE +/- 6.09, N = 3 SE +/- 27.37, N = 3 SE +/- 16.74, N = 3 SE +/- 3.26, N = 3 9215.24 9117.75 9078.88 9073.57 9048.74 9022.45 9012.11 8995.85 8983.76 8970.77 8963.64 8945.24 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 7542 EPYC 7402P EPYC 7502P EPYC 7302P EPYC 7F32 EPYC 7552 EPYC 7662 EPYC 7532 EPYC 7702 EPYC 7F52 40 80 120 160 200 185.90 183.37 179.48 160.00 159.14 158.03 154.41 149.02 134.77 117.41 112.76 111.88 108.64
Result Confidence
OpenBenchmarking.org MiB/s, More Is Better MBW 2018-09-08 Test: Memory Copy, Fixed Block Size - Array Size: 8192 MiB EPYC 7F32 EPYC 7542 EPYC 7502P EPYC 7662 EPYC 7702 EPYC 7552 EPYC 7402P EPYC 7302P EPYC 7232P EPYC 7272 EPYC 7532 EPYC 7282 EPYC 7F52 1600 3200 4800 6400 8000 Min: 9203.97 / Avg: 9215.24 / Max: 9223.37 Min: 9112.63 / Avg: 9117.75 / Max: 9122.1 Min: 9045.61 / Avg: 9078.88 / Max: 9098.27 Min: 9065.01 / Avg: 9073.56 / Max: 9082.25 Min: 9023.71 / Avg: 9048.74 / Max: 9084.85 Min: 9010.61 / Avg: 9022.45 / Max: 9043.42 Min: 8974.68 / Avg: 9012.11 / Max: 9036.23 Min: 8971.17 / Avg: 8995.85 / Max: 9033.63 Min: 8971.61 / Avg: 8983.76 / Max: 8998.15 Min: 8960.57 / Avg: 8970.77 / Max: 8981.63 Min: 8910.42 / Avg: 8963.64 / Max: 9001.37 Min: 8912.98 / Avg: 8945.24 / Max: 8969.13 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 7F32 EPYC 7232P EPYC 7272 EPYC 7302P EPYC 7282 EPYC 7F52 EPYC 7402P EPYC 7502P EPYC 7542 EPYC 7532 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 3 6 9 12 15 SE +/- 0.03, N = 3 SE +/- 0.02, N = 3 SE +/- 0.02, N = 3 SE +/- 0.02, N = 3 SE +/- 0.04, N = 3 SE +/- 0.01, N = 3 SE +/- 0.01, N = 3 SE +/- 0.05, N = 3 SE +/- 0.03, N = 3 SE +/- 0.05, N = 11 SE +/- 0.67, N = 3 SE +/- 0.26, N = 12 SE +/- 0.37, N = 9 SE +/- 0.25, N = 9 3.30 3.49 3.54 3.72 3.74 3.82 4.21 4.60 4.61 4.95 6.57 6.80 8.68 9.32 MIN: 3.2 / MAX: 3.51 MIN: 3.4 / MAX: 3.75 MIN: 3.43 / MAX: 3.74 MIN: 3.58 / MAX: 5.16 MIN: 3.58 / MAX: 8.88 MIN: 3.72 / MAX: 4.1 MIN: 4.06 / MAX: 5.91 MIN: 4.38 / MAX: 6.31 MIN: 4.45 / MAX: 4.81 MIN: 4.63 / MAX: 6.53 MIN: 5.73 / MAX: 18.41 MIN: 5.67 / MAX: 11.73 MIN: 6.7 / MAX: 15.99 MIN: 7.36 / MAX: 18.28 1. (CXX) g++ options: -O3 -rdynamic -lgomp -lpthread
Result Confidence
OpenBenchmarking.org ms, Fewer Is Better NCNN 20201218 Target: CPU - Model: blazeface EPYC 7F32 EPYC 7232P EPYC 7272 EPYC 7302P EPYC 7282 EPYC 7F52 EPYC 7402P EPYC 7502P EPYC 7542 EPYC 7532 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 3 6 9 12 15 Min: 3.26 / Avg: 3.3 / Max: 3.36 Min: 3.46 / Avg: 3.49 / Max: 3.51 Min: 3.5 / Avg: 3.54 / Max: 3.58 Min: 3.68 / Avg: 3.72 / Max: 3.75 Min: 3.67 / Avg: 3.74 / Max: 3.82 Min: 3.79 / Avg: 3.82 / Max: 3.83 Min: 4.19 / Avg: 4.21 / Max: 4.23 Min: 4.49 / Avg: 4.6 / Max: 4.66 Min: 4.55 / Avg: 4.61 / Max: 4.67 Min: 4.75 / Avg: 4.95 / Max: 5.37 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 1. (CXX) g++ options: -O3 -rdynamic -lgomp -lpthread
Result
OpenBenchmarking.org ms, Fewer Is Better NCNN 20201218 Target: CPU - Model: efficientnet-b0 EPYC 7272 EPYC 7282 EPYC 7F32 EPYC 7302P EPYC 7232P EPYC 7402P EPYC 7F52 EPYC 7502P EPYC 7542 EPYC 7532 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 6 12 18 24 30 SE +/- 0.04, N = 3 SE +/- 0.10, N = 3 SE +/- 0.13, N = 3 SE +/- 0.08, N = 3 SE +/- 0.03, N = 3 SE +/- 0.06, N = 3 SE +/- 0.17, N = 3 SE +/- 0.07, N = 3 SE +/- 0.11, N = 3 SE +/- 0.26, N = 11 SE +/- 2.24, N = 3 SE +/- 0.75, N = 12 SE +/- 1.16, N = 9 SE +/- 0.85, N = 9 9.84 10.40 10.55 10.80 10.87 11.69 12.47 12.92 12.94 14.63 19.66 21.71 26.52 26.76 MIN: 9.58 / MAX: 10.75 MIN: 9.83 / MAX: 20.38 MIN: 10.24 / MAX: 69.96 MIN: 10.45 / MAX: 26 MIN: 10.68 / MAX: 11.57 MIN: 11.36 / MAX: 14.13 MIN: 12.02 / MAX: 14.07 MIN: 12.36 / MAX: 16.63 MIN: 12.46 / MAX: 15.4 MIN: 13.29 / MAX: 20.58 MIN: 15.98 / MAX: 32.16 MIN: 16.06 / MAX: 33.9 MIN: 18.34 / MAX: 159.39 MIN: 19.65 / MAX: 171.03 1. (CXX) g++ options: -O3 -rdynamic -lgomp -lpthread
Result Confidence
OpenBenchmarking.org ms, Fewer Is Better NCNN 20201218 Target: CPU - Model: efficientnet-b0 EPYC 7272 EPYC 7282 EPYC 7F32 EPYC 7302P EPYC 7232P EPYC 7402P EPYC 7F52 EPYC 7502P EPYC 7542 EPYC 7532 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 6 12 18 24 30 Min: 9.77 / Avg: 9.84 / Max: 9.88 Min: 10.24 / Avg: 10.4 / Max: 10.57 Min: 10.38 / Avg: 10.55 / Max: 10.8 Min: 10.65 / Avg: 10.8 / Max: 10.94 Min: 10.82 / Avg: 10.87 / Max: 10.92 Min: 11.58 / Avg: 11.69 / Max: 11.76 Min: 12.29 / Avg: 12.47 / Max: 12.8 Min: 12.84 / Avg: 12.92 / Max: 13.06 Min: 12.72 / Avg: 12.94 / Max: 13.1 Min: 13.74 / Avg: 14.63 / Max: 16.32 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 1. (CXX) g++ options: -O3 -rdynamic -lgomp -lpthread
Result
OpenBenchmarking.org ms, Fewer Is Better NCNN 20201218 Target: CPU - Model: mnasnet EPYC 7F32 EPYC 7272 EPYC 7232P EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7F52 EPYC 7502P EPYC 7542 EPYC 7532 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 5 10 15 20 25 SE +/- 0.12, N = 3 SE +/- 0.02, N = 3 SE +/- 0.03, N = 3 SE +/- 0.04, N = 3 SE +/- 0.06, N = 3 SE +/- 0.04, N = 2 SE +/- 0.31, N = 3 SE +/- 0.05, N = 3 SE +/- 0.37, N = 3 SE +/- 0.23, N = 11 SE +/- 2.35, N = 3 SE +/- 0.94, N = 12 SE +/- 1.14, N = 9 SE +/- 0.77, N = 9 6.42 6.49 6.64 6.95 7.32 8.16 8.72 9.07 9.28 10.38 15.49 16.71 22.05 22.34 MIN: 6.09 / MAX: 7.09 MIN: 6.37 / MAX: 6.92 MIN: 6.54 / MAX: 7.23 MIN: 6.71 / MAX: 14.84 MIN: 7.05 / MAX: 8.22 MIN: 7.75 / MAX: 9.91 MIN: 8.12 / MAX: 10.61 MIN: 8.75 / MAX: 11.1 MIN: 8.66 / MAX: 11.37 MIN: 9.3 / MAX: 16.29 MIN: 11.65 / MAX: 28.64 MIN: 11.37 / MAX: 30.58 MIN: 13.54 / MAX: 37.68 MIN: 14.54 / MAX: 162.38 1. (CXX) g++ options: -O3 -rdynamic -lgomp -lpthread
Result Confidence
OpenBenchmarking.org ms, Fewer Is Better NCNN 20201218 Target: CPU - Model: mnasnet EPYC 7F32 EPYC 7272 EPYC 7232P EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7F52 EPYC 7502P EPYC 7542 EPYC 7532 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 5 10 15 20 25 Min: 6.18 / Avg: 6.42 / Max: 6.58 Min: 6.47 / Avg: 6.49 / Max: 6.52 Min: 6.59 / Avg: 6.64 / Max: 6.7 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: 8.32 / Avg: 8.72 / Max: 9.32 Min: 8.98 / Avg: 9.07 / Max: 9.14 Min: 8.87 / Avg: 9.28 / Max: 10.01 Min: 9.65 / Avg: 10.38 / Max: 12.34 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 1. (CXX) g++ options: -O3 -rdynamic -lgomp -lpthread
Result
OpenBenchmarking.org ms, Fewer Is Better NCNN 20201218 Target: CPU - Model: shufflenet-v2 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7F32 EPYC 7272 EPYC 7502P EPYC 7542 EPYC 7F52 EPYC 7232P EPYC 7532 EPYC 7552 EPYC 7642 EPYC 7702 EPYC 7662 4 8 12 16 20 SE +/- 0.04, N = 3 SE +/- 0.04, N = 3 SE +/- 0.02, N = 3 SE +/- 0.04, N = 3 SE +/- 0.03, N = 3 SE +/- 0.04, N = 3 SE +/- 0.07, N = 3 SE +/- 0.36, N = 3 SE +/- 0.01, N = 3 SE +/- 0.07, N = 11 SE +/- 0.60, N = 3 SE +/- 0.42, N = 12 SE +/- 0.35, N = 9 SE +/- 0.61, N = 9 8.87 8.91 9.52 9.60 9.61 9.94 9.97 9.99 10.20 10.68 12.82 14.06 16.71 17.29 MIN: 8.52 / MAX: 34.05 MIN: 8.74 / MAX: 12.61 MIN: 9.28 / MAX: 10.99 MIN: 9.43 / MAX: 10.04 MIN: 9.51 / MAX: 13.18 MIN: 9.64 / MAX: 11.99 MIN: 9.68 / MAX: 12.72 MIN: 9.5 / MAX: 11.56 MIN: 10.07 / MAX: 10.8 MIN: 10.17 / MAX: 154.31 MIN: 12.07 / MAX: 17.58 MIN: 11.71 / MAX: 20.88 MIN: 14.39 / MAX: 153.63 MIN: 13.68 / MAX: 128.19 1. (CXX) g++ options: -O3 -rdynamic -lgomp -lpthread
Result Confidence
OpenBenchmarking.org ms, Fewer Is Better NCNN 20201218 Target: CPU - Model: shufflenet-v2 EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7F32 EPYC 7272 EPYC 7502P EPYC 7542 EPYC 7F52 EPYC 7232P EPYC 7532 EPYC 7552 EPYC 7642 EPYC 7702 EPYC 7662 4 8 12 16 20 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: 9.56 / Avg: 9.6 / Max: 9.68 Min: 9.56 / Avg: 9.61 / Max: 9.65 Min: 9.85 / Avg: 9.94 / Max: 9.98 Min: 9.83 / Avg: 9.97 / Max: 10.05 Min: 9.61 / Avg: 9.99 / Max: 10.71 Min: 10.18 / Avg: 10.2 / Max: 10.21 Min: 10.49 / Avg: 10.68 / Max: 11.36 Min: 12.17 / Avg: 12.82 / Max: 14.01 Min: 12.14 / Avg: 14.06 / Max: 16.52 Min: 14.5 / Avg: 16.71 / Max: 17.77 Min: 13.79 / Avg: 17.29 / Max: 19.27 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 7272 EPYC 7F32 EPYC 7232P EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7F52 EPYC 7502P EPYC 7542 EPYC 7532 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 5 10 15 20 25 SE +/- 0.01, N = 3 SE +/- 0.02, N = 3 SE +/- 0.02, N = 3 SE +/- 0.02, N = 3 SE +/- 0.08, N = 3 SE +/- 0.04, N = 3 SE +/- 0.20, N = 3 SE +/- 0.07, N = 3 SE +/- 0.19, N = 3 SE +/- 0.18, N = 11 SE +/- 1.69, N = 3 SE +/- 0.60, N = 12 SE +/- 1.03, N = 9 SE +/- 0.75, N = 9 6.54 6.58 6.72 6.94 7.31 8.13 8.74 9.11 9.20 10.51 14.21 15.94 20.29 20.70 MIN: 6.36 / MAX: 10.78 MIN: 6.13 / MAX: 7.08 MIN: 6.58 / MAX: 8.56 MIN: 6.68 / MAX: 16.72 MIN: 7.02 / MAX: 19.94 MIN: 7.77 / MAX: 9.9 MIN: 8.27 / MAX: 12.35 MIN: 8.69 / MAX: 12.94 MIN: 8.74 / MAX: 13.15 MIN: 9.5 / MAX: 16.4 MIN: 11.65 / MAX: 24.12 MIN: 11.89 / MAX: 108.3 MIN: 13.64 / MAX: 155.26 MIN: 14.71 / MAX: 286.24 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 7272 EPYC 7F32 EPYC 7232P EPYC 7282 EPYC 7302P EPYC 7402P EPYC 7F52 EPYC 7502P EPYC 7542 EPYC 7532 EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7702 5 10 15 20 25 Min: 6.53 / Avg: 6.54 / Max: 6.55 Min: 6.55 / Avg: 6.58 / Max: 6.62 Min: 6.68 / Avg: 6.72 / Max: 6.76 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: 8.53 / Avg: 8.74 / Max: 9.13 Min: 8.97 / Avg: 9.11 / Max: 9.18 Min: 8.99 / Avg: 9.2 / Max: 9.58 Min: 9.94 / Avg: 10.51 / Max: 11.53 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 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 7F32 EPYC 7272 EPYC 7232P EPYC 7302P EPYC 7282 EPYC 7402P EPYC 7502P EPYC 7F52 EPYC 7542 EPYC 7532 EPYC 7552 EPYC 7642 EPYC 7702 EPYC 7662 6 12 18 24 30 SE +/- 0.03, N = 3 SE +/- 0.01, N = 3 SE +/- 0.02, N = 3 SE +/- 0.04, N = 3 SE +/- 0.01, N = 3 SE +/- 0.04, N = 3 SE +/- 0.04, N = 3 SE +/- 0.27, N = 3 SE +/- 0.17, N = 3 SE +/- 0.22, N = 11 SE +/- 2.17, N = 3 SE +/- 1.02, N = 12 SE +/- 0.94, N = 9 SE +/- 1.26, N = 9 7.13 7.32 7.61 7.85 7.88 8.41 10.07 10.11 10.15 11.55 16.05 17.78 22.98 23.01 MIN: 6.91 / MAX: 7.7 MIN: 7.06 / MAX: 11.87 MIN: 7.45 / MAX: 8.18 MIN: 7.44 / MAX: 11.79 MIN: 7.53 / MAX: 17.78 MIN: 7.96 / MAX: 10.39 MIN: 9.55 / MAX: 13.68 MIN: 9.12 / MAX: 13.81 MIN: 9.54 / MAX: 14.14 MIN: 10.24 / MAX: 25.89 MIN: 12.41 / MAX: 30.85 MIN: 12.27 / MAX: 35.04 MIN: 15.37 / MAX: 193.31 MIN: 14.46 / MAX: 130.77 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 7F32 EPYC 7272 EPYC 7232P EPYC 7302P EPYC 7282 EPYC 7402P EPYC 7502P EPYC 7F52 EPYC 7542 EPYC 7532 EPYC 7552 EPYC 7642 EPYC 7702 EPYC 7662 5 10 15 20 25 Min: 7.08 / Avg: 7.13 / Max: 7.18 Min: 7.3 / Avg: 7.32 / Max: 7.34 Min: 7.59 / Avg: 7.61 / Max: 7.64 Min: 7.8 / Avg: 7.85 / Max: 7.92 Min: 7.86 / Avg: 7.88 / Max: 7.9 Min: 8.33 / Avg: 8.41 / Max: 8.48 Min: 10 / Avg: 10.07 / Max: 10.13 Min: 9.76 / Avg: 10.11 / Max: 10.65 Min: 9.86 / Avg: 10.15 / Max: 10.44 Min: 10.7 / Avg: 11.55 / Max: 13.04 Min: 13.72 / Avg: 16.05 / Max: 20.38 Min: 12.86 / Avg: 17.78 / Max: 24.89 Min: 19.59 / Avg: 22.98 / Max: 29.47 Min: 16.68 / Avg: 23.01 / Max: 27.84 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 7542 EPYC 7502P EPYC 7552 EPYC 7232P EPYC 7402P EPYC 7532 EPYC 7282 EPYC 7302P EPYC 7662 EPYC 7272 EPYC 7702 EPYC 7F52 EPYC 7F32 0.1553 0.3106 0.4659 0.6212 0.7765 0.69 0.66 0.63 0.63 0.62 0.58 0.55 0.54 0.53 0.50 0.50 0.47 0.38
Result
OpenBenchmarking.org Bogo Ops/s, More Is Better Stress-NG 0.11.07 Test: CPU Cache EPYC 7532 EPYC 7552 EPYC 7542 EPYC 7F52 EPYC 7502P EPYC 7662 EPYC 7702 EPYC 7402P EPYC 7302P EPYC 7232P EPYC 7282 EPYC 7272 EPYC 7F32 12 24 36 48 60 SE +/- 1.06, N = 15 SE +/- 0.96, N = 12 SE +/- 0.67, N = 3 SE +/- 1.23, N = 12 SE +/- 1.28, N = 12 SE +/- 0.36, N = 3 SE +/- 0.81, N = 15 SE +/- 0.69, N = 12 SE +/- 0.68, N = 15 SE +/- 0.49, N = 13 SE +/- 0.37, N = 15 SE +/- 0.77, N = 12 SE +/- 0.72, N = 15 51.39 49.78 49.19 46.39 45.23 44.36 43.70 41.11 32.72 32.53 30.12 25.17 24.85 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 7542 EPYC 7502P EPYC 7552 EPYC 7232P EPYC 7402P EPYC 7532 EPYC 7282 EPYC 7302P EPYC 7662 EPYC 7272 EPYC 7702 EPYC 7F52 EPYC 7F32 0.1553 0.3106 0.4659 0.6212 0.7765 0.69 0.66 0.63 0.63 0.62 0.58 0.55 0.54 0.53 0.50 0.50 0.47 0.38
Result Confidence
OpenBenchmarking.org Bogo Ops/s, More Is Better Stress-NG 0.11.07 Test: CPU Cache EPYC 7532 EPYC 7552 EPYC 7542 EPYC 7F52 EPYC 7502P EPYC 7662 EPYC 7702 EPYC 7402P EPYC 7302P EPYC 7232P EPYC 7282 EPYC 7272 EPYC 7F32 10 20 30 40 50 Min: 45.08 / Avg: 51.39 / Max: 61.54 Min: 45.03 / Avg: 49.78 / Max: 56.32 Min: 48.23 / Avg: 49.19 / Max: 50.47 Min: 38.66 / Avg: 46.39 / Max: 52.29 Min: 35.87 / Avg: 45.23 / Max: 51.94 Min: 43.65 / Avg: 44.36 / Max: 44.75 Min: 38.22 / Avg: 43.7 / Max: 48.67 Min: 35.35 / Avg: 41.11 / Max: 44.78 Min: 28.49 / Avg: 32.72 / Max: 38.56 Min: 29.83 / Avg: 32.53 / Max: 36.16 Min: 28.09 / Avg: 30.12 / Max: 33.69 Min: 20.46 / Avg: 25.17 / Max: 29.16 Min: 20.06 / Avg: 24.85 / Max: 30.63 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 7662 EPYC 7702 EPYC 7502P EPYC 7542 EPYC 7402P EPYC 7552 EPYC 7532 EPYC 7642 EPYC 7302P EPYC 7F52 EPYC 7282 EPYC 7272 EPYC 7F32 EPYC 7232P 10K 20K 30K 40K 50K SE +/- 249.84, N = 3 SE +/- 312.03, N = 3 SE +/- 1515.78, N = 3 SE +/- 1923.72, N = 3 SE +/- 1363.32, N = 3 SE +/- 2893.83, N = 3 SE +/- 1222.34, N = 3 SE +/- 2455.63, N = 3 SE +/- 448.51, N = 3 SE +/- 379.22, N = 3 SE +/- 361.51, N = 3 SE +/- 66.78, N = 3 SE +/- 648.32, N = 3 SE +/- 510.12, N = 3 45477 44434 43733 43408 42491 41586 39412 39319 37026 36834 33627 28663 27443 21916 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 7662 EPYC 7702 EPYC 7502P EPYC 7542 EPYC 7402P EPYC 7552 EPYC 7532 EPYC 7642 EPYC 7302P EPYC 7F52 EPYC 7282 EPYC 7272 EPYC 7F32 EPYC 7232P 8K 16K 24K 32K 40K Min: 44984 / Avg: 45477 / Max: 45794 Min: 43811 / Avg: 44434.33 / Max: 44772 Min: 40707 / Avg: 43733 / Max: 45405 Min: 39566 / Avg: 43408.33 / Max: 45501 Min: 39807 / Avg: 42491 / Max: 44249 Min: 35861 / Avg: 41586 / Max: 45184 Min: 36967 / Avg: 39411.67 / Max: 40640 Min: 34451 / Avg: 39318.67 / Max: 42318 Min: 36148 / Avg: 37025.67 / Max: 37625 Min: 36386 / Avg: 36834 / Max: 37588 Min: 33112 / Avg: 33627 / Max: 34324 Min: 28551 / Avg: 28663 / Max: 28782 Min: 26499 / Avg: 27443.33 / Max: 28685 Min: 20947 / Avg: 21916 / Max: 22677 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 7542 EPYC 7502P EPYC 7402P EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7532 EPYC 7282 EPYC 7702 EPYC 7302P EPYC 7272 EPYC 7F52 EPYC 7232P EPYC 7F32 1.1565 2.313 3.4695 4.626 5.7825 5.14 5.00 4.59 4.48 4.11 4.04 4.00 3.89 3.67 3.55 3.02 2.19 1.90 1.67
Result
OpenBenchmarking.org Frames Per Second, More Is Better SVT-VP9 0.1 Tuning: Visual Quality Optimized - Input: Bosphorus 1080p EPYC 7542 EPYC 7642 EPYC 7552 EPYC 7502P EPYC 7662 EPYC 7532 EPYC 7402P EPYC 7702 EPYC 7302P EPYC 7F52 EPYC 7282 EPYC 7272 EPYC 7F32 EPYC 7232P 80 160 240 320 400 SE +/- 6.75, N = 15 SE +/- 6.69, N = 15 SE +/- 6.16, N = 15 SE +/- 5.89, N = 15 SE +/- 5.77, N = 15 SE +/- 5.85, N = 15 SE +/- 5.48, N = 15 SE +/- 4.45, N = 15 SE +/- 2.50, N = 15 SE +/- 2.97, N = 15 SE +/- 1.82, N = 15 SE +/- 1.04, N = 9 SE +/- 0.53, N = 7 SE +/- 0.51, N = 7 350.63 346.63 336.24 334.18 332.56 325.84 319.05 305.10 242.24 230.31 229.82 184.83 124.35 107.11 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 7542 EPYC 7502P EPYC 7402P EPYC 7552 EPYC 7642 EPYC 7662 EPYC 7532 EPYC 7282 EPYC 7702 EPYC 7302P EPYC 7272 EPYC 7F52 EPYC 7232P EPYC 7F32 1.1565 2.313 3.4695 4.626 5.7825 5.14 5.00 4.59 4.48 4.11 4.04 4.00 3.89 3.67 3.55 3.02 2.19 1.90 1.67
Result Confidence
OpenBenchmarking.org Frames Per Second, More Is Better SVT-VP9 0.1 Tuning: Visual Quality Optimized - Input: Bosphorus 1080p EPYC 7542 EPYC 7642 EPYC 7552 EPYC 7502P EPYC 7662 EPYC 7532 EPYC 7402P EPYC 7702 EPYC 7302P EPYC 7F52 EPYC 7282 EPYC 7272 EPYC 7F32 EPYC 7232P 60 120 180 240 300 Min: 256.63 / Avg: 350.63 / Max: 362.54 Min: 253.27 / Avg: 346.63 / Max: 357.36 Min: 250.31 / Avg: 336.24 / Max: 345.82 Min: 252.42 / Avg: 334.18 / Max: 348.23 Min: 253.16 / Avg: 332.56 / Max: 350.88 Min: 244.6 / Avg: 325.84 / Max: 336.51 Min: 242.72 / Avg: 319.05 / Max: 326.26 Min: 248.76 / Avg: 305.1 / Max: 317.63 Min: 207.33 / Avg: 242.24 / Max: 245.7 Min: 188.8 / Avg: 230.31 / Max: 234.56 Min: 204.43 / Avg: 229.82 / Max: 232.47 Min: 176.68 / Avg: 184.83 / Max: 187.03 Min: 121.26 / Avg: 124.35 / Max: 125.39 Min: 104.11 / Avg: 107.11 / Max: 107.86 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 7662 EPYC 7702 EPYC 7552 EPYC 7502P EPYC 7542 EPYC 7642 EPYC 7402P EPYC 7532 EPYC 7282 EPYC 7302P EPYC 7272 EPYC 7F52 EPYC 7232P EPYC 7F32 120 240 360 480 600 565.67 562.57 474.77 441.39 438.65 432.56 318.51 286.60 255.88 224.80 201.02 175.98 140.99 128.88
Result
OpenBenchmarking.org kH/s, More Is Better Cpuminer-Opt 3.15.5 Algorithm: Deepcoin EPYC 7702 EPYC 7662 EPYC 7642 EPYC 7552 EPYC 7502P EPYC 7542 EPYC 7532 EPYC 7402P EPYC 7F52 EPYC 7282 EPYC 7302P EPYC 7272 EPYC 7F32 EPYC 7232P 10K 20K 30K 40K 50K SE +/- 2134.76, N = 15 SE +/- 1295.28, N = 15 SE +/- 1521.20, N = 15 SE +/- 964.94, N = 15 SE +/- 1900.37, N = 15 SE +/- 991.42, N = 15 SE +/- 38.44, N = 3 SE +/- 94.04, N = 3 SE +/- 333.56, N = 15 SE +/- 407.34, N = 15 SE +/- 14.53, N = 3 SE +/- 78.72, N = 3 SE +/- 73.09, N = 6 SE +/- 0.23, N = 3 46113.00 45051.00 34363.00 33589.00 26546.00 26493.00 23013.00 19363.00 15338.00 12793.00 12697.00 9361.06 7644.10 6207.89 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 7662 EPYC 7702 EPYC 7552 EPYC 7502P EPYC 7542 EPYC 7642 EPYC 7402P EPYC 7532 EPYC 7282 EPYC 7302P EPYC 7272 EPYC 7F52 EPYC 7232P EPYC 7F32 120 240 360 480 600 565.67 562.57 474.77 441.39 438.65 432.56 318.51 286.60 255.88 224.80 201.02 175.98 140.99 128.88
Result Confidence
OpenBenchmarking.org kH/s, More Is Better Cpuminer-Opt 3.15.5 Algorithm: Deepcoin EPYC 7702 EPYC 7662 EPYC 7642 EPYC 7552 EPYC 7502P EPYC 7542 EPYC 7532 EPYC 7402P EPYC 7F52 EPYC 7282 EPYC 7302P EPYC 7272 EPYC 7F32 EPYC 7232P 8K 16K 24K 32K 40K Min: 42730 / Avg: 46112.67 / Max: 75810 Min: 42590 / Avg: 45050.67 / Max: 63100 Min: 32480 / Avg: 34363.33 / Max: 55610 Min: 32160 / Avg: 33588.67 / Max: 46960 Min: 23580 / Avg: 26546 / Max: 44860 Min: 25310 / Avg: 26492.67 / Max: 40340 Min: 22940 / Avg: 23013.33 / Max: 23070 Min: 19250 / Avg: 19363.33 / Max: 19550 Min: 14690 / Avg: 15338 / Max: 19990 Min: 12330 / Avg: 12793.33 / Max: 18480 Min: 12670 / Avg: 12696.67 / Max: 12720 Min: 9269.8 / Avg: 9361.06 / Max: 9517.79 Min: 7535.18 / Avg: 7644.1 / Max: 7997.88 Min: 6207.47 / Avg: 6207.89 / Max: 6208.24 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 7662 EPYC 7702 EPYC 7552 EPYC 7542 EPYC 7642 EPYC 7502P EPYC 7532 EPYC 7402P EPYC 7282 EPYC 7302P EPYC 7272 EPYC 7F52 EPYC 7232P EPYC 7F32 20 40 60 80 100 105.24 101.85 97.57 89.06 88.03 86.48 63.17 62.91 52.46 45.58 41.66 33.55 31.40 27.22
Result
OpenBenchmarking.org kH/s, More Is Better Cpuminer-Opt 3.15.5 Algorithm: Garlicoin EPYC 7702 EPYC 7662 EPYC 7642 EPYC 7552 EPYC 7542 EPYC 7502P EPYC 7532 EPYC 7402P EPYC 7F52 EPYC 7282 EPYC 7302P EPYC 7272 EPYC 7F32 EPYC 7232P 2K 4K 6K 8K 10K SE +/- 215.48, N = 14 SE +/- 72.85, N = 13 SE +/- 113.98, N = 14 SE +/- 49.30, N = 3 SE +/- 157.39, N = 15 SE +/- 179.55, N = 12 SE +/- 135.96, N = 15 SE +/- 8.85, N = 3 SE +/- 3.02, N = 3 SE +/- 46.80, N = 15 SE +/- 6.92, N = 3 SE +/- 22.88, N = 15 SE +/- 8.24, N = 3 SE +/- 24.63, N = 15 9581.06 9507.95 7961.64 7811.99 6242.21 6104.27 5725.79 4490.86 3522.44 2991.73 2965.29 2192.82 1769.46 1473.31 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: Garlicoin EPYC 7662 EPYC 7702 EPYC 7552 EPYC 7542 EPYC 7642 EPYC 7502P EPYC 7532 EPYC 7402P EPYC 7282 EPYC 7302P EPYC 7272 EPYC 7F52 EPYC 7232P EPYC 7F32 20 40 60 80 100 105.24 101.85 97.57 89.06 88.03 86.48 63.17 62.91 52.46 45.58 41.66 33.55 31.40 27.22
Result Confidence
OpenBenchmarking.org kH/s, More Is Better Cpuminer-Opt 3.15.5 Algorithm: Garlicoin EPYC 7702 EPYC 7662 EPYC 7642 EPYC 7552 EPYC 7542 EPYC 7502P EPYC 7532 EPYC 7402P EPYC 7F52 EPYC 7282 EPYC 7302P EPYC 7272 EPYC 7F32 EPYC 7232P 1700 3400 5100 6800 8500 Min: 9331.1 / Avg: 9581.06 / Max: 12370 Min: 9387.02 / Avg: 9507.95 / Max: 10330 Min: 7778.26 / Avg: 7961.64 / Max: 9440.93 Min: 7760.8 / Avg: 7811.99 / Max: 7910.57 Min: 5942.72 / Avg: 6242.21 / Max: 7690.85 Min: 5581 / Avg: 6104.27 / Max: 7538.77 Min: 5501.12 / Avg: 5725.79 / Max: 7108.86 Min: 4477.91 / Avg: 4490.86 / Max: 4507.79 Min: 3516.78 / Avg: 3522.44 / Max: 3527.08 Min: 2871.77 / Avg: 2991.73 / Max: 3335.77 Min: 2956.9 / Avg: 2965.29 / Max: 2979.02 Min: 2113.61 / Avg: 2192.82 / Max: 2419.18 Min: 1758.86 / Avg: 1769.46 / Max: 1785.69 Min: 1428.33 / Avg: 1473.31 / Max: 1776.69 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 7662 EPYC 7702 EPYC 7552 EPYC 7642 EPYC 7502P EPYC 7542 EPYC 7402P EPYC 7532 EPYC 7282 EPYC 7302P EPYC 7272 EPYC 7232P EPYC 7F52 EPYC 7F32 3 6 9 12 15 9.95 9.94 8.88 7.80 7.53 7.25 7.07 5.88 4.95 4.46 3.88 3.24 2.99 2.72
Result
OpenBenchmarking.org kH/s, More Is Better Cpuminer-Opt 3.15.5 Algorithm: x25x EPYC 7662 EPYC 7702 EPYC 7642 EPYC 7552 EPYC 7542 EPYC 7502P EPYC 7402P EPYC 7532 EPYC 7F52 EPYC 7302P EPYC 7282 EPYC 7272 EPYC 7F32 EPYC 7232P 300 600 900 1200 1500 SE +/- 32.30, N = 15 SE +/- 29.63, N = 14 SE +/- 1.46, N = 3 SE +/- 11.98, N = 15 SE +/- 2.23, N = 3 SE +/- 37.08, N = 15 SE +/- 39.35, N = 15 SE +/- 0.86, N = 3 SE +/- 1.25, N = 3 SE +/- 0.74, N = 3 SE +/- 1.04, N = 3 SE +/- 0.69, N = 3 SE +/- 1.31, N = 3 SE +/- 1.33, N = 3 1398.77 1360.06 1147.36 1139.38 891.02 883.87 862.81 807.02 524.31 447.01 429.51 322.83 262.90 216.58 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 7662 EPYC 7702 EPYC 7552 EPYC 7642 EPYC 7502P EPYC 7542 EPYC 7402P EPYC 7532 EPYC 7282 EPYC 7302P EPYC 7272 EPYC 7232P EPYC 7F52 EPYC 7F32 3 6 9 12 15 9.95 9.94 8.88 7.80 7.53 7.25 7.07 5.88 4.95 4.46 3.88 3.24 2.99 2.72
Result Confidence
OpenBenchmarking.org kH/s, More Is Better Cpuminer-Opt 3.15.5 Algorithm: x25x EPYC 7662 EPYC 7702 EPYC 7642 EPYC 7552 EPYC 7542 EPYC 7502P EPYC 7402P EPYC 7532 EPYC 7F52 EPYC 7302P EPYC 7282 EPYC 7272 EPYC 7F32 EPYC 7232P 200 400 600 800 1000 Min: 1361.4 / Avg: 1398.77 / Max: 1850.16 Min: 1313.18 / Avg: 1360.06 / Max: 1735.96 Min: 1144.44 / Avg: 1147.36 / Max: 1148.92 Min: 1114.29 / Avg: 1139.38 / Max: 1274.78 Min: 887.85 / Avg: 891.02 / Max: 895.31 Min: 822.42 / Avg: 883.87 / Max: 1393.5 Min: 675.58 / Avg: 862.81 / Max: 1074.46 Min: 806.02 / Avg: 807.02 / Max: 808.73 Min: 521.85 / Avg: 524.31 / Max: 525.94 Min: 445.61 / Avg: 447.01 / Max: 448.15 Min: 427.95 / Avg: 429.51 / Max: 431.48 Min: 321.57 / Avg: 322.83 / Max: 323.96 Min: 260.27 / Avg: 262.9 / Max: 264.3 Min: 214.04 / Avg: 216.58 / Max: 218.55 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 7702 EPYC 7662 EPYC 7642 EPYC 7532 EPYC 7552 EPYC 7302P EPYC 7502P EPYC 7542 EPYC 7402P EPYC 7282 EPYC 7272 EPYC 7F52 EPYC 7F32 EPYC 7232P 3 6 9 12 15 SE +/- 0.025502, N = 9 SE +/- 0.021316, N = 15 SE +/- 0.024850, N = 7 SE +/- 0.046959, N = 15 SE +/- 0.017804, N = 7 SE +/- 0.040278, N = 15 SE +/- 0.076520, N = 15 SE +/- 0.076268, N = 15 SE +/- 0.017882, N = 6 SE +/- 0.040723, N = 15 SE +/- 0.172857, N = 15 SE +/- 0.084885, N = 6 SE +/- 0.288514, N = 15 SE +/- 0.312883, N = 14 3.086435 3.100122 3.194662 3.621507 3.779568 4.176971 4.246361 4.395850 4.572591 5.758925 7.631597 8.683131 9.844102 10.635023 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 7702 EPYC 7662 EPYC 7642 EPYC 7532 EPYC 7552 EPYC 7302P EPYC 7502P EPYC 7542 EPYC 7402P EPYC 7282 EPYC 7272 EPYC 7F52 EPYC 7F32 EPYC 7232P 3 6 9 12 15 Min: 2.96 / Avg: 3.09 / Max: 3.21 Min: 2.98 / Avg: 3.1 / Max: 3.25 Min: 3.06 / Avg: 3.19 / Max: 3.27 Min: 3.4 / Avg: 3.62 / Max: 3.93 Min: 3.72 / Avg: 3.78 / Max: 3.86 Min: 4 / Avg: 4.18 / Max: 4.54 Min: 3.7 / Avg: 4.25 / Max: 4.54 Min: 3.64 / Avg: 4.4 / Max: 4.73 Min: 4.53 / Avg: 4.57 / Max: 4.63 Min: 5.51 / Avg: 5.76 / Max: 6.05 Min: 5.38 / Avg: 7.63 / Max: 8.15 Min: 8.26 / Avg: 8.68 / Max: 8.8 Min: 6.2 / Avg: 9.84 / Max: 10.6 Min: 6.84 / Avg: 10.64 / Max: 11.74 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 7402P EPYC 7532 EPYC 7552 EPYC 7642 EPYC 7302P EPYC 7542 EPYC 7662 EPYC 7502P EPYC 7272 EPYC 7702 EPYC 7282 EPYC 7232P EPYC 7F32 EPYC 7F52 400K 800K 1200K 1600K 2000K 1932212.23 1673190.41 1673028.98 1663875.88 1638766.48 1635500.08 1604877.74 1575405.35 1508621.96 1423158.29 1357552.35 1349588.10 1163515.81 514628.71
Result
OpenBenchmarking.org Throughput FoM, More Is Better Kripke 1.2.4 EPYC 7642 EPYC 7532 EPYC 7662 EPYC 7552 EPYC 7402P EPYC 7702 EPYC 7542 EPYC 7502P EPYC 7302P EPYC 7F32 EPYC 7272 EPYC 7282 EPYC 7232P EPYC 7F52 50M 100M 150M 200M 250M SE +/- 5572341.62, N = 12 SE +/- 5452949.69, N = 15 SE +/- 2208966.30, N = 15 SE +/- 1883204.11, N = 15 SE +/- 481377.88, N = 4 SE +/- 2966178.44, N = 15 SE +/- 3811837.38, N = 15 SE +/- 2175939.87, N = 3 SE +/- 3144064.63, N = 15 SE +/- 1036502.10, N = 15 SE +/- 1366026.89, N = 3 SE +/- 927929.45, N = 9 SE +/- 1075776.09, N = 4 SE +/- 574642.20, N = 15 230851783 216525133 215771227 211310307 209811150 199683960 187397007 176798867 162898387 129536920 121256433 112489722 100898758 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 7402P EPYC 7532 EPYC 7552 EPYC 7642 EPYC 7302P EPYC 7542 EPYC 7662 EPYC 7502P EPYC 7272 EPYC 7702 EPYC 7282 EPYC 7232P EPYC 7F32 EPYC 7F52 400K 800K 1200K 1600K 2000K 1932212.23 1673190.41 1673028.98 1663875.88 1638766.48 1635500.08 1604877.74 1575405.35 1508621.96 1423158.29 1357552.35 1349588.10 1163515.81 514628.71
Result Confidence
OpenBenchmarking.org Throughput FoM, More Is Better Kripke 1.2.4 EPYC 7642 EPYC 7532 EPYC 7662 EPYC 7552 EPYC 7402P EPYC 7702 EPYC 7542 EPYC 7502P EPYC 7302P EPYC 7F32 EPYC 7272 EPYC 7282 EPYC 7232P EPYC 7F52 40M 80M 120M 160M 200M Min: 196106600 / Avg: 230851783.33 / Max: 255760700 Min: 170848300 / Avg: 216525133.33 / Max: 232847700 Min: 199388700 / Avg: 215771226.67 / Max: 228027900 Min: 200163900 / Avg: 211310306.67 / Max: 221141000 Min: 208902500 / Avg: 209811150 / Max: 211002600 Min: 179253900 / Avg: 199683960 / Max: 214308000 Min: 160767700 / Avg: 187397006.67 / Max: 215708300 Min: 172473100 / Avg: 176798866.67 / Max: 179374000 Min: 148262800 / Avg: 162898386.67 / Max: 178935200 Min: 124322100 / Avg: 129536920 / Max: 133041300 Min: 119380500 / Avg: 121256433.33 / Max: 123914500 Min: 107412100 / Avg: 112489722.22 / Max: 117685700 Min: 97675130 / Avg: 100898757.5 / Max: 102097200 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.