AMD EPYC 7343 16-Core testing with a Supermicro H12SSL-i v1.02 (2.4 BIOS) and astdrmfb on AlmaLinux 9.1 via the Phoronix Test Suite.
Compare your own system(s) to this result file with the
Phoronix Test Suite by running the command:
phoronix-test-suite benchmark 2304307-NE-EPYCLAST283 epyc last - Phoronix Test Suite epyc last AMD EPYC 7343 16-Core testing with a Supermicro H12SSL-i v1.02 (2.4 BIOS) and astdrmfb on AlmaLinux 9.1 via the Phoronix Test Suite.
HTML result view exported from: https://openbenchmarking.org/result/2304307-NE-EPYCLAST283&rdt&grr .
epyc last Processor Motherboard Memory Disk Graphics Monitor OS Kernel Compiler File-System Screen Resolution a b c d AMD EPYC 7343 16-Core @ 3.20GHz (16 Cores / 32 Threads) Supermicro H12SSL-i v1.02 (2.4 BIOS) 8 x 64 GB DDR4-3200MT/s Samsung M393A8G40AB2-CWE 2 x 1920GB SAMSUNG MZQL21T9HCJR-00A07 astdrmfb DELL E207WFP AlmaLinux 9.1 5.14.0-162.12.1.el9_1.x86_64 (x86_64) GCC 11.3.1 20220421 ext4 1680x1050 OpenBenchmarking.org Kernel Details - Transparent Huge Pages: always Compiler Details - --build=x86_64-redhat-linux --disable-libunwind-exceptions --enable-__cxa_atexit --enable-bootstrap --enable-cet --enable-checking=release --enable-gnu-indirect-function --enable-gnu-unique-object --enable-host-bind-now --enable-host-pie --enable-initfini-array --enable-languages=c,c++,fortran,lto --enable-link-serialization=1 --enable-multilib --enable-offload-targets=nvptx-none --enable-plugin --enable-shared --enable-threads=posix --mandir=/usr/share/man --with-arch_32=x86-64 --with-arch_64=x86-64-v2 --with-build-config=bootstrap-lto --with-gcc-major-version-only --with-linker-hash-style=gnu --with-tune=generic --without-cuda-driver --without-isl Disk Details - NONE / relatime,rw,stripe=32 / raid1 nvme1n1p3[0] nvme0n1p3[1] Block Size: 4096 Processor Details - Scaling Governor: acpi-cpufreq performance (Boost: Enabled) - CPU Microcode: 0xa001173 Python Details - Python 3.9.14 Security Details - itlb_multihit: Not affected + l1tf: Not affected + mds: Not affected + meltdown: Not affected + mmio_stale_data: Not affected + retbleed: Not affected + spec_store_bypass: Mitigation of SSB disabled via prctl + spectre_v1: Mitigation of usercopy/swapgs barriers and __user pointer sanitization + spectre_v2: Mitigation of Retpolines IBPB: conditional IBRS_FW STIBP: always-on RSB filling PBRSB-eIBRS: Not affected + srbds: Not affected + tsx_async_abort: Not affected
epyc last intel-tensorflow: mobilenetv1_fp32_pretrained_model - 960 intel-tensorflow: inceptionv4_fp32_pretrained_model - 960 intel-tensorflow: mobilenetv1_fp32_pretrained_model - 512 intel-tensorflow: mobilenetv1_int8_pretrained_model - 960 intel-tensorflow: inceptionv4_fp32_pretrained_model - 512 intel-tensorflow: inceptionv4_int8_pretrained_model - 960 intel-tensorflow: mobilenetv1_fp32_pretrained_model - 256 intel-tensorflow: mobilenetv1_int8_pretrained_model - 512 intel-tensorflow: resnet50_fp32_pretrained_model - 960 intel-tensorflow: inceptionv4_fp32_pretrained_model - 256 intel-tensorflow: inceptionv4_int8_pretrained_model - 512 intel-tensorflow: resnet50_fp32_pretrained_model - 512 intel-tensorflow: mobilenetv1_int8_pretrained_model - 256 intel-tensorflow: mobilenetv1_fp32_pretrained_model - 96 intel-tensorflow: inceptionv4_int8_pretrained_model - 256 intel-tensorflow: resnet50_int8_pretrained_model - 960 intel-tensorflow: resnet50_fp32_pretrained_model - 256 intel-tensorflow: inceptionv4_fp32_pretrained_model - 96 intel-tensorflow: mobilenetv1_fp32_pretrained_model - 64 intel-tensorflow: inceptionv4_fp32_pretrained_model - 64 intel-tensorflow: resnet50_fp32_pretrained_model - 96 intel-tensorflow: resnet50_int8_pretrained_model - 512 intel-tensorflow: mobilenetv1_int8_pretrained_model - 96 influxdb: 4 - 10000 - 2,5000,1 - 10000 influxdb: 64 - 10000 - 2,5000,1 - 10000 intel-tensorflow: resnet50_fp32_pretrained_model - 64 intel-tensorflow: inceptionv4_int8_pretrained_model - 96 intel-tensorflow: resnet50_fp32_pretrained_model - 32 intel-tensorflow: mobilenetv1_fp32_pretrained_model - 32 intel-tensorflow: resnet50_fp32_pretrained_model - 16 intel-tensorflow: mobilenetv1_int8_pretrained_model - 64 intel-tensorflow: resnet50_fp32_pretrained_model - 1 intel-tensorflow: resnet50_fp32_pretrained_model - 1 svt-av1: Preset 4 - Bosphorus 4K intel-tensorflow: mobilenetv1_int8_pretrained_model - 32 intel-tensorflow: inceptionv4_fp32_pretrained_model - 32 intel-tensorflow: resnet50_int8_pretrained_model - 256 intel-tensorflow: inceptionv4_int8_pretrained_model - 64 intel-tensorflow: mobilenetv1_fp32_pretrained_model - 16 quantlib: intel-tensorflow: inceptionv4_int8_pretrained_model - 32 sqlite: 16 intel-tensorflow: inceptionv4_fp32_pretrained_model - 16 svt-av1: Preset 4 - Bosphorus 1080p intel-tensorflow: resnet50_int8_pretrained_model - 96 intel-tensorflow: inceptionv4_int8_pretrained_model - 16 intel-tensorflow: mobilenetv1_int8_pretrained_model - 16 intel-tensorflow: resnet50_int8_pretrained_model - 64 svt-av1: Preset 8 - Bosphorus 4K sqlite: 32 intel-tensorflow: resnet50_int8_pretrained_model - 32 sqlite: 4 intel-tensorflow: mobilenetv1_fp32_pretrained_model - 1 intel-tensorflow: resnet50_int8_pretrained_model - 16 intel-tensorflow: inceptionv4_int8_pretrained_model - 1 intel-tensorflow: inceptionv4_int8_pretrained_model - 1 svt-av1: Preset 8 - Bosphorus 1080p intel-tensorflow: resnet50_int8_pretrained_model - 1 intel-tensorflow: resnet50_int8_pretrained_model - 1 intel-tensorflow: inceptionv4_fp32_pretrained_model - 1 intel-tensorflow: inceptionv4_fp32_pretrained_model - 1 intel-tensorflow: mobilenetv1_int8_pretrained_model - 1 sqlite: 8 svt-av1: Preset 13 - Bosphorus 4K svt-av1: Preset 12 - Bosphorus 4K sqlite: 2 svt-av1: Preset 12 - Bosphorus 1080p svt-av1: Preset 13 - Bosphorus 1080p a b c d 983.76 51.76 976.58 2133.18 51.76 120.74 1001.61 2170.09 168.721 51.92 119.90 168.371 2090.97 990.35 119.18 391.680 167.968 51.83 998.43 52.44 169.726 383.615 2083.55 1547894.4 1602099.9 170.509 118.25 174.040 981.32 168.744 2112.33 12.613 79.283 3.766 2056.18 53.10 382.093 118.48 932.19 3202.1 117.00 8.476 53.20 9.027 373.126 113.31 2003.49 365.095 52.582 11.321 356.317 3.178 1045.59 346.017 14.436 69.04 95.925 4.508 221.855 30.817 32.23 1933.37 5.065 160.501 174.519 2.150 547.498 548.007 982.71 51.78 974.84 2128.1 51.87 120.94 1000.28 2179.09 169.729 52.07 119.61 168.641 2106.54 986.72 119.18 392.07 167.998 51.72 997.73 52.40 169.649 385.546 2081.87 1545780.8 1593776.4 170.516 119.097759734 174.303 984.41 171.632 2120.77 12.535 79.776 3.782 2110.19 52.91 380.652 118.93 929.58 3206.1 117.81 6.209 53.47 9.064 373.723 111.63 2002.09 364.043 51.982 11.811 361.362 2.938 1048.2 347.926 14.415 69.16 95.707 4.509 221.769 30.475 33.16 1932.47 3.856 160.664 175.683 2.041 542.028 542.625 982.46 51.59 976.22 2137.2 51.77 120.74 1001.43 2161.98 170.093 52.06 119.91 168.788 2028.82 988.15 119.33 392.383 168.055 51.90 999.93 51.72 169.971 385.5 2087.39 1552035.6 1599391.9 170.603 119.82 174.255 982.66 171.049 2063.78 12.502 79.988 3.791 2037.86 53.11 381.064 117.61 933.76 3200.7 116.93 7.198 52.99 9.121 372.933 113.63 1989 365.003 52.523 11.743 357.714 2.904 1046.79 348.365 14.426 69.01 96.329 4.622 216.369 30.647 32.06 1933.58 3.966 160.139 172.696 2.106 535.678 545.864 984.36 51.62 974.69 2132.29 51.76 120.57 1001.3 2171.79 169.338 52.04 120.56 168.365 2091.6 988.72 119.45 391.383 168.16 52.00 999.92 51.97 169.31 384.26 2071.18 1560758 1600346.9 170.261 118.23 172.269 981.61 169.333 2091.66 12.466 80.218 3.784 2033.57 53.27 380.015 119.83 931.22 3192.7 117.89 6.075 53.22 9.28 372.928 113.36 1984.38 365.305 52.572 11.598 357.035 2.712 1046.4 344.868 14.377 69.07 95.648 4.596 217.593 30.723 31.86 1934.32 3.761 159.521 174.836 2.039 539.588 547.432 OpenBenchmarking.org
Intel TensorFlow Model: mobilenetv1_fp32_pretrained_model - Batch Size: 960 OpenBenchmarking.org images/sec, More Is Better Intel TensorFlow 2.12 Model: mobilenetv1_fp32_pretrained_model - Batch Size: 960 a b c d 200 400 600 800 1000 SE +/- 0.13, N = 3 983.76 982.71 982.46 984.36
Intel TensorFlow Model: inceptionv4_fp32_pretrained_model - Batch Size: 960 OpenBenchmarking.org images/sec, More Is Better Intel TensorFlow 2.12 Model: inceptionv4_fp32_pretrained_model - Batch Size: 960 a b c d 12 24 36 48 60 SE +/- 0.11, N = 3 51.76 51.78 51.59 51.62
Intel TensorFlow Model: mobilenetv1_fp32_pretrained_model - Batch Size: 512 OpenBenchmarking.org images/sec, More Is Better Intel TensorFlow 2.12 Model: mobilenetv1_fp32_pretrained_model - Batch Size: 512 a b c d 200 400 600 800 1000 SE +/- 0.75, N = 3 976.58 974.84 976.22 974.69
Intel TensorFlow Model: mobilenetv1_int8_pretrained_model - Batch Size: 960 OpenBenchmarking.org images/sec, More Is Better Intel TensorFlow 2.12 Model: mobilenetv1_int8_pretrained_model - Batch Size: 960 a b c d 500 1000 1500 2000 2500 SE +/- 2.58, N = 3 2133.18 2128.10 2137.20 2132.29
Intel TensorFlow Model: inceptionv4_fp32_pretrained_model - Batch Size: 512 OpenBenchmarking.org images/sec, More Is Better Intel TensorFlow 2.12 Model: inceptionv4_fp32_pretrained_model - Batch Size: 512 a b c d 12 24 36 48 60 SE +/- 0.05, N = 3 51.76 51.87 51.77 51.76
Intel TensorFlow Model: inceptionv4_int8_pretrained_model - Batch Size: 960 OpenBenchmarking.org images/sec, More Is Better Intel TensorFlow 2.12 Model: inceptionv4_int8_pretrained_model - Batch Size: 960 a b c d 30 60 90 120 150 SE +/- 0.16, N = 3 120.74 120.94 120.74 120.57
Intel TensorFlow Model: mobilenetv1_fp32_pretrained_model - Batch Size: 256 OpenBenchmarking.org images/sec, More Is Better Intel TensorFlow 2.12 Model: mobilenetv1_fp32_pretrained_model - Batch Size: 256 a b c d 200 400 600 800 1000 SE +/- 0.11, N = 3 1001.61 1000.28 1001.43 1001.30
Intel TensorFlow Model: mobilenetv1_int8_pretrained_model - Batch Size: 512 OpenBenchmarking.org images/sec, More Is Better Intel TensorFlow 2.12 Model: mobilenetv1_int8_pretrained_model - Batch Size: 512 a b c d 500 1000 1500 2000 2500 SE +/- 2.76, N = 3 2170.09 2179.09 2161.98 2171.79
Intel TensorFlow Model: resnet50_fp32_pretrained_model - Batch Size: 960 OpenBenchmarking.org images/sec, More Is Better Intel TensorFlow 2.12 Model: resnet50_fp32_pretrained_model - Batch Size: 960 a b c d 40 80 120 160 200 SE +/- 0.30, N = 3 168.72 169.73 170.09 169.34
Intel TensorFlow Model: inceptionv4_fp32_pretrained_model - Batch Size: 256 OpenBenchmarking.org images/sec, More Is Better Intel TensorFlow 2.12 Model: inceptionv4_fp32_pretrained_model - Batch Size: 256 a b c d 12 24 36 48 60 SE +/- 0.02, N = 3 51.92 52.07 52.06 52.04
Intel TensorFlow Model: inceptionv4_int8_pretrained_model - Batch Size: 512 OpenBenchmarking.org images/sec, More Is Better Intel TensorFlow 2.12 Model: inceptionv4_int8_pretrained_model - Batch Size: 512 a b c d 30 60 90 120 150 SE +/- 0.14, N = 3 119.90 119.61 119.91 120.56
Intel TensorFlow Model: resnet50_fp32_pretrained_model - Batch Size: 512 OpenBenchmarking.org images/sec, More Is Better Intel TensorFlow 2.12 Model: resnet50_fp32_pretrained_model - Batch Size: 512 a b c d 40 80 120 160 200 SE +/- 0.21, N = 3 168.37 168.64 168.79 168.37
Intel TensorFlow Model: mobilenetv1_int8_pretrained_model - Batch Size: 256 OpenBenchmarking.org images/sec, More Is Better Intel TensorFlow 2.12 Model: mobilenetv1_int8_pretrained_model - Batch Size: 256 a b c d 500 1000 1500 2000 2500 SE +/- 14.60, N = 3 2090.97 2106.54 2028.82 2091.60
Intel TensorFlow Model: mobilenetv1_fp32_pretrained_model - Batch Size: 96 OpenBenchmarking.org images/sec, More Is Better Intel TensorFlow 2.12 Model: mobilenetv1_fp32_pretrained_model - Batch Size: 96 a b c d 200 400 600 800 1000 SE +/- 1.26, N = 3 990.35 986.72 988.15 988.72
Intel TensorFlow Model: inceptionv4_int8_pretrained_model - Batch Size: 256 OpenBenchmarking.org images/sec, More Is Better Intel TensorFlow 2.12 Model: inceptionv4_int8_pretrained_model - Batch Size: 256 a b c d 30 60 90 120 150 SE +/- 0.27, N = 3 119.18 119.18 119.33 119.45
Intel TensorFlow Model: resnet50_int8_pretrained_model - Batch Size: 960 OpenBenchmarking.org images/sec, More Is Better Intel TensorFlow 2.12 Model: resnet50_int8_pretrained_model - Batch Size: 960 a b c d 90 180 270 360 450 SE +/- 0.57, N = 3 391.68 392.07 392.38 391.38
Intel TensorFlow Model: resnet50_fp32_pretrained_model - Batch Size: 256 OpenBenchmarking.org images/sec, More Is Better Intel TensorFlow 2.12 Model: resnet50_fp32_pretrained_model - Batch Size: 256 a b c d 40 80 120 160 200 SE +/- 0.12, N = 3 167.97 168.00 168.06 168.16
Intel TensorFlow Model: inceptionv4_fp32_pretrained_model - Batch Size: 96 OpenBenchmarking.org images/sec, More Is Better Intel TensorFlow 2.12 Model: inceptionv4_fp32_pretrained_model - Batch Size: 96 a b c d 12 24 36 48 60 SE +/- 0.07, N = 3 51.83 51.72 51.90 52.00
Intel TensorFlow Model: mobilenetv1_fp32_pretrained_model - Batch Size: 64 OpenBenchmarking.org images/sec, More Is Better Intel TensorFlow 2.12 Model: mobilenetv1_fp32_pretrained_model - Batch Size: 64 a b c d 200 400 600 800 1000 SE +/- 0.55, N = 3 998.43 997.73 999.93 999.92
Intel TensorFlow Model: inceptionv4_fp32_pretrained_model - Batch Size: 64 OpenBenchmarking.org images/sec, More Is Better Intel TensorFlow 2.12 Model: inceptionv4_fp32_pretrained_model - Batch Size: 64 a b c d 12 24 36 48 60 SE +/- 0.12, N = 3 52.44 52.40 51.72 51.97
Intel TensorFlow Model: resnet50_fp32_pretrained_model - Batch Size: 96 OpenBenchmarking.org images/sec, More Is Better Intel TensorFlow 2.12 Model: resnet50_fp32_pretrained_model - Batch Size: 96 a b c d 40 80 120 160 200 SE +/- 0.11, N = 3 169.73 169.65 169.97 169.31
Intel TensorFlow Model: resnet50_int8_pretrained_model - Batch Size: 512 OpenBenchmarking.org images/sec, More Is Better Intel TensorFlow 2.12 Model: resnet50_int8_pretrained_model - Batch Size: 512 a b c d 80 160 240 320 400 SE +/- 0.21, N = 3 383.62 385.55 385.50 384.26
Intel TensorFlow Model: mobilenetv1_int8_pretrained_model - Batch Size: 96 OpenBenchmarking.org images/sec, More Is Better Intel TensorFlow 2.12 Model: mobilenetv1_int8_pretrained_model - Batch Size: 96 a b c d 400 800 1200 1600 2000 SE +/- 2.02, N = 3 2083.55 2081.87 2087.39 2071.18
InfluxDB Concurrent Streams: 4 - Batch Size: 10000 - Tags: 2,5000,1 - Points Per Series: 10000 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 a b c d 300K 600K 900K 1200K 1500K SE +/- 5338.36, N = 3 1547894.4 1545780.8 1552035.6 1560758.0
InfluxDB Concurrent Streams: 64 - Batch Size: 10000 - Tags: 2,5000,1 - Points Per Series: 10000 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 a b c d 300K 600K 900K 1200K 1500K SE +/- 3918.66, N = 3 1602099.9 1593776.4 1599391.9 1600346.9
Intel TensorFlow Model: resnet50_fp32_pretrained_model - Batch Size: 64 OpenBenchmarking.org images/sec, More Is Better Intel TensorFlow 2.12 Model: resnet50_fp32_pretrained_model - Batch Size: 64 a b c d 40 80 120 160 200 SE +/- 0.12, N = 3 170.51 170.52 170.60 170.26
Intel TensorFlow Model: inceptionv4_int8_pretrained_model - Batch Size: 96 OpenBenchmarking.org images/sec, More Is Better Intel TensorFlow 2.12 Model: inceptionv4_int8_pretrained_model - Batch Size: 96 a b c d 30 60 90 120 150 SE +/- 0.42, N = 3 118.25 119.10 119.82 118.23
Intel TensorFlow Model: resnet50_fp32_pretrained_model - Batch Size: 32 OpenBenchmarking.org images/sec, More Is Better Intel TensorFlow 2.12 Model: resnet50_fp32_pretrained_model - Batch Size: 32 a b c d 40 80 120 160 200 SE +/- 0.31, N = 3 174.04 174.30 174.26 172.27
Intel TensorFlow Model: mobilenetv1_fp32_pretrained_model - Batch Size: 32 OpenBenchmarking.org images/sec, More Is Better Intel TensorFlow 2.12 Model: mobilenetv1_fp32_pretrained_model - Batch Size: 32 a b c d 200 400 600 800 1000 SE +/- 1.14, N = 3 981.32 984.41 982.66 981.61
Intel TensorFlow Model: resnet50_fp32_pretrained_model - Batch Size: 16 OpenBenchmarking.org images/sec, More Is Better Intel TensorFlow 2.12 Model: resnet50_fp32_pretrained_model - Batch Size: 16 a b c d 40 80 120 160 200 SE +/- 0.83, N = 3 168.74 171.63 171.05 169.33
Intel TensorFlow Model: mobilenetv1_int8_pretrained_model - Batch Size: 64 OpenBenchmarking.org images/sec, More Is Better Intel TensorFlow 2.12 Model: mobilenetv1_int8_pretrained_model - Batch Size: 64 a b c d 500 1000 1500 2000 2500 SE +/- 10.67, N = 3 2112.33 2120.77 2063.78 2091.66
Intel TensorFlow Model: resnet50_fp32_pretrained_model - Batch Size: 1 OpenBenchmarking.org ms, Fewer Is Better Intel TensorFlow 2.12 Model: resnet50_fp32_pretrained_model - Batch Size: 1 a b c d 3 6 9 12 15 SE +/- 0.01, N = 3 12.61 12.54 12.50 12.47
Intel TensorFlow Model: resnet50_fp32_pretrained_model - Batch Size: 1 OpenBenchmarking.org images/sec, More Is Better Intel TensorFlow 2.12 Model: resnet50_fp32_pretrained_model - Batch Size: 1 a b c d 20 40 60 80 100 SE +/- 0.09, N = 3 79.28 79.78 79.99 80.22
SVT-AV1 Encoder Mode: Preset 4 - Input: Bosphorus 4K OpenBenchmarking.org Frames Per Second, More Is Better SVT-AV1 1.5 Encoder Mode: Preset 4 - Input: Bosphorus 4K a b c d 0.853 1.706 2.559 3.412 4.265 SE +/- 0.019, N = 3 3.766 3.782 3.791 3.784 1. (CXX) g++ options: -march=native -mno-avx -mavx2 -mavx512f -mavx512bw -mavx512dq
Intel TensorFlow Model: mobilenetv1_int8_pretrained_model - Batch Size: 32 OpenBenchmarking.org images/sec, More Is Better Intel TensorFlow 2.12 Model: mobilenetv1_int8_pretrained_model - Batch Size: 32 a b c d 500 1000 1500 2000 2500 SE +/- 19.33, N = 7 2056.18 2110.19 2037.86 2033.57
Intel TensorFlow Model: inceptionv4_fp32_pretrained_model - Batch Size: 32 OpenBenchmarking.org images/sec, More Is Better Intel TensorFlow 2.12 Model: inceptionv4_fp32_pretrained_model - Batch Size: 32 a b c d 12 24 36 48 60 SE +/- 0.09, N = 3 53.10 52.91 53.11 53.27
Intel TensorFlow Model: resnet50_int8_pretrained_model - Batch Size: 256 OpenBenchmarking.org images/sec, More Is Better Intel TensorFlow 2.12 Model: resnet50_int8_pretrained_model - Batch Size: 256 a b c d 80 160 240 320 400 SE +/- 0.54, N = 3 382.09 380.65 381.06 380.02
Intel TensorFlow Model: inceptionv4_int8_pretrained_model - Batch Size: 64 OpenBenchmarking.org images/sec, More Is Better Intel TensorFlow 2.12 Model: inceptionv4_int8_pretrained_model - Batch Size: 64 a b c d 30 60 90 120 150 SE +/- 0.54, N = 3 118.48 118.93 117.61 119.83
Intel TensorFlow Model: mobilenetv1_fp32_pretrained_model - Batch Size: 16 OpenBenchmarking.org images/sec, More Is Better Intel TensorFlow 2.12 Model: mobilenetv1_fp32_pretrained_model - Batch Size: 16 a b c d 200 400 600 800 1000 SE +/- 0.39, N = 3 932.19 929.58 933.76 931.22
QuantLib OpenBenchmarking.org MFLOPS, More Is Better QuantLib 1.30 a b c d 700 1400 2100 2800 3500 SE +/- 1.35, N = 3 3202.1 3206.1 3200.7 3192.7 1. (CXX) g++ options: -O3 -march=native -fPIE -pie
Intel TensorFlow Model: inceptionv4_int8_pretrained_model - Batch Size: 32 OpenBenchmarking.org images/sec, More Is Better Intel TensorFlow 2.12 Model: inceptionv4_int8_pretrained_model - Batch Size: 32 a b c d 30 60 90 120 150 SE +/- 0.81, N = 3 117.00 117.81 116.93 117.89
SQLite Threads / Copies: 16 OpenBenchmarking.org Seconds, Fewer Is Better SQLite 3.41.2 Threads / Copies: 16 a b c d 2 4 6 8 10 SE +/- 0.163, N = 13 8.476 6.209 7.198 6.075 1. (CC) gcc options: -O2 -lz -lm
Intel TensorFlow Model: inceptionv4_fp32_pretrained_model - Batch Size: 16 OpenBenchmarking.org images/sec, More Is Better Intel TensorFlow 2.12 Model: inceptionv4_fp32_pretrained_model - Batch Size: 16 a b c d 12 24 36 48 60 SE +/- 0.07, N = 3 53.20 53.47 52.99 53.22
SVT-AV1 Encoder Mode: Preset 4 - Input: Bosphorus 1080p OpenBenchmarking.org Frames Per Second, More Is Better SVT-AV1 1.5 Encoder Mode: Preset 4 - Input: Bosphorus 1080p a b c d 3 6 9 12 15 SE +/- 0.031, N = 3 9.027 9.064 9.121 9.280 1. (CXX) g++ options: -march=native -mno-avx -mavx2 -mavx512f -mavx512bw -mavx512dq
Intel TensorFlow Model: resnet50_int8_pretrained_model - Batch Size: 96 OpenBenchmarking.org images/sec, More Is Better Intel TensorFlow 2.12 Model: resnet50_int8_pretrained_model - Batch Size: 96 a b c d 80 160 240 320 400 SE +/- 0.27, N = 3 373.13 373.72 372.93 372.93
Intel TensorFlow Model: inceptionv4_int8_pretrained_model - Batch Size: 16 OpenBenchmarking.org images/sec, More Is Better Intel TensorFlow 2.12 Model: inceptionv4_int8_pretrained_model - Batch Size: 16 a b c d 30 60 90 120 150 SE +/- 0.30, N = 3 113.31 111.63 113.63 113.36
Intel TensorFlow Model: mobilenetv1_int8_pretrained_model - Batch Size: 16 OpenBenchmarking.org images/sec, More Is Better Intel TensorFlow 2.12 Model: mobilenetv1_int8_pretrained_model - Batch Size: 16 a b c d 400 800 1200 1600 2000 SE +/- 14.27, N = 3 2003.49 2002.09 1989.00 1984.38
Intel TensorFlow Model: resnet50_int8_pretrained_model - Batch Size: 64 OpenBenchmarking.org images/sec, More Is Better Intel TensorFlow 2.12 Model: resnet50_int8_pretrained_model - Batch Size: 64 a b c d 80 160 240 320 400 SE +/- 0.43, N = 3 365.10 364.04 365.00 365.31
SVT-AV1 Encoder Mode: Preset 8 - Input: Bosphorus 4K OpenBenchmarking.org Frames Per Second, More Is Better SVT-AV1 1.5 Encoder Mode: Preset 8 - Input: Bosphorus 4K a b c d 12 24 36 48 60 SE +/- 0.19, N = 3 52.58 51.98 52.52 52.57 1. (CXX) g++ options: -march=native -mno-avx -mavx2 -mavx512f -mavx512bw -mavx512dq
SQLite Threads / Copies: 32 OpenBenchmarking.org Seconds, Fewer Is Better SQLite 3.41.2 Threads / Copies: 32 a b c d 3 6 9 12 15 SE +/- 0.05, N = 3 11.32 11.81 11.74 11.60 1. (CC) gcc options: -O2 -lz -lm
Intel TensorFlow Model: resnet50_int8_pretrained_model - Batch Size: 32 OpenBenchmarking.org images/sec, More Is Better Intel TensorFlow 2.12 Model: resnet50_int8_pretrained_model - Batch Size: 32 a b c d 80 160 240 320 400 SE +/- 0.47, N = 3 356.32 361.36 357.71 357.04
SQLite Threads / Copies: 4 OpenBenchmarking.org Seconds, Fewer Is Better SQLite 3.41.2 Threads / Copies: 4 a b c d 0.7151 1.4302 2.1453 2.8604 3.5755 SE +/- 0.030, N = 15 3.178 2.938 2.904 2.712 1. (CC) gcc options: -O2 -lz -lm
Intel TensorFlow Model: mobilenetv1_fp32_pretrained_model - Batch Size: 1 OpenBenchmarking.org images/sec, More Is Better Intel TensorFlow 2.12 Model: mobilenetv1_fp32_pretrained_model - Batch Size: 1 a b c d 200 400 600 800 1000 SE +/- 0.98, N = 3 1045.59 1048.20 1046.79 1046.40
Intel TensorFlow Model: resnet50_int8_pretrained_model - Batch Size: 16 OpenBenchmarking.org images/sec, More Is Better Intel TensorFlow 2.12 Model: resnet50_int8_pretrained_model - Batch Size: 16 a b c d 80 160 240 320 400 SE +/- 1.45, N = 3 346.02 347.93 348.37 344.87
Intel TensorFlow Model: inceptionv4_int8_pretrained_model - Batch Size: 1 OpenBenchmarking.org ms, Fewer Is Better Intel TensorFlow 2.12 Model: inceptionv4_int8_pretrained_model - Batch Size: 1 a b c d 4 8 12 16 20 SE +/- 0.03, N = 3 14.44 14.42 14.43 14.38
Intel TensorFlow Model: inceptionv4_int8_pretrained_model - Batch Size: 1 OpenBenchmarking.org images/sec, More Is Better Intel TensorFlow 2.12 Model: inceptionv4_int8_pretrained_model - Batch Size: 1 a b c d 15 30 45 60 75 SE +/- 0.07, N = 3 69.04 69.16 69.01 69.07
SVT-AV1 Encoder Mode: Preset 8 - Input: Bosphorus 1080p OpenBenchmarking.org Frames Per Second, More Is Better SVT-AV1 1.5 Encoder Mode: Preset 8 - Input: Bosphorus 1080p a b c d 20 40 60 80 100 SE +/- 0.42, N = 3 95.93 95.71 96.33 95.65 1. (CXX) g++ options: -march=native -mno-avx -mavx2 -mavx512f -mavx512bw -mavx512dq
Intel TensorFlow Model: resnet50_int8_pretrained_model - Batch Size: 1 OpenBenchmarking.org ms, Fewer Is Better Intel TensorFlow 2.12 Model: resnet50_int8_pretrained_model - Batch Size: 1 a b c d 1.04 2.08 3.12 4.16 5.2 SE +/- 0.032, N = 3 4.508 4.509 4.622 4.596
Intel TensorFlow Model: resnet50_int8_pretrained_model - Batch Size: 1 OpenBenchmarking.org images/sec, More Is Better Intel TensorFlow 2.12 Model: resnet50_int8_pretrained_model - Batch Size: 1 a b c d 50 100 150 200 250 SE +/- 1.58, N = 3 221.86 221.77 216.37 217.59
Intel TensorFlow Model: inceptionv4_fp32_pretrained_model - Batch Size: 1 OpenBenchmarking.org ms, Fewer Is Better Intel TensorFlow 2.12 Model: inceptionv4_fp32_pretrained_model - Batch Size: 1 a b c d 7 14 21 28 35 SE +/- 0.10, N = 3 30.82 30.48 30.65 30.72
Intel TensorFlow Model: inceptionv4_fp32_pretrained_model - Batch Size: 1 OpenBenchmarking.org images/sec, More Is Better Intel TensorFlow 2.12 Model: inceptionv4_fp32_pretrained_model - Batch Size: 1 a b c d 8 16 24 32 40 SE +/- 0.26, N = 3 32.23 33.16 32.06 31.86
Intel TensorFlow Model: mobilenetv1_int8_pretrained_model - Batch Size: 1 OpenBenchmarking.org images/sec, More Is Better Intel TensorFlow 2.12 Model: mobilenetv1_int8_pretrained_model - Batch Size: 1 a b c d 400 800 1200 1600 2000 SE +/- 0.61, N = 3 1933.37 1932.47 1933.58 1934.32
SQLite Threads / Copies: 8 OpenBenchmarking.org Seconds, Fewer Is Better SQLite 3.41.2 Threads / Copies: 8 a b c d 1.1396 2.2792 3.4188 4.5584 5.698 SE +/- 0.038, N = 3 5.065 3.856 3.966 3.761 1. (CC) gcc options: -O2 -lz -lm
SVT-AV1 Encoder Mode: Preset 13 - Input: Bosphorus 4K OpenBenchmarking.org Frames Per Second, More Is Better SVT-AV1 1.5 Encoder Mode: Preset 13 - Input: Bosphorus 4K a b c d 40 80 120 160 200 SE +/- 0.85, N = 3 160.50 160.66 160.14 159.52 1. (CXX) g++ options: -march=native -mno-avx -mavx2 -mavx512f -mavx512bw -mavx512dq
SVT-AV1 Encoder Mode: Preset 12 - Input: Bosphorus 4K OpenBenchmarking.org Frames Per Second, More Is Better SVT-AV1 1.5 Encoder Mode: Preset 12 - Input: Bosphorus 4K a b c d 40 80 120 160 200 SE +/- 0.56, N = 3 174.52 175.68 172.70 174.84 1. (CXX) g++ options: -march=native -mno-avx -mavx2 -mavx512f -mavx512bw -mavx512dq
SQLite Threads / Copies: 2 OpenBenchmarking.org Seconds, Fewer Is Better SQLite 3.41.2 Threads / Copies: 2 a b c d 0.4838 0.9676 1.4514 1.9352 2.419 SE +/- 0.004, N = 3 2.150 2.041 2.106 2.039 1. (CC) gcc options: -O2 -lz -lm
SVT-AV1 Encoder Mode: Preset 12 - Input: Bosphorus 1080p OpenBenchmarking.org Frames Per Second, More Is Better SVT-AV1 1.5 Encoder Mode: Preset 12 - Input: Bosphorus 1080p a b c d 120 240 360 480 600 SE +/- 0.64, N = 3 547.50 542.03 535.68 539.59 1. (CXX) g++ options: -march=native -mno-avx -mavx2 -mavx512f -mavx512bw -mavx512dq
SVT-AV1 Encoder Mode: Preset 13 - Input: Bosphorus 1080p OpenBenchmarking.org Frames Per Second, More Is Better SVT-AV1 1.5 Encoder Mode: Preset 13 - Input: Bosphorus 1080p a b c d 120 240 360 480 600 SE +/- 0.34, N = 3 548.01 542.63 545.86 547.43 1. (CXX) g++ options: -march=native -mno-avx -mavx2 -mavx512f -mavx512bw -mavx512dq
Phoronix Test Suite v10.8.4