pytorch bench

AMD Ryzen Threadripper 3990X 64-Core testing with a Gigabyte TRX40 AORUS PRO WIFI (F6 BIOS) and AMD Radeon RX 5700 8GB on Ubuntu 23.10 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 2311179-PTS-PYTORCHB94
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a
November 16
  5 Hours, 10 Minutes
b
November 17
  1 Hour, 39 Minutes
c
November 17
  1 Hour, 38 Minutes
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  2 Hours, 49 Minutes

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pytorch benchOpenBenchmarking.orgPhoronix Test SuiteAMD Ryzen Threadripper 3990X 64-Core @ 2.90GHz (64 Cores / 128 Threads)Gigabyte TRX40 AORUS PRO WIFI (F6 BIOS)AMD Starship/Matisse128GBSamsung SSD 970 EVO Plus 500GBAMD Radeon RX 5700 8GB (1750/875MHz)AMD Navi 10 HDMI AudioDELL P2415QIntel I211 + Intel Wi-Fi 6 AX200Ubuntu 23.106.5.0-10-generic (x86_64)GNOME Shell 45.0X Server + Wayland4.6 Mesa 23.2.1-1ubuntu3 (LLVM 15.0.7 DRM 3.54)GCC 13.2.0ext43840x2160ProcessorMotherboardChipsetMemoryDiskGraphicsAudioMonitorNetworkOSKernelDesktopDisplay ServerOpenGLCompilerFile-SystemScreen ResolutionPytorch Bench BenchmarksSystem Logs- Transparent Huge Pages: madvise- Scaling Governor: acpi-cpufreq schedutil (Boost: Enabled) - CPU Microcode: 0x830107a- Python 3.11.6- gather_data_sampling: Not affected + itlb_multihit: Not affected + l1tf: Not affected + mds: Not affected + meltdown: Not affected + mmio_stale_data: Not affected + retbleed: Mitigation of untrained return thunk; SMT enabled with STIBP protection + spec_rstack_overflow: Mitigation of safe RET + 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 STIBP: always-on RSB filling PBRSB-eIBRS: Not affected + srbds: Not affected + tsx_async_abort: Not affected

abcResult OverviewPhoronix Test Suite100%103%106%109%PyTorchPyTorchPyTorchPyTorchPyTorchPyTorchPyTorchPyTorchPyTorchPyTorchPyTorchPyTorchPyTorchPyTorchPyTorchPyTorchPyTorchPyTorchCPU - 1 - ResNet-50CPU - 16 - ResNet-50CPU - 256 - ResNet-152CPU - 32 - ResNet-50CPU - 512 - ResNet-50CPU - 16 - Efficientnet_v2_lCPU - 512 - ResNet-152CPU - 256 - Efficientnet_v2_lCPU - 1 - ResNet-152CPU - 1 - Efficientnet_v2_lCPU - 256 - ResNet-50CPU - 512 - Efficientnet_v2_lCPU - 64 - ResNet-152CPU - 64 - ResNet-50CPU - 16 - ResNet-152CPU - 32 - Efficientnet_v2_lCPU - 64 - Efficientnet_v2_lCPU - 32 - ResNet-152

pytorch benchpytorch: CPU - 1 - ResNet-50pytorch: CPU - 16 - ResNet-50pytorch: CPU - 256 - ResNet-152pytorch: CPU - 32 - ResNet-50pytorch: CPU - 512 - ResNet-50pytorch: CPU - 16 - Efficientnet_v2_lpytorch: CPU - 512 - ResNet-152pytorch: CPU - 256 - Efficientnet_v2_lpytorch: CPU - 1 - ResNet-152pytorch: CPU - 1 - Efficientnet_v2_lpytorch: CPU - 256 - ResNet-50pytorch: CPU - 512 - Efficientnet_v2_lpytorch: CPU - 64 - ResNet-152pytorch: CPU - 64 - ResNet-50pytorch: CPU - 16 - ResNet-152pytorch: CPU - 32 - Efficientnet_v2_lpytorch: CPU - 64 - Efficientnet_v2_lpytorch: CPU - 32 - ResNet-152abc20.8816.887.0117.1116.593.076.892.938.224.3616.662.926.8415.966.693.012.966.7818.6316.036.5216.0916.062.906.662.867.804.1716.832.916.8215.996.812.992.926.7619.1815.576.6516.5215.642.936.513.028.034.1616.272.996.6716.356.762.962.966.69OpenBenchmarking.org

PyTorch

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.1Device: CPU - Batch Size: 1 - Model: ResNet-50abc510152025SE +/- 0.27, N = 320.8818.6319.18MIN: 19.27 / MAX: 22.47MIN: 17.58 / MAX: 19.74MIN: 18.22 / MAX: 20.52
OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.1Device: CPU - Batch Size: 1 - Model: ResNet-50abc510152025Min: 20.38 / Avg: 20.88 / Max: 21.31

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.1Device: CPU - Batch Size: 16 - Model: ResNet-50abc48121620SE +/- 0.19, N = 316.8816.0315.57MIN: 15.77 / MAX: 18.22MIN: 14.93 / MAX: 16.68MIN: 14.78 / MAX: 16.29
OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.1Device: CPU - Batch Size: 16 - Model: ResNet-50abc48121620Min: 16.59 / Avg: 16.88 / Max: 17.25

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.1Device: CPU - Batch Size: 256 - Model: ResNet-152abc246810SE +/- 0.05, N = 37.016.526.65MIN: 6.51 / MAX: 7.22MIN: 6.32 / MAX: 6.71MIN: 6.45 / MAX: 6.82
OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.1Device: CPU - Batch Size: 256 - Model: ResNet-152abc3691215Min: 6.92 / Avg: 7.01 / Max: 7.09

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.1Device: CPU - Batch Size: 32 - Model: ResNet-50abc48121620SE +/- 0.20, N = 317.1116.0916.52MIN: 15.92 / MAX: 18.06MIN: 15.44 / MAX: 16.98MIN: 15.52 / MAX: 17.2
OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.1Device: CPU - Batch Size: 32 - Model: ResNet-50abc48121620Min: 16.73 / Avg: 17.11 / Max: 17.41

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.1Device: CPU - Batch Size: 512 - Model: ResNet-50abc48121620SE +/- 0.14, N = 816.5916.0615.64MIN: 15.41 / MAX: 17.89MIN: 14.68 / MAX: 16.72MIN: 15.06 / MAX: 16.39
OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.1Device: CPU - Batch Size: 512 - Model: ResNet-50abc48121620Min: 16.14 / Avg: 16.59 / Max: 17.24

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.1Device: CPU - Batch Size: 16 - Model: Efficientnet_v2_labc0.69081.38162.07242.76323.454SE +/- 0.03, N = 33.072.902.93MIN: 2.85 / MAX: 3.2MIN: 2.73 / MAX: 3.05MIN: 2.82 / MAX: 3.07
OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.1Device: CPU - Batch Size: 16 - Model: Efficientnet_v2_labc246810Min: 3.01 / Avg: 3.07 / Max: 3.1

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.1Device: CPU - Batch Size: 512 - Model: ResNet-152abc246810SE +/- 0.01, N = 36.896.666.51MIN: 6.48 / MAX: 7.08MIN: 6.29 / MAX: 6.85MIN: 6.34 / MAX: 6.69
OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.1Device: CPU - Batch Size: 512 - Model: ResNet-152abc3691215Min: 6.87 / Avg: 6.89 / Max: 6.91

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.1Device: CPU - Batch Size: 256 - Model: Efficientnet_v2_labc0.67951.3592.03852.7183.3975SE +/- 0.02, N = 32.932.863.02MIN: 2.74 / MAX: 3.09MIN: 2.76 / MAX: 2.99MIN: 2.9 / MAX: 3.14
OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.1Device: CPU - Batch Size: 256 - Model: Efficientnet_v2_labc246810Min: 2.88 / Avg: 2.93 / Max: 2.95

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.1Device: CPU - Batch Size: 1 - Model: ResNet-152abc246810SE +/- 0.10, N = 38.227.808.03MIN: 7.88 / MAX: 8.56MIN: 7.62 / MAX: 8.01MIN: 7.82 / MAX: 8.21
OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.1Device: CPU - Batch Size: 1 - Model: ResNet-152abc3691215Min: 8.07 / Avg: 8.22 / Max: 8.4

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.1Device: CPU - Batch Size: 1 - Model: Efficientnet_v2_labc0.9811.9622.9433.9244.905SE +/- 0.04, N = 34.364.174.16MIN: 4.07 / MAX: 4.56MIN: 3.98 / MAX: 4.35MIN: 3.9 / MAX: 4.35
OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.1Device: CPU - Batch Size: 1 - Model: Efficientnet_v2_labc246810Min: 4.27 / Avg: 4.36 / Max: 4.42

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.1Device: CPU - Batch Size: 256 - Model: ResNet-50abc48121620SE +/- 0.21, N = 316.6616.8316.27MIN: 15.65 / MAX: 17.93MIN: 15.98 / MAX: 17.49MIN: 15.45 / MAX: 16.87
OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.1Device: CPU - Batch Size: 256 - Model: ResNet-50abc48121620Min: 16.36 / Avg: 16.66 / Max: 17.07

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.1Device: CPU - Batch Size: 512 - Model: Efficientnet_v2_labc0.67281.34562.01842.69123.364SE +/- 0.02, N = 32.922.912.99MIN: 2.78 / MAX: 3.12MIN: 2.77 / MAX: 3.03MIN: 2.84 / MAX: 3.16
OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.1Device: CPU - Batch Size: 512 - Model: Efficientnet_v2_labc246810Min: 2.89 / Avg: 2.92 / Max: 2.95

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.1Device: CPU - Batch Size: 64 - Model: ResNet-152abc246810SE +/- 0.08, N = 36.846.826.67MIN: 6.51 / MAX: 7.13MIN: 6.66 / MAX: 6.95MIN: 6.48 / MAX: 6.83
OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.1Device: CPU - Batch Size: 64 - Model: ResNet-152abc3691215Min: 6.7 / Avg: 6.84 / Max: 6.98

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.1Device: CPU - Batch Size: 64 - Model: ResNet-50abc48121620SE +/- 0.13, N = 315.9615.9916.35MIN: 14.8 / MAX: 17.08MIN: 15.31 / MAX: 16.83MIN: 15.49 / MAX: 17.11
OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.1Device: CPU - Batch Size: 64 - Model: ResNet-50abc48121620Min: 15.73 / Avg: 15.96 / Max: 16.16

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.1Device: CPU - Batch Size: 16 - Model: ResNet-152abc246810SE +/- 0.06, N = 36.696.816.76MIN: 6.41 / MAX: 6.91MIN: 6.67 / MAX: 7MIN: 6.34 / MAX: 6.95
OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.1Device: CPU - Batch Size: 16 - Model: ResNet-152abc3691215Min: 6.57 / Avg: 6.69 / Max: 6.76

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.1Device: CPU - Batch Size: 32 - Model: Efficientnet_v2_labc0.67731.35462.03192.70923.3865SE +/- 0.04, N = 43.012.992.96MIN: 2.81 / MAX: 3.25MIN: 2.79 / MAX: 3.27MIN: 2.83 / MAX: 3.07
OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.1Device: CPU - Batch Size: 32 - Model: Efficientnet_v2_labc246810Min: 2.96 / Avg: 3.01 / Max: 3.12

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.1Device: CPU - Batch Size: 64 - Model: Efficientnet_v2_labc0.6661.3321.9982.6643.33SE +/- 0.00, N = 32.962.922.96MIN: 2.81 / MAX: 3.09MIN: 2.76 / MAX: 3.04MIN: 2.82 / MAX: 3.09
OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.1Device: CPU - Batch Size: 64 - Model: Efficientnet_v2_labc246810Min: 2.95 / Avg: 2.96 / Max: 2.97

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.1Device: CPU - Batch Size: 32 - Model: ResNet-152abc246810SE +/- 0.06, N = 36.786.766.69MIN: 6.21 / MAX: 7.03MIN: 6.63 / MAX: 6.89MIN: 6.25 / MAX: 6.86
OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.1Device: CPU - Batch Size: 32 - Model: ResNet-152abc3691215Min: 6.67 / Avg: 6.78 / Max: 6.86