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AMD Ryzen Threadripper PRO 5965WX 24-Cores testing with a ASUS Pro WS WRX80E-SAGE SE WIFI (1201 BIOS) and ASUS NVIDIA NV106 2GB 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 2311165-NE-PYT74848100
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November 16 2023
  46 Minutes
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November 16 2023
  46 Minutes
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November 17 2023
  46 Minutes
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pytOpenBenchmarking.orgPhoronix Test SuiteAMD Ryzen Threadripper PRO 5965WX 24-Cores @ 3.80GHz (24 Cores / 48 Threads)ASUS Pro WS WRX80E-SAGE SE WIFI (1201 BIOS)AMD Starship/Matisse128GB2048GB SOLIDIGM SSDPFKKW020X7ASUS NVIDIA NV106 2GBAMD Starship/MatisseVA24312 x Intel X550 + Intel Wi-Fi 6 AX200Ubuntu 23.106.5.0-10-generic (x86_64)GNOME Shell 45.0X Server + Waylandnouveau4.3 Mesa 23.2.1-1ubuntu3GCC 13.2.0ext41920x1080ProcessorMotherboardChipsetMemoryDiskGraphicsAudioMonitorNetworkOSKernelDesktopDisplay ServerDisplay DriverOpenGLCompilerFile-SystemScreen ResolutionPyt BenchmarksSystem Logs- Transparent Huge Pages: madvise- Scaling Governor: acpi-cpufreq schedutil (Boost: Enabled) - CPU Microcode: 0xa008205- 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: Not affected + spec_rstack_overflow: Mitigation of safe RET no microcode + 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

abcResult OverviewPhoronix Test Suite100%101%102%102%103%PyTorchPyTorchPyTorchPyTorchPyTorchPyTorchPyTorchPyTorchPyTorchPyTorchPyTorchPyTorchPyTorchPyTorchPyTorchPyTorchPyTorchPyTorchCPU - 32 - ResNet-50CPU - 32 - ResNet-152CPU - 256 - ResNet-50CPU - 1 - ResNet-152CPU - 16 - Efficientnet_v2_lCPU - 16 - ResNet-152CPU - 64 - ResNet-50CPU - 512 - ResNet-50CPU - 1 - ResNet-50CPU - 1 - Efficientnet_v2_lCPU - 512 - ResNet-152CPU - 32 - Efficientnet_v2_lCPU - 256 - ResNet-152CPU - 64 - Efficientnet_v2_lCPU - 512 - Efficientnet_v2_lCPU - 16 - ResNet-50CPU - 64 - ResNet-152CPU - 256 - Efficientnet_v2_l

pytpytorch: CPU - 32 - ResNet-50pytorch: CPU - 32 - ResNet-152pytorch: CPU - 256 - ResNet-50pytorch: CPU - 1 - ResNet-152pytorch: CPU - 16 - Efficientnet_v2_lpytorch: CPU - 16 - ResNet-152pytorch: CPU - 64 - ResNet-50pytorch: CPU - 512 - ResNet-50pytorch: CPU - 1 - ResNet-50pytorch: CPU - 1 - Efficientnet_v2_lpytorch: CPU - 512 - ResNet-152pytorch: CPU - 32 - Efficientnet_v2_lpytorch: CPU - 256 - ResNet-152pytorch: CPU - 64 - Efficientnet_v2_lpytorch: CPU - 512 - Efficientnet_v2_lpytorch: CPU - 16 - ResNet-50pytorch: CPU - 64 - ResNet-152pytorch: CPU - 256 - Efficientnet_v2_labc31.1912.6032.4115.787.0612.6131.9032.0840.499.6712.466.9312.426.986.9831.7712.456.9932.1712.2932.0015.827.0412.4531.6732.1740.329.6912.376.9912.336.956.9931.9512.487.0032.2012.5231.7016.126.9512.4231.4732.5140.809.5912.356.9312.376.936.9531.9112.486.99OpenBenchmarking.org

PyTorch

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.1Device: CPU - Batch Size: 32 - Model: ResNet-50abc71421283531.1932.1732.20MIN: 26.98 / MAX: 32.29MIN: 30.23 / MAX: 32.41MIN: 30.06 / MAX: 32.51

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.1Device: CPU - Batch Size: 32 - Model: ResNet-152abc369121512.6012.2912.52MIN: 12.25 / MAX: 12.67MIN: 11.92 / MAX: 12.37MIN: 12.14 / MAX: 12.59

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.1Device: CPU - Batch Size: 256 - Model: ResNet-50abc81624324032.4132.0031.70MIN: 30.42 / MAX: 32.66MIN: 27.01 / MAX: 32.27MIN: 29.83 / MAX: 32.04

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.1Device: CPU - Batch Size: 1 - Model: ResNet-152abc4812162015.7815.8216.12MIN: 13.65 / MAX: 16MIN: 15.34 / MAX: 15.9MIN: 15.63 / MAX: 16.18

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.1Device: CPU - Batch Size: 16 - Model: Efficientnet_v2_labc2468107.067.046.95MIN: 6.96 / MAX: 7.09MIN: 6.94 / MAX: 7.07MIN: 6.84 / MAX: 6.99

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.1Device: CPU - Batch Size: 16 - Model: ResNet-152abc369121512.6112.4512.42MIN: 11.48 / MAX: 12.74MIN: 12.05 / MAX: 12.53MIN: 12.08 / MAX: 12.5

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.1Device: CPU - Batch Size: 64 - Model: ResNet-50abc71421283531.9031.6731.47MIN: 28.18 / MAX: 32.3MIN: 29.72 / MAX: 31.94MIN: 29.63 / MAX: 31.67

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.1Device: CPU - Batch Size: 512 - Model: ResNet-50abc81624324032.0832.1732.51MIN: 30.03 / MAX: 32.31MIN: 30.04 / MAX: 32.45MIN: 28.02 / MAX: 32.79

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.1Device: CPU - Batch Size: 1 - Model: ResNet-50abc91827364540.4940.3240.80MIN: 36.35 / MAX: 40.84MIN: 37.53 / MAX: 40.57MIN: 37.94 / MAX: 41.03

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.1Device: CPU - Batch Size: 1 - Model: Efficientnet_v2_labc36912159.679.699.59MIN: 9.48 / MAX: 9.72MIN: 9.49 / MAX: 9.73MIN: 9.39 / MAX: 9.62

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.1Device: CPU - Batch Size: 512 - Model: ResNet-152abc369121512.4612.3712.35MIN: 12.15 / MAX: 12.52MIN: 12.07 / MAX: 12.44MIN: 10.69 / MAX: 12.45

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.1Device: CPU - Batch Size: 32 - Model: Efficientnet_v2_labc2468106.936.996.93MIN: 6.83 / MAX: 6.96MIN: 6.14 / MAX: 7.09MIN: 6.36 / MAX: 6.96

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.1Device: CPU - Batch Size: 256 - Model: ResNet-152abc369121512.4212.3312.37MIN: 12.09 / MAX: 12.48MIN: 12 / MAX: 12.45MIN: 12.04 / MAX: 12.42

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.1Device: CPU - Batch Size: 64 - Model: Efficientnet_v2_labc2468106.986.956.93MIN: 6.87 / MAX: 7.01MIN: 6.85 / MAX: 6.98MIN: 6.83 / MAX: 6.97

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.1Device: CPU - Batch Size: 512 - Model: Efficientnet_v2_labc2468106.986.996.95MIN: 6.87 / MAX: 7.01MIN: 6.89 / MAX: 7.02MIN: 6.84 / MAX: 6.97

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.1Device: CPU - Batch Size: 16 - Model: ResNet-50abc71421283531.7731.9531.91MIN: 28.82 / MAX: 32.17MIN: 29.97 / MAX: 32.29MIN: 30.03 / MAX: 32.14

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.1Device: CPU - Batch Size: 64 - Model: ResNet-152abc369121512.4512.4812.48MIN: 12.16 / MAX: 12.53MIN: 12.14 / MAX: 12.58MIN: 12.17 / MAX: 12.57

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.1Device: CPU - Batch Size: 256 - Model: Efficientnet_v2_labc2468106.997.006.99MIN: 6.47 / MAX: 7.04MIN: 6.89 / MAX: 7.03MIN: 6.92 / MAX: 7.03