pyt

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.

HTML result view exported from: https://openbenchmarking.org/result/2311165-NE-PYT74848100&grw&sro&rro.

pytProcessorMotherboardChipsetMemoryDiskGraphicsAudioMonitorNetworkOSKernelDesktopDisplay ServerDisplay DriverOpenGLCompilerFile-SystemScreen ResolutionabcAMD 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 13.2.0ext41920x1080OpenBenchmarking.orgKernel Details- Transparent Huge Pages: madviseProcessor Details- Scaling Governor: acpi-cpufreq schedutil (Boost: Enabled) - CPU Microcode: 0xa008205Python Details- Python 3.11.6Security Details- 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

pytpytorch: CPU - 1 - ResNet-50pytorch: CPU - 1 - ResNet-152pytorch: CPU - 16 - ResNet-50pytorch: CPU - 32 - ResNet-50pytorch: CPU - 64 - ResNet-50pytorch: CPU - 16 - ResNet-152pytorch: CPU - 256 - ResNet-50pytorch: CPU - 32 - ResNet-152pytorch: CPU - 512 - ResNet-50pytorch: CPU - 64 - ResNet-152pytorch: CPU - 256 - ResNet-152pytorch: CPU - 512 - ResNet-152pytorch: CPU - 1 - Efficientnet_v2_lpytorch: CPU - 16 - Efficientnet_v2_lpytorch: CPU - 32 - Efficientnet_v2_lpytorch: CPU - 64 - Efficientnet_v2_lpytorch: CPU - 256 - Efficientnet_v2_lpytorch: CPU - 512 - Efficientnet_v2_labc40.4915.7831.7731.1931.9012.6132.4112.6032.0812.4512.4212.469.677.066.936.986.996.9840.3215.8231.9532.1731.6712.4532.0012.2932.1712.4812.3312.379.697.046.996.957.006.9940.8016.1231.9132.2031.4712.4231.7012.5232.5112.4812.3712.359.596.956.936.936.996.95OpenBenchmarking.org

PyTorch

Device: CPU - Batch Size: 1 - Model: ResNet-50

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.1Device: CPU - Batch Size: 1 - Model: ResNet-50cba91827364540.8040.3240.49MIN: 37.94 / MAX: 41.03MIN: 37.53 / MAX: 40.57MIN: 36.35 / MAX: 40.84

PyTorch

Device: CPU - Batch Size: 1 - Model: ResNet-152

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.1Device: CPU - Batch Size: 1 - Model: ResNet-152cba4812162016.1215.8215.78MIN: 15.63 / MAX: 16.18MIN: 15.34 / MAX: 15.9MIN: 13.65 / MAX: 16

PyTorch

Device: CPU - Batch Size: 16 - Model: ResNet-50

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.1Device: CPU - Batch Size: 16 - Model: ResNet-50cba71421283531.9131.9531.77MIN: 30.03 / MAX: 32.14MIN: 29.97 / MAX: 32.29MIN: 28.82 / MAX: 32.17

PyTorch

Device: CPU - Batch Size: 32 - Model: ResNet-50

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.1Device: CPU - Batch Size: 32 - Model: ResNet-50cba71421283532.2032.1731.19MIN: 30.06 / MAX: 32.51MIN: 30.23 / MAX: 32.41MIN: 26.98 / MAX: 32.29

PyTorch

Device: CPU - Batch Size: 64 - Model: ResNet-50

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.1Device: CPU - Batch Size: 64 - Model: ResNet-50cba71421283531.4731.6731.90MIN: 29.63 / MAX: 31.67MIN: 29.72 / MAX: 31.94MIN: 28.18 / MAX: 32.3

PyTorch

Device: CPU - Batch Size: 16 - Model: ResNet-152

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.1Device: CPU - Batch Size: 16 - Model: ResNet-152cba369121512.4212.4512.61MIN: 12.08 / MAX: 12.5MIN: 12.05 / MAX: 12.53MIN: 11.48 / MAX: 12.74

PyTorch

Device: CPU - Batch Size: 256 - Model: ResNet-50

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.1Device: CPU - Batch Size: 256 - Model: ResNet-50cba81624324031.7032.0032.41MIN: 29.83 / MAX: 32.04MIN: 27.01 / MAX: 32.27MIN: 30.42 / MAX: 32.66

PyTorch

Device: CPU - Batch Size: 32 - Model: ResNet-152

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.1Device: CPU - Batch Size: 32 - Model: ResNet-152cba369121512.5212.2912.60MIN: 12.14 / MAX: 12.59MIN: 11.92 / MAX: 12.37MIN: 12.25 / MAX: 12.67

PyTorch

Device: CPU - Batch Size: 512 - Model: ResNet-50

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.1Device: CPU - Batch Size: 512 - Model: ResNet-50cba81624324032.5132.1732.08MIN: 28.02 / MAX: 32.79MIN: 30.04 / MAX: 32.45MIN: 30.03 / MAX: 32.31

PyTorch

Device: CPU - Batch Size: 64 - Model: ResNet-152

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.1Device: CPU - Batch Size: 64 - Model: ResNet-152cba369121512.4812.4812.45MIN: 12.17 / MAX: 12.57MIN: 12.14 / MAX: 12.58MIN: 12.16 / MAX: 12.53

PyTorch

Device: CPU - Batch Size: 256 - Model: ResNet-152

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.1Device: CPU - Batch Size: 256 - Model: ResNet-152cba369121512.3712.3312.42MIN: 12.04 / MAX: 12.42MIN: 12 / MAX: 12.45MIN: 12.09 / MAX: 12.48

PyTorch

Device: CPU - Batch Size: 512 - Model: ResNet-152

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.1Device: CPU - Batch Size: 512 - Model: ResNet-152cba369121512.3512.3712.46MIN: 10.69 / MAX: 12.45MIN: 12.07 / MAX: 12.44MIN: 12.15 / MAX: 12.52

PyTorch

Device: CPU - Batch Size: 1 - Model: Efficientnet_v2_l

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.1Device: CPU - Batch Size: 1 - Model: Efficientnet_v2_lcba36912159.599.699.67MIN: 9.39 / MAX: 9.62MIN: 9.49 / MAX: 9.73MIN: 9.48 / MAX: 9.72

PyTorch

Device: CPU - Batch Size: 16 - Model: Efficientnet_v2_l

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.1Device: CPU - Batch Size: 16 - Model: Efficientnet_v2_lcba2468106.957.047.06MIN: 6.84 / MAX: 6.99MIN: 6.94 / MAX: 7.07MIN: 6.96 / MAX: 7.09

PyTorch

Device: CPU - Batch Size: 32 - Model: Efficientnet_v2_l

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.1Device: CPU - Batch Size: 32 - Model: Efficientnet_v2_lcba2468106.936.996.93MIN: 6.36 / MAX: 6.96MIN: 6.14 / MAX: 7.09MIN: 6.83 / MAX: 6.96

PyTorch

Device: CPU - Batch Size: 64 - Model: Efficientnet_v2_l

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.1Device: CPU - Batch Size: 64 - Model: Efficientnet_v2_lcba2468106.936.956.98MIN: 6.83 / MAX: 6.97MIN: 6.85 / MAX: 6.98MIN: 6.87 / MAX: 7.01

PyTorch

Device: CPU - Batch Size: 256 - Model: Efficientnet_v2_l

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.1Device: CPU - Batch Size: 256 - Model: Efficientnet_v2_lcba2468106.997.006.99MIN: 6.92 / MAX: 7.03MIN: 6.89 / MAX: 7.03MIN: 6.47 / MAX: 7.04

PyTorch

Device: CPU - Batch Size: 512 - Model: Efficientnet_v2_l

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.1Device: CPU - Batch Size: 512 - Model: Efficientnet_v2_lcba2468106.956.996.98MIN: 6.84 / MAX: 6.97MIN: 6.89 / MAX: 7.02MIN: 6.87 / MAX: 7.01


Phoronix Test Suite v10.8.5