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&sro&grt.

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-50abc91827364540.4940.3240.80MIN: 36.35 / MAX: 40.84MIN: 37.53 / MAX: 40.57MIN: 37.94 / MAX: 41.03

PyTorch

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

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

PyTorch

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

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

PyTorch

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

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

PyTorch

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

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

PyTorch

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

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

PyTorch

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

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

PyTorch

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

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

PyTorch

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

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

PyTorch

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

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

PyTorch

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

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

PyTorch

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

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

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_labc36912159.679.699.59MIN: 9.48 / MAX: 9.72MIN: 9.49 / MAX: 9.73MIN: 9.39 / MAX: 9.62

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_labc2468107.067.046.95MIN: 6.96 / MAX: 7.09MIN: 6.94 / MAX: 7.07MIN: 6.84 / MAX: 6.99

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_labc2468106.936.996.93MIN: 6.83 / MAX: 6.96MIN: 6.14 / MAX: 7.09MIN: 6.36 / 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_labc2468106.986.956.93MIN: 6.87 / MAX: 7.01MIN: 6.85 / MAX: 6.98MIN: 6.83 / MAX: 6.97

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_labc2468106.997.006.99MIN: 6.47 / MAX: 7.04MIN: 6.89 / MAX: 7.03MIN: 6.92 / MAX: 7.03

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_labc2468106.986.996.95MIN: 6.87 / MAX: 7.01MIN: 6.89 / MAX: 7.02MIN: 6.84 / MAX: 6.97


Phoronix Test Suite v10.8.5