pytorch 2.2.1 AMD EPYC Siena

AMD EPYC 8534P 64-Core testing with a AMD Cinnabar (RCB1009C BIOS) and ASPEED on Ubuntu 23.10 via the Phoronix Test Suite.

HTML result view exported from: https://openbenchmarking.org/result/2403269-NE-PYTORCH2202&grr&sor.

pytorch 2.2.1 AMD EPYC SienaProcessorMotherboardChipsetMemoryDiskGraphicsNetworkOSKernelDesktopDisplay ServerCompilerFile-SystemScreen ResolutionabcAMD EPYC 8534P 64-Core @ 2.30GHz (64 Cores / 128 Threads)AMD Cinnabar (RCB1009C BIOS)AMD Device 14a46 x 32GB DRAM-4800MT/s Samsung M321R4GA0BB0-CQKMG3201GB Micron_7450_MTFDKCB3T2TFS + 2000GB Corsair MP700ASPEED2 x Broadcom NetXtreme BCM5720 PCIeUbuntu 23.106.8.1-060801-generic (x86_64)GNOME Shell 45.2X Server 1.21.1.7GCC 13.2.0ext41920x1200OpenBenchmarking.orgKernel Details- Transparent Huge Pages: madviseProcessor Details- Scaling Governor: acpi-cpufreq performance (Boost: Enabled) - CPU Microcode: 0xaa00212 Python 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 + reg_file_data_sampling: Not affected + retbleed: Not affected + 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 Enhanced / Automatic IBRS IBPB: conditional STIBP: always-on RSB filling PBRSB-eIBRS: Not affected + srbds: Not affected + tsx_async_abort: Not affected

pytorch 2.2.1 AMD EPYC Sienapytorch: CPU - 16 - Efficientnet_v2_lpytorch: CPU - 64 - Efficientnet_v2_lpytorch: CPU - 32 - Efficientnet_v2_lpytorch: CPU - 512 - Efficientnet_v2_lpytorch: CPU - 256 - Efficientnet_v2_lpytorch: CPU - 64 - ResNet-152pytorch: CPU - 32 - ResNet-152pytorch: CPU - 512 - ResNet-152pytorch: CPU - 16 - ResNet-152pytorch: CPU - 256 - ResNet-152pytorch: CPU - 1 - Efficientnet_v2_lpytorch: CPU - 1 - ResNet-152pytorch: CPU - 32 - ResNet-50pytorch: CPU - 16 - ResNet-50pytorch: CPU - 512 - ResNet-50pytorch: CPU - 256 - ResNet-50pytorch: CPU - 64 - ResNet-50pytorch: CPU - 1 - ResNet-50abc5.655.675.645.685.6512.9613.0713.2413.1912.978.6415.1532.9433.3033.4233.6733.8641.115.655.635.625.655.6712.9913.0313.0913.0613.108.7814.8833.6533.3133.5133.3433.5140.675.625.665.695.655.6813.2212.9913.1013.1013.398.6415.0333.3633.5433.6233.5433.6540.75OpenBenchmarking.org

PyTorch

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

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.2.1Device: CPU - Batch Size: 16 - Model: Efficientnet_v2_lbac1.27132.54263.81395.08526.35655.655.655.62MIN: 4.71 / MAX: 5.76MIN: 4.48 / MAX: 5.76MIN: 4.63 / MAX: 5.72

PyTorch

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

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.2.1Device: CPU - Batch Size: 64 - Model: Efficientnet_v2_lacb1.27582.55163.82745.10326.3795.675.665.63MIN: 5.32 / MAX: 5.76MIN: 4.52 / MAX: 5.76MIN: 4.88 / MAX: 5.72

PyTorch

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

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.2.1Device: CPU - Batch Size: 32 - Model: Efficientnet_v2_lcab1.28032.56063.84095.12126.40155.695.645.62MIN: 4.72 / MAX: 5.78MIN: 4.7 / MAX: 5.75MIN: 5.06 / MAX: 5.71

PyTorch

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

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.2.1Device: CPU - Batch Size: 512 - Model: Efficientnet_v2_lacb1.2782.5563.8345.1126.395.685.655.65MIN: 4.6 / MAX: 5.77MIN: 4.41 / MAX: 5.74MIN: 5.38 / MAX: 5.73

PyTorch

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

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.2.1Device: CPU - Batch Size: 256 - Model: Efficientnet_v2_lcba1.2782.5563.8345.1126.395.685.675.65MIN: 5.4 / MAX: 5.78MIN: 4.55 / MAX: 5.76MIN: 4.62 / MAX: 5.73

PyTorch

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

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.2.1Device: CPU - Batch Size: 64 - Model: ResNet-152cba369121513.2212.9912.96MIN: 13.02 / MAX: 13.32MIN: 12.86 / MAX: 13.09MIN: 12.23 / MAX: 13.06

PyTorch

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

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.2.1Device: CPU - Batch Size: 32 - Model: ResNet-152abc369121513.0713.0312.99MIN: 8.78 / MAX: 13.2MIN: 12.7 / MAX: 13.14MIN: 8.89 / MAX: 13.09

PyTorch

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

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.2.1Device: CPU - Batch Size: 512 - Model: ResNet-152acb369121513.2413.1013.09MIN: 12.34 / MAX: 13.35MIN: 12.96 / MAX: 13.2MIN: 8.81 / MAX: 13.18

PyTorch

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

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.2.1Device: CPU - Batch Size: 16 - Model: ResNet-152acb369121513.1913.1013.06MIN: 13.07 / MAX: 13.3MIN: 12.7 / MAX: 13.21MIN: 8.77 / MAX: 13.16

PyTorch

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

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.2.1Device: CPU - Batch Size: 256 - Model: ResNet-152cba369121513.3913.1012.97MIN: 8.95 / MAX: 13.48MIN: 13 / MAX: 13.2MIN: 8.8 / MAX: 13.09

PyTorch

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

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.2.1Device: CPU - Batch Size: 1 - Model: Efficientnet_v2_lbca2468108.788.648.64MIN: 6.74 / MAX: 8.86MIN: 8.5 / MAX: 8.72MIN: 8.55 / MAX: 8.71

PyTorch

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

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.2.1Device: CPU - Batch Size: 1 - Model: ResNet-152acb4812162015.1515.0314.88MIN: 14.65 / MAX: 15.33MIN: 9.88 / MAX: 15.14MIN: 14.71 / MAX: 15

PyTorch

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

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.2.1Device: CPU - Batch Size: 32 - Model: ResNet-50bca81624324033.6533.3632.94MIN: 32.2 / MAX: 34.12MIN: 31.61 / MAX: 33.8MIN: 14.77 / MAX: 33.36

PyTorch

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

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.2.1Device: CPU - Batch Size: 16 - Model: ResNet-50cba81624324033.5433.3133.30MIN: 18.28 / MAX: 34MIN: 32.5 / MAX: 33.78MIN: 16.55 / MAX: 33.78

PyTorch

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

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.2.1Device: CPU - Batch Size: 512 - Model: ResNet-50cba81624324033.6233.5133.42MIN: 32.63 / MAX: 34.14MIN: 32.71 / MAX: 33.92MIN: 32.29 / MAX: 33.81

PyTorch

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

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.2.1Device: CPU - Batch Size: 256 - Model: ResNet-50acb81624324033.6733.5433.34MIN: 32.41 / MAX: 34.14MIN: 16.1 / MAX: 34.1MIN: 32.81 / MAX: 33.77

PyTorch

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

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.2.1Device: CPU - Batch Size: 64 - Model: ResNet-50acb81624324033.8633.6533.51MIN: 32.86 / MAX: 34.37MIN: 32.6 / MAX: 34.13MIN: 15.58 / MAX: 33.94

PyTorch

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

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.2.1Device: CPU - Batch Size: 1 - Model: ResNet-50acb91827364541.1140.7540.67MIN: 39.95 / MAX: 41.96MIN: 39.84 / MAX: 41.56MIN: 39.57 / MAX: 41.58

Phoronix Test Suite v10.8.5