pytorch001

AMD Ryzen Threadripper PRO 7965WX 24-Cores testing with a ASUS Pro WS WRX90E-SAGE SE (0404 BIOS) and NVIDIA GeForce RTX 4090 24GB on Ubuntu 22.04 via the Phoronix Test Suite.

HTML result view exported from: https://openbenchmarking.org/result/2403301-NE-PYTORCH0019.

pytorch001ProcessorMotherboardChipsetMemoryDiskGraphicsAudioMonitorNetworkOSKernelDesktopDisplay ServerDisplay DriverCompilerFile-SystemScreen Resolutiontest001AMD Ryzen Threadripper PRO 7965WX 24-Cores @ 7.30GHz (24 Cores / 48 Threads)ASUS Pro WS WRX90E-SAGE SE (0404 BIOS)AMD Device 14a4128GB2000GB Sabrent SB-ROCKET-NVMe4-2TB + 0GB Virtual HDisk0NVIDIA GeForce RTX 4090 24GBNVIDIA Device 22baDELL U2723QE2 x Intel X710 for 10GBASE-TUbuntu 22.046.5.0-26-generic (x86_64)GNOME Shell 42.9X Server 1.21.1.4NVIDIA 545.23.08GCC 11.4.0 + CUDA 12.3ext44480x2160OpenBenchmarking.org- Transparent Huge Pages: madvise- Scaling Governor: amd-pstate-epp powersave (EPP: performance) - CPU Microcode: 0xa108105- Python 3.11.8- 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 + 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

pytorch001pytorch: CPU - 32 - ResNet-50pytorch: CPU - 32 - ResNet-152pytorch: CPU - 32 - Efficientnet_v2_lpytorch: NVIDIA CUDA GPU - 32 - ResNet-50pytorch: NVIDIA CUDA GPU - 32 - ResNet-152pytorch: NVIDIA CUDA GPU - 32 - Efficientnet_v2_ltest00146.0017.849.92364.38132.7866.63OpenBenchmarking.org

PyTorch

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

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.2.1Device: CPU - Batch Size: 32 - Model: ResNet-50test0011020304050SE +/- 0.09, N = 346.00MIN: 40.27 / MAX: 46.99

PyTorch

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

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.2.1Device: CPU - Batch Size: 32 - Model: ResNet-152test00148121620SE +/- 0.12, N = 317.84MIN: 17.03 / MAX: 18.28

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_ltest0013691215SE +/- 0.00, N = 39.92MIN: 8.18 / MAX: 10.32

PyTorch

Device: NVIDIA CUDA GPU - Batch Size: 32 - Model: ResNet-50

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.2.1Device: NVIDIA CUDA GPU - Batch Size: 32 - Model: ResNet-50test00180160240320400SE +/- 0.60, N = 3364.38MIN: 330.44 / MAX: 371.21

PyTorch

Device: NVIDIA CUDA GPU - Batch Size: 32 - Model: ResNet-152

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.2.1Device: NVIDIA CUDA GPU - Batch Size: 32 - Model: ResNet-152test001306090120150SE +/- 1.16, N = 3132.78MIN: 114.16 / MAX: 136.93

PyTorch

Device: NVIDIA CUDA GPU - Batch Size: 32 - Model: Efficientnet_v2_l

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.2.1Device: NVIDIA CUDA GPU - Batch Size: 32 - Model: Efficientnet_v2_ltest0011530456075SE +/- 0.60, N = 366.63MIN: 56.43 / MAX: 68.66


Phoronix Test Suite v10.8.4