240225pytorch

Intel Core i7-13700K testing with a ASUS PRIME Z790-P WIFI (1010 BIOS) and NVIDIA GeForce RTX 3090 24GB on Ubuntu 22.04 via the Phoronix Test Suite.

HTML result view exported from: https://openbenchmarking.org/result/2402267-NE-240225PYT25&grt.

240225pytorchProcessorMotherboardChipsetMemoryDiskGraphicsAudioMonitorNetworkOSKernelDesktopDisplay ServerDisplay DriverOpenGLCompilerFile-SystemScreen Resolution240225pytorchIntel Core i7-13700K @ 5.30GHz (16 Cores / 24 Threads)ASUS PRIME Z790-P WIFI (1010 BIOS)Intel Device 7a2764GB2000GB Samsung SSD 990 PRO with Heatsink 2TBNVIDIA GeForce RTX 3090 24GBRealtek ALC897Sceptre K32 + HP VH240aRealtek RTL8125 2.5GbE + Intel Device 7a70Ubuntu 22.046.5.0-21-generic (x86_64)GNOME Shell 42.9X Server 1.21.1.4NVIDIA 535.154.054.6.0GCC 12.3.0 + Clang 15.0.7 + CUDA 12.3ext41920x2160OpenBenchmarking.org- Transparent Huge Pages: madvise- Scaling Governor: intel_pstate powersave (EPP: performance) - CPU Microcode: 0x11d - Thermald 2.4.9 - Python 3.10.12- 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: Not affected + 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 RSB filling PBRSB-eIBRS: SW sequence + srbds: Not affected + tsx_async_abort: Not affected

240225pytorchpytorch: CPU - 16 - ResNet-50pytorch: CPU - 32 - ResNet-50pytorch: CPU - 64 - ResNet-50pytorch: CPU - 256 - ResNet-50pytorch: NVIDIA CUDA GPU - 16 - ResNet-50pytorch: NVIDIA CUDA GPU - 32 - ResNet-50pytorch: NVIDIA CUDA GPU - 64 - ResNet-50pytorch: NVIDIA CUDA GPU - 256 - ResNet-50240225pytorch34.4833.6233.2834.08436.14436.80431.20436.12OpenBenchmarking.org

PyTorch

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

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.1Device: CPU - Batch Size: 16 - Model: ResNet-50240225pytorch816243240SE +/- 0.35, N = 1434.48MIN: 30.05 / MAX: 35.87

PyTorch

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

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.1Device: CPU - Batch Size: 32 - Model: ResNet-50240225pytorch816243240SE +/- 0.47, N = 1233.62MIN: 28.51 / MAX: 35.44

PyTorch

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

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.1Device: CPU - Batch Size: 64 - Model: ResNet-50240225pytorch816243240SE +/- 0.48, N = 1533.28MIN: 30.23 / MAX: 35.55

PyTorch

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

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.1Device: CPU - Batch Size: 256 - Model: ResNet-50240225pytorch816243240SE +/- 0.47, N = 1534.08MIN: 30.43 / MAX: 35.71

PyTorch

Device: NVIDIA CUDA GPU - Batch Size: 16 - Model: ResNet-50

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.1Device: NVIDIA CUDA GPU - Batch Size: 16 - Model: ResNet-50240225pytorch90180270360450SE +/- 0.46, N = 3436.14MIN: 353.17 / MAX: 439.52

PyTorch

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

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.1Device: NVIDIA CUDA GPU - Batch Size: 32 - Model: ResNet-50240225pytorch90180270360450SE +/- 0.37, N = 3436.80MIN: 364.53 / MAX: 439.61

PyTorch

Device: NVIDIA CUDA GPU - Batch Size: 64 - Model: ResNet-50

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.1Device: NVIDIA CUDA GPU - Batch Size: 64 - Model: ResNet-50240225pytorch90180270360450SE +/- 4.35, N = 5431.20MIN: 321.3 / MAX: 440.12

PyTorch

Device: NVIDIA CUDA GPU - Batch Size: 256 - Model: ResNet-50

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.1Device: NVIDIA CUDA GPU - Batch Size: 256 - Model: ResNet-50240225pytorch90180270360450SE +/- 0.17, N = 3436.12MIN: 353.29 / MAX: 439.01

Phoronix Test Suite v10.8.5