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.

Compare your own system(s) to this result file with the Phoronix Test Suite by running the command: phoronix-test-suite benchmark 2402267-NE-240225PYT25
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240225pytorch
February 26
  54 Minutes
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240225pytorchOpenBenchmarking.orgPhoronix Test SuiteIntel 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 12.3ext41920x2160ProcessorMotherboardChipsetMemoryDiskGraphicsAudioMonitorNetworkOSKernelDesktopDisplay ServerDisplay DriverOpenGLCompilerFile-SystemScreen Resolution240225pytorch BenchmarksSystem Logs- 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

This is a benchmark of PyTorch making use of pytorch-benchmark [https://github.com/LukasHedegaard/pytorch-benchmark]. Currently this test profile is catered to CPU-based testing. Learn more via the OpenBenchmarking.org test page.

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

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

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

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

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

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

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

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