pytorch1

AMD Ryzen 7 7700X 8-Core testing with a MSI PRO B650M-A WIFI (MS-7D77) v1.0 (1.F0 BIOS) and MSI NVIDIA GeForce RTX 4070 SUPER 12GB on Pop 22.04 via the Phoronix Test Suite.

HTML result view exported from: https://openbenchmarking.org/result/2403300-NE-PYTORCH1166.

pytorch1ProcessorMotherboardChipsetMemoryDiskGraphicsAudioMonitorNetworkOSKernelDesktopDisplay ServerDisplay DriverOpenGLOpenCLVulkanCompilerFile-SystemScreen Resolutionpytorch1AMD Ryzen 7 7700X 8-Core @ 5.57GHz (8 Cores / 16 Threads)MSI PRO B650M-A WIFI (MS-7D77) v1.0 (1.F0 BIOS)AMD Device 14d864GB2000GB Samsung SSD 990 PRO 2TBMSI NVIDIA GeForce RTX 4070 SUPER 12GBNVIDIA Device 22bcLC49G95TRealtek RTL8125 2.5GbE + MEDIATEK Device 0616Pop 22.046.8.0-76060800daily20240311-generic (x86_64)GNOME Shell 42.5X Server 1.21.1.4NVIDIA 550.674.6.0OpenCL 3.0 CUDA 12.4.1251.3.277GCC 11.4.0ext42560x1440OpenBenchmarking.org- Transparent Huge Pages: madvise- Scaling Governor: amd-pstate-epp powersave (EPP: balance_performance) - CPU Microcode: 0xa601206 - 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: 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

pytorch1pytorch: NVIDIA CUDA GPU - 256 - ResNet-50pytorch: NVIDIA CUDA GPU - 256 - ResNet-152pytorch: NVIDIA CUDA GPU - 256 - Efficientnet_v2_lpytorch1377.25136.7168.84OpenBenchmarking.org

PyTorch

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

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.2.1Device: NVIDIA CUDA GPU - Batch Size: 256 - Model: ResNet-50pytorch180160240320400SE +/- 1.08, N = 3377.25MIN: 209.86 / MAX: 387.68

PyTorch

Device: NVIDIA CUDA GPU - Batch Size: 256 - Model: ResNet-152

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.2.1Device: NVIDIA CUDA GPU - Batch Size: 256 - Model: ResNet-152pytorch1306090120150SE +/- 1.02, N = 3136.71MIN: 117.53 / MAX: 141.43

PyTorch

Device: NVIDIA CUDA GPU - Batch Size: 256 - Model: Efficientnet_v2_l

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.2.1Device: NVIDIA CUDA GPU - Batch Size: 256 - Model: Efficientnet_v2_lpytorch11530456075SE +/- 0.32, N = 368.84MIN: 58.96 / MAX: 69.96

Phoronix Test Suite v10.8.4