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 .
pytorch1 Processor Motherboard Chipset Memory Disk Graphics Audio Monitor Network OS Kernel Desktop Display Server Display Driver OpenGL OpenCL Vulkan Compiler File-System Screen Resolution pytorch1 AMD 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 14d8 64GB 2000GB Samsung SSD 990 PRO 2TB MSI NVIDIA GeForce RTX 4070 SUPER 12GB NVIDIA Device 22bc LC49G95T Realtek RTL8125 2.5GbE + MEDIATEK Device 0616 Pop 22.04 6.8.0-76060800daily20240311-generic (x86_64) GNOME Shell 42.5 X Server 1.21.1.4 NVIDIA 550.67 4.6.0 OpenCL 3.0 CUDA 12.4.125 1.3.277 GCC 11.4.0 ext4 2560x1440 OpenBenchmarking.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
pytorch1 pytorch: NVIDIA CUDA GPU - 256 - ResNet-50 pytorch: NVIDIA CUDA GPU - 256 - ResNet-152 pytorch: NVIDIA CUDA GPU - 256 - Efficientnet_v2_l pytorch1 377.25 136.71 68.84 OpenBenchmarking.org
PyTorch Device: NVIDIA CUDA GPU - Batch Size: 256 - Model: ResNet-50 OpenBenchmarking.org batches/sec, More Is Better PyTorch 2.2.1 Device: NVIDIA CUDA GPU - Batch Size: 256 - Model: ResNet-50 pytorch1 80 160 240 320 400 SE +/- 1.08, N = 3 377.25 MIN: 209.86 / MAX: 387.68
PyTorch Device: NVIDIA CUDA GPU - Batch Size: 256 - Model: ResNet-152 OpenBenchmarking.org batches/sec, More Is Better PyTorch 2.2.1 Device: NVIDIA CUDA GPU - Batch Size: 256 - Model: ResNet-152 pytorch1 30 60 90 120 150 SE +/- 1.02, N = 3 136.71 MIN: 117.53 / MAX: 141.43
PyTorch Device: NVIDIA CUDA GPU - Batch Size: 256 - Model: Efficientnet_v2_l OpenBenchmarking.org batches/sec, More Is Better PyTorch 2.2.1 Device: NVIDIA CUDA GPU - Batch Size: 256 - Model: Efficientnet_v2_l pytorch1 15 30 45 60 75 SE +/- 0.32, N = 3 68.84 MIN: 58.96 / MAX: 69.96
Phoronix Test Suite v10.8.4