pytorch 2.2.1 ryzen AMD Ryzen 9 7950X 16-Core testing with a ASUS ROG STRIX X670E-E GAMING WIFI (1905 BIOS) and NVIDIA GeForce RTX 3080 10GB on Ubuntu 23.10 via the Phoronix Test Suite.
HTML result view exported from: https://openbenchmarking.org/result/2403270-PTS-PYTORCH233&sor .
pytorch 2.2.1 ryzen Processor Motherboard Chipset Memory Disk Graphics Audio Monitor Network OS Kernel Desktop Display Server Display Driver OpenGL OpenCL Compiler File-System Screen Resolution a b c d AMD Ryzen 9 7950X 16-Core @ 5.88GHz (16 Cores / 32 Threads) ASUS ROG STRIX X670E-E GAMING WIFI (1905 BIOS) AMD Device 14d8 2 x 16GB DRAM-6000MT/s G Skill F5-6000J3038F16G 2000GB Samsung SSD 980 PRO 2TB + 123GB SanDisk 3.2Gen1 NVIDIA GeForce RTX 3080 10GB NVIDIA GA102 HD Audio DELL U2723QE Intel I225-V + Intel Wi-Fi 6 AX210/AX211/AX411 Ubuntu 23.10 6.7.0-060700-generic (x86_64) GNOME Shell 45.2 X Server 1.21.1.7 NVIDIA 550.54.14 4.6.0 OpenCL 3.0 CUDA 12.4.89 GCC 13.2.0 ext4 3840x2160 OpenBenchmarking.org Kernel Details - Transparent Huge Pages: madvise Processor Details - Scaling Governor: amd-pstate-epp powersave (EPP: balance_performance) - CPU Microcode: 0xa601206 Python Details - Python 3.11.6 Security Details - 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
pytorch 2.2.1 ryzen pytorch: CPU - 1 - ResNet-50 pytorch: CPU - 1 - ResNet-152 pytorch: CPU - 16 - ResNet-50 pytorch: CPU - 32 - ResNet-50 pytorch: CPU - 64 - ResNet-50 pytorch: CPU - 16 - ResNet-152 pytorch: CPU - 256 - ResNet-50 pytorch: CPU - 32 - ResNet-152 pytorch: CPU - 512 - ResNet-50 pytorch: CPU - 64 - ResNet-152 pytorch: CPU - 256 - ResNet-152 pytorch: CPU - 512 - ResNet-152 pytorch: CPU - 1 - Efficientnet_v2_l pytorch: CPU - 16 - Efficientnet_v2_l pytorch: CPU - 32 - Efficientnet_v2_l pytorch: CPU - 64 - Efficientnet_v2_l pytorch: CPU - 256 - Efficientnet_v2_l pytorch: CPU - 512 - Efficientnet_v2_l a b c d 72.75 30.33 49.18 48.64 48.19 20.10 48.89 19.81 48.44 20.30 20.54 19.40 16.55 11.79 11.42 11.80 11.70 11.76 72.66 29.81 48.67 49.02 47.97 20.01 47.49 20.26 48.83 19.64 19.91 19.69 16.09 11.77 11.73 11.87 11.78 11.67 72.25 29.32 49.73 48.85 48.52 20.16 48.61 20.06 49.32 20.06 19.79 19.98 15.77 11.62 11.78 11.59 11.75 11.56 71.23 28.96 47.61 48.34 48.51 20.18 48.38 20.24 48.19 20.14 19.75 19.93 16.22 11.84 11.73 11.88 11.74 11.76 OpenBenchmarking.org
PyTorch Device: CPU - Batch Size: 1 - Model: ResNet-50 OpenBenchmarking.org batches/sec, More Is Better PyTorch 2.2.1 Device: CPU - Batch Size: 1 - Model: ResNet-50 a b c d 16 32 48 64 80 SE +/- 0.34, N = 3 72.75 72.66 72.25 71.23 MIN: 69.82 / MAX: 74.29 MIN: 67.96 / MAX: 74.36 MIN: 57.14 / MAX: 74.16 MIN: 64.96 / MAX: 73.24
PyTorch Device: CPU - Batch Size: 1 - Model: ResNet-152 OpenBenchmarking.org batches/sec, More Is Better PyTorch 2.2.1 Device: CPU - Batch Size: 1 - Model: ResNet-152 a b c d 7 14 21 28 35 SE +/- 0.11, N = 3 30.33 29.81 29.32 28.96 MIN: 23.35 / MAX: 30.76 MIN: 28.63 / MAX: 30.21 MIN: 28.93 / MAX: 29.59 MIN: 22.78 / MAX: 29.7
PyTorch Device: CPU - Batch Size: 16 - Model: ResNet-50 OpenBenchmarking.org batches/sec, More Is Better PyTorch 2.2.1 Device: CPU - Batch Size: 16 - Model: ResNet-50 c a b d 11 22 33 44 55 SE +/- 0.11, N = 3 49.73 49.18 48.67 47.61 MIN: 48.72 / MAX: 50.57 MIN: 48.1 / MAX: 49.79 MIN: 46.88 / MAX: 49.75 MIN: 45.13 / MAX: 48.9
PyTorch Device: CPU - Batch Size: 32 - Model: ResNet-50 OpenBenchmarking.org batches/sec, More Is Better PyTorch 2.2.1 Device: CPU - Batch Size: 32 - Model: ResNet-50 b c a d 11 22 33 44 55 SE +/- 0.13, N = 3 49.02 48.85 48.64 48.34 MIN: 47.89 / MAX: 49.85 MIN: 46.2 / MAX: 49.69 MIN: 47.2 / MAX: 49.77 MIN: 45.85 / MAX: 49.33
PyTorch Device: CPU - Batch Size: 64 - Model: ResNet-50 OpenBenchmarking.org batches/sec, More Is Better PyTorch 2.2.1 Device: CPU - Batch Size: 64 - Model: ResNet-50 c d a b 11 22 33 44 55 SE +/- 0.35, N = 3 48.52 48.51 48.19 47.97 MIN: 47.06 / MAX: 49.51 MIN: 46.37 / MAX: 49.94 MIN: 45.76 / MAX: 49.14 MIN: 45.74 / MAX: 49.08
PyTorch Device: CPU - Batch Size: 16 - Model: ResNet-152 OpenBenchmarking.org batches/sec, More Is Better PyTorch 2.2.1 Device: CPU - Batch Size: 16 - Model: ResNet-152 d c a b 5 10 15 20 25 SE +/- 0.04, N = 3 20.18 20.16 20.10 20.01 MIN: 19.67 / MAX: 20.58 MIN: 19.7 / MAX: 20.4 MIN: 19.61 / MAX: 20.33 MIN: 17.16 / MAX: 20.31
PyTorch Device: CPU - Batch Size: 256 - Model: ResNet-50 OpenBenchmarking.org batches/sec, More Is Better PyTorch 2.2.1 Device: CPU - Batch Size: 256 - Model: ResNet-50 a c d b 11 22 33 44 55 SE +/- 0.66, N = 3 48.89 48.61 48.38 47.49 MIN: 46.38 / MAX: 49.85 MIN: 46.63 / MAX: 49.33 MIN: 45.71 / MAX: 50.11 MIN: 46.32 / MAX: 48.77
PyTorch Device: CPU - Batch Size: 32 - Model: ResNet-152 OpenBenchmarking.org batches/sec, More Is Better PyTorch 2.2.1 Device: CPU - Batch Size: 32 - Model: ResNet-152 b d c a 5 10 15 20 25 SE +/- 0.03, N = 3 20.26 20.24 20.06 19.81 MIN: 19.92 / MAX: 20.55 MIN: 19.62 / MAX: 20.59 MIN: 19.66 / MAX: 20.42 MIN: 19.34 / MAX: 20.05
PyTorch Device: CPU - Batch Size: 512 - Model: ResNet-50 OpenBenchmarking.org batches/sec, More Is Better PyTorch 2.2.1 Device: CPU - Batch Size: 512 - Model: ResNet-50 c b a d 11 22 33 44 55 SE +/- 0.19, N = 3 49.32 48.83 48.44 48.19 MIN: 47.73 / MAX: 50.31 MIN: 47.52 / MAX: 50.16 MIN: 46.94 / MAX: 49.13 MIN: 37.3 / MAX: 49.6
PyTorch Device: CPU - Batch Size: 64 - Model: ResNet-152 OpenBenchmarking.org batches/sec, More Is Better PyTorch 2.2.1 Device: CPU - Batch Size: 64 - Model: ResNet-152 a d c b 5 10 15 20 25 SE +/- 0.04, N = 3 20.30 20.14 20.06 19.64 MIN: 20 / MAX: 20.47 MIN: 19.6 / MAX: 20.53 MIN: 19.3 / MAX: 20.27 MIN: 19.34 / MAX: 19.92
PyTorch Device: CPU - Batch Size: 256 - Model: ResNet-152 OpenBenchmarking.org batches/sec, More Is Better PyTorch 2.2.1 Device: CPU - Batch Size: 256 - Model: ResNet-152 a b c d 5 10 15 20 25 SE +/- 0.13, N = 3 20.54 19.91 19.79 19.75 MIN: 20.16 / MAX: 20.7 MIN: 19.61 / MAX: 20.22 MIN: 19.52 / MAX: 19.99 MIN: 19.22 / MAX: 20.44
PyTorch Device: CPU - Batch Size: 512 - Model: ResNet-152 OpenBenchmarking.org batches/sec, More Is Better PyTorch 2.2.1 Device: CPU - Batch Size: 512 - Model: ResNet-152 c d b a 5 10 15 20 25 SE +/- 0.08, N = 3 19.98 19.93 19.69 19.40 MIN: 19.59 / MAX: 20.45 MIN: 17.21 / MAX: 20.37 MIN: 19.19 / MAX: 20.13 MIN: 18.86 / MAX: 19.68
PyTorch Device: CPU - Batch Size: 1 - Model: Efficientnet_v2_l OpenBenchmarking.org batches/sec, More Is Better PyTorch 2.2.1 Device: CPU - Batch Size: 1 - Model: Efficientnet_v2_l a d b c 4 8 12 16 20 SE +/- 0.07, N = 3 16.55 16.22 16.09 15.77 MIN: 14.5 / MAX: 16.83 MIN: 15.75 / MAX: 16.51 MIN: 15.88 / MAX: 16.28 MIN: 13.93 / MAX: 16.03
PyTorch Device: CPU - Batch Size: 16 - Model: Efficientnet_v2_l OpenBenchmarking.org batches/sec, More Is Better PyTorch 2.2.1 Device: CPU - Batch Size: 16 - Model: Efficientnet_v2_l d a b c 3 6 9 12 15 SE +/- 0.03, N = 3 11.84 11.79 11.77 11.62 MIN: 9.62 / MAX: 12.79 MIN: 9.57 / MAX: 12.78 MIN: 9.55 / MAX: 12.38 MIN: 9.52 / MAX: 12.22
PyTorch Device: CPU - Batch Size: 32 - Model: Efficientnet_v2_l OpenBenchmarking.org batches/sec, More Is Better PyTorch 2.2.1 Device: CPU - Batch Size: 32 - Model: Efficientnet_v2_l c d b a 3 6 9 12 15 SE +/- 0.03, N = 3 11.78 11.73 11.73 11.42 MIN: 9.57 / MAX: 12.66 MIN: 9.64 / MAX: 12.74 MIN: 9.61 / MAX: 12.62 MIN: 9.66 / MAX: 12.53
PyTorch Device: CPU - Batch Size: 64 - Model: Efficientnet_v2_l OpenBenchmarking.org batches/sec, More Is Better PyTorch 2.2.1 Device: CPU - Batch Size: 64 - Model: Efficientnet_v2_l d b a c 3 6 9 12 15 SE +/- 0.14, N = 3 11.88 11.87 11.80 11.59 MIN: 9.72 / MAX: 12.8 MIN: 9.59 / MAX: 12.72 MIN: 9.74 / MAX: 12.67 MIN: 9.5 / MAX: 12.72
PyTorch Device: CPU - Batch Size: 256 - Model: Efficientnet_v2_l OpenBenchmarking.org batches/sec, More Is Better PyTorch 2.2.1 Device: CPU - Batch Size: 256 - Model: Efficientnet_v2_l b c d a 3 6 9 12 15 SE +/- 0.10, N = 3 11.78 11.75 11.74 11.70 MIN: 9.74 / MAX: 12.5 MIN: 9.7 / MAX: 12.73 MIN: 9.67 / MAX: 12.77 MIN: 9.54 / MAX: 12.17
PyTorch Device: CPU - Batch Size: 512 - Model: Efficientnet_v2_l OpenBenchmarking.org batches/sec, More Is Better PyTorch 2.2.1 Device: CPU - Batch Size: 512 - Model: Efficientnet_v2_l d a b c 3 6 9 12 15 SE +/- 0.01, N = 3 11.76 11.76 11.67 11.56 MIN: 9.68 / MAX: 12.8 MIN: 9.55 / MAX: 12.64 MIN: 9.73 / MAX: 12.76 MIN: 9.64 / MAX: 12.51
Phoronix Test Suite v10.8.4