pytorch 2.2.1 AMD Ryzen Threadripper 7980X 64-Cores testing with a System76 Thelio Major (FA Z5 BIOS) and AMD Radeon Pro W7900 45GB on Ubuntu 23.10 via the Phoronix Test Suite.
HTML result view exported from: https://openbenchmarking.org/result/2403260-PTS-PYTORCH257&grr&sor .
pytorch 2.2.1 Processor Motherboard Chipset Memory Disk Graphics Audio Monitor Network OS Kernel Desktop Display Server OpenGL Compiler File-System Screen Resolution a b c d AMD Ryzen Threadripper 7980X 64-Cores @ 7.79GHz (64 Cores / 128 Threads) System76 Thelio Major (FA Z5 BIOS) AMD Device 14a4 4 x 32GB DRAM-4800MT/s Micron MTC20F1045S1RC48BA2 1000GB CT1000T700SSD5 AMD Radeon Pro W7900 45GB (1760/1124MHz) AMD Device 14cc DELL P2415Q Aquantia AQC113C NBase-T/IEEE + Realtek RTL8125 2.5GbE + Intel Wi-Fi 6 AX210/AX211/AX411 Ubuntu 23.10 6.5.0-26-generic (x86_64) GNOME Shell 45.2 X Server + Wayland 4.6 Mesa 23.2.1-1ubuntu3.1 (LLVM 15.0.7 DRM 3.54) GCC 13.2.0 ext4 1920x1080 OpenBenchmarking.org Kernel Details - Transparent Huge Pages: madvise Processor Details - Scaling Governor: amd-pstate-epp powersave (EPP: balance_performance) - CPU Microcode: 0xa108105 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 pytorch: CPU - 64 - Efficientnet_v2_l pytorch: CPU - 256 - Efficientnet_v2_l pytorch: CPU - 16 - Efficientnet_v2_l pytorch: CPU - 32 - Efficientnet_v2_l pytorch: CPU - 512 - Efficientnet_v2_l pytorch: CPU - 512 - ResNet-152 pytorch: CPU - 16 - ResNet-152 pytorch: CPU - 256 - ResNet-152 pytorch: CPU - 32 - ResNet-152 pytorch: CPU - 64 - ResNet-152 pytorch: CPU - 1 - Efficientnet_v2_l pytorch: CPU - 1 - ResNet-152 pytorch: CPU - 32 - ResNet-50 pytorch: CPU - 512 - ResNet-50 pytorch: CPU - 16 - ResNet-50 pytorch: CPU - 64 - ResNet-50 pytorch: CPU - 256 - ResNet-50 pytorch: CPU - 1 - ResNet-50 a b c d 7.78 7.78 7.80 7.81 7.78 18.81 18.71 19.02 19.00 18.97 11.99 21.82 48.43 47.84 48.10 48.25 48.50 59.87 7.80 7.77 7.81 7.79 7.79 19.05 19.43 19.47 18.93 19.34 11.94 21.87 46.91 48.12 48.04 47.84 47.98 60.44 7.76 7.74 7.82 7.77 7.79 18.74 19.18 18.88 19.09 18.51 12.00 21.75 47.35 48.13 47.59 47.79 47.63 59.76 7.80 7.81 7.74 7.79 7.75 19.16 18.62 18.92 19.37 19.43 12.05 22.04 47.11 47.27 47.90 47.52 48.71 59.78 OpenBenchmarking.org
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 2 4 6 8 10 SE +/- 0.02, N = 3 7.80 7.80 7.78 7.76 MIN: 7.12 / MAX: 8.13 MIN: 7.04 / MAX: 8.09 MIN: 7.07 / MAX: 8.15 MIN: 7.17 / MAX: 8.13
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 d a b c 2 4 6 8 10 SE +/- 0.01, N = 3 7.81 7.78 7.77 7.74 MIN: 7.08 / MAX: 8.17 MIN: 7.1 / MAX: 8.12 MIN: 7.09 / MAX: 8.11 MIN: 7 / MAX: 8.06
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 c b a d 2 4 6 8 10 SE +/- 0.02, N = 3 7.82 7.81 7.80 7.74 MIN: 7.22 / MAX: 8.18 MIN: 7.14 / MAX: 8.1 MIN: 7.02 / MAX: 8.19 MIN: 7 / MAX: 8.01
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 a d b c 2 4 6 8 10 SE +/- 0.01, N = 3 7.81 7.79 7.79 7.77 MIN: 7.09 / MAX: 8.15 MIN: 7.2 / MAX: 8.08 MIN: 7.08 / MAX: 8.09 MIN: 7.04 / MAX: 8.06
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 c b a d 2 4 6 8 10 SE +/- 0.02, N = 3 7.79 7.79 7.78 7.75 MIN: 7.14 / MAX: 8.11 MIN: 7.21 / MAX: 8.14 MIN: 7.11 / MAX: 8.12 MIN: 7.2 / MAX: 8.05
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 d b a c 5 10 15 20 25 SE +/- 0.12, N = 3 19.16 19.05 18.81 18.74 MIN: 18.7 / MAX: 19.35 MIN: 18.53 / MAX: 19.21 MIN: 18.12 / MAX: 19.1 MIN: 18.24 / MAX: 18.88
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 b c a d 5 10 15 20 25 SE +/- 0.07, N = 3 19.43 19.18 18.71 18.62 MIN: 18.98 / MAX: 19.61 MIN: 18.6 / MAX: 19.36 MIN: 18.06 / MAX: 18.98 MIN: 18.1 / MAX: 18.77
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 b a d c 5 10 15 20 25 SE +/- 0.05, N = 3 19.47 19.02 18.92 18.88 MIN: 18.9 / MAX: 19.63 MIN: 18.43 / MAX: 19.26 MIN: 18.19 / MAX: 19.1 MIN: 18.14 / MAX: 19.04
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 d c a b 5 10 15 20 25 SE +/- 0.02, N = 3 19.37 19.09 19.00 18.93 MIN: 18.65 / MAX: 19.53 MIN: 18.53 / MAX: 19.25 MIN: 18.39 / MAX: 19.17 MIN: 18.35 / MAX: 19.07
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 d b a c 5 10 15 20 25 SE +/- 0.15, N = 3 19.43 19.34 18.97 18.51 MIN: 19.02 / MAX: 19.6 MIN: 18.65 / MAX: 19.48 MIN: 18.22 / MAX: 19.28 MIN: 17.93 / MAX: 18.68
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 d c a b 3 6 9 12 15 SE +/- 0.09, N = 3 12.05 12.00 11.99 11.94 MIN: 11.9 / MAX: 12.2 MIN: 10.62 / MAX: 12.16 MIN: 11.68 / MAX: 12.24 MIN: 11.71 / MAX: 12.13
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 d b a c 5 10 15 20 25 SE +/- 0.08, N = 3 22.04 21.87 21.82 21.75 MIN: 21.04 / MAX: 22.24 MIN: 20.98 / MAX: 22.14 MIN: 21.05 / MAX: 22.15 MIN: 20.95 / MAX: 21.96
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 a c d b 11 22 33 44 55 SE +/- 0.09, N = 3 48.43 47.35 47.11 46.91 MIN: 43.88 / MAX: 49.3 MIN: 43.64 / MAX: 48.24 MIN: 44.02 / MAX: 47.74 MIN: 43.81 / MAX: 47.55
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 +/- 0.10, N = 3 48.13 48.12 47.84 47.27 MIN: 43.45 / MAX: 48.9 MIN: 44.65 / MAX: 48.96 MIN: 43.86 / MAX: 48.56 MIN: 43.83 / MAX: 48.07
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 a b d c 11 22 33 44 55 SE +/- 0.25, N = 3 48.10 48.04 47.90 47.59 MIN: 42 / MAX: 49.24 MIN: 44.19 / MAX: 48.74 MIN: 44.12 / MAX: 48.66 MIN: 44.44 / MAX: 48.39
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 a b c d 11 22 33 44 55 SE +/- 0.16, N = 3 48.25 47.84 47.79 47.52 MIN: 43.55 / MAX: 49.28 MIN: 44.44 / MAX: 48.63 MIN: 44.49 / MAX: 48.52 MIN: 43.99 / MAX: 48.23
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 d a b c 11 22 33 44 55 SE +/- 0.17, N = 3 48.71 48.50 47.98 47.63 MIN: 44.82 / MAX: 49.49 MIN: 44.96 / MAX: 49.46 MIN: 43.06 / MAX: 48.63 MIN: 43.91 / MAX: 48.42
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 b a d c 14 28 42 56 70 SE +/- 0.10, N = 3 60.44 59.87 59.78 59.76 MIN: 55.61 / MAX: 61.31 MIN: 53.95 / MAX: 61.32 MIN: 53.76 / MAX: 60.69 MIN: 54.51 / MAX: 60.81
Phoronix Test Suite v10.8.5