pytorch bench AMD Ryzen Threadripper 3990X 64-Core testing with a Gigabyte TRX40 AORUS PRO WIFI (F6 BIOS) and AMD Radeon RX 5700 8GB on Ubuntu 23.10 via the Phoronix Test Suite.
HTML result view exported from: https://openbenchmarking.org/result/2311179-PTS-PYTORCHB94&grw&rdt .
pytorch bench Processor Motherboard Chipset Memory Disk Graphics Audio Monitor Network OS Kernel Desktop Display Server OpenGL Compiler File-System Screen Resolution a b c AMD Ryzen Threadripper 3990X 64-Core @ 2.90GHz (64 Cores / 128 Threads) Gigabyte TRX40 AORUS PRO WIFI (F6 BIOS) AMD Starship/Matisse 128GB Samsung SSD 970 EVO Plus 500GB AMD Radeon RX 5700 8GB (1750/875MHz) AMD Navi 10 HDMI Audio DELL P2415Q Intel I211 + Intel Wi-Fi 6 AX200 Ubuntu 23.10 6.5.0-10-generic (x86_64) GNOME Shell 45.0 X Server + Wayland 4.6 Mesa 23.2.1-1ubuntu3 (LLVM 15.0.7 DRM 3.54) GCC 13.2.0 ext4 3840x2160 OpenBenchmarking.org Kernel Details - Transparent Huge Pages: madvise Processor Details - Scaling Governor: acpi-cpufreq schedutil (Boost: Enabled) - CPU Microcode: 0x830107a 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: Mitigation of untrained return thunk; SMT enabled with STIBP protection + 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 Retpolines IBPB: conditional STIBP: always-on RSB filling PBRSB-eIBRS: Not affected + srbds: Not affected + tsx_async_abort: Not affected
pytorch bench 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 20.88 8.22 16.88 17.11 15.96 6.69 16.66 6.78 16.59 6.84 7.01 6.89 4.36 3.07 3.01 2.96 2.93 2.92 18.63 7.80 16.03 16.09 15.99 6.81 16.83 6.76 16.06 6.82 6.52 6.66 4.17 2.90 2.99 2.92 2.86 2.91 19.18 8.03 15.57 16.52 16.35 6.76 16.27 6.69 15.64 6.67 6.65 6.51 4.16 2.93 2.96 2.96 3.02 2.99 OpenBenchmarking.org
PyTorch Device: CPU - Batch Size: 1 - Model: ResNet-50 OpenBenchmarking.org batches/sec, More Is Better PyTorch 2.1 Device: CPU - Batch Size: 1 - Model: ResNet-50 a b c 5 10 15 20 25 SE +/- 0.27, N = 3 20.88 18.63 19.18 MIN: 19.27 / MAX: 22.47 MIN: 17.58 / MAX: 19.74 MIN: 18.22 / MAX: 20.52
PyTorch Device: CPU - Batch Size: 1 - Model: ResNet-152 OpenBenchmarking.org batches/sec, More Is Better PyTorch 2.1 Device: CPU - Batch Size: 1 - Model: ResNet-152 a b c 2 4 6 8 10 SE +/- 0.10, N = 3 8.22 7.80 8.03 MIN: 7.88 / MAX: 8.56 MIN: 7.62 / MAX: 8.01 MIN: 7.82 / MAX: 8.21
PyTorch Device: CPU - Batch Size: 16 - Model: ResNet-50 OpenBenchmarking.org batches/sec, More Is Better PyTorch 2.1 Device: CPU - Batch Size: 16 - Model: ResNet-50 a b c 4 8 12 16 20 SE +/- 0.19, N = 3 16.88 16.03 15.57 MIN: 15.77 / MAX: 18.22 MIN: 14.93 / MAX: 16.68 MIN: 14.78 / MAX: 16.29
PyTorch Device: CPU - Batch Size: 32 - Model: ResNet-50 OpenBenchmarking.org batches/sec, More Is Better PyTorch 2.1 Device: CPU - Batch Size: 32 - Model: ResNet-50 a b c 4 8 12 16 20 SE +/- 0.20, N = 3 17.11 16.09 16.52 MIN: 15.92 / MAX: 18.06 MIN: 15.44 / MAX: 16.98 MIN: 15.52 / MAX: 17.2
PyTorch Device: CPU - Batch Size: 64 - Model: ResNet-50 OpenBenchmarking.org batches/sec, More Is Better PyTorch 2.1 Device: CPU - Batch Size: 64 - Model: ResNet-50 a b c 4 8 12 16 20 SE +/- 0.13, N = 3 15.96 15.99 16.35 MIN: 14.8 / MAX: 17.08 MIN: 15.31 / MAX: 16.83 MIN: 15.49 / MAX: 17.11
PyTorch Device: CPU - Batch Size: 16 - Model: ResNet-152 OpenBenchmarking.org batches/sec, More Is Better PyTorch 2.1 Device: CPU - Batch Size: 16 - Model: ResNet-152 a b c 2 4 6 8 10 SE +/- 0.06, N = 3 6.69 6.81 6.76 MIN: 6.41 / MAX: 6.91 MIN: 6.67 / MAX: 7 MIN: 6.34 / MAX: 6.95
PyTorch Device: CPU - Batch Size: 256 - Model: ResNet-50 OpenBenchmarking.org batches/sec, More Is Better PyTorch 2.1 Device: CPU - Batch Size: 256 - Model: ResNet-50 a b c 4 8 12 16 20 SE +/- 0.21, N = 3 16.66 16.83 16.27 MIN: 15.65 / MAX: 17.93 MIN: 15.98 / MAX: 17.49 MIN: 15.45 / MAX: 16.87
PyTorch Device: CPU - Batch Size: 32 - Model: ResNet-152 OpenBenchmarking.org batches/sec, More Is Better PyTorch 2.1 Device: CPU - Batch Size: 32 - Model: ResNet-152 a b c 2 4 6 8 10 SE +/- 0.06, N = 3 6.78 6.76 6.69 MIN: 6.21 / MAX: 7.03 MIN: 6.63 / MAX: 6.89 MIN: 6.25 / MAX: 6.86
PyTorch Device: CPU - Batch Size: 512 - Model: ResNet-50 OpenBenchmarking.org batches/sec, More Is Better PyTorch 2.1 Device: CPU - Batch Size: 512 - Model: ResNet-50 a b c 4 8 12 16 20 SE +/- 0.14, N = 8 16.59 16.06 15.64 MIN: 15.41 / MAX: 17.89 MIN: 14.68 / MAX: 16.72 MIN: 15.06 / MAX: 16.39
PyTorch Device: CPU - Batch Size: 64 - Model: ResNet-152 OpenBenchmarking.org batches/sec, More Is Better PyTorch 2.1 Device: CPU - Batch Size: 64 - Model: ResNet-152 a b c 2 4 6 8 10 SE +/- 0.08, N = 3 6.84 6.82 6.67 MIN: 6.51 / MAX: 7.13 MIN: 6.66 / MAX: 6.95 MIN: 6.48 / MAX: 6.83
PyTorch Device: CPU - Batch Size: 256 - Model: ResNet-152 OpenBenchmarking.org batches/sec, More Is Better PyTorch 2.1 Device: CPU - Batch Size: 256 - Model: ResNet-152 a b c 2 4 6 8 10 SE +/- 0.05, N = 3 7.01 6.52 6.65 MIN: 6.51 / MAX: 7.22 MIN: 6.32 / MAX: 6.71 MIN: 6.45 / MAX: 6.82
PyTorch Device: CPU - Batch Size: 512 - Model: ResNet-152 OpenBenchmarking.org batches/sec, More Is Better PyTorch 2.1 Device: CPU - Batch Size: 512 - Model: ResNet-152 a b c 2 4 6 8 10 SE +/- 0.01, N = 3 6.89 6.66 6.51 MIN: 6.48 / MAX: 7.08 MIN: 6.29 / MAX: 6.85 MIN: 6.34 / MAX: 6.69
PyTorch Device: CPU - Batch Size: 1 - Model: Efficientnet_v2_l OpenBenchmarking.org batches/sec, More Is Better PyTorch 2.1 Device: CPU - Batch Size: 1 - Model: Efficientnet_v2_l a b c 0.981 1.962 2.943 3.924 4.905 SE +/- 0.04, N = 3 4.36 4.17 4.16 MIN: 4.07 / MAX: 4.56 MIN: 3.98 / MAX: 4.35 MIN: 3.9 / MAX: 4.35
PyTorch Device: CPU - Batch Size: 16 - Model: Efficientnet_v2_l OpenBenchmarking.org batches/sec, More Is Better PyTorch 2.1 Device: CPU - Batch Size: 16 - Model: Efficientnet_v2_l a b c 0.6908 1.3816 2.0724 2.7632 3.454 SE +/- 0.03, N = 3 3.07 2.90 2.93 MIN: 2.85 / MAX: 3.2 MIN: 2.73 / MAX: 3.05 MIN: 2.82 / MAX: 3.07
PyTorch Device: CPU - Batch Size: 32 - Model: Efficientnet_v2_l OpenBenchmarking.org batches/sec, More Is Better PyTorch 2.1 Device: CPU - Batch Size: 32 - Model: Efficientnet_v2_l a b c 0.6773 1.3546 2.0319 2.7092 3.3865 SE +/- 0.04, N = 4 3.01 2.99 2.96 MIN: 2.81 / MAX: 3.25 MIN: 2.79 / MAX: 3.27 MIN: 2.83 / MAX: 3.07
PyTorch Device: CPU - Batch Size: 64 - Model: Efficientnet_v2_l OpenBenchmarking.org batches/sec, More Is Better PyTorch 2.1 Device: CPU - Batch Size: 64 - Model: Efficientnet_v2_l a b c 0.666 1.332 1.998 2.664 3.33 SE +/- 0.00, N = 3 2.96 2.92 2.96 MIN: 2.81 / MAX: 3.09 MIN: 2.76 / MAX: 3.04 MIN: 2.82 / MAX: 3.09
PyTorch Device: CPU - Batch Size: 256 - Model: Efficientnet_v2_l OpenBenchmarking.org batches/sec, More Is Better PyTorch 2.1 Device: CPU - Batch Size: 256 - Model: Efficientnet_v2_l a b c 0.6795 1.359 2.0385 2.718 3.3975 SE +/- 0.02, N = 3 2.93 2.86 3.02 MIN: 2.74 / MAX: 3.09 MIN: 2.76 / MAX: 2.99 MIN: 2.9 / MAX: 3.14
PyTorch Device: CPU - Batch Size: 512 - Model: Efficientnet_v2_l OpenBenchmarking.org batches/sec, More Is Better PyTorch 2.1 Device: CPU - Batch Size: 512 - Model: Efficientnet_v2_l a b c 0.6728 1.3456 2.0184 2.6912 3.364 SE +/- 0.02, N = 3 2.92 2.91 2.99 MIN: 2.78 / MAX: 3.12 MIN: 2.77 / MAX: 3.03 MIN: 2.84 / MAX: 3.16
Phoronix Test Suite v10.8.5