ripper-pytorch AMD Ryzen Threadripper 7960X 24-Cores testing with a ASRock TRX50 WS (7.09 BIOS) and NVIDIA GeForce RTX 4060 Ti 16GB on Ubuntu 22.04 via the Phoronix Test Suite.
HTML result view exported from: https://openbenchmarking.org/result/2403309-NE-RIPPERPYT22 .
ripper-pytorch Processor Motherboard Chipset Memory Disk Graphics Audio Monitor Network OS Kernel Desktop Display Server Display Driver OpenGL OpenCL Vulkan Compiler File-System Screen Resolution ripper-pytorch AMD Ryzen Threadripper 7960X 24-Cores @ 8.23GHz (24 Cores / 48 Threads) ASRock TRX50 WS (7.09 BIOS) AMD Device 14a4 128GB 2000GB Samsung SSD 980 PRO with Heatsink 2TB NVIDIA GeForce RTX 4060 Ti 16GB AMD Device 14cc SyncMaster Aquantia Device 04c0 + Realtek RTL8125 2.5GbE + MEDIATEK Device 0616 Ubuntu 22.04 6.5.0-26-generic (x86_64) GNOME Shell 42.9 X Server 1.21.1.4 NVIDIA 545.29.06 4.6.0 OpenCL 3.0 CUDA 12.3.99 1.3.260 GCC 11.4.0 ext4 1680x1050 OpenBenchmarking.org - Transparent Huge Pages: madvise - Scaling Governor: amd-pstate-epp powersave (EPP: performance) - CPU Microcode: 0xa108105 - 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
ripper-pytorch 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 pytorch: NVIDIA CUDA GPU - 1 - ResNet-50 pytorch: NVIDIA CUDA GPU - 1 - ResNet-152 pytorch: NVIDIA CUDA GPU - 16 - ResNet-50 pytorch: NVIDIA CUDA GPU - 32 - ResNet-50 pytorch: NVIDIA CUDA GPU - 64 - ResNet-50 pytorch: NVIDIA CUDA GPU - 16 - ResNet-152 pytorch: NVIDIA CUDA GPU - 256 - ResNet-50 pytorch: NVIDIA CUDA GPU - 32 - ResNet-152 pytorch: NVIDIA CUDA GPU - 512 - ResNet-50 pytorch: NVIDIA CUDA GPU - 64 - ResNet-152 pytorch: NVIDIA CUDA GPU - 256 - ResNet-152 pytorch: NVIDIA CUDA GPU - 512 - ResNet-152 pytorch: NVIDIA CUDA GPU - 1 - Efficientnet_v2_l pytorch: NVIDIA CUDA GPU - 16 - Efficientnet_v2_l pytorch: NVIDIA CUDA GPU - 32 - Efficientnet_v2_l pytorch: NVIDIA CUDA GPU - 64 - Efficientnet_v2_l pytorch: NVIDIA CUDA GPU - 256 - Efficientnet_v2_l pytorch: NVIDIA CUDA GPU - 512 - Efficientnet_v2_l ripper-pytorch 64.47 25.21 49.48 49.00 49.02 19.16 49.30 19.30 48.95 19.27 19.26 19.20 15.20 10.82 10.82 10.77 10.92 10.82 334.53 118.70 308.84 313.80 310.95 118.70 316.14 119.37 316.76 118.01 120.96 120.45 62.79 61.22 61.10 61.07 60.00 60.24 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 ripper-pytorch 14 28 42 56 70 SE +/- 0.27, N = 3 64.47 MIN: 49.55 / MAX: 66.67
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 ripper-pytorch 6 12 18 24 30 SE +/- 0.15, N = 3 25.21 MIN: 20.13 / MAX: 25.88
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 ripper-pytorch 11 22 33 44 55 SE +/- 0.11, N = 3 49.48 MIN: 46.91 / MAX: 50.12
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 ripper-pytorch 11 22 33 44 55 SE +/- 0.31, N = 3 49.00 MIN: 45.84 / MAX: 50.07
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 ripper-pytorch 11 22 33 44 55 SE +/- 0.26, N = 3 49.02 MIN: 46.16 / MAX: 49.85
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 ripper-pytorch 5 10 15 20 25 SE +/- 0.12, N = 3 19.16 MIN: 17.87 / MAX: 19.55
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 ripper-pytorch 11 22 33 44 55 SE +/- 0.22, N = 3 49.30 MIN: 46.71 / MAX: 50.14
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 ripper-pytorch 5 10 15 20 25 SE +/- 0.02, N = 3 19.30 MIN: 18.88 / MAX: 19.46
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 ripper-pytorch 11 22 33 44 55 SE +/- 0.17, N = 3 48.95 MIN: 45.69 / MAX: 49.93
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 ripper-pytorch 5 10 15 20 25 SE +/- 0.02, N = 3 19.27 MIN: 18.8 / MAX: 19.46
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 ripper-pytorch 5 10 15 20 25 SE +/- 0.02, N = 3 19.26 MIN: 18.76 / MAX: 19.4
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 ripper-pytorch 5 10 15 20 25 SE +/- 0.07, N = 3 19.20 MIN: 18.72 / MAX: 19.42
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 ripper-pytorch 4 8 12 16 20 SE +/- 0.07, N = 3 15.20 MIN: 12.84 / MAX: 15.51
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 ripper-pytorch 3 6 9 12 15 SE +/- 0.01, N = 3 10.82 MIN: 9.7 / MAX: 11.03
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 ripper-pytorch 3 6 9 12 15 SE +/- 0.01, N = 3 10.82 MIN: 9.47 / MAX: 11.07
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 ripper-pytorch 3 6 9 12 15 SE +/- 0.07, N = 3 10.77 MIN: 9.05 / MAX: 11.14
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 ripper-pytorch 3 6 9 12 15 SE +/- 0.04, N = 3 10.92 MIN: 9.71 / MAX: 11.17
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 ripper-pytorch 3 6 9 12 15 SE +/- 0.02, N = 3 10.82 MIN: 9.59 / MAX: 11.05
PyTorch Device: NVIDIA CUDA GPU - Batch Size: 1 - Model: ResNet-50 OpenBenchmarking.org batches/sec, More Is Better PyTorch 2.2.1 Device: NVIDIA CUDA GPU - Batch Size: 1 - Model: ResNet-50 ripper-pytorch 70 140 210 280 350 SE +/- 2.80, N = 3 334.53 MIN: 278.54 / MAX: 343.94
PyTorch Device: NVIDIA CUDA GPU - Batch Size: 1 - Model: ResNet-152 OpenBenchmarking.org batches/sec, More Is Better PyTorch 2.2.1 Device: NVIDIA CUDA GPU - Batch Size: 1 - Model: ResNet-152 ripper-pytorch 30 60 90 120 150 SE +/- 0.39, N = 3 118.70 MIN: 104.59 / MAX: 121.02
PyTorch Device: NVIDIA CUDA GPU - Batch Size: 16 - Model: ResNet-50 OpenBenchmarking.org batches/sec, More Is Better PyTorch 2.2.1 Device: NVIDIA CUDA GPU - Batch Size: 16 - Model: ResNet-50 ripper-pytorch 70 140 210 280 350 SE +/- 1.97, N = 3 308.84 MIN: 286.79 / MAX: 316.03
PyTorch Device: NVIDIA CUDA GPU - Batch Size: 32 - Model: ResNet-50 OpenBenchmarking.org batches/sec, More Is Better PyTorch 2.2.1 Device: NVIDIA CUDA GPU - Batch Size: 32 - Model: ResNet-50 ripper-pytorch 70 140 210 280 350 SE +/- 2.54, N = 3 313.80 MIN: 289.68 / MAX: 320.89
PyTorch Device: NVIDIA CUDA GPU - Batch Size: 64 - Model: ResNet-50 OpenBenchmarking.org batches/sec, More Is Better PyTorch 2.2.1 Device: NVIDIA CUDA GPU - Batch Size: 64 - Model: ResNet-50 ripper-pytorch 70 140 210 280 350 SE +/- 3.16, N = 3 310.95 MIN: 284.77 / MAX: 319.52
PyTorch Device: NVIDIA CUDA GPU - Batch Size: 16 - Model: ResNet-152 OpenBenchmarking.org batches/sec, More Is Better PyTorch 2.2.1 Device: NVIDIA CUDA GPU - Batch Size: 16 - Model: ResNet-152 ripper-pytorch 30 60 90 120 150 SE +/- 1.27, N = 3 118.70 MIN: 105.17 / MAX: 122.87
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 ripper-pytorch 70 140 210 280 350 SE +/- 1.84, N = 3 316.14 MIN: 296.19 / MAX: 323.31
PyTorch Device: NVIDIA CUDA GPU - Batch Size: 32 - Model: ResNet-152 OpenBenchmarking.org batches/sec, More Is Better PyTorch 2.2.1 Device: NVIDIA CUDA GPU - Batch Size: 32 - Model: ResNet-152 ripper-pytorch 30 60 90 120 150 SE +/- 0.31, N = 3 119.37 MIN: 106.4 / MAX: 120.94
PyTorch Device: NVIDIA CUDA GPU - Batch Size: 512 - Model: ResNet-50 OpenBenchmarking.org batches/sec, More Is Better PyTorch 2.2.1 Device: NVIDIA CUDA GPU - Batch Size: 512 - Model: ResNet-50 ripper-pytorch 70 140 210 280 350 SE +/- 1.73, N = 3 316.76 MIN: 288.88 / MAX: 324.66
PyTorch Device: NVIDIA CUDA GPU - Batch Size: 64 - Model: ResNet-152 OpenBenchmarking.org batches/sec, More Is Better PyTorch 2.2.1 Device: NVIDIA CUDA GPU - Batch Size: 64 - Model: ResNet-152 ripper-pytorch 30 60 90 120 150 SE +/- 0.89, N = 3 118.01 MIN: 105.65 / MAX: 120.3
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 ripper-pytorch 30 60 90 120 150 SE +/- 1.01, N = 3 120.96 MIN: 107.66 / MAX: 123.82
PyTorch Device: NVIDIA CUDA GPU - Batch Size: 512 - Model: ResNet-152 OpenBenchmarking.org batches/sec, More Is Better PyTorch 2.2.1 Device: NVIDIA CUDA GPU - Batch Size: 512 - Model: ResNet-152 ripper-pytorch 30 60 90 120 150 SE +/- 0.12, N = 3 120.45 MIN: 107.48 / MAX: 122.04
PyTorch Device: NVIDIA CUDA GPU - Batch Size: 1 - Model: Efficientnet_v2_l OpenBenchmarking.org batches/sec, More Is Better PyTorch 2.2.1 Device: NVIDIA CUDA GPU - Batch Size: 1 - Model: Efficientnet_v2_l ripper-pytorch 14 28 42 56 70 SE +/- 0.30, N = 3 62.79 MIN: 54.78 / MAX: 63.93
PyTorch Device: NVIDIA CUDA GPU - Batch Size: 16 - Model: Efficientnet_v2_l OpenBenchmarking.org batches/sec, More Is Better PyTorch 2.2.1 Device: NVIDIA CUDA GPU - Batch Size: 16 - Model: Efficientnet_v2_l ripper-pytorch 14 28 42 56 70 SE +/- 0.18, N = 3 61.22 MIN: 53.84 / MAX: 62.11
PyTorch Device: NVIDIA CUDA GPU - Batch Size: 32 - Model: Efficientnet_v2_l OpenBenchmarking.org batches/sec, More Is Better PyTorch 2.2.1 Device: NVIDIA CUDA GPU - Batch Size: 32 - Model: Efficientnet_v2_l ripper-pytorch 14 28 42 56 70 SE +/- 0.60, N = 3 61.10 MIN: 54.19 / MAX: 62.82
PyTorch Device: NVIDIA CUDA GPU - Batch Size: 64 - Model: Efficientnet_v2_l OpenBenchmarking.org batches/sec, More Is Better PyTorch 2.2.1 Device: NVIDIA CUDA GPU - Batch Size: 64 - Model: Efficientnet_v2_l ripper-pytorch 14 28 42 56 70 SE +/- 0.60, N = 5 61.07 MIN: 52.92 / MAX: 62.55
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 ripper-pytorch 13 26 39 52 65 SE +/- 0.52, N = 3 60.00 MIN: 52.58 / MAX: 61.37
PyTorch Device: NVIDIA CUDA GPU - Batch Size: 512 - Model: Efficientnet_v2_l OpenBenchmarking.org batches/sec, More Is Better PyTorch 2.2.1 Device: NVIDIA CUDA GPU - Batch Size: 512 - Model: Efficientnet_v2_l ripper-pytorch 13 26 39 52 65 SE +/- 0.62, N = 3 60.24 MIN: 53.1 / MAX: 61.93
Phoronix Test Suite v10.8.5