pytorch tensorflow 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/2403274-PTS-PYTORCHT32&grr .
pytorch tensorflow Processor Motherboard Chipset Memory Disk Graphics Audio Monitor Network OS Kernel Desktop Display Server Display Driver OpenGL OpenCL Compiler File-System Screen Resolution AMD Ryzen 9 7950X 16-Core - NVIDIA GeForce RTX 3080 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 - Transparent Huge Pages: madvise - Scaling Governor: amd-pstate-epp powersave (EPP: balance_performance) - CPU Microcode: 0xa601206 - Python 3.11.6 - 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 tensorflow tensorflow: CPU - 64 - VGG-16 tensorflow: CPU - 32 - VGG-16 pytorch: CPU - 16 - Efficientnet_v2_l tensorflow: CPU - 64 - ResNet-50 pytorch: CPU - 64 - Efficientnet_v2_l pytorch: CPU - 32 - Efficientnet_v2_l pytorch: CPU - 256 - Efficientnet_v2_l tensorflow: CPU - 16 - VGG-16 pytorch: CPU - 32 - ResNet-152 pytorch: CPU - 64 - ResNet-152 pytorch: CPU - 256 - ResNet-152 pytorch: CPU - 16 - ResNet-152 tensorflow: CPU - 32 - ResNet-50 pytorch: CPU - 1 - Efficientnet_v2_l tensorflow: CPU - 64 - GoogLeNet tensorflow: CPU - 16 - ResNet-50 pytorch: CPU - 64 - ResNet-50 pytorch: CPU - 32 - ResNet-50 pytorch: CPU - 256 - ResNet-50 pytorch: CPU - 1 - ResNet-152 pytorch: CPU - 16 - ResNet-50 tensorflow: CPU - 32 - GoogLeNet tensorflow: CPU - 64 - AlexNet tensorflow: CPU - 1 - VGG-16 pytorch: CPU - 1 - ResNet-50 tensorflow: CPU - 32 - AlexNet tensorflow: CPU - 16 - GoogLeNet tensorflow: CPU - 16 - AlexNet tensorflow: CPU - 1 - ResNet-50 tensorflow: CPU - 1 - AlexNet tensorflow: CPU - 1 - GoogLeNet AMD Ryzen 9 7950X 16-Core - NVIDIA GeForce RTX 3080 19.68 18.99 11.56 42.68 11.77 11.86 11.84 18.05 19.52 19.69 19.90 20.08 42.48 16.53 138.76 41.34 48.57 48.54 48.51 29.39 48.85 141.41 334.74 5.65 71.77 254.51 142.24 170.76 16.15 16.11 61.10 OpenBenchmarking.org
TensorFlow Device: CPU - Batch Size: 64 - Model: VGG-16 OpenBenchmarking.org images/sec, More Is Better TensorFlow 2.16.1 Device: CPU - Batch Size: 64 - Model: VGG-16 AMD Ryzen 9 7950X 16-Core - NVIDIA GeForce RTX 3080 5 10 15 20 25 SE +/- 0.01, N = 3 19.68
TensorFlow Device: CPU - Batch Size: 32 - Model: VGG-16 OpenBenchmarking.org images/sec, More Is Better TensorFlow 2.16.1 Device: CPU - Batch Size: 32 - Model: VGG-16 AMD Ryzen 9 7950X 16-Core - NVIDIA GeForce RTX 3080 5 10 15 20 25 SE +/- 0.02, N = 3 18.99
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 AMD Ryzen 9 7950X 16-Core - NVIDIA GeForce RTX 3080 3 6 9 12 15 SE +/- 0.15, N = 3 11.56 MIN: 9.38 / MAX: 12.7
TensorFlow Device: CPU - Batch Size: 64 - Model: ResNet-50 OpenBenchmarking.org images/sec, More Is Better TensorFlow 2.16.1 Device: CPU - Batch Size: 64 - Model: ResNet-50 AMD Ryzen 9 7950X 16-Core - NVIDIA GeForce RTX 3080 10 20 30 40 50 SE +/- 0.01, N = 3 42.68
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 AMD Ryzen 9 7950X 16-Core - NVIDIA GeForce RTX 3080 3 6 9 12 15 SE +/- 0.08, N = 3 11.77 MIN: 9.64 / MAX: 12.77
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 AMD Ryzen 9 7950X 16-Core - NVIDIA GeForce RTX 3080 3 6 9 12 15 SE +/- 0.05, N = 3 11.86 MIN: 9.68 / MAX: 12.71
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 AMD Ryzen 9 7950X 16-Core - NVIDIA GeForce RTX 3080 3 6 9 12 15 SE +/- 0.10, N = 3 11.84 MIN: 9.61 / MAX: 12.83
TensorFlow Device: CPU - Batch Size: 16 - Model: VGG-16 OpenBenchmarking.org images/sec, More Is Better TensorFlow 2.16.1 Device: CPU - Batch Size: 16 - Model: VGG-16 AMD Ryzen 9 7950X 16-Core - NVIDIA GeForce RTX 3080 4 8 12 16 20 SE +/- 0.12, N = 3 18.05
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 AMD Ryzen 9 7950X 16-Core - NVIDIA GeForce RTX 3080 5 10 15 20 25 SE +/- 0.14, N = 3 19.52 MIN: 18.86 / MAX: 20.1
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 AMD Ryzen 9 7950X 16-Core - NVIDIA GeForce RTX 3080 5 10 15 20 25 SE +/- 0.21, N = 3 19.69 MIN: 19.03 / MAX: 20.31
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 AMD Ryzen 9 7950X 16-Core - NVIDIA GeForce RTX 3080 5 10 15 20 25 SE +/- 0.21, N = 3 19.90 MIN: 19.05 / MAX: 20.71
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 AMD Ryzen 9 7950X 16-Core - NVIDIA GeForce RTX 3080 5 10 15 20 25 SE +/- 0.15, N = 3 20.08 MIN: 15.43 / MAX: 20.67
TensorFlow Device: CPU - Batch Size: 32 - Model: ResNet-50 OpenBenchmarking.org images/sec, More Is Better TensorFlow 2.16.1 Device: CPU - Batch Size: 32 - Model: ResNet-50 AMD Ryzen 9 7950X 16-Core - NVIDIA GeForce RTX 3080 10 20 30 40 50 SE +/- 0.01, N = 3 42.48
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 AMD Ryzen 9 7950X 16-Core - NVIDIA GeForce RTX 3080 4 8 12 16 20 SE +/- 0.05, N = 3 16.53 MIN: 14.7 / MAX: 16.81
TensorFlow Device: CPU - Batch Size: 64 - Model: GoogLeNet OpenBenchmarking.org images/sec, More Is Better TensorFlow 2.16.1 Device: CPU - Batch Size: 64 - Model: GoogLeNet AMD Ryzen 9 7950X 16-Core - NVIDIA GeForce RTX 3080 30 60 90 120 150 SE +/- 0.01, N = 3 138.76
TensorFlow Device: CPU - Batch Size: 16 - Model: ResNet-50 OpenBenchmarking.org images/sec, More Is Better TensorFlow 2.16.1 Device: CPU - Batch Size: 16 - Model: ResNet-50 AMD Ryzen 9 7950X 16-Core - NVIDIA GeForce RTX 3080 9 18 27 36 45 SE +/- 0.04, N = 3 41.34
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 AMD Ryzen 9 7950X 16-Core - NVIDIA GeForce RTX 3080 11 22 33 44 55 SE +/- 0.40, N = 3 48.57 MIN: 45.94 / MAX: 49.92
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 AMD Ryzen 9 7950X 16-Core - NVIDIA GeForce RTX 3080 11 22 33 44 55 SE +/- 0.47, N = 3 48.54 MIN: 38.25 / MAX: 50.46
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 AMD Ryzen 9 7950X 16-Core - NVIDIA GeForce RTX 3080 11 22 33 44 55 SE +/- 0.15, N = 3 48.51 MIN: 46.12 / MAX: 49.98
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 AMD Ryzen 9 7950X 16-Core - NVIDIA GeForce RTX 3080 7 14 21 28 35 SE +/- 0.31, N = 3 29.39 MIN: 22.95 / MAX: 30.32
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 AMD Ryzen 9 7950X 16-Core - NVIDIA GeForce RTX 3080 11 22 33 44 55 SE +/- 0.29, N = 3 48.85 MIN: 47.27 / MAX: 50.05
TensorFlow Device: CPU - Batch Size: 32 - Model: GoogLeNet OpenBenchmarking.org images/sec, More Is Better TensorFlow 2.16.1 Device: CPU - Batch Size: 32 - Model: GoogLeNet AMD Ryzen 9 7950X 16-Core - NVIDIA GeForce RTX 3080 30 60 90 120 150 SE +/- 0.10, N = 3 141.41
TensorFlow Device: CPU - Batch Size: 64 - Model: AlexNet OpenBenchmarking.org images/sec, More Is Better TensorFlow 2.16.1 Device: CPU - Batch Size: 64 - Model: AlexNet AMD Ryzen 9 7950X 16-Core - NVIDIA GeForce RTX 3080 70 140 210 280 350 SE +/- 0.08, N = 3 334.74
TensorFlow Device: CPU - Batch Size: 1 - Model: VGG-16 OpenBenchmarking.org images/sec, More Is Better TensorFlow 2.16.1 Device: CPU - Batch Size: 1 - Model: VGG-16 AMD Ryzen 9 7950X 16-Core - NVIDIA GeForce RTX 3080 1.2713 2.5426 3.8139 5.0852 6.3565 SE +/- 0.00, N = 3 5.65
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 AMD Ryzen 9 7950X 16-Core - NVIDIA GeForce RTX 3080 16 32 48 64 80 SE +/- 0.19, N = 3 71.77 MIN: 57.05 / MAX: 74.1
TensorFlow Device: CPU - Batch Size: 32 - Model: AlexNet OpenBenchmarking.org images/sec, More Is Better TensorFlow 2.16.1 Device: CPU - Batch Size: 32 - Model: AlexNet AMD Ryzen 9 7950X 16-Core - NVIDIA GeForce RTX 3080 60 120 180 240 300 SE +/- 0.04, N = 3 254.51
TensorFlow Device: CPU - Batch Size: 16 - Model: GoogLeNet OpenBenchmarking.org images/sec, More Is Better TensorFlow 2.16.1 Device: CPU - Batch Size: 16 - Model: GoogLeNet AMD Ryzen 9 7950X 16-Core - NVIDIA GeForce RTX 3080 30 60 90 120 150 SE +/- 0.23, N = 3 142.24
TensorFlow Device: CPU - Batch Size: 16 - Model: AlexNet OpenBenchmarking.org images/sec, More Is Better TensorFlow 2.16.1 Device: CPU - Batch Size: 16 - Model: AlexNet AMD Ryzen 9 7950X 16-Core - NVIDIA GeForce RTX 3080 40 80 120 160 200 SE +/- 0.23, N = 3 170.76
TensorFlow Device: CPU - Batch Size: 1 - Model: ResNet-50 OpenBenchmarking.org images/sec, More Is Better TensorFlow 2.16.1 Device: CPU - Batch Size: 1 - Model: ResNet-50 AMD Ryzen 9 7950X 16-Core - NVIDIA GeForce RTX 3080 4 8 12 16 20 SE +/- 0.03, N = 3 16.15
TensorFlow Device: CPU - Batch Size: 1 - Model: AlexNet OpenBenchmarking.org images/sec, More Is Better TensorFlow 2.16.1 Device: CPU - Batch Size: 1 - Model: AlexNet AMD Ryzen 9 7950X 16-Core - NVIDIA GeForce RTX 3080 4 8 12 16 20 SE +/- 0.01, N = 3 16.11
TensorFlow Device: CPU - Batch Size: 1 - Model: GoogLeNet OpenBenchmarking.org images/sec, More Is Better TensorFlow 2.16.1 Device: CPU - Batch Size: 1 - Model: GoogLeNet AMD Ryzen 9 7950X 16-Core - NVIDIA GeForce RTX 3080 14 28 42 56 70 SE +/- 0.30, N = 3 61.10
Phoronix Test Suite v10.8.5