res4 AMD Ryzen 9 5900X 12-Core testing with a ASRock X570 Steel Legend (P5.63 BIOS) and MSI NVIDIA GeForce RTX 3080 12GB on Ubuntu 22.04 via the Phoronix Test Suite.
HTML result view exported from: https://openbenchmarking.org/result/2412139-NE-RES40086214&grt .
res4 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 5900X 12-Core - MSI NVIDIA GeForce RTX AMD Ryzen 9 5900X 12-Core @ 3.70GHz (12 Cores / 24 Threads) ASRock X570 Steel Legend (P5.63 BIOS) AMD Starship/Matisse 2 x 16GB DDR4-3600MT/s TEAMGROUP-UD4-3200 1000GB Western Digital WDS100T3X0C-00SJG0 + 1000GB Western Digital WD Blue SN580 1TB + 2000GB Seagate ST2000DX001-1CM1 MSI NVIDIA GeForce RTX 3080 12GB NVIDIA GA102 HD Audio DELL S2721QS Intel I211 + Intel Dual Band-AC 3168NGW Ubuntu 22.04 6.8.0-49-generic (x86_64) GNOME Shell 42.9 X Server 1.21.1.4 NVIDIA 560.35.05 4.6.0 OpenCL 3.0 CUDA 12.6.65 GCC 11.4.0 + CUDA 12.6 ext4 5120x2880 OpenBenchmarking.org - Transparent Huge Pages: madvise - Scaling Governor: acpi-cpufreq schedutil (Boost: Enabled) - CPU Microcode: 0xa20102b - 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 + reg_file_data_sampling: 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 Retpolines; IBPB: conditional; IBRS_FW; STIBP: always-on; RSB filling; PBRSB-eIBRS: Not affected; BHI: Not affected + srbds: Not affected + tsx_async_abort: Not affected
res4 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 AMD Ryzen 9 5900X 12-Core - MSI NVIDIA GeForce RTX 43.00 16.62 31.34 30.89 31.50 12.59 31.29 12.54 31.29 12.67 12.54 12.48 10.75 7.44 7.42 7.47 7.46 7.47 214.06 74.95 216.90 214.52 215.27 74.74 216.56 74.87 215.46 77.23 75.90 75.09 39.31 38.68 38.77 38.69 38.89 38.48 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 AMD Ryzen 9 5900X 12-Core - MSI NVIDIA GeForce RTX 10 20 30 40 50 SE +/- 0.03, N = 3 43.00 MIN: 38.05 / MAX: 43.7
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 5900X 12-Core - MSI NVIDIA GeForce RTX 4 8 12 16 20 SE +/- 0.09, N = 3 16.62 MIN: 15.98 / MAX: 16.91
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 5900X 12-Core - MSI NVIDIA GeForce RTX 7 14 21 28 35 SE +/- 0.16, N = 3 31.34 MIN: 30.35 / MAX: 31.89
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 5900X 12-Core - MSI NVIDIA GeForce RTX 7 14 21 28 35 SE +/- 0.28, N = 6 30.89 MIN: 28.53 / MAX: 31.81
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 5900X 12-Core - MSI NVIDIA GeForce RTX 7 14 21 28 35 SE +/- 0.17, N = 3 31.50 MIN: 28.43 / MAX: 32.09
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 5900X 12-Core - MSI NVIDIA GeForce RTX 3 6 9 12 15 SE +/- 0.03, N = 3 12.59 MIN: 11.67 / MAX: 12.74
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 5900X 12-Core - MSI NVIDIA GeForce RTX 7 14 21 28 35 SE +/- 0.10, N = 3 31.29 MIN: 29.83 / MAX: 31.97
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 5900X 12-Core - MSI NVIDIA GeForce RTX 3 6 9 12 15 SE +/- 0.03, N = 3 12.54 MIN: 12.07 / MAX: 12.69
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 AMD Ryzen 9 5900X 12-Core - MSI NVIDIA GeForce RTX 7 14 21 28 35 SE +/- 0.26, N = 3 31.29 MIN: 29.95 / MAX: 31.91
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 5900X 12-Core - MSI NVIDIA GeForce RTX 3 6 9 12 15 SE +/- 0.12, N = 3 12.67 MIN: 12.32 / MAX: 12.98
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 5900X 12-Core - MSI NVIDIA GeForce RTX 3 6 9 12 15 SE +/- 0.03, N = 3 12.54 MIN: 11.57 / MAX: 12.69
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 AMD Ryzen 9 5900X 12-Core - MSI NVIDIA GeForce RTX 3 6 9 12 15 SE +/- 0.04, N = 3 12.48 MIN: 11.94 / MAX: 12.66
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 5900X 12-Core - MSI NVIDIA GeForce RTX 3 6 9 12 15 SE +/- 0.01, N = 3 10.75 MIN: 10.61 / MAX: 10.83
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 5900X 12-Core - MSI NVIDIA GeForce RTX 2 4 6 8 10 SE +/- 0.00, N = 3 7.44 MIN: 7.32 / MAX: 7.51
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 5900X 12-Core - MSI NVIDIA GeForce RTX 2 4 6 8 10 SE +/- 0.02, N = 3 7.42 MIN: 7.33 / MAX: 7.51
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 5900X 12-Core - MSI NVIDIA GeForce RTX 2 4 6 8 10 SE +/- 0.06, N = 3 7.47 MIN: 7.17 / MAX: 7.65
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 5900X 12-Core - MSI NVIDIA GeForce RTX 2 4 6 8 10 SE +/- 0.01, N = 3 7.46 MIN: 7.34 / MAX: 7.53
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 AMD Ryzen 9 5900X 12-Core - MSI NVIDIA GeForce RTX 2 4 6 8 10 SE +/- 0.06, N = 3 7.47 MIN: 7.34 / MAX: 7.62
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 AMD Ryzen 9 5900X 12-Core - MSI NVIDIA GeForce RTX 50 100 150 200 250 SE +/- 2.68, N = 3 214.06 MIN: 189.9 / MAX: 220.75
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 AMD Ryzen 9 5900X 12-Core - MSI NVIDIA GeForce RTX 20 40 60 80 100 SE +/- 0.54, N = 15 74.95 MIN: 68.83 / MAX: 79.29
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 AMD Ryzen 9 5900X 12-Core - MSI NVIDIA GeForce RTX 50 100 150 200 250 SE +/- 2.43, N = 3 216.90 MIN: 162.31 / MAX: 223.42
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 AMD Ryzen 9 5900X 12-Core - MSI NVIDIA GeForce RTX 50 100 150 200 250 SE +/- 2.51, N = 4 214.52 MIN: 201.54 / MAX: 223.62
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 AMD Ryzen 9 5900X 12-Core - MSI NVIDIA GeForce RTX 50 100 150 200 250 SE +/- 1.54, N = 12 215.27 MIN: 193.15 / MAX: 224.79
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 AMD Ryzen 9 5900X 12-Core - MSI NVIDIA GeForce RTX 20 40 60 80 100 SE +/- 0.75, N = 3 74.74 MIN: 70.11 / MAX: 78.16
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 AMD Ryzen 9 5900X 12-Core - MSI NVIDIA GeForce RTX 50 100 150 200 250 SE +/- 3.02, N = 3 216.56 MIN: 196.66 / MAX: 221.76
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 AMD Ryzen 9 5900X 12-Core - MSI NVIDIA GeForce RTX 20 40 60 80 100 SE +/- 0.25, N = 3 74.87 MIN: 69.21 / MAX: 75.96
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 AMD Ryzen 9 5900X 12-Core - MSI NVIDIA GeForce RTX 50 100 150 200 250 SE +/- 2.58, N = 4 215.46 MIN: 200.19 / MAX: 224.64
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 AMD Ryzen 9 5900X 12-Core - MSI NVIDIA GeForce RTX 20 40 60 80 100 SE +/- 0.33, N = 3 77.23 MIN: 70.71 / MAX: 78.87
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 AMD Ryzen 9 5900X 12-Core - MSI NVIDIA GeForce RTX 20 40 60 80 100 SE +/- 0.57, N = 3 75.90 MIN: 69.34 / MAX: 77.48
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 AMD Ryzen 9 5900X 12-Core - MSI NVIDIA GeForce RTX 20 40 60 80 100 SE +/- 0.61, N = 3 75.09 MIN: 69.51 / MAX: 76.61
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 AMD Ryzen 9 5900X 12-Core - MSI NVIDIA GeForce RTX 9 18 27 36 45 SE +/- 0.10, N = 3 39.31 MIN: 36.39 / MAX: 39.7
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 AMD Ryzen 9 5900X 12-Core - MSI NVIDIA GeForce RTX 9 18 27 36 45 SE +/- 0.27, N = 15 38.68 MIN: 34.84 / MAX: 41.43
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 AMD Ryzen 9 5900X 12-Core - MSI NVIDIA GeForce RTX 9 18 27 36 45 SE +/- 0.39, N = 5 38.77 MIN: 36.02 / MAX: 39.78
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 AMD Ryzen 9 5900X 12-Core - MSI NVIDIA GeForce RTX 9 18 27 36 45 SE +/- 0.20, N = 3 38.69 MIN: 35.76 / MAX: 39.49
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 AMD Ryzen 9 5900X 12-Core - MSI NVIDIA GeForce RTX 9 18 27 36 45 SE +/- 0.19, N = 3 38.89 MIN: 35.84 / MAX: 39.35
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 AMD Ryzen 9 5900X 12-Core - MSI NVIDIA GeForce RTX 9 18 27 36 45 SE +/- 0.17, N = 3 38.48 MIN: 35.86 / MAX: 39.27
Phoronix Test Suite v10.8.5