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.

res4ProcessorMotherboardChipsetMemoryDiskGraphicsAudioMonitorNetworkOSKernelDesktopDisplay ServerDisplay DriverOpenGLOpenCLCompilerFile-SystemScreen ResolutionAMD Ryzen 9 5900X 12-Core - MSI NVIDIA GeForce RTXAMD Ryzen 9 5900X 12-Core @ 3.70GHz (12 Cores / 24 Threads)ASRock X570 Steel Legend (P5.63 BIOS)AMD Starship/Matisse2 x 16GB DDR4-3600MT/s TEAMGROUP-UD4-32001000GB Western Digital WDS100T3X0C-00SJG0 + 1000GB Western Digital WD Blue SN580 1TB + 2000GB Seagate ST2000DX001-1CM1MSI NVIDIA GeForce RTX 3080 12GBNVIDIA GA102 HD AudioDELL S2721QSIntel I211 + Intel Dual Band-AC 3168NGWUbuntu 22.046.8.0-49-generic (x86_64)GNOME Shell 42.9X Server 1.21.1.4NVIDIA 560.35.054.6.0OpenCL 3.0 CUDA 12.6.65GCC 11.4.0 + CUDA 12.6ext45120x2880OpenBenchmarking.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

res4pytorch: CPU - 1 - ResNet-50pytorch: CPU - 1 - ResNet-152pytorch: CPU - 16 - ResNet-50pytorch: CPU - 32 - ResNet-50pytorch: CPU - 64 - ResNet-50pytorch: CPU - 16 - ResNet-152pytorch: CPU - 256 - ResNet-50pytorch: CPU - 32 - ResNet-152pytorch: CPU - 512 - ResNet-50pytorch: CPU - 64 - ResNet-152pytorch: CPU - 256 - ResNet-152pytorch: CPU - 512 - ResNet-152pytorch: CPU - 1 - Efficientnet_v2_lpytorch: CPU - 16 - Efficientnet_v2_lpytorch: CPU - 32 - Efficientnet_v2_lpytorch: CPU - 64 - Efficientnet_v2_lpytorch: CPU - 256 - Efficientnet_v2_lpytorch: CPU - 512 - Efficientnet_v2_lpytorch: NVIDIA CUDA GPU - 1 - ResNet-50pytorch: NVIDIA CUDA GPU - 1 - ResNet-152pytorch: NVIDIA CUDA GPU - 16 - ResNet-50pytorch: NVIDIA CUDA GPU - 32 - ResNet-50pytorch: NVIDIA CUDA GPU - 64 - ResNet-50pytorch: NVIDIA CUDA GPU - 16 - ResNet-152pytorch: NVIDIA CUDA GPU - 256 - ResNet-50pytorch: NVIDIA CUDA GPU - 32 - ResNet-152pytorch: NVIDIA CUDA GPU - 512 - ResNet-50pytorch: NVIDIA CUDA GPU - 64 - ResNet-152pytorch: NVIDIA CUDA GPU - 256 - ResNet-152pytorch: NVIDIA CUDA GPU - 512 - ResNet-152pytorch: NVIDIA CUDA GPU - 1 - Efficientnet_v2_lpytorch: NVIDIA CUDA GPU - 16 - Efficientnet_v2_lpytorch: NVIDIA CUDA GPU - 32 - Efficientnet_v2_lpytorch: NVIDIA CUDA GPU - 64 - Efficientnet_v2_lpytorch: NVIDIA CUDA GPU - 256 - Efficientnet_v2_lpytorch: NVIDIA CUDA GPU - 512 - Efficientnet_v2_lAMD Ryzen 9 5900X 12-Core - MSI NVIDIA GeForce RTX43.0016.6231.3430.8931.5012.5931.2912.5431.2912.6712.5412.4810.757.447.427.477.467.47214.0674.95216.90214.52215.2774.74216.5674.87215.4677.2375.9075.0939.3138.6838.7738.6938.8938.48OpenBenchmarking.org

PyTorch

Device: CPU - Batch Size: 1 - Model: ResNet-50

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.2.1Device: CPU - Batch Size: 1 - Model: ResNet-50AMD Ryzen 9 5900X 12-Core - MSI NVIDIA GeForce RTX1020304050SE +/- 0.03, N = 343.00MIN: 38.05 / MAX: 43.7

PyTorch

Device: CPU - Batch Size: 1 - Model: ResNet-152

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.2.1Device: CPU - Batch Size: 1 - Model: ResNet-152AMD Ryzen 9 5900X 12-Core - MSI NVIDIA GeForce RTX48121620SE +/- 0.09, N = 316.62MIN: 15.98 / MAX: 16.91

PyTorch

Device: CPU - Batch Size: 16 - Model: ResNet-50

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.2.1Device: CPU - Batch Size: 16 - Model: ResNet-50AMD Ryzen 9 5900X 12-Core - MSI NVIDIA GeForce RTX714212835SE +/- 0.16, N = 331.34MIN: 30.35 / MAX: 31.89

PyTorch

Device: CPU - Batch Size: 32 - Model: ResNet-50

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.2.1Device: CPU - Batch Size: 32 - Model: ResNet-50AMD Ryzen 9 5900X 12-Core - MSI NVIDIA GeForce RTX714212835SE +/- 0.28, N = 630.89MIN: 28.53 / MAX: 31.81

PyTorch

Device: CPU - Batch Size: 64 - Model: ResNet-50

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.2.1Device: CPU - Batch Size: 64 - Model: ResNet-50AMD Ryzen 9 5900X 12-Core - MSI NVIDIA GeForce RTX714212835SE +/- 0.17, N = 331.50MIN: 28.43 / MAX: 32.09

PyTorch

Device: CPU - Batch Size: 16 - Model: ResNet-152

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.2.1Device: CPU - Batch Size: 16 - Model: ResNet-152AMD Ryzen 9 5900X 12-Core - MSI NVIDIA GeForce RTX3691215SE +/- 0.03, N = 312.59MIN: 11.67 / MAX: 12.74

PyTorch

Device: CPU - Batch Size: 256 - Model: ResNet-50

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.2.1Device: CPU - Batch Size: 256 - Model: ResNet-50AMD Ryzen 9 5900X 12-Core - MSI NVIDIA GeForce RTX714212835SE +/- 0.10, N = 331.29MIN: 29.83 / MAX: 31.97

PyTorch

Device: CPU - Batch Size: 32 - Model: ResNet-152

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.2.1Device: CPU - Batch Size: 32 - Model: ResNet-152AMD Ryzen 9 5900X 12-Core - MSI NVIDIA GeForce RTX3691215SE +/- 0.03, N = 312.54MIN: 12.07 / MAX: 12.69

PyTorch

Device: CPU - Batch Size: 512 - Model: ResNet-50

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.2.1Device: CPU - Batch Size: 512 - Model: ResNet-50AMD Ryzen 9 5900X 12-Core - MSI NVIDIA GeForce RTX714212835SE +/- 0.26, N = 331.29MIN: 29.95 / MAX: 31.91

PyTorch

Device: CPU - Batch Size: 64 - Model: ResNet-152

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.2.1Device: CPU - Batch Size: 64 - Model: ResNet-152AMD Ryzen 9 5900X 12-Core - MSI NVIDIA GeForce RTX3691215SE +/- 0.12, N = 312.67MIN: 12.32 / MAX: 12.98

PyTorch

Device: CPU - Batch Size: 256 - Model: ResNet-152

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.2.1Device: CPU - Batch Size: 256 - Model: ResNet-152AMD Ryzen 9 5900X 12-Core - MSI NVIDIA GeForce RTX3691215SE +/- 0.03, N = 312.54MIN: 11.57 / MAX: 12.69

PyTorch

Device: CPU - Batch Size: 512 - Model: ResNet-152

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.2.1Device: CPU - Batch Size: 512 - Model: ResNet-152AMD Ryzen 9 5900X 12-Core - MSI NVIDIA GeForce RTX3691215SE +/- 0.04, N = 312.48MIN: 11.94 / MAX: 12.66

PyTorch

Device: CPU - Batch Size: 1 - Model: Efficientnet_v2_l

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.2.1Device: CPU - Batch Size: 1 - Model: Efficientnet_v2_lAMD Ryzen 9 5900X 12-Core - MSI NVIDIA GeForce RTX3691215SE +/- 0.01, N = 310.75MIN: 10.61 / MAX: 10.83

PyTorch

Device: CPU - Batch Size: 16 - Model: Efficientnet_v2_l

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.2.1Device: CPU - Batch Size: 16 - Model: Efficientnet_v2_lAMD Ryzen 9 5900X 12-Core - MSI NVIDIA GeForce RTX246810SE +/- 0.00, N = 37.44MIN: 7.32 / MAX: 7.51

PyTorch

Device: CPU - Batch Size: 32 - Model: Efficientnet_v2_l

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.2.1Device: CPU - Batch Size: 32 - Model: Efficientnet_v2_lAMD Ryzen 9 5900X 12-Core - MSI NVIDIA GeForce RTX246810SE +/- 0.02, N = 37.42MIN: 7.33 / MAX: 7.51

PyTorch

Device: CPU - Batch Size: 64 - Model: Efficientnet_v2_l

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.2.1Device: CPU - Batch Size: 64 - Model: Efficientnet_v2_lAMD Ryzen 9 5900X 12-Core - MSI NVIDIA GeForce RTX246810SE +/- 0.06, N = 37.47MIN: 7.17 / MAX: 7.65

PyTorch

Device: CPU - Batch Size: 256 - Model: Efficientnet_v2_l

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.2.1Device: CPU - Batch Size: 256 - Model: Efficientnet_v2_lAMD Ryzen 9 5900X 12-Core - MSI NVIDIA GeForce RTX246810SE +/- 0.01, N = 37.46MIN: 7.34 / MAX: 7.53

PyTorch

Device: CPU - Batch Size: 512 - Model: Efficientnet_v2_l

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.2.1Device: CPU - Batch Size: 512 - Model: Efficientnet_v2_lAMD Ryzen 9 5900X 12-Core - MSI NVIDIA GeForce RTX246810SE +/- 0.06, N = 37.47MIN: 7.34 / MAX: 7.62

PyTorch

Device: NVIDIA CUDA GPU - Batch Size: 1 - Model: ResNet-50

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.2.1Device: NVIDIA CUDA GPU - Batch Size: 1 - Model: ResNet-50AMD Ryzen 9 5900X 12-Core - MSI NVIDIA GeForce RTX50100150200250SE +/- 2.68, N = 3214.06MIN: 189.9 / MAX: 220.75

PyTorch

Device: NVIDIA CUDA GPU - Batch Size: 1 - Model: ResNet-152

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.2.1Device: NVIDIA CUDA GPU - Batch Size: 1 - Model: ResNet-152AMD Ryzen 9 5900X 12-Core - MSI NVIDIA GeForce RTX20406080100SE +/- 0.54, N = 1574.95MIN: 68.83 / MAX: 79.29

PyTorch

Device: NVIDIA CUDA GPU - Batch Size: 16 - Model: ResNet-50

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.2.1Device: NVIDIA CUDA GPU - Batch Size: 16 - Model: ResNet-50AMD Ryzen 9 5900X 12-Core - MSI NVIDIA GeForce RTX50100150200250SE +/- 2.43, N = 3216.90MIN: 162.31 / MAX: 223.42

PyTorch

Device: NVIDIA CUDA GPU - Batch Size: 32 - Model: ResNet-50

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.2.1Device: NVIDIA CUDA GPU - Batch Size: 32 - Model: ResNet-50AMD Ryzen 9 5900X 12-Core - MSI NVIDIA GeForce RTX50100150200250SE +/- 2.51, N = 4214.52MIN: 201.54 / MAX: 223.62

PyTorch

Device: NVIDIA CUDA GPU - Batch Size: 64 - Model: ResNet-50

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.2.1Device: NVIDIA CUDA GPU - Batch Size: 64 - Model: ResNet-50AMD Ryzen 9 5900X 12-Core - MSI NVIDIA GeForce RTX50100150200250SE +/- 1.54, N = 12215.27MIN: 193.15 / MAX: 224.79

PyTorch

Device: NVIDIA CUDA GPU - Batch Size: 16 - Model: ResNet-152

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.2.1Device: NVIDIA CUDA GPU - Batch Size: 16 - Model: ResNet-152AMD Ryzen 9 5900X 12-Core - MSI NVIDIA GeForce RTX20406080100SE +/- 0.75, N = 374.74MIN: 70.11 / MAX: 78.16

PyTorch

Device: NVIDIA CUDA GPU - Batch Size: 256 - Model: ResNet-50

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.2.1Device: NVIDIA CUDA GPU - Batch Size: 256 - Model: ResNet-50AMD Ryzen 9 5900X 12-Core - MSI NVIDIA GeForce RTX50100150200250SE +/- 3.02, N = 3216.56MIN: 196.66 / MAX: 221.76

PyTorch

Device: NVIDIA CUDA GPU - Batch Size: 32 - Model: ResNet-152

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.2.1Device: NVIDIA CUDA GPU - Batch Size: 32 - Model: ResNet-152AMD Ryzen 9 5900X 12-Core - MSI NVIDIA GeForce RTX20406080100SE +/- 0.25, N = 374.87MIN: 69.21 / MAX: 75.96

PyTorch

Device: NVIDIA CUDA GPU - Batch Size: 512 - Model: ResNet-50

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.2.1Device: NVIDIA CUDA GPU - Batch Size: 512 - Model: ResNet-50AMD Ryzen 9 5900X 12-Core - MSI NVIDIA GeForce RTX50100150200250SE +/- 2.58, N = 4215.46MIN: 200.19 / MAX: 224.64

PyTorch

Device: NVIDIA CUDA GPU - Batch Size: 64 - Model: ResNet-152

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.2.1Device: NVIDIA CUDA GPU - Batch Size: 64 - Model: ResNet-152AMD Ryzen 9 5900X 12-Core - MSI NVIDIA GeForce RTX20406080100SE +/- 0.33, N = 377.23MIN: 70.71 / MAX: 78.87

PyTorch

Device: NVIDIA CUDA GPU - Batch Size: 256 - Model: ResNet-152

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.2.1Device: NVIDIA CUDA GPU - Batch Size: 256 - Model: ResNet-152AMD Ryzen 9 5900X 12-Core - MSI NVIDIA GeForce RTX20406080100SE +/- 0.57, N = 375.90MIN: 69.34 / MAX: 77.48

PyTorch

Device: NVIDIA CUDA GPU - Batch Size: 512 - Model: ResNet-152

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.2.1Device: NVIDIA CUDA GPU - Batch Size: 512 - Model: ResNet-152AMD Ryzen 9 5900X 12-Core - MSI NVIDIA GeForce RTX20406080100SE +/- 0.61, N = 375.09MIN: 69.51 / MAX: 76.61

PyTorch

Device: NVIDIA CUDA GPU - Batch Size: 1 - Model: Efficientnet_v2_l

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.2.1Device: NVIDIA CUDA GPU - Batch Size: 1 - Model: Efficientnet_v2_lAMD Ryzen 9 5900X 12-Core - MSI NVIDIA GeForce RTX918273645SE +/- 0.10, N = 339.31MIN: 36.39 / MAX: 39.7

PyTorch

Device: NVIDIA CUDA GPU - Batch Size: 16 - Model: Efficientnet_v2_l

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.2.1Device: NVIDIA CUDA GPU - Batch Size: 16 - Model: Efficientnet_v2_lAMD Ryzen 9 5900X 12-Core - MSI NVIDIA GeForce RTX918273645SE +/- 0.27, N = 1538.68MIN: 34.84 / MAX: 41.43

PyTorch

Device: NVIDIA CUDA GPU - Batch Size: 32 - Model: Efficientnet_v2_l

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.2.1Device: NVIDIA CUDA GPU - Batch Size: 32 - Model: Efficientnet_v2_lAMD Ryzen 9 5900X 12-Core - MSI NVIDIA GeForce RTX918273645SE +/- 0.39, N = 538.77MIN: 36.02 / MAX: 39.78

PyTorch

Device: NVIDIA CUDA GPU - Batch Size: 64 - Model: Efficientnet_v2_l

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.2.1Device: NVIDIA CUDA GPU - Batch Size: 64 - Model: Efficientnet_v2_lAMD Ryzen 9 5900X 12-Core - MSI NVIDIA GeForce RTX918273645SE +/- 0.20, N = 338.69MIN: 35.76 / MAX: 39.49

PyTorch

Device: NVIDIA CUDA GPU - Batch Size: 256 - Model: Efficientnet_v2_l

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.2.1Device: NVIDIA CUDA GPU - Batch Size: 256 - Model: Efficientnet_v2_lAMD Ryzen 9 5900X 12-Core - MSI NVIDIA GeForce RTX918273645SE +/- 0.19, N = 338.89MIN: 35.84 / MAX: 39.35

PyTorch

Device: NVIDIA CUDA GPU - Batch Size: 512 - Model: Efficientnet_v2_l

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.2.1Device: NVIDIA CUDA GPU - Batch Size: 512 - Model: Efficientnet_v2_lAMD Ryzen 9 5900X 12-Core - MSI NVIDIA GeForce RTX918273645SE +/- 0.17, N = 338.48MIN: 35.86 / MAX: 39.27


Phoronix Test Suite v10.8.5