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.

Compare your own system(s) to this result file with the Phoronix Test Suite by running the command: phoronix-test-suite benchmark 2403274-PTS-PYTORCHT32
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Result
Identifier
Performance Per
Dollar
Date
Run
  Test
  Duration
AMD Ryzen 9 7950X 16-Core - NVIDIA GeForce RTX 3080
March 27
  2 Hours, 4 Minutes
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AMD Ryzen 9 7950X 16-Core - NVIDIA GeForce RTX 3080

Processor: AMD Ryzen 9 7950X 16-Core @ 5.88GHz (16 Cores / 32 Threads), Motherboard: ASUS ROG STRIX X670E-E GAMING WIFI (1905 BIOS), Chipset: AMD Device 14d8, Memory: 2 x 16GB DRAM-6000MT/s G Skill F5-6000J3038F16G, Disk: 2000GB Samsung SSD 980 PRO 2TB + 123GB SanDisk 3.2Gen1, Graphics: NVIDIA GeForce RTX 3080 10GB, Audio: NVIDIA GA102 HD Audio, Monitor: DELL U2723QE, Network: Intel I225-V + Intel Wi-Fi 6 AX210/AX211/AX411

OS: Ubuntu 23.10, Kernel: 6.7.0-060700-generic (x86_64), Desktop: GNOME Shell 45.2, Display Server: X Server 1.21.1.7, Display Driver: NVIDIA 550.54.14, OpenGL: 4.6.0, OpenCL: OpenCL 3.0 CUDA 12.4.89, Compiler: GCC 13.2.0, File-System: ext4, Screen Resolution: 3840x2160

Kernel Notes: Transparent Huge Pages: madvise
Processor Notes: Scaling Governor: amd-pstate-epp powersave (EPP: balance_performance) - CPU Microcode: 0xa601206
Python Notes: Python 3.11.6
Security Notes: 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 tensorflowOpenBenchmarking.orgPhoronix Test SuiteAMD Ryzen 9 7950X 16-Core @ 5.88GHz (16 Cores / 32 Threads)ASUS ROG STRIX X670E-E GAMING WIFI (1905 BIOS)AMD Device 14d82 x 16GB DRAM-6000MT/s G Skill F5-6000J3038F16G2000GB Samsung SSD 980 PRO 2TB + 123GB SanDisk 3.2Gen1NVIDIA GeForce RTX 3080 10GBNVIDIA GA102 HD AudioDELL U2723QEIntel I225-V + Intel Wi-Fi 6 AX210/AX211/AX411Ubuntu 23.106.7.0-060700-generic (x86_64)GNOME Shell 45.2X Server 1.21.1.7NVIDIA 550.54.144.6.0OpenCL 3.0 CUDA 12.4.89GCC 13.2.0ext43840x2160ProcessorMotherboardChipsetMemoryDiskGraphicsAudioMonitorNetworkOSKernelDesktopDisplay ServerDisplay DriverOpenGLOpenCLCompilerFile-SystemScreen ResolutionPytorch Tensorflow BenchmarksSystem Logs- 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 tensorflowtensorflow: CPU - 64 - ResNet-50tensorflow: CPU - 64 - GoogLeNettensorflow: CPU - 32 - ResNet-50tensorflow: CPU - 32 - GoogLeNettensorflow: CPU - 16 - ResNet-50tensorflow: CPU - 16 - GoogLeNettensorflow: CPU - 1 - ResNet-50tensorflow: CPU - 1 - GoogLeNettensorflow: CPU - 64 - AlexNettensorflow: CPU - 32 - AlexNettensorflow: CPU - 16 - AlexNettensorflow: CPU - 64 - VGG-16tensorflow: CPU - 32 - VGG-16tensorflow: CPU - 16 - VGG-16tensorflow: CPU - 1 - AlexNettensorflow: CPU - 1 - VGG-16pytorch: CPU - 256 - Efficientnet_v2_lpytorch: CPU - 64 - Efficientnet_v2_lpytorch: CPU - 32 - Efficientnet_v2_lpytorch: CPU - 16 - Efficientnet_v2_lpytorch: CPU - 1 - Efficientnet_v2_lpytorch: CPU - 256 - ResNet-152pytorch: CPU - 64 - ResNet-152pytorch: CPU - 32 - ResNet-152pytorch: CPU - 256 - ResNet-50pytorch: CPU - 16 - ResNet-152pytorch: CPU - 64 - ResNet-50pytorch: CPU - 32 - ResNet-50pytorch: CPU - 16 - ResNet-50pytorch: CPU - 1 - ResNet-152pytorch: CPU - 1 - ResNet-50AMD Ryzen 9 7950X 16-Core - NVIDIA GeForce RTX 308042.68138.7642.48141.4141.34142.2416.1561.10334.74254.51170.7619.6818.9918.0516.115.6511.8411.7711.8611.5616.5319.9019.6919.5248.5120.0848.5748.5448.8529.3971.77OpenBenchmarking.org

TensorFlow

This is a benchmark of the TensorFlow deep learning framework using the TensorFlow reference benchmarks (tensorflow/benchmarks with tf_cnn_benchmarks.py). Note with the Phoronix Test Suite there is also pts/tensorflow-lite for benchmarking the TensorFlow Lite binaries if desired for complementary metrics. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgimages/sec, More Is BetterTensorFlow 2.16.1Device: CPU - Batch Size: 64 - Model: ResNet-50AMD Ryzen 9 7950X 16-Core - NVIDIA GeForce RTX 30801020304050SE +/- 0.01, N = 342.68

OpenBenchmarking.orgimages/sec, More Is BetterTensorFlow 2.16.1Device: CPU - Batch Size: 64 - Model: GoogLeNetAMD Ryzen 9 7950X 16-Core - NVIDIA GeForce RTX 3080306090120150SE +/- 0.01, N = 3138.76

OpenBenchmarking.orgimages/sec, More Is BetterTensorFlow 2.16.1Device: CPU - Batch Size: 32 - Model: ResNet-50AMD Ryzen 9 7950X 16-Core - NVIDIA GeForce RTX 30801020304050SE +/- 0.01, N = 342.48

OpenBenchmarking.orgimages/sec, More Is BetterTensorFlow 2.16.1Device: CPU - Batch Size: 32 - Model: GoogLeNetAMD Ryzen 9 7950X 16-Core - NVIDIA GeForce RTX 3080306090120150SE +/- 0.10, N = 3141.41

OpenBenchmarking.orgimages/sec, More Is BetterTensorFlow 2.16.1Device: CPU - Batch Size: 16 - Model: ResNet-50AMD Ryzen 9 7950X 16-Core - NVIDIA GeForce RTX 3080918273645SE +/- 0.04, N = 341.34

OpenBenchmarking.orgimages/sec, More Is BetterTensorFlow 2.16.1Device: CPU - Batch Size: 16 - Model: GoogLeNetAMD Ryzen 9 7950X 16-Core - NVIDIA GeForce RTX 3080306090120150SE +/- 0.23, N = 3142.24

OpenBenchmarking.orgimages/sec, More Is BetterTensorFlow 2.16.1Device: CPU - Batch Size: 1 - Model: ResNet-50AMD Ryzen 9 7950X 16-Core - NVIDIA GeForce RTX 308048121620SE +/- 0.03, N = 316.15

OpenBenchmarking.orgimages/sec, More Is BetterTensorFlow 2.16.1Device: CPU - Batch Size: 1 - Model: GoogLeNetAMD Ryzen 9 7950X 16-Core - NVIDIA GeForce RTX 30801428425670SE +/- 0.30, N = 361.10

OpenBenchmarking.orgimages/sec, More Is BetterTensorFlow 2.16.1Device: CPU - Batch Size: 64 - Model: AlexNetAMD Ryzen 9 7950X 16-Core - NVIDIA GeForce RTX 308070140210280350SE +/- 0.08, N = 3334.74

OpenBenchmarking.orgimages/sec, More Is BetterTensorFlow 2.16.1Device: CPU - Batch Size: 32 - Model: AlexNetAMD Ryzen 9 7950X 16-Core - NVIDIA GeForce RTX 308060120180240300SE +/- 0.04, N = 3254.51

OpenBenchmarking.orgimages/sec, More Is BetterTensorFlow 2.16.1Device: CPU - Batch Size: 16 - Model: AlexNetAMD Ryzen 9 7950X 16-Core - NVIDIA GeForce RTX 30804080120160200SE +/- 0.23, N = 3170.76

OpenBenchmarking.orgimages/sec, More Is BetterTensorFlow 2.16.1Device: CPU - Batch Size: 64 - Model: VGG-16AMD Ryzen 9 7950X 16-Core - NVIDIA GeForce RTX 3080510152025SE +/- 0.01, N = 319.68

OpenBenchmarking.orgimages/sec, More Is BetterTensorFlow 2.16.1Device: CPU - Batch Size: 32 - Model: VGG-16AMD Ryzen 9 7950X 16-Core - NVIDIA GeForce RTX 3080510152025SE +/- 0.02, N = 318.99

OpenBenchmarking.orgimages/sec, More Is BetterTensorFlow 2.16.1Device: CPU - Batch Size: 16 - Model: VGG-16AMD Ryzen 9 7950X 16-Core - NVIDIA GeForce RTX 308048121620SE +/- 0.12, N = 318.05

OpenBenchmarking.orgimages/sec, More Is BetterTensorFlow 2.16.1Device: CPU - Batch Size: 1 - Model: AlexNetAMD Ryzen 9 7950X 16-Core - NVIDIA GeForce RTX 308048121620SE +/- 0.01, N = 316.11

OpenBenchmarking.orgimages/sec, More Is BetterTensorFlow 2.16.1Device: CPU - Batch Size: 1 - Model: VGG-16AMD Ryzen 9 7950X 16-Core - NVIDIA GeForce RTX 30801.27132.54263.81395.08526.3565SE +/- 0.00, N = 35.65

PyTorch

This is a benchmark of PyTorch making use of pytorch-benchmark [https://github.com/LukasHedegaard/pytorch-benchmark]. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.2.1Device: CPU - Batch Size: 256 - Model: Efficientnet_v2_lAMD Ryzen 9 7950X 16-Core - NVIDIA GeForce RTX 30803691215SE +/- 0.10, N = 311.84MIN: 9.61 / MAX: 12.83

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.2.1Device: CPU - Batch Size: 64 - Model: Efficientnet_v2_lAMD Ryzen 9 7950X 16-Core - NVIDIA GeForce RTX 30803691215SE +/- 0.08, N = 311.77MIN: 9.64 / MAX: 12.77

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.2.1Device: CPU - Batch Size: 32 - Model: Efficientnet_v2_lAMD Ryzen 9 7950X 16-Core - NVIDIA GeForce RTX 30803691215SE +/- 0.05, N = 311.86MIN: 9.68 / MAX: 12.71

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.2.1Device: CPU - Batch Size: 16 - Model: Efficientnet_v2_lAMD Ryzen 9 7950X 16-Core - NVIDIA GeForce RTX 30803691215SE +/- 0.15, N = 311.56MIN: 9.38 / MAX: 12.7

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.2.1Device: CPU - Batch Size: 1 - Model: Efficientnet_v2_lAMD Ryzen 9 7950X 16-Core - NVIDIA GeForce RTX 308048121620SE +/- 0.05, N = 316.53MIN: 14.7 / MAX: 16.81

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.2.1Device: CPU - Batch Size: 256 - Model: ResNet-152AMD Ryzen 9 7950X 16-Core - NVIDIA GeForce RTX 3080510152025SE +/- 0.21, N = 319.90MIN: 19.05 / MAX: 20.71

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.2.1Device: CPU - Batch Size: 64 - Model: ResNet-152AMD Ryzen 9 7950X 16-Core - NVIDIA GeForce RTX 3080510152025SE +/- 0.21, N = 319.69MIN: 19.03 / MAX: 20.31

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.2.1Device: CPU - Batch Size: 32 - Model: ResNet-152AMD Ryzen 9 7950X 16-Core - NVIDIA GeForce RTX 3080510152025SE +/- 0.14, N = 319.52MIN: 18.86 / MAX: 20.1

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.2.1Device: CPU - Batch Size: 256 - Model: ResNet-50AMD Ryzen 9 7950X 16-Core - NVIDIA GeForce RTX 30801122334455SE +/- 0.15, N = 348.51MIN: 46.12 / MAX: 49.98

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.2.1Device: CPU - Batch Size: 16 - Model: ResNet-152AMD Ryzen 9 7950X 16-Core - NVIDIA GeForce RTX 3080510152025SE +/- 0.15, N = 320.08MIN: 15.43 / MAX: 20.67

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.2.1Device: CPU - Batch Size: 64 - Model: ResNet-50AMD Ryzen 9 7950X 16-Core - NVIDIA GeForce RTX 30801122334455SE +/- 0.40, N = 348.57MIN: 45.94 / MAX: 49.92

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.2.1Device: CPU - Batch Size: 32 - Model: ResNet-50AMD Ryzen 9 7950X 16-Core - NVIDIA GeForce RTX 30801122334455SE +/- 0.47, N = 348.54MIN: 38.25 / MAX: 50.46

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.2.1Device: CPU - Batch Size: 16 - Model: ResNet-50AMD Ryzen 9 7950X 16-Core - NVIDIA GeForce RTX 30801122334455SE +/- 0.29, N = 348.85MIN: 47.27 / MAX: 50.05

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.2.1Device: CPU - Batch Size: 1 - Model: ResNet-152AMD Ryzen 9 7950X 16-Core - NVIDIA GeForce RTX 3080714212835SE +/- 0.31, N = 329.39MIN: 22.95 / MAX: 30.32

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.2.1Device: CPU - Batch Size: 1 - Model: ResNet-50AMD Ryzen 9 7950X 16-Core - NVIDIA GeForce RTX 30801632486480SE +/- 0.19, N = 371.77MIN: 57.05 / MAX: 74.1

AMD Ryzen 9 7950X 16-Core - NVIDIA GeForce RTX 3080

Processor: AMD Ryzen 9 7950X 16-Core @ 5.88GHz (16 Cores / 32 Threads), Motherboard: ASUS ROG STRIX X670E-E GAMING WIFI (1905 BIOS), Chipset: AMD Device 14d8, Memory: 2 x 16GB DRAM-6000MT/s G Skill F5-6000J3038F16G, Disk: 2000GB Samsung SSD 980 PRO 2TB + 123GB SanDisk 3.2Gen1, Graphics: NVIDIA GeForce RTX 3080 10GB, Audio: NVIDIA GA102 HD Audio, Monitor: DELL U2723QE, Network: Intel I225-V + Intel Wi-Fi 6 AX210/AX211/AX411

OS: Ubuntu 23.10, Kernel: 6.7.0-060700-generic (x86_64), Desktop: GNOME Shell 45.2, Display Server: X Server 1.21.1.7, Display Driver: NVIDIA 550.54.14, OpenGL: 4.6.0, OpenCL: OpenCL 3.0 CUDA 12.4.89, Compiler: GCC 13.2.0, File-System: ext4, Screen Resolution: 3840x2160

Kernel Notes: Transparent Huge Pages: madvise
Processor Notes: Scaling Governor: amd-pstate-epp powersave (EPP: balance_performance) - CPU Microcode: 0xa601206
Python Notes: Python 3.11.6
Security Notes: 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

Testing initiated at 27 March 2024 12:25 by user pts.