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
pytorch tensorflow,
"TensorFlow 2.16.1 - Device: CPU - Batch Size: 64 - Model: VGG-16",
Higher Results Are Better
"AMD Ryzen 9 7950X 16-Core - NVIDIA GeForce RTX 3080",19.68,19.69,19.66
"TensorFlow 2.16.1 - Device: CPU - Batch Size: 32 - Model: VGG-16",
Higher Results Are Better
"AMD Ryzen 9 7950X 16-Core - NVIDIA GeForce RTX 3080",19.02,19,18.95
"PyTorch 2.2.1 - Device: CPU - Batch Size: 16 - Model: Efficientnet_v2_l",
Higher Results Are Better
"AMD Ryzen 9 7950X 16-Core - NVIDIA GeForce RTX 3080",11.822533587024,11.583071180378,11.287287599075
"TensorFlow 2.16.1 - Device: CPU - Batch Size: 64 - Model: ResNet-50",
Higher Results Are Better
"AMD Ryzen 9 7950X 16-Core - NVIDIA GeForce RTX 3080",42.68,42.67,42.69
"PyTorch 2.2.1 - Device: CPU - Batch Size: 64 - Model: Efficientnet_v2_l",
Higher Results Are Better
"AMD Ryzen 9 7950X 16-Core - NVIDIA GeForce RTX 3080",11.63062461278,11.794551211274,11.899762990215
"PyTorch 2.2.1 - Device: CPU - Batch Size: 32 - Model: Efficientnet_v2_l",
Higher Results Are Better
"AMD Ryzen 9 7950X 16-Core - NVIDIA GeForce RTX 3080",11.867976551107,11.938182164031,11.774564716042
"PyTorch 2.2.1 - Device: CPU - Batch Size: 256 - Model: Efficientnet_v2_l",
Higher Results Are Better
"AMD Ryzen 9 7950X 16-Core - NVIDIA GeForce RTX 3080",11.689293210126,11.826016718462,12.018788982287
"TensorFlow 2.16.1 - Device: CPU - Batch Size: 16 - Model: VGG-16",
Higher Results Are Better
"AMD Ryzen 9 7950X 16-Core - NVIDIA GeForce RTX 3080",17.97,18.29,17.88
"PyTorch 2.2.1 - Device: CPU - Batch Size: 32 - Model: ResNet-152",
Higher Results Are Better
"AMD Ryzen 9 7950X 16-Core - NVIDIA GeForce RTX 3080",19.799766204534,19.312347316862,19.451511576328
"PyTorch 2.2.1 - Device: CPU - Batch Size: 64 - Model: ResNet-152",
Higher Results Are Better
"AMD Ryzen 9 7950X 16-Core - NVIDIA GeForce RTX 3080",20.110454438451,19.449897713202,19.504422715232
"PyTorch 2.2.1 - Device: CPU - Batch Size: 256 - Model: ResNet-152",
Higher Results Are Better
"AMD Ryzen 9 7950X 16-Core - NVIDIA GeForce RTX 3080",19.622330209476,20.314303711799,19.772425996763
"PyTorch 2.2.1 - Device: CPU - Batch Size: 16 - Model: ResNet-152",
Higher Results Are Better
"AMD Ryzen 9 7950X 16-Core - NVIDIA GeForce RTX 3080",20.305700881055,20.138529782297,19.799037169644
"TensorFlow 2.16.1 - Device: CPU - Batch Size: 32 - Model: ResNet-50",
Higher Results Are Better
"AMD Ryzen 9 7950X 16-Core - NVIDIA GeForce RTX 3080",42.51,42.46,42.48
"PyTorch 2.2.1 - Device: CPU - Batch Size: 1 - Model: Efficientnet_v2_l",
Higher Results Are Better
"AMD Ryzen 9 7950X 16-Core - NVIDIA GeForce RTX 3080",16.562701978842,16.423885462608,16.588491367851
"TensorFlow 2.16.1 - Device: CPU - Batch Size: 64 - Model: GoogLeNet",
Higher Results Are Better
"AMD Ryzen 9 7950X 16-Core - NVIDIA GeForce RTX 3080",138.75,138.78,138.75
"TensorFlow 2.16.1 - Device: CPU - Batch Size: 16 - Model: ResNet-50",
Higher Results Are Better
"AMD Ryzen 9 7950X 16-Core - NVIDIA GeForce RTX 3080",41.41,41.32,41.28
"PyTorch 2.2.1 - Device: CPU - Batch Size: 64 - Model: ResNet-50",
Higher Results Are Better
"AMD Ryzen 9 7950X 16-Core - NVIDIA GeForce RTX 3080",48.228485369507,48.109277915954,49.360600812822
"PyTorch 2.2.1 - Device: CPU - Batch Size: 32 - Model: ResNet-50",
Higher Results Are Better
"AMD Ryzen 9 7950X 16-Core - NVIDIA GeForce RTX 3080",49.348312317754,47.732136951402,48.544436443411
"PyTorch 2.2.1 - Device: CPU - Batch Size: 256 - Model: ResNet-50",
Higher Results Are Better
"AMD Ryzen 9 7950X 16-Core - NVIDIA GeForce RTX 3080",48.795615416401,48.451953442923,48.281367726731
"PyTorch 2.2.1 - Device: CPU - Batch Size: 1 - Model: ResNet-152",
Higher Results Are Better
"AMD Ryzen 9 7950X 16-Core - NVIDIA GeForce RTX 3080",29.46594012514,28.819796823688,29.880026969208
"PyTorch 2.2.1 - Device: CPU - Batch Size: 16 - Model: ResNet-50",
Higher Results Are Better
"AMD Ryzen 9 7950X 16-Core - NVIDIA GeForce RTX 3080",49.409538238317,48.459491510389,48.693000618621
"TensorFlow 2.16.1 - Device: CPU - Batch Size: 32 - Model: GoogLeNet",
Higher Results Are Better
"AMD Ryzen 9 7950X 16-Core - NVIDIA GeForce RTX 3080",141.46,141.55,141.21
"TensorFlow 2.16.1 - Device: CPU - Batch Size: 64 - Model: AlexNet",
Higher Results Are Better
"AMD Ryzen 9 7950X 16-Core - NVIDIA GeForce RTX 3080",334.58,334.84,334.81
"TensorFlow 2.16.1 - Device: CPU - Batch Size: 1 - Model: VGG-16",
Higher Results Are Better
"AMD Ryzen 9 7950X 16-Core - NVIDIA GeForce RTX 3080",5.65,5.65,5.65
"PyTorch 2.2.1 - Device: CPU - Batch Size: 1 - Model: ResNet-50",
Higher Results Are Better
"AMD Ryzen 9 7950X 16-Core - NVIDIA GeForce RTX 3080",72.036469803985,71.860981642129,71.413467489235
"TensorFlow 2.16.1 - Device: CPU - Batch Size: 32 - Model: AlexNet",
Higher Results Are Better
"AMD Ryzen 9 7950X 16-Core - NVIDIA GeForce RTX 3080",254.43,254.54,254.55
"TensorFlow 2.16.1 - Device: CPU - Batch Size: 16 - Model: GoogLeNet",
Higher Results Are Better
"AMD Ryzen 9 7950X 16-Core - NVIDIA GeForce RTX 3080",142.04,141.97,142.7
"TensorFlow 2.16.1 - Device: CPU - Batch Size: 16 - Model: AlexNet",
Higher Results Are Better
"AMD Ryzen 9 7950X 16-Core - NVIDIA GeForce RTX 3080",171.2,170.4,170.68
"TensorFlow 2.16.1 - Device: CPU - Batch Size: 1 - Model: ResNet-50",
Higher Results Are Better
"AMD Ryzen 9 7950X 16-Core - NVIDIA GeForce RTX 3080",16.16,16.2,16.1
"TensorFlow 2.16.1 - Device: CPU - Batch Size: 1 - Model: AlexNet",
Higher Results Are Better
"AMD Ryzen 9 7950X 16-Core - NVIDIA GeForce RTX 3080",16.11,16.12,16.09
"TensorFlow 2.16.1 - Device: CPU - Batch Size: 1 - Model: GoogLeNet",
Higher Results Are Better
"AMD Ryzen 9 7950X 16-Core - NVIDIA GeForce RTX 3080",60.53,61.21,61.55