AMD Ryzen 9 7950X 16-Core testing with a ASUS ROG STRIX X670E-E GAMING WIFI (1416 BIOS) and NVIDIA NV174 8GB 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 2401073-PTS-TPY9619764
tpy,
"Quicksilver 20230818 - Input: CTS2",
Higher Results Are Better
"a",
"b",
"c",
"d",
"Quicksilver 20230818 - Input: CORAL2 P1",
Higher Results Are Better
"a",
"b",
"c",
"d",
"Quicksilver 20230818 - Input: CORAL2 P2",
Higher Results Are Better
"a",
"b",
"c",
"d",
"Y-Cruncher 0.8.3 - Pi Digits To Calculate: 1B",
Lower Results Are Better
"a",
"b",
"c",
"d",
"Y-Cruncher 0.8.3 - Pi Digits To Calculate: 5B",
Lower Results Are Better
"a",
"b",
"c",
"d",
"Y-Cruncher 0.8.3 - Pi Digits To Calculate: 500M",
Lower Results Are Better
"a",
"b",
"c",
"d",
"PyTorch 2.1 - Device: CPU - Batch Size: 1 - Model: ResNet-50",
Higher Results Are Better
"a",75.349514135227
"b",75.882041655409
"c",76.245990447073
"d",74.613531196059
"PyTorch 2.1 - Device: CPU - Batch Size: 1 - Model: ResNet-152",
Higher Results Are Better
"a",31.51559348825
"b",31.433753363159
"c",30.271476219482
"d",29.63530294413
"PyTorch 2.1 - Device: CPU - Batch Size: 16 - Model: ResNet-50",
Higher Results Are Better
"a",50.471854641503
"b",50.63946530914
"c",49.489162469155
"d",50.455045416743
"PyTorch 2.1 - Device: CPU - Batch Size: 16 - Model: ResNet-152",
Higher Results Are Better
"a",21.038093847961
"b",20.934586857677
"c",20.906083248007
"d",21.025746066482
"PyTorch 2.1 - Device: CPU - Batch Size: 1 - Model: Efficientnet_v2_l",
Higher Results Are Better
"a",16.630720048847
"b",16.923976242293
"c",16.605455162946
"d",16.794791792456
"PyTorch 2.1 - Device: CPU - Batch Size: 16 - Model: Efficientnet_v2_l",
Higher Results Are Better
"a",12.598118185674
"b",12.542958006363
"c",12.589642219234
"d",12.627339876215
"TensorFlow 2.12 - Device: CPU - Batch Size: 1 - Model: VGG-16",
Higher Results Are Better
"a",
"b",
"c",
"d",
"TensorFlow 2.12 - Device: CPU - Batch Size: 1 - Model: AlexNet",
Higher Results Are Better
"a",
"b",
"c",
"d",
"TensorFlow 2.12 - Device: CPU - Batch Size: 16 - Model: VGG-16",
Higher Results Are Better
"a",
"b",
"c",
"d",
"TensorFlow 2.12 - Device: CPU - Batch Size: 16 - Model: AlexNet",
Higher Results Are Better
"a",
"b",
"c",
"d",
"TensorFlow 2.12 - Device: CPU - Batch Size: 1 - Model: GoogLeNet",
Higher Results Are Better
"a",
"b",
"c",
"d",
"TensorFlow 2.12 - Device: CPU - Batch Size: 1 - Model: ResNet-50",
Higher Results Are Better
"a",
"b",
"c",
"d",
"TensorFlow 2.12 - Device: CPU - Batch Size: 16 - Model: GoogLeNet",
Higher Results Are Better
"a",
"b",
"c",
"d",
"TensorFlow 2.12 - Device: CPU - Batch Size: 16 - Model: ResNet-50",
Higher Results Are Better
"a",
"b",
"c",
"d",
"Speedb 2.7 - Test: Random Fill",
Higher Results Are Better
"a",
"b",
"c",
"d",
"Speedb 2.7 - Test: Random Read",
Higher Results Are Better
"a",
"b",
"c",
"d",
"Speedb 2.7 - Test: Update Random",
Higher Results Are Better
"a",
"b",
"c",
"d",
"Speedb 2.7 - Test: Sequential Fill",
Higher Results Are Better
"a",
"b",
"c",
"d",
"Speedb 2.7 - Test: Random Fill Sync",
Higher Results Are Better
"a",
"b",
"c",
"d",
"Speedb 2.7 - Test: Read While Writing",
Higher Results Are Better
"a",
"b",
"c",
"d",
"Speedb 2.7 - Test: Read Random Write Random",
Higher Results Are Better
"a",
"b",
"c",
"d",