AMD Ryzen 5 5500U testing with a NB01 NL5xNU (1.07.11RTR1 BIOS) and AMD Lucienne 512MB on Tuxedo 22.04 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 2401075-NE-FHD99334640
fhd,
"TensorFlow 2.12 - Device: CPU - Batch Size: 16 - Model: ResNet-50",
Higher Results Are Better
"s",6.55,6.54,6.55
"b",
"c",
"Quicksilver 20230818 - Input: CORAL2 P1",
Higher Results Are Better
"s",6063000,6083000,6111000
"b",
"c",
"TensorFlow 2.12 - Device: CPU - Batch Size: 32 - Model: ResNet-50",
Higher Results Are Better
"s",6.68,6.65,6.64
"b",
"c",
"Quicksilver 20230818 - Input: CORAL2 P2",
Higher Results Are Better
"s",11380000,11440000,11340000
"b",
"c",
"TensorFlow 2.12 - Device: CPU - Batch Size: 1 - Model: ResNet-50",
Higher Results Are Better
"s",4.35,4.36,4.35
"b",
"c",
"TensorFlow 2.12 - Device: CPU - Batch Size: 64 - Model: ResNet-50",
Higher Results Are Better
"s",6.65,6.69,6.68
"b",
"c",
"PyTorch 2.1 - Device: CPU - Batch Size: 1 - Model: ResNet-50",
Higher Results Are Better
"s",17.918337941875,17.962152052012,18.362610186991
"b",18.609511298591
"c",17.684943418153
"PyTorch 2.1 - Device: CPU - Batch Size: 1 - Model: ResNet-152",
Higher Results Are Better
"s",7.355594142629,7.4255776717159,7.2385970769592
"b",7.569662918828
"c",7.4839272366714
"PyTorch 2.1 - Device: CPU - Batch Size: 16 - Model: ResNet-50",
Higher Results Are Better
"s",9.891189480196,9.9863407899101,9.7677614525644
"b",10.132136119713
"c",10.048821710358
"PyTorch 2.1 - Device: CPU - Batch Size: 32 - Model: ResNet-50",
Higher Results Are Better
"s",9.8668927879084,9.9158376023005,10.018437875401
"b",10.380257674181
"c",10.095883784258
"PyTorch 2.1 - Device: CPU - Batch Size: 64 - Model: ResNet-50",
Higher Results Are Better
"s",10.023310381135,9.5693121670909,10.137612831611,10.153627712596,10.103971214062
"b",10.099734279053
"c",10.048845632053
"PyTorch 2.1 - Device: CPU - Batch Size: 16 - Model: ResNet-152",
Higher Results Are Better
"s",4.1952445103691,4.2415473542726,4.289038185484
"b",4.3526001330624
"c",4.265498594925
"PyTorch 2.1 - Device: CPU - Batch Size: 32 - Model: ResNet-152",
Higher Results Are Better
"s",4.2374637877759,4.2371754155485,4.2464940994241
"b",4.2834925837925
"c",4.2181010388166
"Quicksilver 20230818 - Input: CTS2",
Higher Results Are Better
"s",5822000,5806000,5777000
"b",
"c",
"PyTorch 2.1 - Device: CPU - Batch Size: 64 - Model: ResNet-152",
Higher Results Are Better
"s",4.1329988400044,4.193586026103,4.2946373808168
"b",4.3374920317558
"c",4.330794563931
"PyTorch 2.1 - Device: CPU - Batch Size: 1 - Model: Efficientnet_v2_l",
Higher Results Are Better
"s",4.9364141037036,4.8635307979182,4.8285016056976
"b",4.9483940502654
"c",4.9158180186916
"PyTorch 2.1 - Device: CPU - Batch Size: 16 - Model: Efficientnet_v2_l",
Higher Results Are Better
"s",2.9137625316641,2.9982533093084,2.9786594567062
"b",2.9962352607882
"c",2.9975586980892
"PyTorch 2.1 - Device: CPU - Batch Size: 32 - Model: Efficientnet_v2_l",
Higher Results Are Better
"s",2.968917750627,2.975451290162,2.9879994952087
"b",2.9690161962437
"c",3.0099283618538
"PyTorch 2.1 - Device: CPU - Batch Size: 64 - Model: Efficientnet_v2_l",
Higher Results Are Better
"s",3.0036056605959,3.0140187312711,3.0118608531392
"b",2.9663727952097
"c",3.0377704025343