Intel Core i9-11900K testing with a ASUS ROG MAXIMUS XIII HERO (0707 BIOS) and AMD Radeon VII 16GB on Fedora 34 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 2106186-IB-11900KNN693
11900k nn,
"Mobile Neural Network 1.2 - Model: mobilenetV3",
Lower Results Are Better
"1",1.057,1.047,1.057
"2",1.045,1.058,1.058
"3",1.054,1.048,1.055
"4",1.057,1.048,1.059
"5",1.059,1.048,1.048
"Mobile Neural Network 1.2 - Model: squeezenetv1.1",
Lower Results Are Better
"1",2.323,2.271,2.332
"2",2.266,2.313,2.316
"3",2.327,2.316,2.337
"4",2.316,2.316,2.346
"5",2.35,2.272,2.325
"Mobile Neural Network 1.2 - Model: resnet-v2-50",
Lower Results Are Better
"1",18.441,18.277,18.469
"2",18.256,18.498,18.539
"3",18.494,18.477,18.474
"4",18.422,18.497,18.499
"5",18.445,18.313,18.446
"Mobile Neural Network 1.2 - Model: SqueezeNetV1.0",
Lower Results Are Better
"1",3.751,3.627,3.763
"2",3.551,3.735,3.789
"3",3.681,3.715,3.801
"4",3.7,3.759,3.802
"5",3.72,3.605,3.773
"Mobile Neural Network 1.2 - Model: MobileNetV2_224",
Lower Results Are Better
"1",1.926,1.905,1.928
"2",1.866,1.923,1.93
"3",1.905,1.926,1.969
"4",1.903,1.918,1.967
"5",1.934,1.91,1.921
"Mobile Neural Network 1.2 - Model: mobilenet-v1-1.0",
Lower Results Are Better
"1",1.803,1.781,1.783
"2",1.786,1.788,1.781
"3",1.772,1.778,1.809
"4",1.774,1.773,1.79
"5",1.777,1.774,1.767
"Mobile Neural Network 1.2 - Model: inception-v3",
Lower Results Are Better
"1",25.016,24.871,25.195
"2",24.579,25.107,25.12
"3",24.913,24.983,25.087
"4",25.057,25.03,25.192
"5",24.986,24.811,25.123
"NCNN 20210525 - Target: CPU - Model: mobilenet",
Lower Results Are Better
"1",12.87,12.83,13.34
"2",12.87,12.86,12.86
"3",12.86,12.87,13.33
"4",12.85,12.88,12.91
"5",12.88,13.36,13.22
"NCNN 20210525 - Target: CPU-v2-v2 - Model: mobilenet-v2",
Lower Results Are Better
"1",3.66,3.59,3.6
"2",3.57,3.57,3.63
"3",3.84,3.61,3.58
"4",3.58,3.58,3.59
"5",3.6,3.58,3.56
"NCNN 20210525 - Target: CPU-v3-v3 - Model: mobilenet-v3",
Lower Results Are Better
"1",2.85,2.82,2.81
"2",2.8,2.8,2.82
"3",2.8,2.82,2.85
"4",2.83,2.78,2.83
"5",2.79,2.78,2.81
"NCNN 20210525 - Target: CPU - Model: shufflenet-v2",
Lower Results Are Better
"1",2.57,2.57,2.54
"2",2.54,2.56,2.56
"3",2.56,2.56,2.59
"4",2.58,2.54,2.58
"5",2.55,2.54,2.56
"NCNN 20210525 - Target: CPU - Model: mnasnet",
Lower Results Are Better
"1",2.58,2.59,2.58
"2",2.6,2.58,2.61
"3",2.6,2.6,2.66
"4",
"5",2.59,2.59,2.57
"NCNN 20210525 - Target: CPU - Model: efficientnet-b0",
Lower Results Are Better
"1",4.61,4.58,4.6
"2",4.58,4.59,4.64
"3",4.62,4.58,4.63
"4",4.61,4.58,4.59
"5",4.59,4.58,4.58
"NCNN 20210525 - Target: CPU - Model: blazeface",
Lower Results Are Better
"1",1.14,1.08,1.07
"2",1.06,1.07,1.08
"3",1.08,1.08,1.09
"4",1.07,1.06,1.1
"5",1.06,1.06,1.07
"NCNN 20210525 - Target: CPU - Model: googlenet",
Lower Results Are Better
"1",11.07,10.4,10.4
"2",10.35,10.37,10.34
"3",10.36,10.36,10.39
"4",10.37,10.34,10.35
"5",10.4,10.37,10.38
"NCNN 20210525 - Target: CPU - Model: vgg16",
Lower Results Are Better
"1",55.22,55.18,55.08
"2",55.42,55.03,54.83
"3",54.76,55,55.09
"4",54.82,54.79,55.27
"5",55.27,54.77,54.72
"NCNN 20210525 - Target: CPU - Model: resnet18",
Lower Results Are Better
"1",11.58,11.54,11.53
"2",11.52,11.05,11.06
"3",11,11.02,11.08
"4",11.04,11.01,11.05
"5",11.57,11.1,11.06
"NCNN 20210525 - Target: CPU - Model: alexnet",
Lower Results Are Better
"1",9.93,9.93,9.91
"2",9.93,9.97,9.9
"3",9.94,9.91,9.94
"4",9.91,9.87,9.92
"5",9.95,9.93,9.95
"NCNN 20210525 - Target: CPU - Model: resnet50",
Lower Results Are Better
"1",19.44,19.46,19.37
"2",19.34,19.45,18.74
"3",18.72,18.71,19.39
"4",18.75,18.72,19.52
"5",19.37,18.75,18.71
"NCNN 20210525 - Target: CPU - Model: yolov4-tiny",
Lower Results Are Better
"1",20.05,19.06,20.43
"2",19.06,19.02,20.05
"3",19.12,19.07,20.43
"4",19.08,19.09,19.07
"5",20.08,20.5,20.41
"NCNN 20210525 - Target: CPU - Model: squeezenet_ssd",
Lower Results Are Better
"1",15.88,15.89,15.93
"2",15.86,15.84,15.8
"3",15.73,15.83,15.84
"4",15.8,15.75,15.84
"5",15.86,15.83,15.83
"NCNN 20210525 - Target: CPU - Model: regnety_400m",
Lower Results Are Better
"1",6.27,6.16,6.12
"2",6.05,6.15,6.16
"3",6.14,6.1,6.19
"4",6.15,6.09,6.15
"5",6.07,6.06,6.1
"TNN 0.3 - Target: CPU - Model: DenseNet",
Lower Results Are Better
"1",2729.126,2733.412,2727.208
"2",2728.8,2729.496,2768.161
"3",2724.307,2739.146,2735.524
"4",2727.628,2728.594,2721.031
"5",2737.692,2724.031,2726.231
"TNN 0.3 - Target: CPU - Model: MobileNet v2",
Lower Results Are Better
"1",247.941,247.854,248.042
"2",247.899,247.863,248.18
"3",248.047,247.808,248.016
"4",248.229,247.929,247.747
"5",247.79,247.92,248.192
"TNN 0.3 - Target: CPU - Model: SqueezeNet v2",
Lower Results Are Better
"1",47.428,47.601,47.715
"2",47.38,48.028,47.524
"3",47.341,47.589,47.693
"4",47.991,47.541,47.42
"5",47.674,47.461,47.573
"TNN 0.3 - Target: CPU - Model: SqueezeNet v1.1",
Lower Results Are Better
"1",236.606,236.29,236.172
"2",236.415,236.517,236.305
"3",236.641,236.476,236.61
"4",236.514,236.74,236.689
"5",236.734,236.676,236.656