2 x Intel Xeon Platinum 8380 testing with a Intel M50CYP2SB2U (SE5C6200.86B.0022.D08.2103221623 BIOS) and ASPEED on CentOS Stream 9 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 2208133-NE-MNNNCNNXE63
mnn ncnn xeon,
"Mobile Neural Network 2.0 - Model: inception-v3",
Lower Results Are Better
"A",20.49,21.538,20.043
"B",20.996,20.445,20.995
"C",20.302,20.896,20.879,21.108,20.955,20.44,21.415,20.745,20.821,20.094,21.056,21.246,20.29,21.694
"D",20.502,20.396,21.236,21.247,20.722,20.653,20.444,20.4,20.765,21.269,20.706,21.493,20.847,20.826,20.931
"E",21.255,21.543,21.24
"Mobile Neural Network 2.0 - Model: mobilenet-v1-1.0",
Lower Results Are Better
"A",2.21,2.27,2.203
"B",2.209,2.201,2.184
"C",2.13,2.189,2.191,2.188,2.254,2.183,2.238,2.152,2.194,2.273,2.135,1.867,2.176
"D",2.215,2.201,2.171,2.27,2.17,2.349,2.204,2.166,2.217,2.193,2.196,2.259,2.175,2.154,2.231
"E",2.211,2.256,2.185
"Mobile Neural Network 2.0 - Model: MobileNetV2_224",
Lower Results Are Better
"A",3.69,3.343,3.212
"B",3.003,3.193,3.256
"C",3.659,3.192,2.843,3.277,3.162,3.111,3.042,3.121,3.337,3.194,3.328,3.269,3.308,3.197
"D",3.698,3.196,3.017,2.793,3.268,3.263,3.251,3.293,3.23,3.158,3.279,3.254,3.234,3.268,3.235
"E",3.264,2.927,3.216
"Mobile Neural Network 2.0 - Model: SqueezeNetV1.0",
Lower Results Are Better
"A",4.063,4.429,3.871
"B",4.301,4.318,4.02
"C",4.176,3.951,4.058,4.309,4.548,4.495,4.385,3.989,4.491,4.022,4.529,4.51,4.26,4.408
"D",3.999,3.989,4.288,4.368,4.343,4.427,4.018,4.203,4.22,4.04,4.214,4.394,4.212,4.388,4.178
"E",4.55,4.239,4.173
"Mobile Neural Network 2.0 - Model: resnet-v2-50",
Lower Results Are Better
"A",8.872,8.983,8.491
"B",9.356,9.006,8.88
"C",8.589,8.801,8.645,8.559,8.912,8.762,8.88,8.682,9.219,8.545,9.13,8.757,8.505,8.739
"D",9.06,8.797,8.75,9.05,8.928,8.816,8.675,8.697,8.871,9.069,8.837,9.041,8.639,8.847,9.215
"E",9.151,9.245,9.2
"Mobile Neural Network 2.0 - Model: squeezenetv1.1",
Lower Results Are Better
"A",2.235,2.517,2.199
"B",2.579,2.198,2.407
"C",2.244,2.219,2.552,2.438,2.554,2.619,2.589,2.24,2.642,2.161,2.656,2.245,2.139,2.647
"D",2.378,2.531,2.611,2.418,2.333,2.331,2.365,2.389,2.643,2.409,2.406,2.61,2.387,2.43,2.465
"E",2.577,2.619,2.363
"Mobile Neural Network 2.0 - Model: mobilenetV3",
Lower Results Are Better
"A",1.825,1.84,1.757
"B",1.82,1.807,1.883
"C",1.808,1.808,1.891,1.776,1.891,1.879,1.919,1.82,1.745,1.699,1.856,1.798,1.72,1.915
"D",1.806,2.077,1.857,1.88,1.795,1.843,1.817,1.872,1.907,1.901,1.848,1.901,1.801,1.812,1.856
"E",1.875,1.9,1.82
"NCNN 20220729 - Target: CPU - Model: FastestDet",
Lower Results Are Better
"A",15.1,15.31,15.59
"B",14.75,14.81,15.38
"C",15.51,16.37,14.8
"D",14.67,15.35,14.73
"E",15.05,14.99,14.74
"NCNN 20220729 - Target: CPU - Model: vision_transformer",
Lower Results Are Better
"A",154.79,150.92,149.62
"B",152.95,152.61,152.34
"C",153.94,151.73,152.71
"D",156.09,155,154.85
"E",155.8,155.39,156.51
"NCNN 20220729 - Target: CPU - Model: regnety_400m",
Lower Results Are Better
"A",60.08,54.58,56.77
"B",59.19,56.77,57.32
"C",59.54,58.05,56.17
"D",54.98,59.16,56.57
"E",57.54,59.2,59.29
"NCNN 20220729 - Target: CPU - Model: squeezenet_ssd",
Lower Results Are Better
"A",26.14,26.27,26.6
"B",26.5,26.09,26.49
"C",26.63,26.86,28.02
"D",26.21,27.14,26.63
"E",25.94,25.75,26.19
"NCNN 20220729 - Target: CPU - Model: yolov4-tiny",
Lower Results Are Better
"A",28.15,26.94,28.31
"B",26.98,27.02,27.75
"C",27.26,27.23,27.34
"D",27.83,27.38,26.93
"E",26.64,26.47,27.1
"NCNN 20220729 - Target: CPU - Model: resnet50",
Lower Results Are Better
"A",25.36,23.44,25.46
"B",24.82,24.75,23.89
"C",24.94,25.52,24.97
"D",25.17,25.16,25.49
"E",24.12,24.47,24.43
"NCNN 20220729 - Target: CPU - Model: alexnet",
Lower Results Are Better
"A",8.93,8.26,9.49
"B",8.83,8.37,8.34
"C",8.49,8.69,8.42
"D",9.65,8.37,9.35
"E",8.35,8.16,9.34
"NCNN 20220729 - Target: CPU - Model: resnet18",
Lower Results Are Better
"A",13.56,12.89,13.65
"B",13.38,12.99,13.17
"C",13.25,13.5,13.77
"D",13.12,13.42,15.08
"E",13.01,13.42,13.18
"NCNN 20220729 - Target: CPU - Model: vgg16",
Lower Results Are Better
"A",32.73,27.74,32.26
"B",29.15,28.92,29.08
"C",30.02,29.64,29.24
"D",30.41,30.81,32.38
"E",28.63,28.76,28.66
"NCNN 20220729 - Target: CPU - Model: googlenet",
Lower Results Are Better
"A",24.85,23.26,23.1
"B",22.87,22.57,22.15
"C",23.27,23.85,22.2
"D",22.67,23.69,24.2
"E",23.15,22.14,22.64
"NCNN 20220729 - Target: CPU - Model: blazeface",
Lower Results Are Better
"A",7.28,7,7.18
"B",7.73,7.08,7.21
"C",7.39,7.39,7.05
"D",6.84,7.27,7.06
"E",7.27,7.14,7.29
"NCNN 20220729 - Target: CPU - Model: efficientnet-b0",
Lower Results Are Better
"A",17.09,16.62,16.97
"B",16.85,16.75,16.4
"C",19.18,17.31,16.77
"D",15.99,16.96,16.67
"E",17.01,15.98,16.52
"NCNN 20220729 - Target: CPU - Model: mnasnet",
Lower Results Are Better
"A",12.11,11.83,11.81
"B",12.01,11.79,12.35
"C",11.91,12.08,11.73
"D",11.49,11.91,11.83
"E",11.89,11.63,11.85
"NCNN 20220729 - Target: CPU - Model: shufflenet-v2",
Lower Results Are Better
"A",13.57,13.56,13.28
"B",14.34,13.45,13.36
"C",13.58,13.68,13.15
"D",13.26,13.56,13.54
"E",14.09,13.2,13.59
"NCNN 20220729 - Target: CPU-v3-v3 - Model: mobilenet-v3",
Lower Results Are Better
"A",12.19,12.14,11.76
"B",12.28,12.51,11.84
"C",12.15,12.36,12.25
"D",12.07,12.14,12.15
"E",12.53,11.98,12.13
"NCNN 20220729 - Target: CPU-v2-v2 - Model: mobilenet-v2",
Lower Results Are Better
"A",12.85,12.86,13.26
"B",12.89,12.77,12.76
"C",12.69,12.87,12.8
"D",12.95,12.84,12.65
"E",13.31,13.83,12.8
"NCNN 20220729 - Target: CPU - Model: mobilenet",
Lower Results Are Better
"A",22.12,21.33,22.28
"B",21.71,21.68,21.65
"C",22.27,22.11,22.66
"D",23.06,22.77,22.73
"E",21.94,21.54,22.08