AMD EPYC 7F32 8-Core testing with a Supermicro H11DSi-NT v2.00 (2.1 BIOS) and llvmpipe on Ubuntu 20.04 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 2012274-HA-EPYC7F32L08
EPYC 7F32 Last,
"CLOMP 1.2 - Static OMP Speedup",
Higher Results Are Better
"Run 1",29.8,29.8,29.7
"Run 2",29.7,29.4,29.6
"Run 3",27.8,29.7,28.9,29.5
"Run 4",29.9,29.9,29.3
"oneDNN 2.0 - Harness: IP Shapes 1D - Data Type: f32 - Engine: CPU",
Lower Results Are Better
"Run 1",3.52232,3.56585,3.56001
"Run 2",3.54244,3.55962,3.55072
"Run 3",3.55304,3.55865,3.56733
"Run 4",3.54964,3.56009,3.56842
"oneDNN 2.0 - Harness: IP Shapes 3D - Data Type: f32 - Engine: CPU",
Lower Results Are Better
"Run 1",6.52361,6.13298,6.15787,6.1484,6.14293
"Run 2",6.12161,6.18998,6.14305
"Run 3",6.11941,6.13406,6.12334
"Run 4",6.15007,6.21023,6.1778
"oneDNN 2.0 - Harness: IP Shapes 1D - Data Type: u8s8f32 - Engine: CPU",
Lower Results Are Better
"Run 1",2.78528,2.78777,2.80115
"Run 2",2.78253,2.79179,2.79496
"Run 3",2.78423,2.7914,2.79446
"Run 4",2.78454,2.79148,2.80259
"oneDNN 2.0 - Harness: IP Shapes 3D - Data Type: u8s8f32 - Engine: CPU",
Lower Results Are Better
"Run 1",0.770455,0.807209,0.789226
"Run 2",0.796044,0.79034,0.800387
"Run 3",0.798562,0.789313,0.803185
"Run 4",0.790855,0.777622,0.795651
"oneDNN 2.0 - Harness: Convolution Batch Shapes Auto - Data Type: f32 - Engine: CPU",
Lower Results Are Better
"Run 1",4.93403,4.96052,5.04737
"Run 2",4.90191,4.94679,4.92142
"Run 3",4.93994,4.96201,4.96151
"Run 4",4.93454,4.96262,4.88977
"oneDNN 2.0 - Harness: Deconvolution Batch shapes_1d - Data Type: f32 - Engine: CPU",
Lower Results Are Better
"Run 1",4.92789,4.9031,5.00129
"Run 2",4.93762,5.04212,4.92494
"Run 3",5.00723,4.93438,4.93217
"Run 4",4.92833,4.98738,4.89499
"oneDNN 2.0 - Harness: Deconvolution Batch shapes_3d - Data Type: f32 - Engine: CPU",
Lower Results Are Better
"Run 1",6.41927,6.42516,6.42817
"Run 2",6.41456,6.43048,6.42083
"Run 3",6.42437,6.42288,6.42208
"Run 4",6.41124,6.41764,6.4244
"oneDNN 2.0 - Harness: Convolution Batch Shapes Auto - Data Type: u8s8f32 - Engine: CPU",
Lower Results Are Better
"Run 1",9.71552,9.8362,9.45098
"Run 2",9.53748,9.49696,9.8362
"Run 3",9.42583,9.42842,9.54432
"Run 4",9.39225,9.50447,9.88915
"oneDNN 2.0 - Harness: Deconvolution Batch shapes_1d - Data Type: u8s8f32 - Engine: CPU",
Lower Results Are Better
"Run 1",7.22763,7.2285,7.14387
"Run 2",7.28959,7.19642,7.17064
"Run 3",7.21506,7.24778,7.20547
"Run 4",7.19526,7.2068,7.25817
"oneDNN 2.0 - Harness: Deconvolution Batch shapes_3d - Data Type: u8s8f32 - Engine: CPU",
Lower Results Are Better
"Run 1",5.57965,5.58744,5.58185
"Run 2",5.58039,5.58033,5.57887
"Run 3",5.57022,5.58025,5.58533
"Run 4",5.59387,5.58573,5.58329
"oneDNN 2.0 - Harness: Recurrent Neural Network Training - Data Type: f32 - Engine: CPU",
Lower Results Are Better
"Run 1",4756.58,3418.82,4776.46,3421.07,3419.63,3424.43,3423.86,3433.27,3431.33,3422.23,3423.21,3425.02,3426.62,3430.11,3433.3
"Run 2",3439.78,3433.92,3435.58
"Run 3",3421.55,3432.93,3440.01
"Run 4",3418.44,3414.93,3418.57
"oneDNN 2.0 - Harness: Recurrent Neural Network Inference - Data Type: f32 - Engine: CPU",
Lower Results Are Better
"Run 1",1708.67,1704.45,1711.76
"Run 2",1705.77,1707.04,1711.84
"Run 3",1709.33,1716.76,1707.34
"Run 4",1712.02,1717.27,1706.32
"oneDNN 2.0 - Harness: Recurrent Neural Network Training - Data Type: u8s8f32 - Engine: CPU",
Lower Results Are Better
"Run 1",3428.76,3437.04,3422.83
"Run 2",3441.12,3440.04,3435.82
"Run 3",3433.89,3439.19,3437.27
"Run 4",3428.26,3427.4,3426.13
"oneDNN 2.0 - Harness: Recurrent Neural Network Inference - Data Type: u8s8f32 - Engine: CPU",
Lower Results Are Better
"Run 1",1712.05,1708.72,1713.41
"Run 2",1718.08,1718.65,1717.69
"Run 3",1715.52,1717.9,1716.17
"Run 4",1708.67,1712.11,1713.07
"oneDNN 2.0 - Harness: Matrix Multiply Batch Shapes Transformer - Data Type: f32 - Engine: CPU",
Lower Results Are Better
"Run 1",1.17158,1.16157,1.16002
"Run 2",1.15372,1.16047,1.16186
"Run 3",1.15713,1.1582,1.16309
"Run 4",1.16192,1.15921,1.16357
"oneDNN 2.0 - Harness: Recurrent Neural Network Training - Data Type: bf16bf16bf16 - Engine: CPU",
Lower Results Are Better
"Run 1",3427.9,3412.04,3413.8
"Run 2",3437.73,3443.34,3444.73
"Run 3",3436.04,3449.63,3437.94
"Run 4",3414.25,3423.08,3428.51
"oneDNN 2.0 - Harness: Recurrent Neural Network Inference - Data Type: bf16bf16bf16 - Engine: CPU",
Lower Results Are Better
"Run 1",1709.82,1704.67,1700.41
"Run 2",1716.62,1714.37,1715.96
"Run 3",1706.24,1713.92,1718.4
"Run 4",1708.31,1722.36,1712
"oneDNN 2.0 - Harness: Matrix Multiply Batch Shapes Transformer - Data Type: u8s8f32 - Engine: CPU",
Lower Results Are Better
"Run 1",3.59064,3.59604,3.60556
"Run 2",3.59777,3.59551,3.59416
"Run 3",3.58933,3.59119,3.59256
"Run 4",3.59074,3.60654,3.59669
"NCNN 20201218 - Target: CPU - Model: mobilenet",
Lower Results Are Better
"Run 1",20.06,19.8,19.95
"Run 2",19.78,19.77,19.87
"Run 3",19.9,19.87,19.91
"Run 4",19.9,19.96,19.79
"NCNN 20201218 - Target: CPU-v2-v2 - Model: mobilenet-v2",
Lower Results Are Better
"Run 1",6.85,6.82,6.93
"Run 2",6.84,6.83,6.84
"Run 3",6.82,6.84,6.89
"Run 4",6.79,6.82,6.88
"NCNN 20201218 - Target: CPU-v3-v3 - Model: mobilenet-v3",
Lower Results Are Better
"Run 1",6.61,6.75,6.62
"Run 2",6.64,6.63,6.66
"Run 3",6.62,6.65,6.6
"Run 4",6.56,6.59,6.66
"NCNN 20201218 - Target: CPU - Model: shufflenet-v2",
Lower Results Are Better
"Run 1",9.61,9.56,9.67
"Run 2",9.64,9.63,9.62
"Run 3",9.58,9.61,9.62
"Run 4",9.59,9.57,9.65
"NCNN 20201218 - Target: CPU - Model: mnasnet",
Lower Results Are Better
"Run 1",5.99,5.9,6.53
"Run 2",5.97,5.92,5.93
"Run 3",5.94,6.01,5.96
"Run 4",5.9,6.21,5.94
"NCNN 20201218 - Target: CPU - Model: efficientnet-b0",
Lower Results Are Better
"Run 1",10.81,10.41,10.52
"Run 2",10.57,10.51,10.56
"Run 3",10.44,10.47,10.47
"Run 4",10.5,10.44,10.49
"NCNN 20201218 - Target: CPU - Model: blazeface",
Lower Results Are Better
"Run 1",3.37,3.27,3.3
"Run 2",3.33,3.27,3.42
"Run 3",3.3,3.3,3.3
"Run 4",3.27,3.34,3.32
"NCNN 20201218 - Target: CPU - Model: googlenet",
Lower Results Are Better
"Run 1",15.93,15.47,15.55
"Run 2",15.35,15.35,15.85
"Run 3",15.45,15.55,15.45
"Run 4",16.93,16.79,15.43
"NCNN 20201218 - Target: CPU - Model: vgg16",
Lower Results Are Better
"Run 1",32.67,32.39,32.28
"Run 2",32.66,32.29,32.29
"Run 3",32.25,32.35,32.35
"Run 4",32.33,32.33,32.27
"NCNN 20201218 - Target: CPU - Model: resnet18",
Lower Results Are Better
"Run 1",11.59,11.58,11.4
"Run 2",11.49,11.57,11.66
"Run 3",11.46,11.49,11.5
"Run 4",11.68,11.58,11.44
"NCNN 20201218 - Target: CPU - Model: alexnet",
Lower Results Are Better
"Run 1",7.58,7.57,7.58
"Run 2",7.57,7.59,7.63
"Run 3",7.59,7.59,7.61
"Run 4",7.59,7.6,7.58
"NCNN 20201218 - Target: CPU - Model: resnet50",
Lower Results Are Better
"Run 1",23.15,23,22.91
"Run 2",22.94,22.89,23.06
"Run 3",22.8,22.93,22.94
"Run 4",23.11,23.09,22.91
"NCNN 20201218 - Target: CPU - Model: yolov4-tiny",
Lower Results Are Better
"Run 1",27.76,27.15,26.27
"Run 2",26.37,26.39,27.38
"Run 3",26.38,26.44,26.39
"Run 4",27.35,27.33,26.62
"NCNN 20201218 - Target: CPU - Model: squeezenet_ssd",
Lower Results Are Better
"Run 1",24.57,24.41,25.61
"Run 2",24.52,24.45,24.47
"Run 3",24.43,24.48,24.47
"Run 4",25.73,25.74,24.47
"NCNN 20201218 - Target: CPU - Model: regnety_400m",
Lower Results Are Better
"Run 1",32.59,31.37,32.25
"Run 2",32.5,31.93,32.15
"Run 3",32.37,32.18,32.49
"Run 4",31.71,31.74,32.64
"Unpacking The Linux Kernel - linux-4.15.tar.xz",
Lower Results Are Better
"Run 1",5.872,6.02,5.925,6.077
"Run 2",5.811,5.814,6.182,6.105,5.947
"Run 3",5.968,6.025,5.972,6.097
"Run 4",5.825,5.694,6.016,5.871
"Build2 0.13 - Time To Compile",
Lower Results Are Better
"Run 1",112.087,112.79,111.357
"Run 2",112.174,113.192,112.967
"Run 3",113.176,113.877,110.967
"Run 4",112.07,112.002,113.3
"Timed Eigen Compilation 3.3.9 - Time To Compile",
Lower Results Are Better
"Run 1",82.91,82.847,82.891
"Run 2",82.966,82.955,82.932
"Run 3",83.045,83.131,83.03
"Run 4",82.99,82.931,83.06
"Monkey Audio Encoding 3.99.6 - WAV To APE",
Lower Results Are Better
"Run 1",12.493,12.572,12.496,12.483,12.492
"Run 2",12.486,12.525,12.554,12.474,12.519
"Run 3",12.509,12.499,12.471,12.489,12.477
"Run 4",12.482,12.494,12.479,12.503,12.507
"Ogg Audio Encoding 1.3.4 - WAV To Ogg",
Lower Results Are Better
"Run 1",20.621,20.55,20.551
"Run 2",20.559,20.621,20.541
"Run 3",20.619,20.546,20.584
"Run 4",20.522,20.564,20.58
"Opus Codec Encoding 1.3.1 - WAV To Opus Encode",
Lower Results Are Better
"Run 1",7.965,7.96,7.993,7.965,7.975
"Run 2",7.963,7.976,7.963,7.98,7.983
"Run 3",7.96,7.974,7.972,7.974,7.966
"Run 4",7.955,7.969,7.958,7.972,7.977
"WavPack Audio Encoding 5.3 - WAV To WavPack",
Lower Results Are Better
"Run 1",13.744,13.731,13.725,13.73,13.726
"Run 2",13.727,13.74,13.73,13.725,13.733
"Run 3",13.725,13.734,13.725,13.732,13.733
"Run 4",13.732,13.73,13.738,13.727,13.732
"Unpacking Firefox 84.0 - Extracting: firefox-84.0.source.tar.xz",
Lower Results Are Better
"Run 1",20.362,20.229,20.457,20.439
"Run 2",20.353,20.348,20.304,20.088
"Run 3",20.053,20.199,20.397,20.234
"Run 4",20.259,20.08,20.289,20.213