AMD EPYC 7502 32-Core testing with a ASRockRack EPYCD8 (P2.10 BIOS) and llvmpipe on Ubuntu 20.10 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 2012126-HA-EPYC7502356
EPYC 7502,
"Compile Bench 0.6 - Test: Compile",
Higher Results Are Better
"1",1820.19,1850.04,1810.75
"2",1820.44,1810.75,1890.94
"3",1844.93,1825.03,1825.03
"Compile Bench 0.6 - Test: Initial Create",
Higher Results Are Better
"1",511.33,538.56,538.5
"2",545.09,542.51,543.8
"3",547.8,539.79,545.15
"Compile Bench 0.6 - Test: Read Compiled Tree",
Higher Results Are Better
"1",2764.89,2793.4,2764.89
"2",2768.41,2738.07,2764.89
"3",2793.4,2793.4,2764.89
"Timed HMMer Search 3.3.1 - Pfam Database Search",
Lower Results Are Better
"1",176.011,177.004,177.296
"2",176.628,176.769,177.175
"3",177.114,176.741,176.406
"Timed MAFFT Alignment 7.471 - Multiple Sequence Alignment - LSU RNA",
Lower Results Are Better
"1",10.425,10.445,10.36
"2",10.349,10.386,10.217
"3",10.243,10.264,10.26
"GraphicsMagick 1.3.33 - Operation: Swirl",
Higher Results Are Better
"1",1203,1199,1193
"2",1195,1193,1194
"3",1202,1199,1199
"GraphicsMagick 1.3.33 - Operation: Rotate",
Higher Results Are Better
"1",519,521,521
"2",503,507,514
"3",
"GraphicsMagick 1.3.33 - Operation: Sharpen",
Higher Results Are Better
"1",373,372,372
"2",
"3",
"GraphicsMagick 1.3.33 - Operation: Enhanced",
Higher Results Are Better
"1",566,567,567
"2",
"3",
"GraphicsMagick 1.3.33 - Operation: Resizing",
Higher Results Are Better
"1",1775,1762,1764
"2",1795,1745,1737
"3",1741,1788,1779
"GraphicsMagick 1.3.33 - Operation: Noise-Gaussian",
Higher Results Are Better
"1",
"2",
"3",514,512,514
"GraphicsMagick 1.3.33 - Operation: HWB Color Space",
Higher Results Are Better
"1",1123,1125,1123
"2",
"3",1134,1132,1134
"oneDNN 2.0 - Harness: IP Shapes 1D - Data Type: f32 - Engine: CPU",
Lower Results Are Better
"1",1.58973,1.59354,1.60137
"2",1.58889,1.60401,1.60838
"3",1.59588,1.59944,1.60223
"oneDNN 2.0 - Harness: IP Shapes 3D - Data Type: f32 - Engine: CPU",
Lower Results Are Better
"1",2.98633,2.99262,3.00075
"2",2.97989,3.01003,3.00655
"3",2.98972,2.98925,2.99355
"oneDNN 2.0 - Harness: IP Shapes 1D - Data Type: u8s8f32 - Engine: CPU",
Lower Results Are Better
"1",1.18218,1.18816,1.19277
"2",1.17572,1.18601,1.19221
"3",1.18293,1.18676,1.19042
"oneDNN 2.0 - Harness: IP Shapes 3D - Data Type: u8s8f32 - Engine: CPU",
Lower Results Are Better
"1",1.00302,1.03306,1.03089
"2",0.991382,1.00568,1.01786
"3",1.00442,1.00701,1.01546
"oneDNN 2.0 - Harness: Convolution Batch Shapes Auto - Data Type: f32 - Engine: CPU",
Lower Results Are Better
"1",3.4871,3.52559,3.50491
"2",3.48433,3.53277,3.50688
"3",3.48469,3.54315,3.47674
"oneDNN 2.0 - Harness: Deconvolution Batch shapes_1d - Data Type: f32 - Engine: CPU",
Lower Results Are Better
"1",2.15111,2.13278,2.11279
"2",2.11443,2.13434,2.1269
"3",2.14124,2.13959,2.12304
"oneDNN 2.0 - Harness: Deconvolution Batch shapes_3d - Data Type: f32 - Engine: CPU",
Lower Results Are Better
"1",3.69364,3.73042,3.67466
"2",3.70067,3.70561,3.68113
"3",3.70571,3.69227,3.672
"oneDNN 2.0 - Harness: Convolution Batch Shapes Auto - Data Type: u8s8f32 - Engine: CPU",
Lower Results Are Better
"1",4.02771,3.997,4.0551
"2",3.93567,4.0331,4.01336
"3",3.92788,4.05105,4.03466
"oneDNN 2.0 - Harness: Deconvolution Batch shapes_1d - Data Type: u8s8f32 - Engine: CPU",
Lower Results Are Better
"1",2.20215,2.21714,2.21231
"2",2.21445,2.20855,2.20292
"3",2.20384,2.23157,2.21109
"oneDNN 2.0 - Harness: Deconvolution Batch shapes_3d - Data Type: u8s8f32 - Engine: CPU",
Lower Results Are Better
"1",1.94822,1.95616,1.9596
"2",1.96035,1.95794,1.95187
"3",1.96143,1.96809,1.9626
"oneDNN 2.0 - Harness: Recurrent Neural Network Training - Data Type: f32 - Engine: CPU",
Lower Results Are Better
"1",2777.24,2771.31,2791.79
"2",2784.4,2776.12,2786.67
"3",2755.65,2766.5,2771.98
"oneDNN 2.0 - Harness: Recurrent Neural Network Inference - Data Type: f32 - Engine: CPU",
Lower Results Are Better
"1",1032.39,1001.25,984.803
"2",1017.59,1019.81,1007
"3",1026.44,1019.25,988.529
"oneDNN 2.0 - Harness: Recurrent Neural Network Training - Data Type: u8s8f32 - Engine: CPU",
Lower Results Are Better
"1",5341.79,2777.98,2778.83,2800.18,2801.63,2793.55,2786.93,2782.33,2780.63,2793.51,2783.49,2794.7,2788.14,2779.93,2799.94
"2",2802.08,2777.19,2783
"3",2779.21,2762.6,2774.31
"oneDNN 2.0 - Harness: Recurrent Neural Network Inference - Data Type: u8s8f32 - Engine: CPU",
Lower Results Are Better
"1",1020.65,1002.79,983.274
"2",995.56,995.64,998.251
"3",1027.73,1023.71,1026.68
"oneDNN 2.0 - Harness: Matrix Multiply Batch Shapes Transformer - Data Type: f32 - Engine: CPU",
Lower Results Are Better
"1",0.541801,0.537968,0.534692
"2",0.540857,0.538716,0.545135
"3",0.542453,0.538025,0.54439
"oneDNN 2.0 - Harness: Recurrent Neural Network Training - Data Type: bf16bf16bf16 - Engine: CPU",
Lower Results Are Better
"1",2785.56,2780.97,2781.59
"2",2792.89,2792.84,2786.88
"3",2786.9,2775.21,2754.31
"oneDNN 2.0 - Harness: Recurrent Neural Network Inference - Data Type: bf16bf16bf16 - Engine: CPU",
Lower Results Are Better
"1",1027.01,1028.32,1014.41
"2",1023.72,1014.99,998.835
"3",1021.98,1022.25,1023.57
"oneDNN 2.0 - Harness: Matrix Multiply Batch Shapes Transformer - Data Type: u8s8f32 - Engine: CPU",
Lower Results Are Better
"1",1.17617,1.17158,1.17522
"2",1.16652,1.18142,1.17311
"3",1.17315,1.17487,1.17193
"Coremark 1.0 - CoreMark Size 666 - Iterations Per Second",
Higher Results Are Better
"1",1132693.243662,1130692.107239,1120693.429059
"2",1131391.700181,1135456.400248,1121478.950366
"3",1134349.521446,1119076.761672,1130742.04947
"Timed FFmpeg Compilation 4.2.2 - Time To Compile",
Lower Results Are Better
"1",26.343,26.096,26.083
"2",26.331,26.154,26.298
"3",26.405,26.257,26.032
"SQLite Speedtest 3.30 - Timed Time - Size 1,000",
Lower Results Are Better
"1",82.896,83.245,82.773
"2",85.509,84.88,84.361
"3",84.929,83.067,82.238
"Apache Siege 2.4.29 - Concurrent Users: 10",
Higher Results Are Better
"1",19011.41,19379.85,20120.72
"2",19960.08,20283.98,20080.32
"Apache Siege 2.4.29 - Concurrent Users: 50",
Higher Results Are Better
"1",29120.56,29359.95,29377.2
"2",29019.15,29342.72,29411.77
"Apache Siege 2.4.29 - Concurrent Users: 100",
Higher Results Are Better
"1",30769.23,30385.9,30469.23
"2",30854.67,30404.38,30330.6
"Apache Siege 2.4.29 - Concurrent Users: 200",
Higher Results Are Better
"1",32938.07,33316.68,32932.65
"2",33036.01,32846.12,32803.02
"Apache Siege 2.4.29 - Concurrent Users: 250",
Higher Results Are Better
"1",36416.61,37913.25,37855.84
"2",34473.25,34335.95,35156.8
"Apache Siege 2.4.29 - Concurrent Users: 500",
Higher Results Are Better
"1",34717.5,39267.02,47362.55,48104.13,48377.92,46287.89,47117.52,47362.55,47887.32,48213.27,48231.51,47265.99,48022.6,48258.89,48004.52
"BRL-CAD 7.30.8 - VGR Performance Metric",
Higher Results Are Better
"1",