8490h april

2 x Intel Xeon Platinum 8490H testing with a Quanta Cloud S6Q-MB-MPS (3A10.uh BIOS) and ASPEED on Ubuntu 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 2304136-NE-8490HAPRI45
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C/C++ Compiler Tests 2 Tests
CPU Massive 5 Tests
Creator Workloads 3 Tests
HPC - High Performance Computing 2 Tests
Machine Learning 2 Tests
Multi-Core 3 Tests
Server 2 Tests
Server CPU Tests 2 Tests

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Date
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  Test
  Duration
a
April 12 2023
  52 Minutes
b
April 12 2023
  4 Hours, 49 Minutes
c
April 13 2023
  52 Minutes
d
April 13 2023
  52 Minutes
e
April 13 2023
  52 Minutes
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  1 Hour, 40 Minutes

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8490h april, "oneDNN 3.1 - Harness: IP Shapes 3D - Data Type: u8s8f32 - Engine: CPU", Lower Results Are Better "a", "b",0.977478,0.983141,0.974666 "c", "d", "e", "oneDNN 3.1 - Harness: Recurrent Neural Network Inference - Data Type: f32 - Engine: CPU", Lower Results Are Better "a", "b",832.831,843.802,774.044,886.79,895.629,885.099,846.225,784.976,829.77,805.715,904.734,846.052,802.055,824.22,852.392 "c", "d", "e", "oneDNN 3.1 - Harness: IP Shapes 3D - Data Type: f32 - Engine: CPU", Lower Results Are Better "a", "b",2.6933,2.60895,2.72872 "c", "d", "e", "VVenC 1.8 - Video Input: Bosphorus 1080p - Video Preset: Faster", Higher Results Are Better "a", "b",30.644,31.107,31.214 "c", "d", "e", "oneDNN 3.1 - Harness: IP Shapes 3D - Data Type: bf16bf16bf16 - Engine: CPU", Lower Results Are Better "a", "b",3.17569,2.70103,3.07863,3.33323,2.85305,3.05523,3.03667,2.9539,3.01186,3.06528,3.06227,3.14776,3.10122,3.01872,3.1012 "c", "d", "e", "oneDNN 3.1 - Harness: Deconvolution Batch shapes_1d - Data Type: u8s8f32 - Engine: CPU", Lower Results Are Better "a", "b",0.401847,0.425472,0.403964,0.423692,0.422955,0.424444,0.426687,0.389414,0.396347,0.407187,0.418908,0.40184,0.390608,0.408464,0.40861 "c", "d", "e", "oneDNN 3.1 - Harness: Recurrent Neural Network Training - Data Type: bf16bf16bf16 - Engine: CPU", Lower Results Are Better "a", "b",1308.2,1198,1248.64,1038.17,1187.93,1193.4,1140.21,1269,1172.1,1102.35,1125,1181.96,1228.56,1160.43,1208.14 "c", "d", "e", "oneDNN 3.1 - Harness: Recurrent Neural Network Inference - Data Type: bf16bf16bf16 - Engine: CPU", Lower Results Are Better "a", "b",849.844,902.463,873.724,897.289,869.127 "c", "d", "e", "Apache HTTP Server 2.4.56 - Concurrent Requests: 500", Higher Results Are Better "a", "b",83868.43,83650.69,83985.32 "c", "d", "e", "srsRAN Project 23.3 - Test: PUSCH Processor Benchmark, Throughput Total", Higher Results Are Better "a", "b",6619.2,7026,6523.2,7085.5,6617.2,6810.8,7013.3,7259.3,7132.8 "c", "d", "e", "TensorFlow 2.12 - Device: CPU - Batch Size: 32 - Model: GoogLeNet", Higher Results Are Better "a", "b",266.86,268.77,265.43 "c", "d", "e", "TensorFlow 2.12 - Device: CPU - Batch Size: 16 - Model: GoogLeNet", Higher Results Are Better "a", "b",183.4,185.12,188.83 "c", "d", "e", "oneDNN 3.1 - Harness: Deconvolution Batch shapes_1d - Data Type: bf16bf16bf16 - Engine: CPU", Lower Results Are Better "a", "b",0.465771,0.473148,0.437698,0.439495,0.449283,0.456386,0.437608,0.457024,0.450184,0.449868,0.448863 "c", "d", "e", "TensorFlow 2.12 - Device: CPU - Batch Size: 32 - Model: AlexNet", Higher Results Are Better "a", "b",534.22,559.26,572.83,556.03,562.43,553.29 "c", "d", "e", "TensorFlow 2.12 - Device: CPU - Batch Size: 16 - Model: AlexNet", Higher Results Are Better "a", "b",389.2,380.33,390.13 "c", "d", "e", "oneDNN 3.1 - Harness: Convolution Batch Shapes Auto - Data Type: bf16bf16bf16 - Engine: CPU", Lower Results Are Better "a", "b",0.218135,0.224679,0.226612 "c", "d", "e", "oneDNN 3.1 - Harness: Deconvolution Batch shapes_3d - Data Type: u8s8f32 - Engine: CPU", Lower Results Are Better "a", "b",0.227623,0.224367,0.223602 "c", "d", "e", "TensorFlow 2.12 - Device: CPU - Batch Size: 64 - Model: GoogLeNet", Higher Results Are Better "a", "b",340.37,338.48,347.93 "c", "d", "e", "Blender 3.5 - Blend File: Fishy Cat - Compute: CPU-Only", Lower Results Are Better "a", "b",19.86,19.71,19.54 "c", "d", "e", "srsRAN Project 23.3 - Test: PUSCH Processor Benchmark, Throughput Thread", Higher Results Are Better "a", "b",29.4,30.1,30 "c", "d", "e", "VVenC 1.8 - Video Input: Bosphorus 1080p - Video Preset: Fast", Higher Results Are Better "a", "b",17.446,17.429,17.312 "c", "d", "e", "Blender 3.5 - Blend File: Pabellon Barcelona - Compute: CPU-Only", Lower Results Are Better "a", "b",47.83,47.67,48.03 "c", "d", "e", "oneDNN 3.1 - Harness: Deconvolution Batch shapes_1d - Data Type: f32 - Engine: CPU", Lower Results Are Better "a", "b",14.6477,14.5315,14.7061 "c", "d", "e", "TensorFlow 2.12 - Device: CPU - Batch Size: 256 - Model: AlexNet", Higher Results Are Better "a", "b",1087.63,1070.77,1074.3 "c", "d", "e", "oneDNN 3.1 - Harness: Deconvolution Batch shapes_3d - Data Type: bf16bf16bf16 - Engine: CPU", Lower Results Are Better "a", "b",0.463632,0.47135,0.463153 "c", "d", "e", "TensorFlow 2.12 - Device: CPU - Batch Size: 256 - Model: ResNet-50", Higher Results Are Better "a", "b",128.79,128.91,128.97 "c", "d", "e", "TensorFlow 2.12 - Device: CPU - Batch Size: 64 - Model: ResNet-50", Higher Results Are Better "a", "b",101.96,101.59,103.07 "c", "d", "e", "TensorFlow 2.12 - Device: CPU - Batch Size: 32 - Model: ResNet-50", Higher Results Are Better "a", "b",84.45,83.84,84.97 "c", "d", "e", "VVenC 1.8 - Video Input: Bosphorus 4K - Video Preset: Fast", Higher Results Are Better "a", "b",6.265,6.393,6.337 "c", "d", "e", "TensorFlow 2.12 - Device: CPU - Batch Size: 512 - Model: GoogLeNet", Higher Results Are Better "a", "b",472.53,464.93,458.47 "c", "d", "e", "oneDNN 3.1 - Harness: Convolution Batch Shapes Auto - Data Type: f32 - Engine: CPU", Lower Results Are Better "a", "b",0.403892,0.40199,0.403068 "c", "d", "e", "Blender 3.5 - Blend File: BMW27 - Compute: CPU-Only", Lower Results Are Better "a", "b",14.6,14.06,13.91,14.21 "c", "d", "e", "TensorFlow 2.12 - Device: CPU - Batch Size: 16 - Model: ResNet-50", Higher Results Are Better "a", "b",65.21,63.87,63.86 "c", "d", "e", "oneDNN 3.1 - Harness: Deconvolution Batch shapes_3d - Data Type: f32 - Engine: CPU", Lower Results Are Better "a", "b",0.715065,0.724259,0.716914 "c", "d", "e", "srsRAN Project 23.3 - Test: Downlink Processor Benchmark", Higher Results Are Better "a", "b",325.8,320.2,326.7 "c", "d", "e", "nginx 1.23.2 - Connections: 500", Higher Results Are Better "a", "b",248737.72,245372.61,244358.01 "c", "d", "e", "TensorFlow 2.12 - Device: CPU - Batch Size: 64 - Model: AlexNet", Higher Results Are Better "a", "b",751.71,742.91,731 "c", "d", "e", "TensorFlow 2.12 - Device: CPU - Batch Size: 512 - Model: ResNet-50", Higher Results Are Better "a", "b",131.84,136.2,134.99 "c", "d", "e", "TensorFlow 2.12 - Device: CPU - Batch Size: 512 - Model: AlexNet", Higher Results Are Better "a", "b",1231.7,1236.58,1227.28 "c", "d", "e", "TensorFlow 2.12 - Device: CPU - Batch Size: 256 - Model: GoogLeNet", Higher Results Are Better "a", "b",436.01,447.48,445.31 "c", "d", "e", "Blender 3.5 - Blend File: Classroom - Compute: CPU-Only", Lower Results Are Better "a", "b",37.25,36.32,36.41 "c", "d", "e", "VVenC 1.8 - Video Input: Bosphorus 4K - Video Preset: Faster", Higher Results Are Better "a", "b",9.72,9.658,10.247,10.152,10.406,10.329,9.96,10.03,10.38,9.789,9.953,10.059,10.035 "c", "d", "e", "Blender 3.5 - Blend File: Barbershop - Compute: CPU-Only", Lower Results Are Better "a", "b",149.34,147.02,146.83 "c", "d", "e", "Apache HTTP Server 2.4.56 - Concurrent Requests: 1000", Higher Results Are Better "a", "b", "c", "d", "e", "Apache HTTP Server 2.4.56 - Concurrent Requests: 200", Higher Results Are Better "a", "b", "c", "d", "e", "Apache HTTP Server 2.4.56 - Concurrent Requests: 100", Higher Results Are Better "a", "b", "c", "d", "e", "nginx 1.23.2 - Connections: 1000", Higher Results Are Better "a", "b", "c", "d", "e", "nginx 1.23.2 - Connections: 200", Higher Results Are Better "a", "b", "c", "d", "e", "nginx 1.23.2 - Connections: 100", Higher Results Are Better "a", "b", "c", "d", "e", "oneDNN 3.1 - Harness: Recurrent Neural Network Inference - Data Type: u8s8f32 - Engine: CPU", Lower Results Are Better "a", "b",940.927,791.232,794.803,776.787,838.313,777.455,817.903,876.216,816.274,939.344,864.716,867.868,791.592,824.329,767.305 "c", "d", "e", "oneDNN 3.1 - Harness: Recurrent Neural Network Training - Data Type: u8s8f32 - Engine: CPU", Lower Results Are Better "a", "b",1256.75,1205.16,1321.51,1234.52,1187.14,1140.44,1067.49,1155.98,1304.61,1224.03,1279.73,1163,1381.13,1338.67 "c", "d", "e", "oneDNN 3.1 - Harness: Recurrent Neural Network Training - Data Type: f32 - Engine: CPU", Lower Results Are Better "a", "b",1235.94,1191.34,1274.38,1157.14,1152.88,1250.84,814.78,1317.46,1050.86,1234.15,1115.02,1074.4 "c", "d", "e", "oneDNN 3.1 - Harness: Convolution Batch Shapes Auto - Data Type: u8s8f32 - Engine: CPU", Lower Results Are Better "a", "b",0.278295,0.40302,0.25274,0.24172,0.374871,0.261977,0.433364,0.238945,0.375465,0.246195,0.285,0.412183,0.255893,0.400146,0.256587 "c", "d", "e", "oneDNN 3.1 - Harness: IP Shapes 1D - Data Type: bf16bf16bf16 - Engine: CPU", Lower Results Are Better "a", "b",5.38854,5.81173,5.61749,5.57014,5.82102,5.72321,5.69408,5.26914,5.20916,5.00731,5.54744,5.26065,5.03955,5.06862,4.78197 "c", "d", "e", "oneDNN 3.1 - Harness: IP Shapes 1D - Data Type: u8s8f32 - Engine: CPU", Lower Results Are Better "a", "b",5.04535,4.73358,5.11201,3.90808,4.35986,5.0957,4.04619,5.04832,3.06944,5.07871,5.03069,4.96947 "c", "d", "e", "oneDNN 3.1 - Harness: IP Shapes 1D - Data Type: f32 - Engine: CPU", Lower Results Are Better "a", "b",3.33553,3.45206,2.40329,2.27942,2.63989,1.95257,3.56932,3.62278,3.05716,2.78374,3.7906,3.79759,3.54502,1.82277,3.69831 "c", "d", "e",