Xeon Gold 6226R December

Intel Xeon Gold 6226R testing with a Supermicro X11SPL-F v1.02 (3.1 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 2012200-HA-XEONGOLD615
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Audio Encoding 2 Tests
Bioinformatics 2 Tests
Timed Code Compilation 3 Tests
C/C++ Compiler Tests 5 Tests
CPU Massive 5 Tests
Creator Workloads 4 Tests
Encoding 2 Tests
HPC - High Performance Computing 4 Tests
Machine Learning 2 Tests
Multi-Core 5 Tests
Programmer / Developer System Benchmarks 6 Tests
Scientific Computing 2 Tests
Server 3 Tests

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December 20 2020
  2 Hours, 20 Minutes
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December 20 2020
  2 Hours, 17 Minutes
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December 20 2020
  2 Hours
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Xeon Gold 6226R December Intel Xeon Gold 6226R testing with a Supermicro X11SPL-F v1.02 (3.1 BIOS) and llvmpipe on Ubuntu 20.04 via the Phoronix Test Suite. ,,"1","2","3" Processor,,Intel Xeon Gold 6226R @ 3.90GHz (16 Cores / 32 Threads),Intel Xeon Gold 6226R @ 3.90GHz (16 Cores / 32 Threads),Intel Xeon Gold 6226R @ 3.90GHz (16 Cores / 32 Threads) Motherboard,,Supermicro X11SPL-F v1.02 (3.1 BIOS),Supermicro X11SPL-F v1.02 (3.1 BIOS),Supermicro X11SPL-F v1.02 (3.1 BIOS) Chipset,,Intel Sky Lake-E DMI3 Registers,Intel Sky Lake-E DMI3 Registers,Intel Sky Lake-E DMI3 Registers Memory,,188GB,188GB,188GB Disk,,3841GB Micron_9300_MTFDHAL3T8TDP,3841GB Micron_9300_MTFDHAL3T8TDP,3841GB Micron_9300_MTFDHAL3T8TDP Graphics,,llvmpipe,llvmpipe,llvmpipe Monitor,,VE228,VE228,VE228 Network,,2 x Intel I210,2 x Intel I210,2 x Intel I210 OS,,Ubuntu 20.04,Ubuntu 20.04,Ubuntu 20.04 Kernel,,5.9.0-050900rc6daily20200921-generic (x86_64) 20200920,5.9.0-050900rc6daily20200921-generic (x86_64) 20200920,5.9.0-050900rc6daily20200921-generic (x86_64) 20200920 Desktop,,GNOME Shell 3.36.4,GNOME Shell 3.36.4,GNOME Shell 3.36.4 Display Server,,X Server 1.20.8,X Server 1.20.8,X Server 1.20.8 Display Driver,,modesetting 1.20.8,modesetting 1.20.8,modesetting 1.20.8 OpenGL,,3.3 Mesa 20.0.8 (LLVM 10.0.0 256 bits),3.3 Mesa 20.0.8 (LLVM 10.0.0 256 bits),3.3 Mesa 20.0.8 (LLVM 10.0.0 256 bits) Compiler,,GCC 9.3.0,GCC 9.3.0,GCC 9.3.0 File-System,,ext4,ext4,ext4 Screen Resolution,,1920x1080,1920x1080,1920x1080 ,,"1","2","3" "simdjson - Throughput Test: Kostya (GB/s)",HIB,0.56,0.56,0.56 "simdjson - Throughput Test: LargeRandom (GB/s)",HIB,0.39,0.39,0.39 "simdjson - Throughput Test: PartialTweets (GB/s)",HIB,0.57,0.57,0.57 "simdjson - Throughput Test: DistinctUserID (GB/s)",HIB,0.58,0.58,0.58 "Coremark - CoreMark Size 666 - Iterations Per Second (Iterations/Sec)",HIB,537952.810837,535255.625888,534883.155085 "Node.js V8 Web Tooling Benchmark - (runs/s)",HIB,10.78,10.69,10.68 "CLOMP - Static OMP Speedup (Speedup)",HIB,26.8,26.2,26.5 "BRL-CAD - VGR Performance Metric (VGR Performance Metric)",HIB,164354,163713, "oneDNN - Harness: IP Shapes 1D - Data Type: f32 - Engine: CPU (ms)",LIB,2.35358,2.35038,2.34990 "oneDNN - Harness: IP Shapes 3D - Data Type: f32 - Engine: CPU (ms)",LIB,3.14816,3.13707,3.15835 "oneDNN - Harness: IP Shapes 1D - Data Type: u8s8f32 - Engine: CPU (ms)",LIB,0.496245,0.491459,0.495733 "oneDNN - Harness: IP Shapes 3D - Data Type: u8s8f32 - Engine: CPU (ms)",LIB,1.24491,1.24781,1.24380 "oneDNN - Harness: IP Shapes 1D - Data Type: bf16bf16bf16 - Engine: CPU (ms)",LIB,5.61346,5.60704,5.60477 "oneDNN - Harness: IP Shapes 3D - Data Type: bf16bf16bf16 - Engine: CPU (ms)",LIB,2.59610,2.58806,2.61350 "oneDNN - Harness: Convolution Batch Shapes Auto - Data Type: f32 - Engine: CPU (ms)",LIB,4.34336,4.34082,4.35080 "oneDNN - Harness: Deconvolution Batch shapes_1d - Data Type: f32 - Engine: CPU (ms)",LIB,2.75497,2.76210,2.75619 "oneDNN - Harness: Deconvolution Batch shapes_3d - Data Type: f32 - Engine: CPU (ms)",LIB,3.21126,3.20825,3.21278 "oneDNN - Harness: Convolution Batch Shapes Auto - Data Type: u8s8f32 - Engine: CPU (ms)",LIB,4.16656,4.16237,4.17445 "oneDNN - Harness: Deconvolution Batch shapes_1d - Data Type: u8s8f32 - Engine: CPU (ms)",LIB,0.526692,0.527252,0.526437 "oneDNN - Harness: Deconvolution Batch shapes_3d - Data Type: u8s8f32 - Engine: CPU (ms)",LIB,0.867040,0.860663,0.862856 "oneDNN - Harness: Recurrent Neural Network Training - Data Type: f32 - Engine: CPU (ms)",LIB,1643.22,1645.08,1647.12 "oneDNN - Harness: Recurrent Neural Network Inference - Data Type: f32 - Engine: CPU (ms)",LIB,922.992,923.536,922.270 "oneDNN - Harness: Recurrent Neural Network Training - Data Type: u8s8f32 - Engine: CPU (ms)",LIB,1643.59,1645.64,1645.91 "oneDNN - Harness: Convolution Batch Shapes Auto - Data Type: bf16bf16bf16 - Engine: CPU (ms)",LIB,9.42174,9.42301,9.42277 "oneDNN - Harness: Deconvolution Batch shapes_1d - Data Type: bf16bf16bf16 - Engine: CPU (ms)",LIB,11.2912,11.2891,11.3162 "oneDNN - Harness: Deconvolution Batch shapes_3d - Data Type: bf16bf16bf16 - Engine: CPU (ms)",LIB,12.5274,12.5418,12.5335 "oneDNN - Harness: Recurrent Neural Network Inference - Data Type: u8s8f32 - Engine: CPU (ms)",LIB,922.874,923.369,923.336 "oneDNN - Harness: Matrix Multiply Batch Shapes Transformer - Data Type: f32 - Engine: CPU (ms)",LIB,0.974624,0.973874,0.977073 "oneDNN - Harness: Recurrent Neural Network Training - Data Type: bf16bf16bf16 - Engine: CPU (ms)",LIB,1645.61,1643.67,1644.83 "oneDNN - Harness: Recurrent Neural Network Inference - Data Type: bf16bf16bf16 - Engine: CPU (ms)",LIB,921.674,923.438,920.863 "oneDNN - Harness: Matrix Multiply Batch Shapes Transformer - Data Type: u8s8f32 - Engine: CPU (ms)",LIB,0.486440,0.477951,0.479216 "oneDNN - Harness: Matrix Multiply Batch Shapes Transformer - Data Type: bf16bf16bf16 - Engine: CPU (ms)",LIB,2.05419,2.05772,2.05675 "NCNN - Target: CPU - Model: mobilenet (ms)",LIB,17.77,16.96,17.73 "NCNN - Target: CPU-v2-v2 - Model: mobilenet-v2 (ms)",LIB,6.07,5.96,5.89 "NCNN - Target: CPU-v3-v3 - Model: mobilenet-v3 (ms)",LIB,5.21,5.14,5.07 "NCNN - Target: CPU - Model: shufflenet-v2 (ms)",LIB,5.94,5.97,6.01 "NCNN - Target: CPU - Model: mnasnet (ms)",LIB,5.56,5.37,5.34 "NCNN - Target: CPU - Model: efficientnet-b0 (ms)",LIB,7.70,7.26,7.20 "NCNN - Target: CPU - Model: blazeface (ms)",LIB,2.93,2.88,2.90 "NCNN - Target: CPU - Model: googlenet (ms)",LIB,14.56,12.99,13.09 "NCNN - Target: CPU - Model: vgg16 (ms)",LIB,29.65,28.04,29.24 "NCNN - Target: CPU - Model: resnet18 (ms)",LIB,10.58,9.41,9.49 "NCNN - Target: CPU - Model: alexnet (ms)",LIB,8.07,6.73,6.99 "NCNN - Target: CPU - Model: resnet50 (ms)",LIB,20.27,18.93,20.38 "NCNN - Target: CPU - Model: yolov4-tiny (ms)",LIB,24.72,24.40,25.22 "NCNN - Target: CPU - Model: squeezenet_ssd (ms)",LIB,16.73,16.45,16.94 "NCNN - Target: CPU - Model: regnety_400m (ms)",LIB,27.19,27.13,27.41 "Timed HMMer Search - Pfam Database Search (sec)",LIB,174.227,174.169,174.447 "Timed MAFFT Alignment - Multiple Sequence Alignment - LSU RNA (sec)",LIB,10.637,10.590,10.549 "Timed FFmpeg Compilation - Time To Compile (sec)",LIB,43.497,43.236,43.454 "Build2 - Time To Compile (sec)",LIB,95.580,95.686,95.528 "Timed Eigen Compilation - Time To Compile (sec)",LIB,85.527,85.551,85.784 "Monkey Audio Encoding - WAV To APE (sec)",LIB,17.528,17.535,17.543 "SQLite Speedtest - Timed Time - Size 1,000 (sec)",LIB,65.363,65.852,65.594 "WavPack Audio Encoding - WAV To WavPack (sec)",LIB,16.731,16.753,16.779