9900k-wiesn

Intel Core i9-9900K testing with a ASRock Z390M Pro4 (P4.20 BIOS) and Intel UHD 630 3GB 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 2009261-FI-9900KWIES08
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BLAS (Basic Linear Algebra Sub-Routine) Tests 2 Tests
C/C++ Compiler Tests 2 Tests
CPU Massive 2 Tests
Creator Workloads 5 Tests
Database Test Suite 2 Tests
Fortran Tests 3 Tests
HPC - High Performance Computing 10 Tests
Imaging 3 Tests
Machine Learning 6 Tests
Molecular Dynamics 2 Tests
MPI Benchmarks 4 Tests
Multi-Core 2 Tests
NVIDIA GPU Compute 3 Tests
OpenMPI Tests 4 Tests
Python Tests 3 Tests
Scientific Computing 4 Tests
Server 2 Tests
Single-Threaded 2 Tests
Vulkan Compute 2 Tests

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1
September 26 2020
  2 Hours, 4 Minutes
2
September 26 2020
  8 Hours, 16 Minutes
3
September 26 2020
  2 Hours, 2 Minutes
3a
September 26 2020
  7 Hours, 44 Minutes
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9900k-wiesn , "AI Benchmark Alpha 0.1.2 - Device Inference Score", Higher Results Are Better "2", "3a", "AI Benchmark Alpha 0.1.2 - Device Training Score", Higher Results Are Better "2", "3a", "AI Benchmark Alpha 0.1.2 - Device AI Score", Higher Results Are Better "2", "3a", "AOM AV1 2.0 - Encoder Mode: Speed 0 Two-Pass", Higher Results Are Better "1",0.32,0.33,0.33 "3a",0.33,0.33,0.33 "Apache CouchDB 3.1.1 - Bulk Size: 100 - Inserts: 1000 - Rounds: 24", Lower Results Are Better "2",74.216,73.95,79.534,77,75.28,74.513 "3a",72.759,73.041,74.802 "dcraw - RAW To PPM Image Conversion", Lower Results Are Better "2",33.509,33.181,33.181 "3a",33.375,33.247,33.211 "eSpeak-NG Speech Engine 20200907 - Text-To-Speech Synthesis", Lower Results Are Better "2",24.003,25.926,24.984,24.96,25.101 "3a",24.679,25.083,25.144,25.075 "GLmark2 2020.04 - Resolution: 1920 x 1080", Higher Results Are Better "1", "2", "3", "3a", "GPAW 20.1 - Input: Carbon Nanotube", Lower Results Are Better "2",342.349,342.385,344.277 "3a",343.548,342.616,344.776 "Incompact3D 2020-09-17 - Input: Cylinder", Lower Results Are Better "1",366.835052,368.060303,368.783234 "2",362.486328,369.256775,369.374695 "3",362.098969,367.261993,368.501312 "3a",360.535522,369.090118,367.43042 "InfluxDB 1.8.2 - Concurrent Streams: 4 - Batch Size: 10000 - Tags: 2,5000,1 - Points Per Series: 10000", Higher Results Are Better "2",1633977.4,1613248.5,1621925.6 "3a",1627088.1,1624475.9,1620401.4 "InfluxDB 1.8.2 - Concurrent Streams: 64 - Batch Size: 10000 - Tags: 2,5000,1 - Points Per Series: 10000", Higher Results Are Better "2",1645331.6,1631208.8,1616473.6 "3a",1632290.1,1640302.5,1629037.7 "InfluxDB 1.8.2 - Concurrent Streams: 1024 - Batch Size: 10000 - Tags: 2,5000,1 - Points Per Series: 10000", Higher Results Are Better "2",1646619.1,1624992.1,1634126.5 "3a",1646222.6,1636832.1,1624662.3 "LAMMPS Molecular Dynamics Simulator 24Aug2020 - Model: 20k Atoms", Higher Results Are Better "1",6.09,6.163,6.15 "2",6.166,6.161,6.119 "3",6.145,6.112,6.138 "3a",6.107,6.181,6.142 "LAMMPS Molecular Dynamics Simulator 24Aug2020 - Model: Rhodopsin Protein", Higher Results Are Better "1",6.888,6.849,6.814 "2",6.851,6.852,6.865 "3",6.231,6.818,6.852,6.94,6.886,6.896,6.893,6.868,6.839,6.867,6.9,6.916,6.852,6.881 "3a",6.851,6.883,6.814 "LeelaChessZero 0.26 - Backend: BLAS", Higher Results Are Better "2",857,870,854 "3a",869,850,858 "LeelaChessZero 0.26 - Backend: Eigen", Higher Results Are Better "2",791,783,783 "3a",788,784,780 "LeelaChessZero 0.26 - Backend: OpenCL", Higher Results Are Better "2",330,323,328 "3a",319,327,316 "LibRaw 0.20 - Post-Processing Benchmark", Higher Results Are Better "1",38.66,38.81,38.99 "2",39.21,39.22,39.17 "3",39.27,39.06,39.31 "3a",38.85,38.88,39.25 "Mobile Neural Network 2020-09-17 - Model: SqueezeNetV1.0", Lower Results Are Better "2",5.778,5.794,5.812 "3a",5.745,5.835,5.87 "Mobile Neural Network 2020-09-17 - Model: resnet-v2-50", Lower Results Are Better "2",34.597,34.721,34.585 "3a",34.683,34.671,35.085 "Mobile Neural Network 2020-09-17 - Model: MobileNetV2_224", Lower Results Are Better "2",2.989,2.941,2.967 "3a",2.99,2.938,2.972 "Mobile Neural Network 2020-09-17 - Model: mobilenet-v1-1.0", Lower Results Are Better "2",6.328,6.358,6.364 "3a",6.332,6.315,6.313 "Mobile Neural Network 2020-09-17 - Model: inception-v3", Lower Results Are Better "2",37.395,38,37.718 "3a",37.641,37.631,38.352 "Monte Carlo Simulations of Ionised Nebulae 2019-03-24 - Input: Dust 2D tau100.0", Lower Results Are Better "1",191,193,192 "2", "3",190,192,192 "3a", "NCNN 20200916 - Target: CPU - Model: squeezenet", Lower Results Are Better "2",15.64,15.4,15.47 "3a",15.34,15.65,15.36 "NCNN 20200916 - Target: CPU - Model: mobilenet", Lower Results Are Better "2",17.9,17.72,17.72 "3a",17.73,17.96,17.68 "NCNN 20200916 - Target: CPU-v2-v2 - Model: mobilenet-v2", Lower Results Are Better "2",4.99,4.98,4.99 "3a",4.96,4.99,5 "NCNN 20200916 - Target: CPU-v3-v3 - Model: mobilenet-v3", Lower Results Are Better "2",3.97,3.99,3.99 "3a",3.95,3.99,4 "NCNN 20200916 - Target: CPU - Model: shufflenet-v2", Lower Results Are Better "2",2.88,2.92,2.9 "3a",2.86,2.88,2.88 "NCNN 20200916 - Target: CPU - Model: mnasnet", Lower Results Are Better "2",3.78,3.77,3.79 "3a",3.74,3.77,3.78 "NCNN 20200916 - Target: CPU - Model: efficientnet-b0", Lower Results Are Better "2",6.22,6.23,6.22 "3a",6.21,6.4,6.23 "NCNN 20200916 - Target: CPU - Model: blazeface", Lower Results Are Better "2",1.49,1.57,1.57 "3a",1.47,1.75,1.57 "NCNN 20200916 - Target: CPU - Model: googlenet", Lower Results Are Better "2",15.44,15.27,15.3 "3a",14.41,16.3,15.27 "NCNN 20200916 - Target: CPU - Model: vgg16", Lower Results Are Better "2",66.24,65.9,65.86 "3a",66,66.3,65.91 "NCNN 20200916 - Target: CPU - Model: resnet18", Lower Results Are Better "2",15.07,14.7,14.63 "3a",14,15.48,14.51 "NCNN 20200916 - Target: CPU - Model: alexnet", Lower Results Are Better "2",15.75,15.84,15.81 "3a",15.54,15.84,15.82 "NCNN 20200916 - Target: CPU - Model: resnet50", Lower Results Are Better "2",27.97,27.05,26.99 "3a",26.34,27.84,26.84 "NCNN 20200916 - Target: CPU - Model: yolov4-tiny", Lower Results Are Better "2",26.59,26.34,26.3 "3a",26.38,26.64,26.3 "NCNN 20200916 - Target: Vulkan GPU - Model: squeezenet", Lower Results Are Better "2",39.54,39.49,39.53 "3a",39.53,39.69,39.5 "NCNN 20200916 - Target: Vulkan GPU - Model: mobilenet", Lower Results Are Better "2",34.76,34.77,34.75 "3a",34.13,34.63,34.77 "NCNN 20200916 - Target: Vulkan GPU-v2-v2 - Model: mobilenet-v2", Lower Results Are Better "2",11.3,11.3,11.29 "3a",11.28,11.29,11.31 "NCNN 20200916 - Target: Vulkan GPU-v3-v3 - Model: mobilenet-v3", Lower Results Are Better "2",12.65,12.64,12.63 "3a",12.65,12.62,12.64 "NCNN 20200916 - Target: Vulkan GPU - Model: shufflenet-v2", Lower Results Are Better "2",7.95,7.99,7.91 "3a",8,7.89,7.96 "NCNN 20200916 - Target: Vulkan GPU - Model: mnasnet", Lower Results Are Better "2",11.78,11.79,11.76 "3a",11.78,11.78,11.76 "NCNN 20200916 - Target: Vulkan GPU - Model: efficientnet-b0", Lower Results Are Better "2",23.62,23.62,23.57 "3a",23.6,23.57,23.57 "NCNN 20200916 - Target: Vulkan GPU - Model: blazeface", Lower Results Are Better "2",1.96,2.02,1.95 "3a",1.95,1.94,1.94 "NCNN 20200916 - Target: Vulkan GPU - Model: googlenet", Lower Results Are Better "2",32.36,32.39,32.31 "3a",32.38,32.3,32.34 "NCNN 20200916 - Target: Vulkan GPU - Model: vgg16", Lower Results Are Better "2",185.26,185.01,185.06 "3a",184.84,184.97,184.79 "NCNN 20200916 - Target: Vulkan GPU - Model: resnet18", Lower Results Are Better "2",28.51,28.52,28.48 "3a",28.54,28.48,28.52 "NCNN 20200916 - Target: Vulkan GPU - Model: alexnet", Lower Results Are Better "2",46.69,46.67,46.96 "3a",46.98,44.16,46.92 "NCNN 20200916 - Target: Vulkan GPU - Model: resnet50", Lower Results Are Better "2",68.69,68.72,68.65 "3a",68.71,68.7,68.71 "NCNN 20200916 - Target: Vulkan GPU - Model: yolov4-tiny", Lower Results Are Better "2",71.1,70.94,70.9 "3a",71.08,69.89,70.99 "OpenCV 4.4 - Test: Features 2D", Lower Results Are Better "2",119277,110112,110449,107014,107713,108682,108604,109510,107197,107193,108413,115570,111234,110512,108149 "3a",112012,109451,109755 "OpenCV 4.4 - Test: Object Detection", Lower Results Are Better "2",39192,39740,37401,37537,36849,37372,37801 "3a",36956,40710,36759,37834,40520,31968,36622,36220,39749,41518,38015,35204,39274,37205,31453 "OpenCV 4.4 - Test: DNN - Deep Neural Network", Lower Results Are Better "2",128352,17430,17128,17651,17417,18339,16769,17725,17872,17401,17759,17579,17224,17962,17791 "3a",17759,17443,17999 "RealSR-NCNN 20200818 - Scale: 4x - TAA: No", Lower Results Are Better "1",253.472,253.428,253.555 "2",253.407,253.379,253.461 "3",253.301,253.365,253.411 "3a",253.337,253.485,253.51 "System GZIP Decompression - ", Lower Results Are Better "2",2.602,2.552,2.545 "3a",2.605,2.552,2.546 "TNN 0.2.3 - Target: CPU - Model: MobileNet v2", Lower Results Are Better "2",285.061,285.426,284.603 "3a",287.583,287.24,290.128 "TNN 0.2.3 - Target: CPU - Model: SqueezeNet v1.1", Lower Results Are Better "2",268.139,268.083,268.055 "3a",268.078,268.254,268.333 "WebP Image Encode 1.1 - Encode Settings: Default", Lower Results Are Better "1",1.35,1.352,1.396 "2",1.349,1.365,1.355 "3",1.349,1.35,1.351 "3a",1.349,1.393,1.35 "WebP Image Encode 1.1 - Encode Settings: Quality 100", Lower Results Are Better "1",2.113,2.111,2.114 "2",2.109,2.11,2.11 "3",2.109,2.11,2.109 "3a",2.109,2.111,2.112 "WebP Image Encode 1.1 - Encode Settings: Quality 100, Lossless", Lower Results Are Better "1",15.538,15.548,15.525 "2",15.558,15.562,15.545 "3",15.247,15.244,15.277 "3a",15.419,15.417,15.432 "WebP Image Encode 1.1 - Encode Settings: Quality 100, Highest Compression", Lower Results Are Better "1",6.311,6.322,6.332 "2",6.345,6.317,6.312 "3",6.301,6.313,6.424 "3a",6.325,6.34,6.313 "WebP Image Encode 1.1 - Encode Settings: Quality 100, Lossless, Highest Compression", Lower Results Are Better "1",33.009,33.014,33.014 "2",32.995,33.072,33.053 "3",32.628,33.1,33.09 "3a",32.844,32.533,32.573