AMD Ryzen 7 1700 Eight-Core testing with a MSI B350 TOMAHAWK (MS-7A34) v1.0 (1.H0 BIOS) and AMD Radeon RX 470/480/570/570X/580/580X/590 8GB on Ubuntu 19.10 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 2009269-FI-3300XNNMO11
3300X NN + More,
"MPV - Video Input: Big Buck Bunny Sunflower 4K - Decode: Software Only",
Higher Results Are Better
"1",557.9044678445,559.19653028529,559.66606104388
"2",557.96083219488,559.56661991012,560.832443248
"4",556.98344365193,558.31594546034,559.01998417253
"MPV - Video Input: Big Buck Bunny Sunflower 1080p - Decode: Software Only",
Higher Results Are Better
"1",1494.9182398409,1504.6140330522,1490.2408834547
"2",1492.0380032518,1498.906819444,1502.3966603552
"4",1491.8141738527,1491.511731939,1489.2126455015
"LibRaw 0.20 - Post-Processing Benchmark",
Higher Results Are Better
"1",24.13,24.27,24.33
"2",24.28,24.21,24.39
"4",24.2,24.12,24.25
"LAMMPS Molecular Dynamics Simulator 24Aug2020 - Model: 20k Atoms",
Higher Results Are Better
"1",4.577,4.61,4.526
"2",4.555,4.533,4.584
"4",4.547,4.12,4.58,4.571,4.497,4.554,4.584,4.563,4.57
"LAMMPS Molecular Dynamics Simulator 24Aug2020 - Model: Rhodopsin Protein",
Higher Results Are Better
"1",4.468,4.307,4.355
"2",4.015,4.434,4.573,4.579,4.443,4.628,4.427,4.409,4.302,3.861,4.556,4.439,4.58,4.609,3.856
"4",4.539,4.511,4.421
"GLmark2 2020.04 - Resolution: 1280 x 1024",
Higher Results Are Better
"1",
"2",
"4",
"GLmark2 2020.04 - Resolution: 1920 x 1080",
Higher Results Are Better
"1",
"2",
"4",
"Kripke 1.2.4 - ",
Higher Results Are Better
"1",2233615,2314842
"InfluxDB 1.8.2 - Concurrent Streams: 4 - Batch Size: 10000 - Tags: 2,5000,1 - Points Per Series: 10000",
Higher Results Are Better
"1",707905.7,511740.8,473942.5,599272.6,642535,564363,521548.9,573349.6,584322.5,615429.2,522900.6,537730
"2",727562.3,469974.5,476034.1,557897.8,479614,516167.5,602199.9,531348.2,475988.3,522604.6,523199.6,456327.7
"4",684103.2,455606.1,538811.8,464541.4,485763.4,462542.8,533587.8,453687.6,511181.8,506491.4,490581.8,500169.6
"InfluxDB 1.8.2 - Concurrent Streams: 64 - Batch Size: 10000 - Tags: 2,5000,1 - Points Per Series: 10000",
Higher Results Are Better
"1",908877.1,884347.8,899415.4
"2",954015.7,863342.8,845169,807592.2,823008.3,860560.3,846837.7,770958.1,792381.1,905213.8,873838.4,838893.7
"4",872035.6,794778.2,717015.8,792513.6,768575.2,764947.3,740279.6,718444,797319.3,745880,712381.4,746207
"InfluxDB 1.8.2 - Concurrent Streams: 1024 - Batch Size: 10000 - Tags: 2,5000,1 - Points Per Series: 10000",
Higher Results Are Better
"1",962933.3,971598.9,957223
"2",973285.6,944247.7,887085.8,846610.7,932387.5,947375.8,950177.5,950658.9,938961.4,948344.2,960595.1,965173.7,444050
"WebP Image Encode 1.1 - Encode Settings: Default",
Lower Results Are Better
"1",1.965,1.979,1.985
"2",1.968,1.954,2.002
"4",1.947,1.974,1.981
"WebP Image Encode 1.1 - Encode Settings: Quality 100",
Lower Results Are Better
"1",2.978,2.936,2.926
"2",2.977,2.966,2.963
"4",2.964,2.942,2.924
"WebP Image Encode 1.1 - Encode Settings: Quality 100, Lossless",
Lower Results Are Better
"1",23.353,23.93,23.923
"2",23.576,23.41,24.013
"4",23.341,23.482,23.496
"WebP Image Encode 1.1 - Encode Settings: Quality 100, Highest Compression",
Lower Results Are Better
"1",9.444,9.514,9.411
"2",9.491,9.449,9.402
"4",9.419,9.473,9.442
"WebP Image Encode 1.1 - Encode Settings: Quality 100, Lossless, Highest Compression",
Lower Results Are Better
"1",49.058,49.831,50.03
"2",50.105,50.191,50.644
"4",50.742,49.972,51.176
"Mobile Neural Network 2020-09-17 - Model: SqueezeNetV1.0",
Lower Results Are Better
"1",12.681,12.382,12.434
"2",12.173,12.529,12.125
"4",12.443,12.546,12.366
"Mobile Neural Network 2020-09-17 - Model: resnet-v2-50",
Lower Results Are Better
"1",71.273,70.783,69.745
"2",69.539,70.015,70.039
"4",69.464,69.561,70.568
"Mobile Neural Network 2020-09-17 - Model: MobileNetV2_224",
Lower Results Are Better
"1",6.875,6.816,6.837
"2",6.996,6.784,6.839
"4",6.9,6.922,6.998
"Mobile Neural Network 2020-09-17 - Model: mobilenet-v1-1.0",
Lower Results Are Better
"1",13.402,13.376,13.381
"2",13.446,13.407,13.432
"4",13.424,13.195,13.475
"Mobile Neural Network 2020-09-17 - Model: inception-v3",
Lower Results Are Better
"1",77.623,73.518,74.652
"2",73.996,73.77,73.618
"4",74.578,73.039,74.286
"NCNN 20200916 - Target: CPU - Model: squeezenet",
Lower Results Are Better
"1",31.01,30.66,30.57
"2",30.52,31.37,30.71
"4",30.59,31.08,30.05
"NCNN 20200916 - Target: CPU - Model: mobilenet",
Lower Results Are Better
"1",37.17,37.87,37.33
"2",37.17,38.14,38.77
"4",37.37,37.8,37.46
"NCNN 20200916 - Target: CPU-v2-v2 - Model: mobilenet-v2",
Lower Results Are Better
"1",10.83,10.9,10.58
"2",10.48,10.01,11.81
"4",11.13,10.49,11.66
"NCNN 20200916 - Target: CPU-v3-v3 - Model: mobilenet-v3",
Lower Results Are Better
"1",9.4,9.38,9.25
"2",9.91,9.56,9.53
"4",9.12,9.29,10.31
"NCNN 20200916 - Target: CPU - Model: shufflenet-v2",
Lower Results Are Better
"1",7.41,7.53,7.35
"2",7.26,7.43,7.45
"4",7.23,7.41,7.47
"NCNN 20200916 - Target: CPU - Model: mnasnet",
Lower Results Are Better
"1",10.25,9.82,9.66
"2",9.34,10.2,9.54
"4",10.2,9.45,10.13
"NCNN 20200916 - Target: CPU - Model: efficientnet-b0",
Lower Results Are Better
"1",14.79,14.1,13.46
"2",14.68,14.46,13.23
"4",14.02,13.69,13.54
"NCNN 20200916 - Target: CPU - Model: blazeface",
Lower Results Are Better
"1",2.77,2.69,3.13
"2",2.78,2.81,2.64
"4",3.09,3.33,3.44
"NCNN 20200916 - Target: CPU - Model: googlenet",
Lower Results Are Better
"1",31.55,30.46,31.22
"2",31.41,25.79,29.94
"4",26.12,30.65,30.29
"NCNN 20200916 - Target: CPU - Model: vgg16",
Lower Results Are Better
"1",113.67,111.47,110.61
"2",110.62,111.54,111.49
"4",110.71,112.51,109.12
"NCNN 20200916 - Target: CPU - Model: resnet18",
Lower Results Are Better
"1",24.51,24.85,22.91
"2",24.67,24.29,21.76
"4",26.3,24.36,24.29
"NCNN 20200916 - Target: CPU - Model: alexnet",
Lower Results Are Better
"1",28.73,29.13,29.38
"2",31.1,29.26,28.38
"4",28.97,29.77,30.45
"NCNN 20200916 - Target: CPU - Model: resnet50",
Lower Results Are Better
"1",56.56,56.09,56.02
"2",53.75,55.22,49.31
"4",56.32,56.37,55.95
"NCNN 20200916 - Target: CPU - Model: yolov4-tiny",
Lower Results Are Better
"1",50.85,50.41,50.37
"2",50.34,50.32,50.72
"4",50.68,50.49,50.15
"NCNN 20200916 - Target: Vulkan GPU - Model: squeezenet",
Lower Results Are Better
"1",18.85,18.92,18.82
"2",18.81,18.84,18.85
"4",18.85,18.85,18.88
"NCNN 20200916 - Target: Vulkan GPU - Model: mobilenet",
Lower Results Are Better
"1",17.88,17.9,17.81
"2",18.03,17.81,17.68
"4",18.2,17.76,17.66
"NCNN 20200916 - Target: Vulkan GPU-v2-v2 - Model: mobilenet-v2",
Lower Results Are Better
"1",8.14,8.06,8.16
"2",8.12,8.12,8.15
"4",8.12,8.08,8.1
"NCNN 20200916 - Target: Vulkan GPU-v3-v3 - Model: mobilenet-v3",
Lower Results Are Better
"1",9.84,9.71,9.72
"2",9.76,9.75,9.77
"4",9.81,9.83,9.69
"NCNN 20200916 - Target: Vulkan GPU - Model: shufflenet-v2",
Lower Results Are Better
"1",5.7,5.66,5.69
"2",5.63,5.68,5.64
"4",5.64,5.66,5.7
"NCNN 20200916 - Target: Vulkan GPU - Model: mnasnet",
Lower Results Are Better
"1",9.05,8.98,8.93
"2",8.98,9,8.9
"4",8.98,8.97,8.94
"NCNN 20200916 - Target: Vulkan GPU - Model: efficientnet-b0",
Lower Results Are Better
"1",19.15,19.44,19.4
"2",19.34,19.09,19.12
"4",19.52,19.21,19.34
"NCNN 20200916 - Target: Vulkan GPU - Model: blazeface",
Lower Results Are Better
"1",1.76,1.8,1.78
"2",1.72,1.72,1.76
"4",1.71,1.76,1.74
"NCNN 20200916 - Target: Vulkan GPU - Model: googlenet",
Lower Results Are Better
"1",20.82,20.72,20.76
"2",20.73,20.7,20.84
"4",20.76,20.75,20.78
"NCNN 20200916 - Target: Vulkan GPU - Model: vgg16",
Lower Results Are Better
"1",66.52,66.59,66.68
"2",66.57,66.52,66.56
"4",66.53,66.5,66.61
"NCNN 20200916 - Target: Vulkan GPU - Model: resnet18",
Lower Results Are Better
"1",11.54,11.59,11.51
"2",11.55,11.56,11.71
"4",11.57,11.56,11.57
"NCNN 20200916 - Target: Vulkan GPU - Model: alexnet",
Lower Results Are Better
"1",12,12.03,12.02
"2",12,12,11.98
"4",12.04,11.96,12.12
"NCNN 20200916 - Target: Vulkan GPU - Model: resnet50",
Lower Results Are Better
"1",28.69,28.57,28.51
"2",28.46,28.39,28.51
"4",28.49,28.52,28.38
"NCNN 20200916 - Target: Vulkan GPU - Model: yolov4-tiny",
Lower Results Are Better
"1",28.49,28.62,28.44
"2",28.48,28.57,28.26
"4",28.51,28.69,28.62
"TNN 0.2.3 - Target: CPU - Model: MobileNet v2",
Lower Results Are Better
"1",332.317,335.664,333.827
"2",331.584,333.005,335.648
"4",334.062,332.54,330.875
"TNN 0.2.3 - Target: CPU - Model: SqueezeNet v1.1",
Lower Results Are Better
"1",304.809,306.367,302.984
"2",303.174,306.408,309.145
"4",306.225,306.622,305.288
"OpenCV 4.4 - Test: DNN - Deep Neural Network",
Lower Results Are Better
"1",21762,19384,22820,21336,20036,20714,22727,22750,19713,22346,25142,20455,20324,19292,23073
"2",22357,20423,20145,21833,18327,19004,21059,20010,18793,22822,18989,21225,19020,18084,18263
"4",20907,21933,21820
"OSBench - Test: Memory Allocations",
Lower Results Are Better
"1",91.562986,91.67099,91.627121
"2",91.984987,91.405869,92.068195
"4",91.07995,91.880083,92.391014
"RealSR-NCNN 20200818 - Scale: 4x - TAA: No",
Lower Results Are Better
"1",58.593,58.385,58.377
"2",58.468,58.395,58.376
"4",58.415,58.392,58.349
"RealSR-NCNN 20200818 - Scale: 4x - TAA: Yes",
Lower Results Are Better
"1",443.794,443.824,443.796
"2",443.842,443.828,443.812
"4",443.816,443.897,443.815
"Incompact3D 2020-09-17 - Input: Cylinder",
Lower Results Are Better
"1",527.63092,536.407043,534.94104
"2",534.171509,526.740112,536.858215
"4",530.458496,544.77832,537.031006
"Monte Carlo Simulations of Ionised Nebulae 2019-03-24 - Input: Dust 2D tau100.0",
Lower Results Are Better
"1",285,283,282
"2",
"4",
"dcraw - RAW To PPM Image Conversion",
Lower Results Are Better
"1",53.803,53.772,53.847
"2",54.317,53.314,53.798
"4",54.542,54.405,54.129
"eSpeak-NG Speech Engine 20200907 - Text-To-Speech Synthesis",
Lower Results Are Better
"1",36.557,39.656,36.567,37.753,38.874,39.805,41.929,42.888,38.049,46.09,47.04,46.195,42.684,45.738,39.541,44.383
"2",39.217,39.773,42.383,52.322,55.309,50.354,49.298,46.979,43.271,40.341,40.235,40.756,42.084,40.768,40.87,39.593,40.199,41.274,42.879,44.793
"4",38.134,39.585,36.551,37.705,38.737
"GPAW 20.1 - Input: Carbon Nanotube",
Lower Results Are Better
"1",520.338,517.793,516.578
"2",512.816,518.579,514.4
"4",517.909,519.445,516.305
"OSBench - Test: Create Files",
Lower Results Are Better
"1",19.413084,19.326959,18.711737
"2",18.905363,18.948776,19.380537
"4",18.902736,18.733663,18.714683
"OSBench - Test: Create Threads",
Lower Results Are Better
"1",16.300678,16.689301,16.717911
"2",16.191006,16.591549,16.050339
"4",16.570091,16.019344,16.150475
"OSBench - Test: Launch Programs",
Lower Results Are Better
"1",57.561398,56.350231,57.199001
"2",57.229996,54.810047,55.971146
"4",62.179565,59.759617,60.210228
"OSBench - Test: Create Processes",
Lower Results Are Better
"1",37.04071,34.549236,33.9818,34.570694,34.39188,39.708614,33.950806,36.261082,32.889843,33.731461,34.208298,37.748814,34.658909,35.5196,36.468506
"2",33.330917,37.670135,37.720203,35.54821,34.050941,34.5397,34.26075,35.450459,36.551952,34.85918,34.320354,32.339096,33.769608,35.209656,33.619404
"4",32.989979,34.730434,36.120415,35.769939,35.250187,38.890839,35.08091,35.722256,33.829212,35.169125,33.891201,36.640167,41.270256,34.329891,35.068989