Intel Core i7-8565U testing with a Dell 0KTW76 (1.0.0 BIOS) and Intel UHD 620 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 2009295-PTS-8565UMON93
8565U Monday,
"Apache CouchDB 3.1.1 - Bulk Size: 100 - Inserts: 1000 - Rounds: 24",
Lower Results Are Better
"1",217.039,218.698,223.054
"2",229.474,232.381,235.895
"3",233.311,238.305,234.204
"BYTE Unix Benchmark 3.6 - Computational Test: Dhrystone 2",
Higher Results Are Better
"1",41167270,41661113.4,41337126.1
"2",41524722.5,41144812.3,41187225
"3",41208461.2,41126355.2,41491400.2
"Caffe 2020-02-13 - Model: AlexNet - Acceleration: CPU - Iterations: 100",
Lower Results Are Better
"1",103210,106339,104397
"2",103519,104013,104947
"3",103857,105442,105288
"Caffe 2020-02-13 - Model: AlexNet - Acceleration: CPU - Iterations: 200",
Lower Results Are Better
"1",209491,209038,209582
"2",210622,211114,209447
"3",209578,210148,210576
"Caffe 2020-02-13 - Model: GoogleNet - Acceleration: CPU - Iterations: 100",
Lower Results Are Better
"1",256857,258544,259306
"2",258471,263504,257495
"3",258193,259329,259457
"Caffe 2020-02-13 - Model: GoogleNet - Acceleration: CPU - Iterations: 200",
Lower Results Are Better
"1",514772,515262,518755
"2",516883,517210,517281
"3",523300,516600,519960
"Dolfyn 0.527 - Computational Fluid Dynamics",
Lower Results Are Better
"1",19.813,19.807,19.973
"2",19.861,20.704,20.752
"3",20.806,20.961,20.513
"FFTE 7.0 - N=256, 3D Complex FFT Routine",
Higher Results Are Better
"1",19769.34066662,16689.443668865,14416.023151452,14435.761149921,14341.480756644,14385.045854005,14469.099784065,14534.774528188,14503.573419997,14398.443476381,14523.533772467,14525.676837527,14480.892589045,14391.227425892,14464.362090932
"2",19497.393244496,13332.40097769,13265.86182338,13208.629266228,13283.414673321,13183.200922647,13168.854114361,13310.188558983,13318.570196222,13156.529238276,13307.720962555,13274.321476637,13311.189191745,13144.449302663,13279.517402898
"3",19256.923914126,15004.224739798,13591.729769404,13541.368564748,13613.667742164,13555.121094819,13558.775497919,13414.726966179,13493.444229806,13435.683731832,13523.414598172,13401.642126349,13587.044459561,13416.482725572,13431.185861932
"GROMACS 2020.3 - Water Benchmark",
Higher Results Are Better
"1",0.349,0.349,0.353
"2",0.349,0.351,0.348
"3",0.342,0.348,0.349
"Hierarchical INTegration 1.0 - Test: FLOAT",
Higher Results Are Better
"1",412628032.75448,414168341.27206,414295334.48364
"2",414942122.97279,413769435.26837,412974884.44515
"3",414419449.09707,414685163.80807,415976884.52629
"LeelaChessZero 0.26 - Backend: BLAS",
Higher Results Are Better
"1",405,377,407,403,414,402,405
"2",387,359,370,388,373,370
"3",372,378,379
"LeelaChessZero 0.26 - Backend: Eigen",
Higher Results Are Better
"1",395,393,391
"2",368,357,351
"3",356,355,363
"LeelaChessZero 0.26 - Backend: Random",
Higher Results Are Better
"1",162908,162248,162518
"2",155776,155134,155813
"3",155790,154929,154628
"Mlpack Benchmark - Benchmark: scikit_ica",
Lower Results Are Better
"1",105.11223077774,106.5629761219,105.13546204567
"2",101.38498020172,103.0671172142,101.65872645378
"3",105.1277384758,99.929653167725,103.48608279228
"Mlpack Benchmark - Benchmark: scikit_qda",
Lower Results Are Better
"1",128.13668227196,128.52994179726,129.23055052757
"2",129.7598772049,130.1007194519,144.15068364143,129.19200468063,131.58279776573,129.00273036957,129.3332157135,129.68564224243,128.97980189323,130.7439289093,129.42986559868,128.71824145317
"3",129.21031141281,129.89992308617,130.35533905029
"Mlpack Benchmark - Benchmark: scikit_svm",
Lower Results Are Better
"1",26.914364099503,26.948214530945,27.181927204132
"2",26.814338684082,26.952872991562,26.782040596008
"3",26.80663895607,26.716058015823,26.787194490433
"Mlpack Benchmark - Benchmark: scikit_linearridgeregression",
Lower Results Are Better
"1",4.9161946773529,4.7557730674744,5.0462384223938
"2",5.0480010509491,5.4191374778748,5.3215610980988,4.8102312088013,5.1682403087616,5.0102412700653,4.8449034690857,5.0704545974731,5.3768303394318,4.9276299476624,4.9093124866486,5.3452179431915,5.1639194488525,5.3769187927246,5.0289199352264
"3",4.6622779369354,4.9926981925964,4.9383561611176,5.4628562927246,5.4844605922699,4.8428056240082,5.1855411529541,5.3749899864197,5.2142548561096,4.7660403251648,5.3551881313324,5.1370205879211,5.3063943386078,5.1525511741638,4.8422341346741
"NCNN 20200916 - Target: CPU - Model: squeezenet",
Lower Results Are Better
"1",33.82,33.88,33.6
"2",33.52,33.72,33.79
"3",33.51,34.09,33.5
"NCNN 20200916 - Target: CPU - Model: mobilenet",
Lower Results Are Better
"1",39.98,39.92,39.74
"2",39.7,39.93,40
"3",39.73,40.4,39.75
"NCNN 20200916 - Target: CPU-v2-v2 - Model: mobilenet-v2",
Lower Results Are Better
"1",7.83,10.64,10.51
"2",7.71,10.65,10.64
"3",7.74,10.59,10.63
"NCNN 20200916 - Target: CPU-v3-v3 - Model: mobilenet-v3",
Lower Results Are Better
"1",8.74,8.77,8.75
"2",8.63,8.76,8.82
"3",8.53,8.83,8.8
"NCNN 20200916 - Target: CPU - Model: shufflenet-v2",
Lower Results Are Better
"1",6.47,6.43,6.43
"2",6.47,6.43,6.45
"3",6.55,6.47,6.49
"NCNN 20200916 - Target: CPU - Model: mnasnet",
Lower Results Are Better
"1",9.33,9.31,9.26
"2",9.24,9.31,9.34
"3",9.28,9.25,9.27
"NCNN 20200916 - Target: CPU - Model: efficientnet-b0",
Lower Results Are Better
"1",14.5,14.48,14.28
"2",14.38,14.46,14.59
"3",14.28,14.38,14.37
"NCNN 20200916 - Target: CPU - Model: blazeface",
Lower Results Are Better
"1",3.01,3.04,2.97
"2",2.96,3.03,3.07
"3",2.95,2.99,2.97
"NCNN 20200916 - Target: CPU - Model: googlenet",
Lower Results Are Better
"1",32.03,32,31.91
"2",32,32,32.16
"3",31.97,32.05,32.09
"NCNN 20200916 - Target: CPU - Model: vgg16",
Lower Results Are Better
"1",112.38,112.38,111.99
"2",112.65,112.7,112.88
"3",112.02,112.49,112.28
"NCNN 20200916 - Target: CPU - Model: resnet18",
Lower Results Are Better
"1",29.93,29.91,29.9
"2",30.71,29.89,29.8
"3",29.89,29.99,29.88
"NCNN 20200916 - Target: CPU - Model: alexnet",
Lower Results Are Better
"1",32.76,32.78,31.56
"2",31.3,33.18,33.2
"3",31.66,31.98,31.46
"NCNN 20200916 - Target: CPU - Model: resnet50",
Lower Results Are Better
"1",58.05,58.21,58.33
"2",58.03,58.08,58.11
"3",58.19,58.25,58.21
"NCNN 20200916 - Target: CPU - Model: yolov4-tiny",
Lower Results Are Better
"1",52.46,52.41,52.26
"2",52.13,52.4,52.5
"3",52.27,52.59,52.31
"NCNN 20200916 - Target: Vulkan GPU - Model: squeezenet",
Lower Results Are Better
"1",113.18,113.17,113.17
"2",113.16,113.36,113.17
"3",111.9,113.03,113.26
"NCNN 20200916 - Target: Vulkan GPU - Model: mobilenet",
Lower Results Are Better
"1",109.84,109.76,109.77
"2",109.94,109.73,110.17
"3",109.56,109.66,110.02
"NCNN 20200916 - Target: Vulkan GPU-v2-v2 - Model: mobilenet-v2",
Lower Results Are Better
"1",39.26,40.63,40.06
"2",39.7,39.8,39.57
"3",39.53,39.22,39.85
"NCNN 20200916 - Target: Vulkan GPU-v3-v3 - Model: mobilenet-v3",
Lower Results Are Better
"1",44.06,44.25,44.18
"2",44.1,43.06,44.14
"3",44.1,44.12,44.15
"NCNN 20200916 - Target: Vulkan GPU - Model: shufflenet-v2",
Lower Results Are Better
"1",27.23,27.29,27.29
"2",27.21,27.2,27.24
"3",26.35,27.24,27.25
"NCNN 20200916 - Target: Vulkan GPU - Model: mnasnet",
Lower Results Are Better
"1",40.99,41.23,40.93
"2",41.29,40.87,41.16
"3",40.96,40.94,41.14
"NCNN 20200916 - Target: Vulkan GPU - Model: efficientnet-b0",
Lower Results Are Better
"1",80.55,80.63,77.12
"2",80.59,80.44,80.51
"3",80.6,80.56,80.14
"NCNN 20200916 - Target: Vulkan GPU - Model: blazeface",
Lower Results Are Better
"1",7.23,7.22,7.26
"2",7.29,7.24,7.26
"3",7.22,7.3,7.25
"NCNN 20200916 - Target: Vulkan GPU - Model: googlenet",
Lower Results Are Better
"1",100.18,100.17,100.21
"2",100.09,99.93,99.9
"3",100.12,100.18,99.62
"NCNN 20200916 - Target: Vulkan GPU - Model: vgg16",
Lower Results Are Better
"1",263.88,265.62,265.22
"2",273.37,262.19,263.61
"3",267.22,265.13,261.12
"NCNN 20200916 - Target: Vulkan GPU - Model: resnet18",
Lower Results Are Better
"1",93.45,93.58,93.53
"2",93.6,93.49,93.35
"3",93.62,93.48,93.64
"NCNN 20200916 - Target: Vulkan GPU - Model: alexnet",
Lower Results Are Better
"1",112.49,112,111.43
"2",109.51,110.69,111.88
"3",111.28,111.66,111.18
"NCNN 20200916 - Target: Vulkan GPU - Model: resnet50",
Lower Results Are Better
"1",146,146.24,145.58
"2",146.19,146.21,146.23
"3",145.8,146.11,146.04
"NCNN 20200916 - Target: Vulkan GPU - Model: yolov4-tiny",
Lower Results Are Better
"1",152.82,152.63,152.71
"2",152.31,152.17,152.09
"3",152.29,152.36,152.4
"RealSR-NCNN 20200818 - Scale: 4x - TAA: No",
Lower Results Are Better
"1",16.509,17.011,16.962
"2",16.619,16.961,17.003
"3",16.887,16.925,17.217
"Timed HMMer Search 3.3.1 - Pfam Database Search",
Lower Results Are Better
"1",115.437,115.984,116.063
"2",119.17,120.081,120.2
"3",123.216,120.557,120.516
"Timed MAFFT Alignment 7.471 - Multiple Sequence Alignment - LSU RNA",
Lower Results Are Better
"1",13.677,14.599,14.332,14.301
"2",14.197,15.149,15.344,15.219,15.11,15.06
"3",14.236,15.268,15.061,15.025,14.921
"TNN 0.2.3 - Target: CPU - Model: MobileNet v2",
Lower Results Are Better
"1",337.579,345.571,365.318,360.512,358.14,358.748
"2",337.739,340.466,362.503,361.607,360.508,359.799,357.061
"3",337.333,339.808,367.634,360.923,364.016,362.415,368.252,359.31,360.438,362.366,358.704
"TNN 0.2.3 - Target: CPU - Model: SqueezeNet v1.1",
Lower Results Are Better
"1",321.161,321.37,321.359
"2",321.562,321.399,321.815
"3",321.179,321.248,321.579