Intel Core i7-9750H testing with a Notebook P95_96_97Ex Rx (1.07.13MIN29 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 2101014-HA-COREI797566
Core i7 9750H EOY,
"Monkey Audio Encoding 3.99.6 - WAV To APE",
Lower Results Are Better
"Run 1",11.16,11.129,10.932,11.044,10.992
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Higher Results Are Better
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"Cryptsetup - Twofish-XTS 512b Encryption",
Higher Results Are Better
"Run 1",448.2,449,441
"Run 2",417.5,412.1,449.5
"Run 3",449.9,438.4,450.4
"Run 4",450.9,416.2,439.2
"Cryptsetup - Twofish-XTS 256b Encryption",
Higher Results Are Better
"Run 1",432.4,450.6,444.6
"Run 2",430.7,413.4,448.3
"Run 3",451.1,436,448.4
"Run 4",449.5,416.3,434.9
"Cryptsetup - PBKDF2-sha512",
Higher Results Are Better
"Run 1",1829975,1829975,1826787
"Run 2",1747626,1795506,1792437
"Run 3",1836385,1826787,1826787
"Run 4",1836385,1829975,1826787
"oneDNN 2.0 - Harness: Deconvolution Batch shapes_1d - Data Type: u8s8f32 - Engine: CPU",
Lower Results Are Better
"Run 1",10.1198,10.1329,9.83334
"Run 2",9.81706,9.85677,9.92756
"Run 3",9.87341,9.8776,9.94212
"Run 4",10.1092,10.1692,10.1884
"Cryptsetup - PBKDF2-whirlpool",
Higher Results Are Better
"Run 1",783689,780190,777875
"Run 2",762046,759837,759837
"Run 3",783689,781353,780190
"Run 4",784862,782519,727167
"Cryptsetup - Twofish-XTS 512b Decryption",
Higher Results Are Better
"Run 1",449.3,453.2,419
"Run 2",440.5,441.1,455
"Run 3",454.7,436.3,454.1
"Run 4",452.7,433,423.6
"Coremark 1.0 - CoreMark Size 666 - Iterations Per Second",
Higher Results Are Better
"Run 1",215491.440201,216489.265741,208387.600938
"Run 2",210846.901722,211727.342234,212320.485978
"Run 3",207253.88601,212307.964497,211540.721589
"Run 4",216909.937186,216596.723975,213732.300294
"Cryptsetup - AES-XTS 512b Encryption",
Higher Results Are Better
"Run 1",2114.4,2109.1,2090.7
"Run 2",1989.4,2090.3,2114.1
"Run 3",2127.9,1983.7,2117.6
"Run 4",2118.5,2125.5,2101.4
"Timed MAFFT Alignment 7.471 - Multiple Sequence Alignment - LSU RNA",
Lower Results Are Better
"Run 1",10.586,10.445,10.436
"Run 2",10.506,10.801,10.881
"Run 3",10.438,10.524,10.626
"Run 4",10.843,10.664,10.313
"NCNN 20201218 - Target: Vulkan GPU - Model: resnet18",
Lower Results Are Better
"Run 1",18.45,18.61,18.59
"Run 2",16.95,18.61,18.87
"Run 3",18.43,18.51,18.58
"Run 4",18.44,18.62,18.55
"NCNN 20201218 - Target: Vulkan GPU - Model: alexnet",
Lower Results Are Better
"Run 1",15.4,15.38,15.49
"Run 2",14.33,15.42,15.7
"Run 3",15.39,15.46,15.51
"Run 4",15.41,15.49,15.53
"oneDNN 2.0 - Harness: Deconvolution Batch shapes_3d - Data Type: f32 - Engine: CPU",
Lower Results Are Better
"Run 1",12.7714,12.7963,12.838
"Run 2",12.8179,12.8027,12.7436
"Run 3",12.8633,12.8144,12.787
"Run 4",10.8371,11.4023,12.7947,12.7826,12.837,12.7889,12.8013,12.7997,12.7687,12.7571,12.7592,12.7542,12.7702,12.7686,12.7905
"oneDNN 2.0 - Harness: Deconvolution Batch shapes_1d - Data Type: f32 - Engine: CPU",
Lower Results Are Better
"Run 1",9.66071,9.45734,9.66669
"Run 2",9.74385,9.75977,9.70027
"Run 3",9.7251,9.37628,9.67258
"Run 4",9.66523,9.5494,9.40395
"Cryptsetup - Twofish-XTS 256b Decryption",
Higher Results Are Better
"Run 1",428,455,444
"Run 2",430.8,441.6,454.5
"Run 3",455.1,433.5,453.4
"Run 4",454.6,434.3,426.6
"oneDNN 2.0 - Harness: IP Shapes 1D - Data Type: f32 - Engine: CPU",
Lower Results Are Better
"Run 1",6.8066,6.77868,6.81971
"Run 2",6.90434,6.93708,6.94701
"Run 3",6.79153,6.8116,6.11187,6.83916,6.85614,6.84283,6.85531,6.84395,6.86925,6.86358,6.87544,6.91753,6.85724,6.91053
"Run 4",6.76857,6.7964,6.81787
"NCNN 20201218 - Target: Vulkan GPU - Model: squeezenet_ssd",
Lower Results Are Better
"Run 1",24.24,24.41,24.62
"Run 2",24.59,24.85,24.94
"Run 3",24.18,24.29,24.53
"Run 4",24.44,24.47,24.24
"SQLite Speedtest 3.30 - Timed Time - Size 1,000",
Lower Results Are Better
"Run 1",61.667,62.1,62.446
"Run 2",62.472,62.798,62.804
"Run 3",61.568,61.887,61.66
"Run 4",62.337,62.492,62.346
"Timed Eigen Compilation 3.3.9 - Time To Compile",
Lower Results Are Better
"Run 1",74.232,74.174,74.283
"Run 2",75.418,75.378,75.376
"Run 3",75.166,74.905,74.948
"Run 4",74.2,74.321,74.264
"oneDNN 2.0 - Harness: IP Shapes 3D - Data Type: f32 - Engine: CPU",
Lower Results Are Better
"Run 1",9.72172,9.79406,9.80627
"Run 2",9.77784,9.81409,9.79911
"Run 3",9.76077,9.81078,9.81968
"Run 4",9.91747,9.89805,9.91821
"NCNN 20201218 - Target: Vulkan GPU - Model: mobilenet",
Lower Results Are Better
"Run 1",23.31,23.45,23.53
"Run 2",23.18,23.8,24
"Run 3",23.26,23.38,23.54
"Run 4",23.4,23.5,23.13
"VkResample 1.0 - Upscale: 2x - Precision: Double",
Lower Results Are Better
"Run 1",1016.221,1001.963,1007.508
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"Run 4",1013.502,1013.655,1016.204
"oneDNN 2.0 - Harness: Recurrent Neural Network Inference - Data Type: f32 - Engine: CPU",
Lower Results Are Better
"Run 1",3434.18,3436.76,3411.91
"Run 2",3474.99,3479.69,3407.98
"Run 3",3406.23,3395.1,3428.91
"Run 4",3436.22,3445.26,3455.3
"oneDNN 2.0 - Harness: Matrix Multiply Batch Shapes Transformer - Data Type: u8s8f32 - Engine: CPU",
Lower Results Are Better
"Run 1",5.74651,5.7568,5.70428
"Run 2",5.76073,5.7684,5.79437
"Run 3",5.79936,5.81847,5.81165
"Run 4",5.7697,5.7857,5.80026
"Ogg Audio Encoding 1.3.4 - WAV To Ogg",
Lower Results Are Better
"Run 1",20.215,20.191,20.17
"Run 2",20.158,20.18,20.364
"Run 3",20.145,20.151,20.206
"Run 4",20.169,20.938,20.164
"NCNN 20201218 - Target: Vulkan GPU - Model: yolov4-tiny",
Lower Results Are Better
"Run 1",33.39,33.61,33.53
"Run 2",33.2,34.05,34.34
"Run 3",33.32,33.52,33.58
"Run 4",33.56,33.52,33.28
"BRL-CAD 7.30.8 - VGR Performance Metric",
Higher Results Are Better
"Run 1",
"Run 2",
"Run 3",
"Run 4",
"oneDNN 2.0 - Harness: Recurrent Neural Network Training - Data Type: bf16bf16bf16 - Engine: CPU",
Lower Results Are Better
"Run 1",6415.38,6429.55,6366.87
"Run 2",6354.07,6309.66,6322.37
"Run 3",6383.73,6373.85,6352.28
"Run 4",6409.6,6371.61,6350.91
"oneDNN 2.0 - Harness: Deconvolution Batch shapes_3d - Data Type: u8s8f32 - Engine: CPU",
Lower Results Are Better
"Run 1",5.74422,5.76667,5.74682
"Run 2",5.74487,6.19306,5.35794,5.77087,5.77099,6.00033,5.7067,5.7757,5.7699,5.77459,5.77084,5.76866
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"Run 4",5.76994,5.79468,5.78547
"oneDNN 2.0 - Harness: Recurrent Neural Network Inference - Data Type: bf16bf16bf16 - Engine: CPU",
Lower Results Are Better
"Run 1",3481.28,3474.59,3416.08
"Run 2",3439.04,3408.59,3409.34
"Run 3",3448.99,3433.63,3438.03
"Run 4",3447.08,3443.45,3444.25
"oneDNN 2.0 - Harness: Recurrent Neural Network Training - Data Type: f32 - Engine: CPU",
Lower Results Are Better
"Run 1",6290.62,6353.9,6380.71
"Run 2",6412.74,6380.5,6420.08
"Run 3",6359.52,6383.78,6361.44
"Run 4",6386.32,6416.91,6345.1
"Cryptsetup - Serpent-XTS 256b Decryption",
Higher Results Are Better
"Run 1",828.1,829.3,826.5
"Run 2",822.3,820.9,829.9
"Run 3",833.4,829.8,829.2
"Run 4",831.1,810.8,826.7
"Cryptsetup - Serpent-XTS 512b Decryption",
Higher Results Are Better
"Run 1",832.5,831.5,827.3
"Run 2",813.7,827.6,829.3
"Run 3",832.8,829.6,830.3
"Run 4",830.8,816.1,827.5
"Cryptsetup - Serpent-XTS 256b Encryption",
Higher Results Are Better
"Run 1",804.8,815.2,812.9
"Run 2",801.2,810.6,810.9
"Run 3",816.4,813.5,814.5
"Run 4",816.3,800.6,811.9
"NCNN 20201218 - Target: Vulkan GPU - Model: vgg16",
Lower Results Are Better
"Run 1",69.62,69.75,69.98
"Run 2",67.62,70.33,70.34
"Run 3",69.73,69.74,70.12
"Run 4",69.98,70.04,70.05
"NCNN 20201218 - Target: Vulkan GPU - Model: resnet50",
Lower Results Are Better
"Run 1",37.49,37.76,37.87
"Run 2",37.4,38.25,38.28
"Run 3",37.34,37.59,38.04
"Run 4",37.65,37.92,37.61
"Timed FFmpeg Compilation 4.2.2 - Time To Compile",
Lower Results Are Better
"Run 1",101.242,101.021,101.586
"Run 2",101.504,101.591,102.093
"Run 3",102.693,102.199,101.337
"Run 4",101.62,102.228,102.525
"oneDNN 2.0 - Harness: Recurrent Neural Network Inference - Data Type: u8s8f32 - Engine: CPU",
Lower Results Are Better
"Run 1",3395.11,3423.94,3445.75
"Run 2",3427.62,3457.03,3446.78
"Run 3",3412.61,3415.54,3446.17
"Run 4",3422.73,3409.2,3414.97
"NCNN 20201218 - Target: CPU - Model: mobilenet",
Lower Results Are Better
"Run 1",23.08,23.15,23.29
"Run 2",23.02,23.03,23.09
"Run 3",23.08,23.15,23.15
"Run 4",23.09,23.26,23.36
"NCNN 20201218 - Target: CPU - Model: resnet18",
Lower Results Are Better
"Run 1",16.95,18.52,18.59
"Run 2",16.82,18.46,18.44
"Run 3",17.09,18.5,18.57
"Run 4",16.97,18.45,18.55
"VkResample 1.0 - Upscale: 2x - Precision: Single",
Lower Results Are Better
"Run 1",461.593,461.428,461.865
"Run 2",464.903,464.527,463.783
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"Run 4",464.969,465.444,464.469
"Cryptsetup - Serpent-XTS 512b Encryption",
Higher Results Are Better
"Run 1",816.8,815.5,813
"Run 2",811.3,811.3,815.6
"Run 3",812.8,814.2,814.3
"Run 4",813.1,802.4,812.3
"NCNN 20201218 - Target: CPU - Model: yolov4-tiny",
Lower Results Are Better
"Run 1",33.14,33.41,33.56
"Run 2",33.08,33.3,33.2
"Run 3",33.17,33.21,33.24
"Run 4",33.17,33.4,33.69
"oneDNN 2.0 - Harness: Matrix Multiply Batch Shapes Transformer - Data Type: f32 - Engine: CPU",
Lower Results Are Better
"Run 1",4.09699,4.0956,4.10784
"Run 2",4.11056,4.1043,4.12315
"Run 3",4.08874,4.12345,4.10919
"Run 4",4.07962,4.09846,4.08543
"oneDNN 2.0 - Harness: Convolution Batch Shapes Auto - Data Type: f32 - Engine: CPU",
Lower Results Are Better
"Run 1",17.2227,17.3448,17.2896
"Run 2",17.2853,17.2871,17.2412
"Run 3",17.2173,17.2665,17.2209
"Run 4",17.2833,17.4352,17.2814
"NCNN 20201218 - Target: CPU - Model: vgg16",
Lower Results Are Better
"Run 1",69.39,69.43,69.75
"Run 2",68.89,69.3,69.37
"Run 3",69.43,69.5,69.52
"Run 4",68.08,69.97,69.98
"NCNN 20201218 - Target: CPU - Model: regnety_400m",
Lower Results Are Better
"Run 1",15.1,16.72,16.73
"Run 2",15.15,16.59,16.63
"Run 3",15.11,16.69,16.77
"Run 4",15.28,16.62,16.57
"oneDNN 2.0 - Harness: Recurrent Neural Network Training - Data Type: u8s8f32 - Engine: CPU",
Lower Results Are Better
"Run 1",6367.36,6381.09,6339.48
"Run 2",6372.46,6429.77,6344.02
"Run 3",6321.25,6376.39,6452.91
"Run 4",6354.31,6420.19,6395.15
"Cryptsetup - AES-XTS 512b Decryption",
Higher Results Are Better
"Run 1",2086.1,2086.2,2062.6
"Run 2",2071,2068.7,2083
"Run 3",2079.6,2080.3,2088.7
"Run 4",2085.4,2089.9,2061.5
"oneDNN 2.0 - Harness: IP Shapes 3D - Data Type: u8s8f32 - Engine: CPU",
Lower Results Are Better
"Run 1",2.75727,2.77791,2.7772
"Run 2",2.75415,2.77668,2.7751
"Run 3",2.76814,2.77381,2.78617
"Run 4",2.75672,2.77111,2.76555
"Unpacking Firefox 84.0 - Extracting: firefox-84.0.source.tar.xz",
Lower Results Are Better
"Run 1",19.067,18.815,18.815,18.83
"Run 2",18.938,18.872,18.846,18.834
"Run 3",19.093,18.818,18.974,18.844
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"Cryptsetup - AES-XTS 256b Encryption",
Higher Results Are Better
"Run 1",2353.4,2378.7,2347.3
"Run 2",2358,2343.1,2375.4
"Run 3",2355.5,2371.6,2373.6
"Run 4",2376.9,2346.9,2348.3
"NCNN 20201218 - Target: CPU - Model: squeezenet_ssd",
Lower Results Are Better
"Run 1",24.15,24.22,24.28
"Run 2",24.12,24.19,24.17
"Run 3",24.25,24.25,24.23
"Run 4",24.18,24.2,24.3
"Build2 0.13 - Time To Compile",
Lower Results Are Better
"Run 1",213.893,215.078,214.256
"Run 2",215.719,213.993,214.795
"Run 3",213.724,214.592,214.218
"Run 4",214.27,214.959,215.345
"Opus Codec Encoding 1.3.1 - WAV To Opus Encode",
Lower Results Are Better
"Run 1",8.574,8.577,8.575,8.567,8.575
"Run 2",8.568,8.567,8.58,8.576,8.58
"Run 3",8.551,8.571,8.566,8.563,8.565
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"Cryptsetup - AES-XTS 256b Decryption",
Higher Results Are Better
"Run 1",2298.1,2325.4,2299.3
"Run 2",2312.4,2300.3,2324
"Run 3",2310.9,2312.5,2320.5
"Run 4",2320.7,2319.2,2297.5
"NCNN 20201218 - Target: CPU - Model: resnet50",
Lower Results Are Better
"Run 1",37.42,37.49,37.46
"Run 2",37.43,37.43,37.44
"Run 3",37.55,37.55,37.51
"Run 4",37.48,37.4,37.57
"oneDNN 2.0 - Harness: IP Shapes 1D - Data Type: u8s8f32 - Engine: CPU",
Lower Results Are Better
"Run 1",3.21752,3.22887,3.23388
"Run 2",3.21095,3.24047,3.24551
"Run 3",3.21459,3.23524,3.23853
"Run 4",3.20948,3.22464,3.2366
"NCNN 20201218 - Target: CPU - Model: alexnet",
Lower Results Are Better
"Run 1",14.26,15.31,15.47
"Run 2",14.29,15.38,15.3
"Run 3",14.3,15.35,15.36
"Run 4",14.3,15.4,15.38
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Higher Results Are Better
"Run 1",
"Run 2",1320,1321,1322
"Run 3",1320,1318,1318
"Run 4",1321,1322,1324
"Timed HMMer Search 3.3.1 - Pfam Database Search",
Lower Results Are Better
"Run 1",117.176,117.229,117.287
"Run 2",117.191,117.073,117.166
"Run 3",117.222,117.198,117.122
"Run 4",117.505,117.587,117.121
"WavPack Audio Encoding 5.3 - WAV To WavPack",
Lower Results Are Better
"Run 1",14.49,14.513,14.513,14.512,14.514
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"Run 3",14.486,14.511,14.526,14.497,14.621
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"oneDNN 2.0 - Harness: Convolution Batch Shapes Auto - Data Type: u8s8f32 - Engine: CPU",
Lower Results Are Better
"Run 1",16.049,16.1777,16.0942
"Run 2",16.0843,16.1435,16.0659
"Run 3",16.1034,16.1264,16.0686
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"CLOMP 1.2 - Static OMP Speedup",
Higher Results Are Better
"Run 1",2.7,2.7,2.7
"Run 2",2.7,2.7,2.7
"Run 3",2.7,2.7,2.7
"Run 4",2.7,2.7,2.7
"NCNN 20201218 - Target: Vulkan GPU - Model: regnety_400m",
Lower Results Are Better
"Run 1",16.53,16.64,16.96
"Run 2",15.1,16.74,16.99
"Run 3",16.46,16.57,16.8
"Run 4",16.61,16.93,16.74
"NCNN 20201218 - Target: Vulkan GPU - Model: googlenet",
Lower Results Are Better
"Run 1",18.68,18.77,18.94
"Run 2",16.54,18.76,19.16
"Run 3",18.79,18.76,18.91
"Run 4",18.75,18.91,18.92
"NCNN 20201218 - Target: Vulkan GPU - Model: blazeface",
Lower Results Are Better
"Run 1",2.38,2.39,2.42
"Run 2",2.07,2.39,2.45
"Run 3",2.36,2.39,2.4
"Run 4",2.39,2.42,2.42
"NCNN 20201218 - Target: Vulkan GPU - Model: efficientnet-b0",
Lower Results Are Better
"Run 1",8.61,8.69,8.76
"Run 2",7.62,8.74,8.82
"Run 3",8.61,8.65,8.7
"Run 4",8.63,8.8,8.72
"NCNN 20201218 - Target: Vulkan GPU - Model: mnasnet",
Lower Results Are Better
"Run 1",5.47,5.45,5.6
"Run 2",4.64,5.46,5.62
"Run 3",5.12,5.46,5.5
"Run 4",5.44,5.51,5.51
"NCNN 20201218 - Target: Vulkan GPU - Model: shufflenet-v2",
Lower Results Are Better
"Run 1",7.79,7.8,7.9
"Run 2",6.6,7.57,8
"Run 3",6.52,7.82,7.88
"Run 4",7.72,7.87,7.89
"NCNN 20201218 - Target: Vulkan GPU-v3-v3 - Model: mobilenet-v3",
Lower Results Are Better
"Run 1",5.34,5.34,5.41
"Run 2",4.77,4.71,5.45
"Run 3",4.69,5.32,5.36
"Run 4",5.32,5.4,5.39
"NCNN 20201218 - Target: Vulkan GPU-v2-v2 - Model: mobilenet-v2",
Lower Results Are Better
"Run 1",6.46,6.53,6.66
"Run 2",5.9,5.79,6.62
"Run 3",5.87,6.48,6.54
"Run 4",6.46,6.62,6.59
"NCNN 20201218 - Target: CPU - Model: googlenet",
Lower Results Are Better
"Run 1",16.53,18.8,18.87
"Run 2",16.5,18.79,18.77
"Run 3",16.75,18.8,18.83
"Run 4",16.6,18.71,18.71
"NCNN 20201218 - Target: CPU - Model: blazeface",
Lower Results Are Better
"Run 1",2.04,2.36,2.39
"Run 2",2.04,2.36,2.41
"Run 3",2.04,2.36,2.37
"Run 4",2.05,2.38,2.43
"NCNN 20201218 - Target: CPU - Model: efficientnet-b0",
Lower Results Are Better
"Run 1",7.64,8.69,8.73
"Run 2",7.66,8.65,8.68
"Run 3",7.68,8.72,8.75
"Run 4",7.64,8.65,8.63
"NCNN 20201218 - Target: CPU - Model: mnasnet",
Lower Results Are Better
"Run 1",4.71,5.63,5.48
"Run 2",4.67,5.49,5.56
"Run 3",4.64,5.58,5.66
"Run 4",4.66,5.49,5.47
"NCNN 20201218 - Target: CPU - Model: shufflenet-v2",
Lower Results Are Better
"Run 1",6.47,7.62,7.41
"Run 2",6.47,7.6,7.56
"Run 3",6.48,7.56,7.49
"Run 4",6.47,7.43,7.79
"NCNN 20201218 - Target: CPU-v3-v3 - Model: mobilenet-v3",
Lower Results Are Better
"Run 1",4.76,4.71,4.79
"Run 2",4.73,4.75,4.67
"Run 3",4.85,4.7,4.72
"Run 4",4.71,4.69,5.33
"NCNN 20201218 - Target: CPU-v2-v2 - Model: mobilenet-v2",
Lower Results Are Better
"Run 1",5.86,5.84,5.89
"Run 2",5.89,5.9,5.85
"Run 3",5.86,5.8,5.81
"Run 4",5.88,5.81,6.53