Intel Core i5-8400 testing with a MSI Z370M MORTAR (MS-7B54) v1.0 (1.80 BIOS) and MSI 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 2103223-IB-8400M557504
8400 m,
"Xcompact3d Incompact3d 2021-03-11 - Input: input.i3d 129 Cells Per Direction",
Lower Results Are Better
"1",43.9811096,43.7897987,43.8383102
"2",43.3745575,42.2439384,43.4151917
"3",43.7961464,43.9042702,43.7719765
"Xcompact3d Incompact3d 2021-03-11 - Input: input.i3d 193 Cells Per Direction",
Lower Results Are Better
"1",151.405762,150.655319,150.600616
"2",149.512192,149.486954,149.668198
"3",150.452332,150.430023,150.610184
"SVT-HEVC 1.5.0 - Tuning: 1 - Input: Bosphorus 1080p",
Higher Results Are Better
"1",4.33,4.31,4.28
"2",4.33,4.34,4.3
"3",4.31,4.27,4.26
"SVT-HEVC 1.5.0 - Tuning: 7 - Input: Bosphorus 1080p",
Higher Results Are Better
"1",63.14,63.19,63.17
"2",63.38,63.17,63.04
"3",63.43,63.18,63.38
"SVT-HEVC 1.5.0 - Tuning: 10 - Input: Bosphorus 1080p",
Higher Results Are Better
"1",132.45,133.01,133.13
"2",132.28,132.68,132.36
"3",133.63,132.89,132.71
"SVT-VP9 0.3 - Tuning: VMAF Optimized - Input: Bosphorus 1080p",
Higher Results Are Better
"1",114.16,118.07,117.3
"2",114.9,116.44,117.74
"3",114.88,117.69,117.36
"SVT-VP9 0.3 - Tuning: PSNR/SSIM Optimized - Input: Bosphorus 1080p",
Higher Results Are Better
"1",117.97,117.91,117.34
"2",117.95,118.04,117.89
"3",117.45,118.33,117.86
"SVT-VP9 0.3 - Tuning: Visual Quality Optimized - Input: Bosphorus 1080p",
Higher Results Are Better
"1",94.51,94.7,95.41
"2",94.93,94.63,95.17
"3",94.8,94.23,94.61
"Stockfish 13 - Total Time",
Higher Results Are Better
"1",12479064,12419337,12372533
"2",12484268,12423435,12478494
"3",12689201,12496247,12602859
"Timed Mesa Compilation 21.0 - Time To Compile",
Lower Results Are Better
"1",96.009,96.304,95.752
"2",95.936,95.916,95.61
"3",96.072,95.888,95.869
"Timed Node.js Compilation 15.11 - Time To Compile",
Lower Results Are Better
"1",868.428,868.858,869.363
"2",868.369,869.157,869.528
"3",868.778,869.62,869.375
"oneDNN 2.1.2 - Harness: IP Shapes 1D - Data Type: f32 - Engine: CPU",
Lower Results Are Better
"1",5.33312,5.35583,5.45888
"2",5.44203,5.45356,5.34664
"3",5.34896,5.37175,5.34453
"oneDNN 2.1.2 - Harness: IP Shapes 3D - Data Type: f32 - Engine: CPU",
Lower Results Are Better
"1",10.4801,10.5364,10.5332
"2",10.3142,10.3518,10.3469
"3",10.5539,10.589,10.6515
"oneDNN 2.1.2 - Harness: IP Shapes 1D - Data Type: u8s8f32 - Engine: CPU",
Lower Results Are Better
"1",3.32095,3.32544,3.32503
"2",3.31514,3.33183,3.32209
"3",3.31876,3.32547,3.33632
"oneDNN 2.1.2 - Harness: IP Shapes 3D - Data Type: u8s8f32 - Engine: CPU",
Lower Results Are Better
"1",2.12244,2.1289,2.17163
"2",2.13657,2.14133,2.15276
"3",2.11858,2.14057,2.14313
"oneDNN 2.1.2 - Harness: Convolution Batch Shapes Auto - Data Type: f32 - Engine: CPU",
Lower Results Are Better
"1",20.5129,20.557,20.5089
"2",20.5043,20.5402,20.5022
"3",20.5188,20.564,20.5125
"oneDNN 2.1.2 - Harness: Deconvolution Batch shapes_1d - Data Type: f32 - Engine: CPU",
Lower Results Are Better
"1",7.35677,7.44124,7.34536
"2",7.35429,7.36155,7.36531
"3",7.3445,7.36508,7.35218
"oneDNN 2.1.2 - Harness: Deconvolution Batch shapes_3d - Data Type: f32 - Engine: CPU",
Lower Results Are Better
"1",9.44337,9.45183,9.34004
"2",9.42959,9.42626,9.45501
"3",9.39607,9.43999,9.42912
"oneDNN 2.1.2 - Harness: Convolution Batch Shapes Auto - Data Type: u8s8f32 - Engine: CPU",
Lower Results Are Better
"1",15.8791,15.9114,15.8436
"2",15.8207,15.8906,15.8092
"3",15.8801,15.8643,15.8886
"oneDNN 2.1.2 - Harness: Deconvolution Batch shapes_1d - Data Type: u8s8f32 - Engine: CPU",
Lower Results Are Better
"1",3.16689,3.16716,3.16586
"2",3.16628,3.17737,3.16645
"3",3.17183,3.17663,3.1655
"oneDNN 2.1.2 - Harness: Deconvolution Batch shapes_3d - Data Type: u8s8f32 - Engine: CPU",
Lower Results Are Better
"1",6.36414,6.34214,6.31684
"2",6.36489,6.34996,6.3058
"3",6.36835,6.36402,6.35501
"oneDNN 2.1.2 - Harness: Recurrent Neural Network Training - Data Type: f32 - Engine: CPU",
Lower Results Are Better
"1",4435.36,4694.62,4693.46,4692.74
"2",4408.87,4509.54,4714.18,4474.92
"3",4466.24,4711.37,4503.7
"oneDNN 2.1.2 - Harness: Recurrent Neural Network Inference - Data Type: f32 - Engine: CPU",
Lower Results Are Better
"1",2539.3,2543.72,2626.2
"2",2537.42,2594.58,2537.32
"3",2538.49,2600.1,2541.55
"oneDNN 2.1.2 - Harness: Recurrent Neural Network Training - Data Type: u8s8f32 - Engine: CPU",
Lower Results Are Better
"1",4567.69,4550.92,4736.75
"2",4687.36,4513.49,4758.66
"3",4597.7,4548.84,4741.1
"oneDNN 2.1.2 - Harness: Recurrent Neural Network Inference - Data Type: u8s8f32 - Engine: CPU",
Lower Results Are Better
"1",2517.26,2618.1,2537.04
"2",2665.72,2599.98,2537.52
"3",2601.79,2562.38,2541.71
"oneDNN 2.1.2 - Harness: Matrix Multiply Batch Shapes Transformer - Data Type: f32 - Engine: CPU",
Lower Results Are Better
"1",3.74931,3.75874,3.75265
"2",3.75446,3.75448,3.75445
"3",3.75273,3.75236,3.75652
"oneDNN 2.1.2 - Harness: Recurrent Neural Network Training - Data Type: bf16bf16bf16 - Engine: CPU",
Lower Results Are Better
"1",4521.45,4582.21,4542.15
"2",4506.81,4736.13,4698.06
"3",4601.31,4571.84,4593.33
"oneDNN 2.1.2 - Harness: Recurrent Neural Network Inference - Data Type: bf16bf16bf16 - Engine: CPU",
Lower Results Are Better
"1",2667.31,2566.33,2612.28
"2",2864.9,2602.93,2596.72,2539.67,2561.15,2548.48,2591,2557.17,2550.25,2562.02,2596.65,2596.7,2637.31,2558.72,2611.08
"3",2696.69,2603.12,2563.96
"oneDNN 2.1.2 - Harness: Matrix Multiply Batch Shapes Transformer - Data Type: u8s8f32 - Engine: CPU",
Lower Results Are Better
"1",4.1834,4.19417,4.2094
"2",4.18811,4.18549,4.18452
"3",4.18132,4.18723,4.18532
"Sysbench 1.0.20 - Test: RAM / Memory",
Higher Results Are Better
"1",12663.33,12458.78,12557.48
"2",12780.9,12638.5,12544.86
"3",12569.38,12515.23,12822.36
"Sysbench 1.0.20 - Test: CPU",
Higher Results Are Better
"1",8032.97,8020.31,8027.86
"2",8030.64,8028.67,8034.41
"3",8032.97,8034.11,8033.9