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
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.
,,"1","2","3"
Processor,,Intel Core i5-8400 @ 4.00GHz (6 Cores),Intel Core i5-8400 @ 4.00GHz (6 Cores),Intel Core i5-8400 @ 4.00GHz (6 Cores)
Motherboard,,MSI Z370M MORTAR (MS-7B54) v1.0 (1.80 BIOS),MSI Z370M MORTAR (MS-7B54) v1.0 (1.80 BIOS),MSI Z370M MORTAR (MS-7B54) v1.0 (1.80 BIOS)
Chipset,,Intel 8th Gen Core,Intel 8th Gen Core,Intel 8th Gen Core
Memory,,8GB,8GB,8GB
Disk,,512GB INTEL SSDPEKNW512G8,512GB INTEL SSDPEKNW512G8,512GB INTEL SSDPEKNW512G8
Graphics,,MSI Intel UHD 630 3GB (1050MHz),MSI Intel UHD 630 3GB (1050MHz),MSI Intel UHD 630 3GB (1050MHz)
Audio,,Realtek ALC892,Realtek ALC892,Realtek ALC892
Monitor,,DELL S2409W,DELL S2409W,DELL S2409W
Network,,Intel I219-V,Intel I219-V,Intel I219-V
OS,,Ubuntu 20.04,Ubuntu 20.04,Ubuntu 20.04
Kernel,,5.9.0-050900rc7daily20200929-generic (x86_64) 20200928,5.9.0-050900rc7daily20200929-generic (x86_64) 20200928,5.9.0-050900rc7daily20200929-generic (x86_64) 20200928
Desktop,,GNOME Shell 3.36.4,GNOME Shell 3.36.4,GNOME Shell 3.36.4
Display Server,,X Server 1.20.9,X Server 1.20.9,X Server 1.20.9
OpenGL,,4.6 Mesa 20.0.8,4.6 Mesa 20.0.8,4.6 Mesa 20.0.8
Compiler,,GCC 9.3.0,GCC 9.3.0,GCC 9.3.0
File-System,,ext4,ext4,ext4
Screen Resolution,,1920x1080,1920x1080,1920x1080
,,"1","2","3"
"Sysbench - Test: CPU (Events/sec)",HIB,8027.05,8031.24,8033.66
"SVT-HEVC - Tuning: 1 - Input: Bosphorus 1080p (FPS)",HIB,4.31,4.32,4.28
"SVT-HEVC - Tuning: 7 - Input: Bosphorus 1080p (FPS)",HIB,63.17,63.20,63.33
"SVT-HEVC - Tuning: 10 - Input: Bosphorus 1080p (FPS)",HIB,132.86,132.44,133.08
"SVT-VP9 - Tuning: VMAF Optimized - Input: Bosphorus 1080p (FPS)",HIB,116.51,116.36,116.64
"SVT-VP9 - Tuning: PSNR/SSIM Optimized - Input: Bosphorus 1080p (FPS)",HIB,117.74,117.96,117.88
"SVT-VP9 - Tuning: Visual Quality Optimized - Input: Bosphorus 1080p (FPS)",HIB,94.87,94.91,94.55
"Sysbench - Test: RAM / Memory (MiB/sec)",HIB,12559.86,12654.75,12635.66
"Stockfish - Total Time (Nodes/s)",HIB,12423645,12462066,12596102
"oneDNN - Harness: IP Shapes 1D - Data Type: f32 - Engine: CPU (ms)",LIB,5.38261,5.41408,5.35508
"oneDNN - Harness: IP Shapes 3D - Data Type: f32 - Engine: CPU (ms)",LIB,10.5166,10.3376,10.5981
"oneDNN - Harness: IP Shapes 1D - Data Type: u8s8f32 - Engine: CPU (ms)",LIB,3.32381,3.32302,3.32685
"oneDNN - Harness: IP Shapes 3D - Data Type: u8s8f32 - Engine: CPU (ms)",LIB,2.14099,2.14355,2.13409
"oneDNN - Harness: Convolution Batch Shapes Auto - Data Type: f32 - Engine: CPU (ms)",LIB,20.5263,20.5156,20.5318
"oneDNN - Harness: Deconvolution Batch shapes_1d - Data Type: f32 - Engine: CPU (ms)",LIB,7.38112,7.36038,7.35392
"oneDNN - Harness: Deconvolution Batch shapes_3d - Data Type: f32 - Engine: CPU (ms)",LIB,9.41175,9.43695,9.42173
"oneDNN - Harness: Convolution Batch Shapes Auto - Data Type: u8s8f32 - Engine: CPU (ms)",LIB,15.8780,15.8402,15.8777
"oneDNN - Harness: Deconvolution Batch shapes_1d - Data Type: u8s8f32 - Engine: CPU (ms)",LIB,3.16664,3.17003,3.17132
"oneDNN - Harness: Deconvolution Batch shapes_3d - Data Type: u8s8f32 - Engine: CPU (ms)",LIB,6.34104,6.34022,6.36246
"oneDNN - Harness: Recurrent Neural Network Training - Data Type: f32 - Engine: CPU (ms)",LIB,4629.05,4526.88,4560.44
"oneDNN - Harness: Recurrent Neural Network Inference - Data Type: f32 - Engine: CPU (ms)",LIB,2569.74,2556.44,2560.05
"oneDNN - Harness: Recurrent Neural Network Training - Data Type: u8s8f32 - Engine: CPU (ms)",LIB,4618.45,4653.17,4629.21
"oneDNN - Harness: Recurrent Neural Network Inference - Data Type: u8s8f32 - Engine: CPU (ms)",LIB,2557.47,2601.07,2568.63
"oneDNN - Harness: Matrix Multiply Batch Shapes Transformer - Data Type: f32 - Engine: CPU (ms)",LIB,3.75357,3.75446,3.75387
"oneDNN - Harness: Recurrent Neural Network Training - Data Type: bf16bf16bf16 - Engine: CPU (ms)",LIB,4548.60,4647.00,4588.83
"oneDNN - Harness: Recurrent Neural Network Inference - Data Type: bf16bf16bf16 - Engine: CPU (ms)",LIB,2615.31,2598.32,2621.26
"oneDNN - Harness: Matrix Multiply Batch Shapes Transformer - Data Type: u8s8f32 - Engine: CPU (ms)",LIB,4.19566,4.18604,4.18462
"Xcompact3d Incompact3d - Input: input.i3d 129 Cells Per Direction (sec)",LIB,43.8697395,43.0112292,43.8241310
"Xcompact3d Incompact3d - Input: input.i3d 193 Cells Per Direction (sec)",LIB,150.887232,149.555781,150.497513
"Timed Mesa Compilation - Time To Compile (sec)",LIB,96.022,95.821,95.943
"Timed Node.js Compilation - Time To Compile (sec)",LIB,868.883,869.018,869.258