9400F mar Intel Core i5-9400F testing with a MSI B360M GAMING PLUS (MS-7B19) v1.0 (1.10 BIOS) and MSI NVIDIA NV106 1GB on Ubuntu 20.04 via the Phoronix Test Suite. 1: Processor: Intel Core i5-9400F @ 4.10GHz (6 Cores), Motherboard: MSI B360M GAMING PLUS (MS-7B19) v1.0 (1.10 BIOS), Chipset: Intel Cannon Lake PCH, Memory: 16GB, Disk: 256GB SAMSUNG MZVPW256HEGL-000H7, Graphics: MSI NVIDIA NV106 1GB, Audio: Realtek ALC887-VD, Monitor: G237HL, Network: Intel I219-V OS: Ubuntu 20.04, Kernel: 5.9.0-050900rc7daily20200928-generic (x86_64) 20200927, Desktop: GNOME Shell 3.36.0, Display Server: X Server 1.20.7, Display Driver: nouveau, OpenGL: 4.3 Mesa 20.0.2, Compiler: GCC 9.3.0, File-System: ext4, Screen Resolution: 1920x1080 2: Processor: Intel Core i5-9400F @ 4.10GHz (6 Cores), Motherboard: MSI B360M GAMING PLUS (MS-7B19) v1.0 (1.10 BIOS), Chipset: Intel Cannon Lake PCH, Memory: 16GB, Disk: 256GB SAMSUNG MZVPW256HEGL-000H7, Graphics: MSI NVIDIA NV106 1GB, Audio: Realtek ALC887-VD, Monitor: G237HL, Network: Intel I219-V OS: Ubuntu 20.04, Kernel: 5.9.0-050900rc7daily20200928-generic (x86_64) 20200927, Desktop: GNOME Shell 3.36.0, Display Server: X Server 1.20.7, Display Driver: nouveau, OpenGL: 4.3 Mesa 20.0.2, Compiler: GCC 9.3.0, File-System: ext4, Screen Resolution: 1920x1080 3: Processor: Intel Core i5-9400F @ 4.10GHz (6 Cores), Motherboard: MSI B360M GAMING PLUS (MS-7B19) v1.0 (1.10 BIOS), Chipset: Intel Cannon Lake PCH, Memory: 16GB, Disk: 256GB SAMSUNG MZVPW256HEGL-000H7, Graphics: MSI NVIDIA NV106 1GB, Audio: Realtek ALC887-VD, Monitor: G237HL, Network: Intel I219-V OS: Ubuntu 20.04, Kernel: 5.9.0-050900rc7daily20200928-generic (x86_64) 20200927, Desktop: GNOME Shell 3.36.0, Display Server: X Server 1.20.7, Display Driver: nouveau, OpenGL: 4.3 Mesa 20.0.2, Compiler: GCC 9.3.0, File-System: ext4, Screen Resolution: 1920x1080 4: Processor: Intel Core i5-9400F @ 4.10GHz (6 Cores), Motherboard: MSI B360M GAMING PLUS (MS-7B19) v1.0 (1.10 BIOS), Chipset: Intel Cannon Lake PCH, Memory: 16GB, Disk: 256GB SAMSUNG MZVPW256HEGL-000H7, Graphics: MSI NVIDIA NV106 1GB, Audio: Realtek ALC887-VD, Monitor: G237HL, Network: Intel I219-V OS: Ubuntu 20.04, Kernel: 5.9.0-050900rc7daily20200928-generic (x86_64) 20200927, Desktop: GNOME Shell 3.36.0, Display Server: X Server 1.20.7, Display Driver: nouveau, OpenGL: 4.3 Mesa 20.0.2, Compiler: GCC 9.3.0, File-System: ext4, Screen Resolution: 1920x1080 Xcompact3d Incompact3d 2021-03-11 Input: input.i3d 129 Cells Per Direction Seconds < Lower Is Better 1 . 50.82 |================================================================= 2 . 52.49 |==================================================================== 3 . 51.30 |================================================================== 4 . 52.87 |==================================================================== Xcompact3d Incompact3d 2021-03-11 Input: input.i3d 192 Cells Per Direction Seconds < Lower Is Better 1 . 455.44 |================================================================== 2 . 457.69 |=================================================================== 3 . 457.61 |=================================================================== 4 . 459.69 |=================================================================== simdjson 0.8.2 Throughput Test: Kostya GB/s > Higher Is Better 1 . 2.54 |===================================================================== 2 . 2.55 |===================================================================== 3 . 2.54 |===================================================================== 4 . 2.54 |===================================================================== simdjson 0.8.2 Throughput Test: LargeRandom GB/s > Higher Is Better 1 . 0.87 |==================================================================== 2 . 0.87 |==================================================================== 3 . 0.88 |===================================================================== 4 . 0.87 |==================================================================== simdjson 0.8.2 Throughput Test: PartialTweets GB/s > Higher Is Better 1 . 3.60 |===================================================================== 2 . 3.60 |===================================================================== 3 . 3.60 |===================================================================== 4 . 3.60 |===================================================================== simdjson 0.8.2 Throughput Test: DistinctUserID GB/s > Higher Is Better 1 . 3.74 |===================================================================== 2 . 3.74 |===================================================================== 3 . 3.74 |===================================================================== 4 . 3.73 |===================================================================== AOM AV1 2.1-rc Encoder Mode: Speed 0 Two-Pass Frames Per Second > Higher Is Better 1 . 0.19 |===================================================================== 2 . 0.19 |===================================================================== 3 . 0.19 |===================================================================== 4 . 0.19 |===================================================================== AOM AV1 2.1-rc Encoder Mode: Speed 4 Two-Pass Frames Per Second > Higher Is Better 1 . 4.78 |===================================================================== 2 . 4.76 |===================================================================== 3 . 4.76 |===================================================================== 4 . 4.76 |===================================================================== AOM AV1 2.1-rc Encoder Mode: Speed 6 Realtime Frames Per Second > Higher Is Better 1 . 16.36 |==================================================================== 2 . 16.28 |==================================================================== 3 . 16.28 |==================================================================== 4 . 16.24 |==================================================================== AOM AV1 2.1-rc Encoder Mode: Speed 6 Two-Pass Frames Per Second > Higher Is Better 1 . 13.23 |==================================================================== 2 . 13.21 |==================================================================== 3 . 13.21 |==================================================================== 4 . 13.20 |==================================================================== AOM AV1 2.1-rc Encoder Mode: Speed 8 Realtime Frames Per Second > Higher Is Better 1 . 79.67 |==================================================================== 2 . 78.92 |=================================================================== 3 . 78.85 |=================================================================== 4 . 78.36 |=================================================================== SVT-HEVC 1.5.0 Tuning: 1 - Input: Bosphorus 1080p Frames Per Second > Higher Is Better 1 . 4.39 |===================================================================== 2 . 4.39 |===================================================================== 3 . 4.39 |===================================================================== 4 . 4.38 |===================================================================== SVT-HEVC 1.5.0 Tuning: 7 - Input: Bosphorus 1080p Frames Per Second > Higher Is Better 1 . 63.38 |==================================================================== 2 . 63.31 |==================================================================== 3 . 63.26 |==================================================================== 4 . 63.20 |==================================================================== SVT-HEVC 1.5.0 Tuning: 10 - Input: Bosphorus 1080p Frames Per Second > Higher Is Better 1 . 130.50 |=================================================================== 2 . 130.96 |=================================================================== 3 . 130.43 |=================================================================== 4 . 130.15 |=================================================================== SVT-VP9 0.3 Tuning: VMAF Optimized - Input: Bosphorus 1080p Frames Per Second > Higher Is Better 1 . 114.66 |=================================================================== 2 . 114.39 |=================================================================== 3 . 114.20 |=================================================================== 4 . 113.07 |================================================================== SVT-VP9 0.3 Tuning: PSNR/SSIM Optimized - Input: Bosphorus 1080p Frames Per Second > Higher Is Better 1 . 115.10 |=================================================================== 2 . 115.03 |=================================================================== 3 . 114.40 |=================================================================== 4 . 113.34 |================================================================== SVT-VP9 0.3 Tuning: Visual Quality Optimized - Input: Bosphorus 1080p Frames Per Second > Higher Is Better 1 . 93.79 |==================================================================== 2 . 93.46 |==================================================================== 3 . 93.81 |==================================================================== 4 . 93.23 |==================================================================== oneDNN 2.1.2 Harness: IP Shapes 1D - Data Type: f32 - Engine: CPU ms < Lower Is Better 1 . 5.74885 |============================================================== 2 . 6.08745 |================================================================== 3 . 6.10535 |================================================================== 4 . 6.08841 |================================================================== oneDNN 2.1.2 Harness: IP Shapes 3D - Data Type: f32 - Engine: CPU ms < Lower Is Better 1 . 9.33806 |============================================= 2 . 12.51330 |============================================================ 3 . 12.67190 |============================================================= 4 . 13.58880 |================================================================= oneDNN 2.1.2 Harness: IP Shapes 1D - Data Type: u8s8f32 - Engine: CPU ms < Lower Is Better 1 . 3.31567 |================================================================== 2 . 3.31990 |================================================================== 3 . 3.31794 |================================================================== 4 . 3.32207 |================================================================== oneDNN 2.1.2 Harness: IP Shapes 3D - Data Type: u8s8f32 - Engine: CPU ms < Lower Is Better 1 . 2.35835 |============================================================== 2 . 2.51852 |================================================================== 3 . 2.51603 |================================================================== 4 . 2.50818 |================================================================== oneDNN 2.1.2 Harness: Convolution Batch Shapes Auto - Data Type: f32 - Engine: CPU ms < Lower Is Better 1 . 24.10 |================================================================= 2 . 24.93 |=================================================================== 3 . 25.02 |==================================================================== 4 . 25.16 |==================================================================== oneDNN 2.1.2 Harness: Deconvolution Batch shapes_1d - Data Type: f32 - Engine: CPU ms < Lower Is Better 1 . 7.28655 |================================================================== 2 . 7.25209 |================================================================== 3 . 7.24862 |================================================================== 4 . 7.25760 |================================================================== oneDNN 2.1.2 Harness: Deconvolution Batch shapes_3d - Data Type: f32 - Engine: CPU ms < Lower Is Better 1 . 9.42941 |================================================================= 2 . 9.55913 |================================================================== 3 . 9.50810 |================================================================== 4 . 9.39419 |================================================================= oneDNN 2.1.2 Harness: Convolution Batch Shapes Auto - Data Type: u8s8f32 - Engine: CPU ms < Lower Is Better 1 . 18.16 |=============================================================== 2 . 19.05 |================================================================== 3 . 19.15 |=================================================================== 4 . 19.52 |==================================================================== oneDNN 2.1.2 Harness: Deconvolution Batch shapes_1d - Data Type: u8s8f32 - Engine: CPU ms < Lower Is Better 1 . 3.11447 |================================================================== 2 . 3.13783 |================================================================== 3 . 3.12549 |================================================================== 4 . 3.11856 |================================================================== oneDNN 2.1.2 Harness: Deconvolution Batch shapes_3d - Data Type: u8s8f32 - Engine: CPU ms < Lower Is Better 1 . 6.31785 |================================================================== 2 . 6.24856 |================================================================= 3 . 6.28776 |================================================================== 4 . 6.21044 |================================================================= oneDNN 2.1.2 Harness: Recurrent Neural Network Training - Data Type: f32 - Engine: CPU ms < Lower Is Better 1 . 4687.02 |================================================================= 2 . 4739.81 |================================================================== 3 . 4742.25 |================================================================== 4 . 4775.31 |================================================================== oneDNN 2.1.2 Harness: Recurrent Neural Network Inference - Data Type: f32 - Engine: CPU ms < Lower Is Better 1 . 2712.79 |================================================================ 2 . 2746.26 |================================================================= 3 . 2755.81 |================================================================= 4 . 2785.40 |================================================================== oneDNN 2.1.2 Harness: Recurrent Neural Network Training - Data Type: u8s8f32 - Engine: CPU ms < Lower Is Better 1 . 4693.82 |================================================================ 2 . 4750.44 |================================================================= 3 . 4748.24 |================================================================= 4 . 4822.05 |================================================================== oneDNN 2.1.2 Harness: Recurrent Neural Network Inference - Data Type: u8s8f32 - Engine: CPU ms < Lower Is Better 1 . 2710.16 |================================================================ 2 . 2750.23 |================================================================= 3 . 2758.35 |================================================================== 4 . 2776.61 |================================================================== oneDNN 2.1.2 Harness: Matrix Multiply Batch Shapes Transformer - Data Type: f32 - Engine: CPU ms < Lower Is Better 1 . 4.43829 |================================================================ 2 . 4.59147 |================================================================== 3 . 4.59240 |================================================================== 4 . 4.58797 |================================================================== oneDNN 2.1.2 Harness: Recurrent Neural Network Training - Data Type: bf16bf16bf16 - Engine: CPU ms < Lower Is Better 1 . 4688.65 |================================================================= 2 . 4745.82 |================================================================= 3 . 4750.15 |================================================================== 4 . 4784.78 |================================================================== oneDNN 2.1.2 Harness: Recurrent Neural Network Inference - Data Type: bf16bf16bf16 - Engine: CPU ms < Lower Is Better 1 . 2716.89 |================================================================= 2 . 2750.92 |================================================================= 3 . 2756.81 |================================================================= 4 . 2778.13 |================================================================== oneDNN 2.1.2 Harness: Matrix Multiply Batch Shapes Transformer - Data Type: u8s8f32 - Engine: CPU ms < Lower Is Better 1 . 4.95866 |================================================================== 2 . 4.96304 |================================================================== 3 . 4.95866 |================================================================== 4 . 4.96107 |================================================================== ASTC Encoder 2.4 Preset: Medium Seconds < Lower Is Better 1 . 8.1425 |=================================================================== 2 . 8.1432 |=================================================================== 3 . 8.1480 |=================================================================== 4 . 8.1484 |=================================================================== ASTC Encoder 2.4 Preset: Thorough Seconds < Lower Is Better 1 . 27.22 |==================================================================== 2 . 27.22 |==================================================================== 3 . 27.23 |==================================================================== 4 . 27.23 |==================================================================== ASTC Encoder 2.4 Preset: Exhaustive Seconds < Lower Is Better 1 . 208.43 |=================================================================== 2 . 208.47 |=================================================================== 3 . 208.54 |=================================================================== 4 . 208.47 |=================================================================== Basis Universal 1.13 Settings: ETC1S Seconds < Lower Is Better 1 . 32.52 |==================================================================== 2 . 32.57 |==================================================================== 3 . 32.55 |==================================================================== 4 . 32.59 |==================================================================== Basis Universal 1.13 Settings: UASTC Level 0 Seconds < Lower Is Better 1 . 9.753 |==================================================================== 2 . 9.772 |==================================================================== 3 . 9.767 |==================================================================== 4 . 9.795 |==================================================================== Basis Universal 1.13 Settings: UASTC Level 2 Seconds < Lower Is Better 1 . 53.51 |==================================================================== 2 . 53.53 |==================================================================== 3 . 53.53 |==================================================================== 4 . 53.55 |==================================================================== Basis Universal 1.13 Settings: UASTC Level 3 Seconds < Lower Is Better 1 . 106.52 |=================================================================== 2 . 106.47 |=================================================================== 3 . 106.54 |=================================================================== 4 . 106.52 |=================================================================== Mobile Neural Network 1.1.3 Model: SqueezeNetV1.0 ms < Lower Is Better 1 . 5.302 |==================================================================== 2 . 5.285 |==================================================================== 3 . 5.307 |==================================================================== 4 . 5.272 |==================================================================== Mobile Neural Network 1.1.3 Model: resnet-v2-50 ms < Lower Is Better 1 . 26.95 |==================================================================== 2 . 26.93 |==================================================================== 3 . 27.02 |==================================================================== 4 . 26.98 |==================================================================== Mobile Neural Network 1.1.3 Model: MobileNetV2_224 ms < Lower Is Better 1 . 3.347 |=================================================================== 2 . 3.372 |==================================================================== 3 . 3.396 |==================================================================== 4 . 3.389 |==================================================================== Mobile Neural Network 1.1.3 Model: mobilenet-v1-1.0 ms < Lower Is Better 1 . 3.509 |==================================================================== 2 . 3.507 |==================================================================== 3 . 3.522 |==================================================================== 4 . 3.502 |==================================================================== Mobile Neural Network 1.1.3 Model: inception-v3 ms < Lower Is Better 1 . 31.72 |==================================================================== 2 . 31.70 |==================================================================== 3 . 31.83 |==================================================================== 4 . 31.58 |=================================================================== Sysbench 1.0.20 Test: RAM / Memory MiB/sec > Higher Is Better 1 . 12977.84 |================================================================ 2 . 12774.42 |=============================================================== 3 . 13109.86 |================================================================ 4 . 13237.06 |================================================================= Sysbench 1.0.20 Test: CPU Events Per Second > Higher Is Better 1 . 8221.43 |================================================================== 2 . 8047.96 |================================================================= 3 . 8211.92 |================================================================== 4 . 8218.83 |================================================================== Timed Mesa Compilation 21.0 Time To Compile Seconds < Lower Is Better 1 . 99.74 |==================================================================== 2 . 98.71 |=================================================================== 3 . 98.77 |=================================================================== 4 . 99.02 |==================================================================== Timed Node.js Compilation 15.11 Time To Compile Seconds < Lower Is Better 1 . 890.18 |=================================================================== 2 . 890.01 |=================================================================== 4 . 891.24 |===================================================================