new tests 10100 Intel Core i3-10100 testing with a Gigabyte B460M DS3H (F2 BIOS) and Gigabyte Intel UHD 630 3GB on Ubuntu 20.04 via the Phoronix Test Suite. 1: Processor: Intel Core i3-10100 @ 4.30GHz (4 Cores / 8 Threads), Motherboard: Gigabyte B460M DS3H (F2 BIOS), Chipset: Intel Device 9b63, Memory: 16GB, Disk: 500GB Western Digital WDS500G3X0C-00SJG0, Graphics: Gigabyte Intel UHD 630 3GB (1100MHz), Audio: Realtek ALC887-VD, Monitor: G237HL, Network: Realtek RTL8111/8168/8411 OS: Ubuntu 20.04, Kernel: 5.9.0-050900rc7daily20201002-generic (x86_64) 20201001, Desktop: GNOME Shell 3.36.3, Display Server: X Server 1.20.8, OpenGL: 4.6 Mesa 20.0.8, Vulkan: 1.2.131, Compiler: GCC 9.3.0, File-System: ext4, Screen Resolution: 1920x1080 2: Processor: Intel Core i3-10100 @ 4.30GHz (4 Cores / 8 Threads), Motherboard: Gigabyte B460M DS3H (F2 BIOS), Chipset: Intel Device 9b63, Memory: 16GB, Disk: 500GB Western Digital WDS500G3X0C-00SJG0, Graphics: Gigabyte Intel UHD 630 3GB (1100MHz), Audio: Realtek ALC887-VD, Monitor: G237HL, Network: Realtek RTL8111/8168/8411 OS: Ubuntu 20.04, Kernel: 5.9.0-050900rc7daily20201002-generic (x86_64) 20201001, Desktop: GNOME Shell 3.36.3, Display Server: X Server 1.20.8, OpenGL: 4.6 Mesa 20.0.8, Vulkan: 1.2.131, Compiler: GCC 9.3.0, File-System: ext4, Screen Resolution: 1920x1080 3: Processor: Intel Core i3-10100 @ 4.30GHz (4 Cores / 8 Threads), Motherboard: Gigabyte B460M DS3H (F2 BIOS), Chipset: Intel Device 9b63, Memory: 16GB, Disk: 500GB Western Digital WDS500G3X0C-00SJG0, Graphics: Gigabyte Intel UHD 630 3GB (1100MHz), Audio: Realtek ALC887-VD, Monitor: G237HL, Network: Realtek RTL8111/8168/8411 OS: Ubuntu 20.04, Kernel: 5.9.0-050900rc7daily20201002-generic (x86_64) 20201001, Desktop: GNOME Shell 3.36.3, Display Server: X Server 1.20.8, OpenGL: 4.6 Mesa 20.0.8, Vulkan: 1.2.131, Compiler: GCC 9.3.0, File-System: ext4, Screen Resolution: 1920x1080 simdjson 0.8.2 Throughput Test: Kostya GB/s > Higher Is Better 1 . 2.75 |===================================================================== 2 . 2.75 |===================================================================== 3 . 2.75 |===================================================================== simdjson 0.8.2 Throughput Test: LargeRandom GB/s > Higher Is Better 1 . 0.98 |===================================================================== 2 . 0.98 |===================================================================== 3 . 0.98 |===================================================================== simdjson 0.8.2 Throughput Test: PartialTweets GB/s > Higher Is Better 1 . 3.86 |===================================================================== 2 . 3.86 |===================================================================== 3 . 3.86 |===================================================================== simdjson 0.8.2 Throughput Test: DistinctUserID GB/s > Higher Is Better 1 . 4.39 |===================================================================== 2 . 4.40 |===================================================================== 3 . 4.40 |===================================================================== AOM AV1 2.1-rc Encoder Mode: Speed 0 Two-Pass Frames Per Second > Higher Is Better 1 . 0.17 |===================================================================== 2 . 0.17 |===================================================================== 3 . 0.17 |===================================================================== AOM AV1 2.1-rc Encoder Mode: Speed 4 Two-Pass Frames Per Second > Higher Is Better 1 . 4.12 |===================================================================== 2 . 4.12 |===================================================================== 3 . 4.12 |===================================================================== AOM AV1 2.1-rc Encoder Mode: Speed 6 Realtime Frames Per Second > Higher Is Better 1 . 13.69 |==================================================================== 2 . 13.63 |==================================================================== 3 . 13.61 |==================================================================== AOM AV1 2.1-rc Encoder Mode: Speed 6 Two-Pass Frames Per Second > Higher Is Better 1 . 10.83 |==================================================================== 2 . 10.78 |==================================================================== 3 . 10.79 |==================================================================== AOM AV1 2.1-rc Encoder Mode: Speed 8 Realtime Frames Per Second > Higher Is Better 1 . 70.25 |==================================================================== 2 . 69.58 |=================================================================== 3 . 69.15 |=================================================================== SVT-HEVC 1.5.0 Tuning: 1 - Input: Bosphorus 1080p Frames Per Second > Higher Is Better 1 . 3.41 |===================================================================== 2 . 3.41 |===================================================================== 3 . 3.41 |===================================================================== SVT-HEVC 1.5.0 Tuning: 7 - Input: Bosphorus 1080p Frames Per Second > Higher Is Better 1 . 52.19 |==================================================================== 2 . 52.12 |==================================================================== 3 . 52.09 |==================================================================== SVT-HEVC 1.5.0 Tuning: 10 - Input: Bosphorus 1080p Frames Per Second > Higher Is Better 1 . 111.02 |=================================================================== 2 . 111.06 |=================================================================== 3 . 111.19 |=================================================================== SVT-VP9 0.3 Tuning: VMAF Optimized - Input: Bosphorus 1080p Frames Per Second > Higher Is Better 1 . 95.27 |==================================================================== 2 . 95.50 |==================================================================== 3 . 94.94 |==================================================================== SVT-VP9 0.3 Tuning: PSNR/SSIM Optimized - Input: Bosphorus 1080p Frames Per Second > Higher Is Better 1 . 95.79 |==================================================================== 2 . 95.70 |==================================================================== 3 . 95.34 |==================================================================== SVT-VP9 0.3 Tuning: Visual Quality Optimized - Input: Bosphorus 1080p Frames Per Second > Higher Is Better 1 . 77.94 |==================================================================== 2 . 77.75 |==================================================================== 3 . 77.79 |==================================================================== oneDNN 2.1.2 Harness: IP Shapes 1D - Data Type: f32 - Engine: CPU ms < Lower Is Better 1 . 8.01920 |=============================================================== 2 . 8.40432 |================================================================== 3 . 8.39119 |================================================================== oneDNN 2.1.2 Harness: IP Shapes 3D - Data Type: f32 - Engine: CPU ms < Lower Is Better 1 . 14.89 |======================================================== 2 . 16.89 |================================================================ 3 . 17.98 |==================================================================== oneDNN 2.1.2 Harness: IP Shapes 1D - Data Type: u8s8f32 - Engine: CPU ms < Lower Is Better 1 . 3.24044 |================================================================== 2 . 3.24580 |================================================================== 3 . 3.23483 |================================================================== oneDNN 2.1.2 Harness: IP Shapes 3D - Data Type: u8s8f32 - Engine: CPU ms < Lower Is Better 1 . 2.76784 |========================================================== 2 . 3.05182 |================================================================ 3 . 3.14284 |================================================================== oneDNN 2.1.2 Harness: Convolution Batch Shapes Auto - Data Type: f32 - Engine: CPU ms < Lower Is Better 1 . 31.31 |================================================================== 2 . 31.97 |==================================================================== 3 . 32.10 |==================================================================== oneDNN 2.1.2 Harness: Deconvolution Batch shapes_1d - Data Type: f32 - Engine: CPU ms < Lower Is Better 1 . 13.67 |==================================================================== 2 . 13.57 |==================================================================== 3 . 13.56 |=================================================================== oneDNN 2.1.2 Harness: Deconvolution Batch shapes_3d - Data Type: f32 - Engine: CPU ms < Lower Is Better 1 . 13.04 |=================================================================== 2 . 13.13 |=================================================================== 3 . 13.27 |==================================================================== oneDNN 2.1.2 Harness: Convolution Batch Shapes Auto - Data Type: u8s8f32 - Engine: CPU ms < Lower Is Better 1 . 22.33 |================================================================ 2 . 23.32 |================================================================== 3 . 23.85 |==================================================================== oneDNN 2.1.2 Harness: Deconvolution Batch shapes_1d - Data Type: u8s8f32 - Engine: CPU ms < Lower Is Better 1 . 4.33807 |================================================================== 2 . 4.36837 |================================================================== 3 . 4.35157 |================================================================== oneDNN 2.1.2 Harness: Deconvolution Batch shapes_3d - Data Type: u8s8f32 - Engine: CPU ms < Lower Is Better 1 . 7.72740 |================================================================== 2 . 7.69929 |================================================================== 3 . 7.71760 |================================================================== oneDNN 2.1.2 Harness: Recurrent Neural Network Training - Data Type: f32 - Engine: CPU ms < Lower Is Better 1 . 6812.98 |================================================================== 2 . 6834.92 |================================================================== 3 . 6848.51 |================================================================== oneDNN 2.1.2 Harness: Recurrent Neural Network Inference - Data Type: f32 - Engine: CPU ms < Lower Is Better 1 . 3677.20 |================================================================= 2 . 3705.86 |================================================================= 3 . 3745.04 |================================================================== oneDNN 2.1.2 Harness: Recurrent Neural Network Training - Data Type: u8s8f32 - Engine: CPU ms < Lower Is Better 1 . 6820.53 |================================================================== 2 . 6844.29 |================================================================== 3 . 6856.43 |================================================================== oneDNN 2.1.2 Harness: Recurrent Neural Network Inference - Data Type: u8s8f32 - Engine: CPU ms < Lower Is Better 1 . 3682.83 |================================================================= 2 . 3697.20 |================================================================= 3 . 3742.78 |================================================================== oneDNN 2.1.2 Harness: Matrix Multiply Batch Shapes Transformer - Data Type: f32 - Engine: CPU ms < Lower Is Better 1 . 5.72882 |=============================================================== 2 . 5.98850 |================================================================== 3 . 6.03398 |================================================================== oneDNN 2.1.2 Harness: Recurrent Neural Network Training - Data Type: bf16bf16bf16 - Engine: CPU ms < Lower Is Better 1 . 6818.43 |================================================================== 2 . 6832.77 |================================================================== 3 . 6850.64 |================================================================== oneDNN 2.1.2 Harness: Recurrent Neural Network Inference - Data Type: bf16bf16bf16 - Engine: CPU ms < Lower Is Better 1 . 3683.18 |================================================================= 2 . 3719.36 |================================================================== 3 . 3730.87 |================================================================== oneDNN 2.1.2 Harness: Matrix Multiply Batch Shapes Transformer - Data Type: u8s8f32 - Engine: CPU ms < Lower Is Better 1 . 5.70520 |================================================================== 2 . 5.70073 |================================================================== 3 . 5.70977 |================================================================== ASTC Encoder 2.4 Preset: Medium Seconds < Lower Is Better 1 . 7.7726 |=================================================================== 2 . 7.7786 |=================================================================== 3 . 7.7849 |=================================================================== ASTC Encoder 2.4 Preset: Thorough Seconds < Lower Is Better 1 . 29.91 |==================================================================== 2 . 29.92 |==================================================================== 3 . 29.91 |==================================================================== ASTC Encoder 2.4 Preset: Exhaustive Seconds < Lower Is Better 1 . 232.17 |=================================================================== 2 . 232.17 |=================================================================== 3 . 232.19 |=================================================================== Basis Universal 1.13 Settings: ETC1S Seconds < Lower Is Better 1 . 32.48 |==================================================================== 2 . 32.59 |==================================================================== 3 . 32.52 |==================================================================== Basis Universal 1.13 Settings: UASTC Level 0 Seconds < Lower Is Better 1 . 9.469 |==================================================================== 2 . 9.469 |==================================================================== 3 . 9.479 |==================================================================== Basis Universal 1.13 Settings: UASTC Level 2 Seconds < Lower Is Better 1 . 64.79 |==================================================================== 2 . 64.78 |==================================================================== 3 . 64.78 |==================================================================== Basis Universal 1.13 Settings: UASTC Level 3 Seconds < Lower Is Better 1 . 128.18 |=================================================================== 2 . 128.19 |=================================================================== 3 . 128.19 |=================================================================== Mobile Neural Network 1.1.3 Model: SqueezeNetV1.0 ms < Lower Is Better 1 . 6.761 |=================================================================== 2 . 6.800 |=================================================================== 3 . 6.879 |==================================================================== Mobile Neural Network 1.1.3 Model: resnet-v2-50 ms < Lower Is Better 1 . 37.00 |=================================================================== 2 . 37.25 |==================================================================== 3 . 37.49 |==================================================================== Mobile Neural Network 1.1.3 Model: MobileNetV2_224 ms < Lower Is Better 1 . 4.010 |==================================================================== 2 . 3.999 |==================================================================== 3 . 3.986 |==================================================================== Mobile Neural Network 1.1.3 Model: mobilenet-v1-1.0 ms < Lower Is Better 1 . 4.333 |==================================================================== 2 . 4.335 |==================================================================== 3 . 4.324 |==================================================================== Mobile Neural Network 1.1.3 Model: inception-v3 ms < Lower Is Better 1 . 47.72 |=================================================================== 2 . 48.37 |==================================================================== 3 . 48.43 |==================================================================== Sysbench 1.0.20 Test: RAM / Memory MiB/sec > Higher Is Better 1 . 17506.93 |================================================================ 2 . 17505.23 |================================================================ 3 . 17728.82 |================================================================= Sysbench 1.0.20 Test: CPU Events Per Second > Higher Is Better 1 . 8712.01 |================================================================== 2 . 8711.53 |================================================================== 3 . 8712.57 |==================================================================