Xeon E3 1280 v5 m Intel Xeon E3-1280 v5 testing with a MSI Z170A SLI PLUS (MS-7998) v1.0 (2.A0 BIOS) and ASUS AMD Radeon HD 7850 / R7 265 R9 270 1024SP on Ubuntu 20.04 via the Phoronix Test Suite. 1: Processor: Intel Xeon E3-1280 v5 @ 4.00GHz (4 Cores / 8 Threads), Motherboard: MSI Z170A SLI PLUS (MS-7998) v1.0 (2.A0 BIOS), Chipset: Intel Xeon E3-1200 v5/E3-1500, Memory: 32GB, Disk: 256GB TOSHIBA RD400, Graphics: ASUS AMD Radeon HD 7850 / R7 265 R9 270 1024SP, Audio: Realtek ALC1150, Monitor: VA2431, Network: Intel I219-V OS: Ubuntu 20.04, Kernel: 5.9.0-050900rc2daily20200826-generic (x86_64) 20200825, Desktop: GNOME Shell 3.36.4, Display Server: X Server 1.20.9, OpenGL: 4.5 Mesa 20.0.8 (LLVM 10.0.0), Compiler: GCC 9.3.0, File-System: ext4, Screen Resolution: 1920x1080 2: Processor: Intel Xeon E3-1280 v5 @ 4.00GHz (4 Cores / 8 Threads), Motherboard: MSI Z170A SLI PLUS (MS-7998) v1.0 (2.A0 BIOS), Chipset: Intel Xeon E3-1200 v5/E3-1500, Memory: 32GB, Disk: 256GB TOSHIBA RD400, Graphics: ASUS AMD Radeon HD 7850 / R7 265 R9 270 1024SP, Audio: Realtek ALC1150, Monitor: VA2431, Network: Intel I219-V OS: Ubuntu 20.04, Kernel: 5.9.0-050900rc2daily20200826-generic (x86_64) 20200825, Desktop: GNOME Shell 3.36.4, Display Server: X Server 1.20.9, OpenGL: 4.5 Mesa 20.0.8 (LLVM 10.0.0), Compiler: GCC 9.3.0, File-System: ext4, Screen Resolution: 1920x1080 3: Processor: Intel Xeon E3-1280 v5 @ 4.00GHz (4 Cores / 8 Threads), Motherboard: MSI Z170A SLI PLUS (MS-7998) v1.0 (2.A0 BIOS), Chipset: Intel Xeon E3-1200 v5/E3-1500, Memory: 32GB, Disk: 256GB TOSHIBA RD400, Graphics: ASUS AMD Radeon HD 7850 / R7 265 R9 270 1024SP, Audio: Realtek ALC1150, Monitor: VA2431, Network: Intel I219-V OS: Ubuntu 20.04, Kernel: 5.9.0-050900rc2daily20200826-generic (x86_64) 20200825, Desktop: GNOME Shell 3.36.4, Display Server: X Server 1.20.9, OpenGL: 4.5 Mesa 20.0.8 (LLVM 10.0.0), 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 . 59.77 |==================================================================== 2 . 59.86 |==================================================================== 3 . 59.83 |==================================================================== Xcompact3d Incompact3d 2021-03-11 Input: input.i3d 193 Cells Per Direction Seconds < Lower Is Better 1 . 203.09 |=================================================================== 2 . 202.93 |=================================================================== 3 . 203.14 |=================================================================== simdjson 0.8.2 Throughput Test: Kostya GB/s > Higher Is Better 1 . 2.36 |===================================================================== 2 . 2.36 |===================================================================== 3 . 2.36 |===================================================================== simdjson 0.8.2 Throughput Test: LargeRandom GB/s > Higher Is Better 1 . 0.88 |===================================================================== 2 . 0.88 |===================================================================== 3 . 0.88 |===================================================================== simdjson 0.8.2 Throughput Test: PartialTweets GB/s > Higher Is Better 1 . 3.52 |===================================================================== 2 . 3.53 |===================================================================== 3 . 3.52 |===================================================================== simdjson 0.8.2 Throughput Test: DistinctUserID GB/s > Higher Is Better 1 . 3.99 |===================================================================== 2 . 3.98 |===================================================================== 3 . 3.98 |===================================================================== AOM AV1 2.1-rc Encoder Mode: Speed 0 Two-Pass Frames Per Second > Higher Is Better 1 . 0.16 |===================================================================== 2 . 0.16 |===================================================================== 3 . 0.16 |===================================================================== AOM AV1 2.1-rc Encoder Mode: Speed 4 Two-Pass Frames Per Second > Higher Is Better 1 . 3.79 |===================================================================== 2 . 3.79 |===================================================================== 3 . 3.80 |===================================================================== AOM AV1 2.1-rc Encoder Mode: Speed 6 Realtime Frames Per Second > Higher Is Better 1 . 12.31 |==================================================================== 2 . 12.33 |==================================================================== 3 . 12.35 |==================================================================== AOM AV1 2.1-rc Encoder Mode: Speed 6 Two-Pass Frames Per Second > Higher Is Better 1 . 9.87 |===================================================================== 2 . 9.86 |===================================================================== 3 . 9.84 |===================================================================== AOM AV1 2.1-rc Encoder Mode: Speed 8 Realtime Frames Per Second > Higher Is Better 1 . 62.44 |==================================================================== 2 . 62.54 |==================================================================== 3 . 62.45 |==================================================================== SVT-HEVC 1.5.0 Tuning: 1 - Input: Bosphorus 1080p Frames Per Second > Higher Is Better 1 . 3.08 |===================================================================== 2 . 3.08 |===================================================================== 3 . 3.08 |===================================================================== SVT-HEVC 1.5.0 Tuning: 7 - Input: Bosphorus 1080p Frames Per Second > Higher Is Better 1 . 47.85 |==================================================================== 2 . 47.78 |==================================================================== 3 . 47.79 |==================================================================== SVT-HEVC 1.5.0 Tuning: 10 - Input: Bosphorus 1080p Frames Per Second > Higher Is Better 1 . 101.85 |=================================================================== 2 . 101.85 |=================================================================== 3 . 101.98 |=================================================================== SVT-VP9 0.3 Tuning: VMAF Optimized - Input: Bosphorus 1080p Frames Per Second > Higher Is Better 1 . 87.85 |==================================================================== 2 . 87.66 |==================================================================== 3 . 87.74 |==================================================================== SVT-VP9 0.3 Tuning: PSNR/SSIM Optimized - Input: Bosphorus 1080p Frames Per Second > Higher Is Better 1 . 88.01 |==================================================================== 2 . 88.04 |==================================================================== 3 . 88.06 |==================================================================== SVT-VP9 0.3 Tuning: Visual Quality Optimized - Input: Bosphorus 1080p Frames Per Second > Higher Is Better 1 . 69.82 |==================================================================== 2 . 70.00 |==================================================================== 3 . 69.87 |==================================================================== Timed Mesa Compilation 21.0 Time To Compile Seconds < Lower Is Better 1 . 126.26 |=================================================================== 2 . 126.19 |=================================================================== 3 . 126.39 |=================================================================== Timed Node.js Compilation 15.11 Time To Compile Seconds < Lower Is Better 1 . 1106.50 |================================================================== 2 . 1106.64 |================================================================== 3 . 1106.68 |================================================================== oneDNN 2.1.2 Harness: IP Shapes 1D - Data Type: f32 - Engine: CPU ms < Lower Is Better 1 . 7.98948 |================================================================== 2 . 8.01298 |================================================================== 3 . 7.97862 |================================================================== oneDNN 2.1.2 Harness: IP Shapes 3D - Data Type: f32 - Engine: CPU ms < Lower Is Better 1 . 12.28 |==================================================================== 2 . 12.10 |=================================================================== 3 . 12.06 |=================================================================== oneDNN 2.1.2 Harness: IP Shapes 1D - Data Type: u8s8f32 - Engine: CPU ms < Lower Is Better 1 . 3.65702 |================================================================== 2 . 3.66132 |================================================================== 3 . 3.65956 |================================================================== oneDNN 2.1.2 Harness: IP Shapes 3D - Data Type: u8s8f32 - Engine: CPU ms < Lower Is Better 1 . 3.28942 |================================================================== 2 . 3.28091 |================================================================== 3 . 3.20399 |================================================================ oneDNN 2.1.2 Harness: Convolution Batch Shapes Auto - Data Type: f32 - Engine: CPU ms < Lower Is Better 1 . 20.90 |==================================================================== 2 . 20.93 |==================================================================== 3 . 20.90 |==================================================================== oneDNN 2.1.2 Harness: Deconvolution Batch shapes_1d - Data Type: f32 - Engine: CPU ms < Lower Is Better 1 . 14.46 |==================================================================== 2 . 14.40 |==================================================================== 3 . 14.43 |==================================================================== oneDNN 2.1.2 Harness: Deconvolution Batch shapes_3d - Data Type: f32 - Engine: CPU ms < Lower Is Better 1 . 14.40 |=================================================================== 2 . 14.51 |==================================================================== 3 . 14.46 |==================================================================== oneDNN 2.1.2 Harness: Convolution Batch Shapes Auto - Data Type: u8s8f32 - Engine: CPU ms < Lower Is Better 1 . 20.50 |==================================================================== 2 . 20.52 |==================================================================== 3 . 20.52 |==================================================================== oneDNN 2.1.2 Harness: Deconvolution Batch shapes_1d - Data Type: u8s8f32 - Engine: CPU ms < Lower Is Better 1 . 4.77871 |================================================================== 2 . 4.76344 |================================================================== 3 . 4.78576 |================================================================== oneDNN 2.1.2 Harness: Deconvolution Batch shapes_3d - Data Type: u8s8f32 - Engine: CPU ms < Lower Is Better 1 . 8.07519 |================================================================== 2 . 8.10192 |================================================================== 3 . 8.08423 |================================================================== oneDNN 2.1.2 Harness: Recurrent Neural Network Training - Data Type: f32 - Engine: CPU ms < Lower Is Better 1 . 7395.55 |================================================================== 2 . 7399.68 |================================================================== 3 . 7394.30 |================================================================== oneDNN 2.1.2 Harness: Recurrent Neural Network Inference - Data Type: f32 - Engine: CPU ms < Lower Is Better 1 . 3948.98 |================================================================== 2 . 3955.17 |================================================================== 3 . 3951.90 |================================================================== oneDNN 2.1.2 Harness: Recurrent Neural Network Training - Data Type: u8s8f32 - Engine: CPU ms < Lower Is Better 1 . 7393.22 |================================================================== 2 . 7401.56 |================================================================== 3 . 7396.59 |================================================================== oneDNN 2.1.2 Harness: Recurrent Neural Network Inference - Data Type: u8s8f32 - Engine: CPU ms < Lower Is Better 1 . 3952.65 |================================================================== 2 . 3952.08 |================================================================== 3 . 3955.00 |================================================================== oneDNN 2.1.2 Harness: Matrix Multiply Batch Shapes Transformer - Data Type: f32 - Engine: CPU ms < Lower Is Better 1 . 5.42817 |================================================================== 2 . 5.42101 |================================================================== 3 . 5.38817 |================================================================== oneDNN 2.1.2 Harness: Recurrent Neural Network Training - Data Type: bf16bf16bf16 - Engine: CPU ms < Lower Is Better 1 . 7395.13 |================================================================== 2 . 7396.46 |================================================================== 3 . 7408.91 |================================================================== oneDNN 2.1.2 Harness: Recurrent Neural Network Inference - Data Type: bf16bf16bf16 - Engine: CPU ms < Lower Is Better 1 . 3955.37 |================================================================== 2 . 3954.96 |================================================================== 3 . 3957.84 |================================================================== oneDNN 2.1.2 Harness: Matrix Multiply Batch Shapes Transformer - Data Type: u8s8f32 - Engine: CPU ms < Lower Is Better 1 . 5.91706 |================================================================== 2 . 5.90636 |================================================================== 3 . 5.90709 |================================================================== ASTC Encoder 2.4 Preset: Medium Seconds < Lower Is Better 1 . 8.9180 |=================================================================== 2 . 8.9380 |=================================================================== 3 . 8.9296 |=================================================================== ASTC Encoder 2.4 Preset: Thorough Seconds < Lower Is Better 1 . 33.01 |==================================================================== 2 . 32.99 |==================================================================== 3 . 33.02 |==================================================================== ASTC Encoder 2.4 Preset: Exhaustive Seconds < Lower Is Better 1 . 256.21 |=================================================================== 2 . 256.09 |=================================================================== 3 . 256.17 |=================================================================== Basis Universal 1.13 Settings: ETC1S Seconds < Lower Is Better 1 . 36.77 |==================================================================== 2 . 36.84 |==================================================================== 3 . 36.84 |==================================================================== Basis Universal 1.13 Settings: UASTC Level 0 Seconds < Lower Is Better 1 . 11.01 |==================================================================== 2 . 11.00 |==================================================================== 3 . 10.99 |==================================================================== Basis Universal 1.13 Settings: UASTC Level 2 Seconds < Lower Is Better 1 . 72.90 |==================================================================== 2 . 72.91 |==================================================================== 3 . 72.89 |==================================================================== Basis Universal 1.13 Settings: UASTC Level 3 Seconds < Lower Is Better 1 . 144.17 |=================================================================== 2 . 144.08 |=================================================================== 3 . 144.08 |=================================================================== Mobile Neural Network 1.1.3 Model: SqueezeNetV1.0 ms < Lower Is Better 1 . 7.550 |==================================================================== 2 . 7.479 |=================================================================== 3 . 7.458 |=================================================================== Mobile Neural Network 1.1.3 Model: resnet-v2-50 ms < Lower Is Better 1 . 45.71 |==================================================================== 2 . 45.35 |=================================================================== 3 . 45.28 |=================================================================== Mobile Neural Network 1.1.3 Model: MobileNetV2_224 ms < Lower Is Better 1 . 4.033 |==================================================================== 2 . 4.011 |==================================================================== 3 . 4.001 |=================================================================== Mobile Neural Network 1.1.3 Model: mobilenet-v1-1.0 ms < Lower Is Better 1 . 4.577 |==================================================================== 2 . 4.545 |==================================================================== 3 . 4.534 |=================================================================== Mobile Neural Network 1.1.3 Model: inception-v3 ms < Lower Is Better 1 . 55.43 |==================================================================== 2 . 54.84 |=================================================================== 3 . 55.04 |==================================================================== Sysbench 1.0.20 Test: RAM / Memory MiB/sec > Higher Is Better 1 . 16690.54 |================================================================ 2 . 16726.66 |================================================================= 3 . 16845.49 |================================================================= Sysbench 1.0.20 Test: CPU Events Per Second > Higher Is Better 1 . 7854.28 |================================================================== 2 . 7845.28 |================================================================== 3 . 7843.34 |================================================================== Stockfish 13 Total Time Nodes Per Second > Higher Is Better 1 . 10343841 |================================================================= 2 . 10338531 |================================================================= 3 . 10254227 |================================================================