Core i3 7100 Xmas Eve Intel Core i3-7100 testing with a Gigabyte B250M-DS3H-CF (F9 BIOS) and Gigabyte Intel HD 630 3GB on Ubuntu 20.10 via the Phoronix Test Suite. 1: Processor: Intel Core i3-7100 @ 3.90GHz (2 Cores / 4 Threads), Motherboard: Gigabyte B250M-DS3H-CF (F9 BIOS), Chipset: Intel Xeon E3-1200 v6/7th + B250, Memory: 8GB, Disk: 250GB Western Digital WDS250G1B0A-, Graphics: Gigabyte Intel HD 630 3GB (1100MHz), Audio: Realtek ALC887-VD, Monitor: VA2431, Network: Realtek RTL8111/8168/8411 OS: Ubuntu 20.10, Kernel: 5.8.0-28-generic (x86_64), Desktop: GNOME Shell 3.38.1, Display Server: X Server 1.20.9, Display Driver: modesetting 1.20.9, OpenGL: 4.6 Mesa 20.2.1, Vulkan: 1.2.145, Compiler: GCC 10.2.0, File-System: ext4, Screen Resolution: 1920x1080 2: Processor: Intel Core i3-7100 @ 3.90GHz (2 Cores / 4 Threads), Motherboard: Gigabyte B250M-DS3H-CF (F9 BIOS), Chipset: Intel Xeon E3-1200 v6/7th + B250, Memory: 8GB, Disk: 250GB Western Digital WDS250G1B0A-, Graphics: Gigabyte Intel HD 630 3GB (1100MHz), Audio: Realtek ALC887-VD, Monitor: VA2431, Network: Realtek RTL8111/8168/8411 OS: Ubuntu 20.10, Kernel: 5.8.0-28-generic (x86_64), Desktop: GNOME Shell 3.38.1, Display Server: X Server 1.20.9, Display Driver: modesetting 1.20.9, OpenGL: 4.6 Mesa 20.2.1, Vulkan: 1.2.145, Compiler: GCC 10.2.0, File-System: ext4, Screen Resolution: 1920x1080 3: Processor: Intel Core i3-7100 @ 3.90GHz (2 Cores / 4 Threads), Motherboard: Gigabyte B250M-DS3H-CF (F9 BIOS), Chipset: Intel Xeon E3-1200 v6/7th + B250, Memory: 8GB, Disk: 250GB Western Digital WDS250G1B0A-, Graphics: Gigabyte Intel HD 630 3GB (1100MHz), Audio: Realtek ALC887-VD, Monitor: VA2431, Network: Realtek RTL8111/8168/8411 OS: Ubuntu 20.10, Kernel: 5.8.0-28-generic (x86_64), Desktop: GNOME Shell 3.38.1, Display Server: X Server 1.20.9, Display Driver: modesetting 1.20.9, OpenGL: 4.6 Mesa 20.2.1, Vulkan: 1.2.145, Compiler: GCC 10.2.0, File-System: ext4, Screen Resolution: 1920x1080 asmFish 2018-07-23 1024 Hash Memory, 26 Depth Nodes/second > Higher Is Better 1 . 6144009 |================================================================= 2 . 6257439 |================================================================== 3 . 6240412 |================================================================== ASTC Encoder 2.0 Preset: Fast Seconds < Lower Is Better 1 . 7.97 |===================================================================== 2 . 7.97 |===================================================================== 3 . 7.96 |===================================================================== ASTC Encoder 2.0 Preset: Medium Seconds < Lower Is Better 1 . 20.42 |==================================================================== 2 . 20.42 |==================================================================== 3 . 20.42 |==================================================================== ASTC Encoder 2.0 Preset: Thorough Seconds < Lower Is Better 1 . 135.29 |=================================================================== 2 . 135.42 |=================================================================== 3 . 135.31 |=================================================================== ASTC Encoder 2.0 Preset: Exhaustive Seconds < Lower Is Better 1 . 1087.58 |================================================================= 2 . 1104.70 |================================================================== 3 . 1088.46 |================================================================= Build2 0.13 Time To Compile Seconds < Lower Is Better 1 . 644.79 |=================================================================== 2 . 648.38 |=================================================================== 3 . 645.35 |=================================================================== CLOMP 1.2 Static OMP Speedup Speedup > Higher Is Better 1 . 1.4 |====================================================================== 2 . 1.4 |====================================================================== 3 . 1.4 |====================================================================== Coremark 1.0 CoreMark Size 666 - Iterations Per Second Iterations/Sec > Higher Is Better 1 . 77661.56 |================================================================= 2 . 77631.83 |================================================================ 3 . 78242.23 |================================================================= Crafty 25.2 Elapsed Time Nodes Per Second > Higher Is Better 1 . 7332207 |================================================================== 2 . 7369776 |================================================================== 3 . 7347021 |================================================================== HPC Challenge 1.5.0 Test / Class: G-HPL GFLOPS > Higher Is Better 1 . 86.84 |==================================================================== 2 . 85.29 |=================================================================== 3 . 86.81 |==================================================================== HPC Challenge 1.5.0 Test / Class: G-Ffte GFLOPS > Higher Is Better 1 . 1.75523 |================================================================== 2 . 1.76210 |================================================================== 3 . 1.75386 |================================================================== HPC Challenge 1.5.0 Test / Class: EP-DGEMM GFLOPS > Higher Is Better 1 . 47.15 |=================================================================== 2 . 47.50 |==================================================================== 3 . 47.69 |==================================================================== HPC Challenge 1.5.0 Test / Class: G-Ptrans GB/s > Higher Is Better 1 . 1.31124 |=========================================================== 2 . 1.46076 |================================================================== 3 . 1.46079 |================================================================== HPC Challenge 1.5.0 Test / Class: EP-STREAM Triad GB/s > Higher Is Better 1 . 9.87479 |================================================================== 2 . 9.88819 |================================================================== 3 . 9.82052 |================================================================== HPC Challenge 1.5.0 Test / Class: G-Random Access GUP/s > Higher Is Better 1 . 0.01270 |================================================================== 2 . 0.01267 |================================================================= 3 . 0.01277 |================================================================== HPC Challenge 1.5.0 Test / Class: Random Ring Latency usecs < Lower Is Better 1 . 0.21035 |================================================================== 2 . 0.20996 |================================================================== 3 . 0.20908 |================================================================== HPC Challenge 1.5.0 Test / Class: Random Ring Bandwidth GB/s > Higher Is Better 1 . 5.14701 |================================================================== 2 . 5.18462 |================================================================== 3 . 4.90255 |============================================================== HPC Challenge 1.5.0 Test / Class: Max Ping Pong Bandwidth MB/s > Higher Is Better 1 . 8711.35 |================================================================= 2 . 8813.10 |================================================================== 3 . 8644.79 |================================================================= Monkey Audio Encoding 3.99.6 WAV To APE Seconds < Lower Is Better 1 . 12.78 |==================================================================== 2 . 12.75 |==================================================================== 3 . 12.77 |==================================================================== NCNN 20201218 Target: CPU - Model: mobilenet ms < Lower Is Better 1 . 43.12 |==================================================================== 2 . 43.24 |==================================================================== 3 . 43.24 |==================================================================== NCNN 20201218 Target: CPU-v2-v2 - Model: mobilenet-v2 ms < Lower Is Better 1 . 10.63 |==================================================================== 2 . 10.65 |==================================================================== 3 . 10.67 |==================================================================== NCNN 20201218 Target: CPU-v3-v3 - Model: mobilenet-v3 ms < Lower Is Better 1 . 9.18 |===================================================================== 2 . 9.18 |===================================================================== 3 . 9.19 |===================================================================== NCNN 20201218 Target: CPU - Model: shufflenet-v2 ms < Lower Is Better 1 . 15.31 |==================================================================== 2 . 15.33 |==================================================================== 3 . 15.31 |==================================================================== NCNN 20201218 Target: CPU - Model: mnasnet ms < Lower Is Better 1 . 9.86 |===================================================================== 2 . 9.91 |===================================================================== 3 . 9.86 |===================================================================== NCNN 20201218 Target: CPU - Model: efficientnet-b0 ms < Lower Is Better 1 . 15.44 |==================================================================== 2 . 15.41 |==================================================================== 3 . 15.36 |==================================================================== NCNN 20201218 Target: CPU - Model: blazeface ms < Lower Is Better 1 . 3.88 |===================================================================== 2 . 3.87 |===================================================================== 3 . 3.88 |===================================================================== NCNN 20201218 Target: CPU - Model: googlenet ms < Lower Is Better 1 . 31.51 |==================================================================== 2 . 31.51 |==================================================================== 3 . 31.52 |==================================================================== NCNN 20201218 Target: CPU - Model: vgg16 ms < Lower Is Better 1 . 111.37 |=================================================================== 2 . 111.63 |=================================================================== 3 . 111.59 |=================================================================== NCNN 20201218 Target: CPU - Model: resnet18 ms < Lower Is Better 1 . 30.82 |==================================================================== 2 . 30.75 |==================================================================== 3 . 30.74 |==================================================================== NCNN 20201218 Target: CPU - Model: alexnet ms < Lower Is Better 1 . 24.95 |==================================================================== 2 . 24.96 |==================================================================== 3 . 24.94 |==================================================================== NCNN 20201218 Target: CPU - Model: resnet50 ms < Lower Is Better 1 . 68.50 |==================================================================== 2 . 68.42 |==================================================================== 3 . 68.42 |==================================================================== NCNN 20201218 Target: CPU - Model: yolov4-tiny ms < Lower Is Better 1 . 57.17 |==================================================================== 2 . 57.23 |==================================================================== 3 . 57.26 |==================================================================== NCNN 20201218 Target: CPU - Model: squeezenet_ssd ms < Lower Is Better 1 . 47.11 |==================================================================== 2 . 47.28 |==================================================================== 3 . 47.15 |==================================================================== NCNN 20201218 Target: CPU - Model: regnety_400m ms < Lower Is Better 1 . 18.60 |==================================================================== 2 . 18.62 |==================================================================== 3 . 18.60 |==================================================================== NCNN 20201218 Target: Vulkan GPU - Model: mobilenet ms < Lower Is Better 1 . 43.07 |==================================================================== 2 . 43.20 |==================================================================== 3 . 43.26 |==================================================================== NCNN 20201218 Target: Vulkan GPU-v2-v2 - Model: mobilenet-v2 ms < Lower Is Better 1 . 10.62 |==================================================================== 2 . 10.64 |==================================================================== 3 . 10.66 |==================================================================== NCNN 20201218 Target: Vulkan GPU-v3-v3 - Model: mobilenet-v3 ms < Lower Is Better 1 . 9.19 |===================================================================== 2 . 9.15 |===================================================================== 3 . 9.15 |===================================================================== NCNN 20201218 Target: Vulkan GPU - Model: shufflenet-v2 ms < Lower Is Better 1 . 15.33 |==================================================================== 2 . 15.32 |==================================================================== 3 . 15.32 |==================================================================== NCNN 20201218 Target: Vulkan GPU - Model: mnasnet ms < Lower Is Better 1 . 9.84 |===================================================================== 2 . 9.87 |===================================================================== 3 . 9.86 |===================================================================== NCNN 20201218 Target: Vulkan GPU - Model: efficientnet-b0 ms < Lower Is Better 1 . 15.32 |==================================================================== 2 . 15.36 |==================================================================== 3 . 15.37 |==================================================================== NCNN 20201218 Target: Vulkan GPU - Model: blazeface ms < Lower Is Better 1 . 3.86 |===================================================================== 2 . 3.87 |===================================================================== 3 . 3.87 |===================================================================== NCNN 20201218 Target: Vulkan GPU - Model: googlenet ms < Lower Is Better 1 . 31.55 |==================================================================== 2 . 31.53 |==================================================================== 3 . 31.48 |==================================================================== NCNN 20201218 Target: Vulkan GPU - Model: vgg16 ms < Lower Is Better 1 . 111.29 |=================================================================== 2 . 111.32 |=================================================================== 3 . 111.09 |=================================================================== NCNN 20201218 Target: Vulkan GPU - Model: resnet18 ms < Lower Is Better 1 . 30.75 |==================================================================== 2 . 30.76 |==================================================================== 3 . 30.72 |==================================================================== NCNN 20201218 Target: Vulkan GPU - Model: alexnet ms < Lower Is Better 1 . 24.93 |==================================================================== 2 . 24.93 |==================================================================== 3 . 24.90 |==================================================================== NCNN 20201218 Target: Vulkan GPU - Model: resnet50 ms < Lower Is Better 1 . 68.43 |==================================================================== 2 . 68.36 |==================================================================== 3 . 68.42 |==================================================================== NCNN 20201218 Target: Vulkan GPU - Model: yolov4-tiny ms < Lower Is Better 1 . 57.15 |==================================================================== 2 . 57.18 |==================================================================== 3 . 57.19 |==================================================================== NCNN 20201218 Target: Vulkan GPU - Model: squeezenet_ssd ms < Lower Is Better 1 . 47.19 |==================================================================== 2 . 47.24 |==================================================================== 3 . 47.26 |==================================================================== NCNN 20201218 Target: Vulkan GPU - Model: regnety_400m ms < Lower Is Better 1 . 18.60 |==================================================================== 2 . 18.67 |==================================================================== 3 . 18.58 |==================================================================== Node.js V8 Web Tooling Benchmark runs/s > Higher Is Better 1 . 9.44 |===================================================================== 2 . 9.34 |==================================================================== 3 . 9.34 |==================================================================== oneDNN 2.0 Harness: IP Shapes 1D - Data Type: f32 - Engine: CPU ms < Lower Is Better 1 . 15.80 |==================================================================== 2 . 15.66 |=================================================================== 3 . 15.74 |==================================================================== oneDNN 2.0 Harness: IP Shapes 3D - Data Type: f32 - Engine: CPU ms < Lower Is Better 1 . 15.54 |================================================================= 2 . 14.84 |============================================================== 3 . 16.18 |==================================================================== oneDNN 2.0 Harness: IP Shapes 1D - Data Type: u8s8f32 - Engine: CPU ms < Lower Is Better 1 . 6.97730 |================================================================== 2 . 6.97030 |================================================================== 3 . 7.01559 |================================================================== oneDNN 2.0 Harness: IP Shapes 3D - Data Type: u8s8f32 - Engine: CPU ms < Lower Is Better 1 . 4.69411 |================================================================ 2 . 4.81695 |================================================================== 3 . 4.70981 |================================================================= oneDNN 2.0 Harness: Convolution Batch Shapes Auto - Data Type: f32 - Engine: CPU ms < Lower Is Better 1 . 20.75 |==================================================================== 2 . 20.63 |==================================================================== 3 . 20.74 |==================================================================== oneDNN 2.0 Harness: Deconvolution Batch shapes_1d - Data Type: f32 - Engine: CPU ms < Lower Is Better 1 . 20.04 |==================================================================== 2 . 19.97 |==================================================================== 3 . 19.86 |=================================================================== oneDNN 2.0 Harness: Deconvolution Batch shapes_3d - Data Type: f32 - Engine: CPU ms < Lower Is Better 1 . 24.58 |==================================================================== 2 . 24.62 |==================================================================== 3 . 24.60 |==================================================================== oneDNN 2.0 Harness: Convolution Batch Shapes Auto - Data Type: u8s8f32 - Engine: CPU ms < Lower Is Better 1 . 24.02 |==================================================================== 2 . 23.94 |==================================================================== 3 . 24.05 |==================================================================== oneDNN 2.0 Harness: Deconvolution Batch shapes_1d - Data Type: u8s8f32 - Engine: CPU ms < Lower Is Better 1 . 20.06 |==================================================================== 2 . 20.02 |==================================================================== 3 . 19.93 |==================================================================== oneDNN 2.0 Harness: Deconvolution Batch shapes_3d - Data Type: u8s8f32 - Engine: CPU ms < Lower Is Better 1 . 13.36 |==================================================================== 2 . 13.34 |==================================================================== 3 . 13.32 |==================================================================== oneDNN 2.0 Harness: Recurrent Neural Network Training - Data Type: f32 - Engine: CPU ms < Lower Is Better 1 . 12994.0 |================================================================ 2 . 13403.5 |================================================================== 3 . 13012.2 |================================================================ oneDNN 2.0 Harness: Recurrent Neural Network Inference - Data Type: f32 - Engine: CPU ms < Lower Is Better 1 . 7188.49 |================================================================ 2 . 7424.10 |================================================================== 3 . 7201.09 |================================================================ oneDNN 2.0 Harness: Recurrent Neural Network Training - Data Type: u8s8f32 - Engine: CPU ms < Lower Is Better 1 . 13022.3 |================================================================ 2 . 13494.4 |================================================================== 3 . 13017.5 |================================================================ oneDNN 2.0 Harness: Recurrent Neural Network Inference - Data Type: u8s8f32 - Engine: CPU ms < Lower Is Better 1 . 7192.68 |================================================================ 2 . 7437.08 |================================================================== 3 . 7207.99 |================================================================ oneDNN 2.0 Harness: Matrix Multiply Batch Shapes Transformer - Data Type: f32 - Engine: CPU ms < Lower Is Better 1 . 6.03889 |================================================================== 2 . 6.03112 |================================================================== 3 . 6.05271 |================================================================== oneDNN 2.0 Harness: Recurrent Neural Network Training - Data Type: bf16bf16bf16 - Engine: CPU ms < Lower Is Better 1 . 12989.9 |================================================================ 2 . 13484.9 |================================================================== 3 . 13005.4 |================================================================ oneDNN 2.0 Harness: Recurrent Neural Network Inference - Data Type: bf16bf16bf16 - Engine: CPU ms < Lower Is Better 1 . 7184.04 |================================================================ 2 . 7447.30 |================================================================== 3 . 7201.51 |================================================================ oneDNN 2.0 Harness: Matrix Multiply Batch Shapes Transformer - Data Type: u8s8f32 - Engine: CPU ms < Lower Is Better 1 . 12.35 |==================================================================== 2 . 12.35 |==================================================================== 3 . 12.34 |==================================================================== Opus Codec Encoding 1.3.1 WAV To Opus Encode Seconds < Lower Is Better 1 . 9.593 |==================================================================== 2 . 9.597 |==================================================================== 3 . 9.599 |==================================================================== PHPBench 0.8.1 PHP Benchmark Suite Score > Higher Is Better 1 . 657887 |=================================================================== 2 . 658126 |=================================================================== 3 . 656295 |=================================================================== rav1e 0.4 Alpha Speed: 1 Frames Per Second > Higher Is Better 1 . 0.253 |==================================================================== 2 . 0.248 |=================================================================== 3 . 0.251 |=================================================================== rav1e 0.4 Alpha Speed: 5 Frames Per Second > Higher Is Better 1 . 0.779 |==================================================================== 2 . 0.779 |==================================================================== 3 . 0.776 |==================================================================== rav1e 0.4 Alpha Speed: 6 Frames Per Second > Higher Is Better 1 . 1.035 |==================================================================== 2 . 1.038 |==================================================================== 3 . 1.036 |==================================================================== rav1e 0.4 Alpha Speed: 10 Frames Per Second > Higher Is Better 1 . 2.404 |==================================================================== 2 . 2.406 |==================================================================== 3 . 2.406 |==================================================================== simdjson 0.7.1 Throughput Test: Kostya GB/s > Higher Is Better 1 . 0.49 |===================================================================== 2 . 0.49 |===================================================================== 3 . 0.49 |===================================================================== simdjson 0.7.1 Throughput Test: LargeRandom GB/s > Higher Is Better 1 . 0.37 |===================================================================== 2 . 0.37 |===================================================================== 3 . 0.37 |===================================================================== simdjson 0.7.1 Throughput Test: PartialTweets GB/s > Higher Is Better 1 . 0.60 |===================================================================== 2 . 0.60 |===================================================================== 3 . 0.60 |===================================================================== simdjson 0.7.1 Throughput Test: DistinctUserID GB/s > Higher Is Better 1 . 0.62 |===================================================================== 2 . 0.62 |===================================================================== 3 . 0.62 |===================================================================== SQLite 3.30.1 Threads / Copies: 1 Seconds < Lower Is Better 1 . 30.32 |================================================================= 2 . 31.92 |==================================================================== 3 . 31.70 |==================================================================== Stockfish 12 Total Time Nodes Per Second > Higher Is Better 1 . 4232953 |================================================================== 2 . 4043871 |=============================================================== 3 . 4101980 |================================================================ Timed Eigen Compilation 3.3.9 Time To Compile Seconds < Lower Is Better 1 . 92.85 |==================================================================== 2 . 92.73 |==================================================================== 3 . 92.92 |==================================================================== Timed FFmpeg Compilation 4.2.2 Time To Compile Seconds < Lower Is Better 1 . 232.09 |=================================================================== 2 . 232.00 |=================================================================== 3 . 231.81 |=================================================================== Timed HMMer Search 3.3.1 Pfam Database Search Seconds < Lower Is Better 1 . 114.83 |=================================================================== 2 . 114.83 |=================================================================== 3 . 114.83 |=================================================================== Timed MAFFT Alignment 7.471 Multiple Sequence Alignment - LSU RNA Seconds < Lower Is Better 1 . 14.00 |==================================================================== 2 . 13.87 |=================================================================== 3 . 14.00 |==================================================================== VkFFT 1.1.1 Benchmark Score > Higher Is Better 1 . 1332 |===================================================================== 2 . 1335 |===================================================================== 3 . 1332 |===================================================================== VKMark 2020-05-21 Resolution: 1280 x 1024 VKMark Score > Higher Is Better 1 . 905 |====================================================================== 2 . 906 |====================================================================== 3 . 881 |==================================================================== VKMark 2020-05-21 Resolution: 1920 x 1080 VKMark Score > Higher Is Better 1 . 614 |====================================================================== 2 . 614 |====================================================================== 3 . 606 |===================================================================== VkResample 1.0 Upscale: 2x - Precision: Double ms < Lower Is Better 1 . 1011.32 |================================================================== 2 . 1010.74 |================================================================== 3 . 1006.89 |================================================================== VkResample 1.0 Upscale: 2x - Precision: Single ms < Lower Is Better 1 . 523.03 |================================================================= 2 . 532.96 |================================================================== 3 . 538.29 |=================================================================== WavPack Audio Encoding 5.3 WAV To WavPack Seconds < Lower Is Better 1 . 16.69 |==================================================================== 2 . 16.70 |==================================================================== 3 . 16.71 |====================================================================