Core i3 7100 Xmas Eve, "SQLite 3.30.1 - Threads / Copies: 1", Lower Results Are Better "1",33.371,32.899,30.824,31.649,29.759,30.875,30.088,30.375,29.168,28.893,29.534,29.531,29.473,29.342,28.944 "2",31.838,31.951,31.958 "3",31.55,32.393,31.162 "VkFFT 1.1.1 - ", Higher Results Are Better "1", "2",1338,1333,1333 "3",1334,1333,1330 "VkResample 1.0 - Upscale: 2x - Precision: Double", Lower Results Are Better "1",1019.709,1012.368,1001.883 "2",1001.909,1019.158,1011.153 "3",1005.785,1011.559,1003.326 "VkResample 1.0 - Upscale: 2x - Precision: Single", Lower Results Are Better "1",528.927,522.985,517.189 "2",541.152,529.172,528.547 "3",529.89,542.906,542.062 "VKMark 2020-05-21 - Resolution: 1280 x 1024", Higher Results Are Better "1",906,906,903 "2",905,906,907 "3",883,886,875 "VKMark 2020-05-21 - Resolution: 1920 x 1080", Higher Results Are Better "1",615,612,616 "2",613,615,614 "3",591,614,613 "HPC Challenge 1.5.0 - Test / Class: G-HPL", Higher Results Are Better "1",86.862,86.9025,86.753 "2",85.7583,85.1517,84.9746 "3",86.9408,86.5134,86.9872 "HPC Challenge 1.5.0 - Test / Class: G-Ffte", Higher Results Are Better "1",1.75598,1.76109,1.74862 "2",1.76528,1.76239,1.75862 "3",1.75448,1.75974,1.74736 "HPC Challenge 1.5.0 - Test / Class: EP-DGEMM", Higher Results Are Better "1",47.5682,47.7756,46.1195 "2",47.5661,47.6974,47.2486 "3",47.8019,47.5048,47.7771 "HPC Challenge 1.5.0 - Test / Class: G-Ptrans", Higher Results Are Better "1",1.46752,1.46914,0.997071 "2",1.46946,1.44406,1.46877 "3",1.46788,1.44877,1.46571 "HPC Challenge 1.5.0 - Test / Class: EP-STREAM Triad", Higher Results Are Better "1",9.90229,9.84008,9.882 "2",9.89898,9.89669,9.86889 "3",9.82499,9.79762,9.83895 "HPC Challenge 1.5.0 - Test / Class: G-Random Access", Higher Results Are Better "1",0.0126968,0.012833,0.0125719 "2",0.0127801,0.012441,0.0127913 "3",0.012785,0.0127007,0.0128209 "HPC Challenge 1.5.0 - Test / Class: Random Ring Latency", Lower Results Are Better "1",0.208798,0.20977,0.212485 "2",0.213953,0.208118,0.207823 "3",0.2099,0.207707,0.209623 "HPC Challenge 1.5.0 - Test / Class: Random Ring Bandwidth", Higher Results Are Better "1",4.96948,5.26393,5.20761 "2",5.28626,5.02267,5.24492 "3",5.00376,4.97902,4.72487 "HPC Challenge 1.5.0 - Test / Class: Max Ping Pong Bandwidth", Higher Results Are Better "1",8515.566,8825.736,8792.755 "2",8868.373,8679.915,8891.003 "3",8715.394,8735.475,8483.509 "CLOMP 1.2 - Static OMP Speedup", Higher Results Are Better "1",1.4,1.4,1.4 "2",1.4,1.4,1.4 "3",1.4,1.4,1.4 "Timed HMMer Search 3.3.1 - Pfam Database Search", Lower Results Are Better "1",114.926,114.752,114.799 "2",114.955,114.793,114.753 "3",114.906,114.812,114.76 "Timed MAFFT Alignment 7.471 - Multiple Sequence Alignment - LSU RNA", Lower Results Are Better "1",14.033,13.849,14.119 "2",13.825,13.829,13.948 "3",13.824,14.197,13.991 "simdjson 0.7.1 - Throughput Test: Kostya", Higher Results Are Better "1",0.49,0.49,0.49 "2",0.49,0.49,0.49 "3",0.49,0.49,0.49 "simdjson 0.7.1 - Throughput Test: LargeRandom", Higher Results Are Better "1",0.37,0.37,0.37 "2",0.37,0.37,0.37 "3",0.37,0.37,0.37 "simdjson 0.7.1 - Throughput Test: PartialTweets", Higher Results Are Better "1",0.6,0.6,0.6 "2",0.6,0.6,0.6 "3",0.61,0.6,0.6 "simdjson 0.7.1 - Throughput Test: DistinctUserID", Higher Results Are Better "1",0.62,0.62,0.62 "2",0.62,0.62,0.62 "3",0.62,0.62,0.62 "Crafty 25.2 - Elapsed Time", Higher Results Are Better "1",7367760,7301846,7327016 "2",7393328,7355287,7360714 "3",7353094,7348429,7339539 "oneDNN 2.0 - Harness: IP Shapes 1D - Data Type: f32 - Engine: CPU", Lower Results Are Better "1",15.7435,15.8343,15.8206 "2",15.6729,15.6327,15.6685 "3",15.7695,15.731,15.7296 "oneDNN 2.0 - Harness: IP Shapes 3D - Data Type: f32 - Engine: CPU", Lower Results Are Better "1",15.4598,15.5073,15.6411 "2",14.8841,14.8116,14.8138 "3",16.1459,16.2094,16.1899 "oneDNN 2.0 - Harness: IP Shapes 1D - Data Type: u8s8f32 - Engine: CPU", Lower Results Are Better "1",6.94613,6.9978,6.98796 "2",6.94817,6.99371,6.96901 "3",6.96331,7.09042,6.99305 "oneDNN 2.0 - Harness: IP Shapes 3D - Data Type: u8s8f32 - Engine: CPU", Lower Results Are Better "1",4.64003,4.80044,4.64186 "2",4.80894,4.83301,4.80891 "3",4.70219,4.704,4.72324 "oneDNN 2.0 - Harness: Convolution Batch Shapes Auto - Data Type: f32 - Engine: CPU", Lower Results Are Better "1",20.7088,20.7794,20.7729 "2",20.6519,20.7008,20.5485 "3",20.7882,20.7381,20.7068 "oneDNN 2.0 - Harness: Deconvolution Batch shapes_1d - Data Type: f32 - Engine: CPU", Lower Results Are Better "1",20.0466,20.229,19.8531 "2",19.9075,20.0765,19.9213 "3",19.8652,19.8448,19.8736 "oneDNN 2.0 - Harness: Deconvolution Batch shapes_3d - Data Type: f32 - Engine: CPU", Lower Results Are Better "1",24.4378,24.6714,24.618 "2",24.5539,24.6355,24.6813 "3",24.6232,24.5975,24.5886 "oneDNN 2.0 - Harness: Convolution Batch Shapes Auto - Data Type: u8s8f32 - Engine: CPU", Lower Results Are Better "1",23.991,24.0524,24.0162 "2",23.9296,23.9927,23.9095 "3",24.0256,24.1032,24.0305 "oneDNN 2.0 - Harness: Deconvolution Batch shapes_1d - Data Type: u8s8f32 - Engine: CPU", Lower Results Are Better "1",20.5199,19.7328,19.9398 "2",19.7255,19.8166,20.532 "3",19.8667,20.0057,19.9144 "oneDNN 2.0 - Harness: Deconvolution Batch shapes_3d - Data Type: u8s8f32 - Engine: CPU", Lower Results Are Better "1",13.3239,13.3988,13.3697 "2",13.2474,13.3992,13.3874 "3",13.3174,13.3287,13.3256 "oneDNN 2.0 - Harness: Recurrent Neural Network Training - Data Type: f32 - Engine: CPU", Lower Results Are Better "1",13001.9,12991.8,12988.2 "2",13250.5,13477.5,13482.5 "3",13018.9,13020.6,12997.1 "oneDNN 2.0 - Harness: Recurrent Neural Network Inference - Data Type: f32 - Engine: CPU", Lower Results Are Better "1",7196.48,7185.97,7183.03 "2",7417.09,7421.73,7433.48 "3",7201.01,7196.37,7205.9 "oneDNN 2.0 - Harness: Recurrent Neural Network Training - Data Type: u8s8f32 - Engine: CPU", Lower Results Are Better "1",12986.9,12989,13090.9 "2",13485.1,13502.5,13495.7 "3",13016.5,13029.6,13006.5 "oneDNN 2.0 - Harness: Recurrent Neural Network Inference - Data Type: u8s8f32 - Engine: CPU", Lower Results Are Better "1",7185.07,7188.9,7204.07 "2",7427.38,7443.76,7440.1 "3",7192.49,7213.4,7218.07 "oneDNN 2.0 - Harness: Matrix Multiply Batch Shapes Transformer - Data Type: f32 - Engine: CPU", Lower Results Are Better "1",6.03734,6.04584,6.0335 "2",6.0221,6.03915,6.03212 "3",6.03765,6.05705,6.06344 "oneDNN 2.0 - Harness: Recurrent Neural Network Training - Data Type: bf16bf16bf16 - Engine: CPU", Lower Results Are Better "1",12992.9,12984.7,12992 "2",13427.9,13506.6,13520.1 "3",13006,13014,12996.3 "oneDNN 2.0 - Harness: Recurrent Neural Network Inference - Data Type: bf16bf16bf16 - Engine: CPU", Lower Results Are Better "1",7185.73,7191.47,7174.93 "2",7433.73,7458.35,7449.83 "3",7199.88,7193.22,7211.42 "oneDNN 2.0 - Harness: Matrix Multiply Batch Shapes Transformer - Data Type: u8s8f32 - Engine: CPU", Lower Results Are Better "1",12.3568,12.3702,12.329 "2",12.3373,12.3627,12.3576 "3",12.3335,12.3552,12.3317 "rav1e 0.4 Alpha - Speed: 1", Higher Results Are Better "1",0.253,0.252,0.254 "2",0.248,0.249,0.246 "3",0.247,0.254,0.252 "rav1e 0.4 Alpha - Speed: 5", Higher Results Are Better "1",0.774,0.782,0.781 "2",0.781,0.774,0.782 "3",0.774,0.776,0.777 "rav1e 0.4 Alpha - Speed: 6", Higher Results Are Better "1",1.037,1.034,1.035 "2",1.039,1.036,1.039 "3",1.037,1.036,1.035 "rav1e 0.4 Alpha - Speed: 10", Higher Results Are Better "1",2.388,2.41,2.413 "2",2.398,2.41,2.41 "3",2.399,2.409,2.409 "Coremark 1.0 - CoreMark Size 666 - Iterations Per Second", Higher Results Are Better "1",76317.672311,78274.057042,78392.944635 "2",78883.794311,76687.116564,77324.569882 "3",77008.230255,79094.36947,78624.078624 "Stockfish 12 - Total Time", Higher Results Are Better "1",4311438,4180251,4207170 "2",4000273,4044918,4086423 "3",4097299,4129018,4079624 "asmFish 2018-07-23 - 1024 Hash Memory, 26 Depth", Higher Results Are Better "1",6185702,6087624,6158701 "2",6229449,6129742,6413125 "3",6264150,6250148,6206939 "Timed FFmpeg Compilation 4.2.2 - Time To Compile", Lower Results Are Better "1",232.624,232.224,231.408 "2",231.957,232.083,231.966 "3",231.93,231.861,231.628 "Build2 0.13 - Time To Compile", Lower Results Are Better "1",644.814,644.312,645.242 "2",647.283,648.779,649.079 "3",644.856,646.167,645.024 "Timed Eigen Compilation 3.3.9 - Time To Compile", Lower Results Are Better "1",92.838,92.897,92.806 "2",92.667,92.746,92.776 "3",92.886,92.92,92.953 "Monkey Audio Encoding 3.99.6 - WAV To APE", Lower Results Are Better "1",12.842,12.813,12.653,12.727,12.871 "2",12.987,12.694,12.747,12.768,12.566 "3",12.98,12.595,12.672,12.803,12.79 "Opus Codec Encoding 1.3.1 - WAV To Opus Encode", Lower Results Are Better "1",9.672,9.6,9.567,9.565,9.562 "2",9.684,9.594,9.577,9.561,9.571 "3",9.686,9.587,9.576,9.57,9.578 "Node.js V8 Web Tooling Benchmark - ", Higher Results Are Better "1",9.46,9.26,9.6 "2",9.33,9.42,9.26 "3",9.31,9.31,9.4 "ASTC Encoder 2.0 - Preset: Fast", Lower Results Are Better "1",7.96,7.97,7.98 "2",7.96,7.97,7.97 "3",7.96,7.97,7.96 "ASTC Encoder 2.0 - Preset: Medium", Lower Results Are Better "1",20.41,20.43,20.41 "2",20.41,20.42,20.42 "3",20.42,20.41,20.43 "ASTC Encoder 2.0 - Preset: Thorough", Lower Results Are Better "1",135.26,135.29,135.32 "2",135.39,135.45,135.43 "3",135.4,135.26,135.26 "ASTC Encoder 2.0 - Preset: Exhaustive", Lower Results Are Better "1",1088.29,1087.02,1087.43 "2",1111.67,1113.92,1088.51 "3",1088.44,1088.17,1088.76 "NCNN 20201218 - Target: CPU - Model: mobilenet", Lower Results Are Better "1",43.12,43.15,43.08 "2",43.23,43.31,43.19 "3",43.26,43.23,43.23 "NCNN 20201218 - Target: CPU-v2-v2 - Model: mobilenet-v2", Lower Results Are Better "1",10.63,10.64,10.63 "2",10.61,10.71,10.63 "3",10.67,10.71,10.64 "NCNN 20201218 - Target: CPU-v3-v3 - Model: mobilenet-v3", Lower Results Are Better "1",9.18,9.18,9.17 "2",9.22,9.16,9.17 "3",9.21,9.21,9.16 "NCNN 20201218 - Target: CPU - Model: shufflenet-v2", Lower Results Are Better "1",15.3,15.33,15.31 "2",15.38,15.25,15.35 "3",15.33,15.28,15.32 "NCNN 20201218 - Target: CPU - Model: mnasnet", Lower Results Are Better "1",9.86,9.89,9.84 "2",9.85,9.86,10.02 "3",9.89,9.84,9.84 "NCNN 20201218 - Target: CPU - Model: efficientnet-b0", Lower Results Are Better "1",15.48,15.39 "2",15.46,15.36 "3",15.36,15.37,15.34 "NCNN 20201218 - Target: CPU - Model: blazeface", Lower Results Are Better "1",3.88,3.88,3.87 "2",3.87,3.88,3.86 "3",3.88,3.88,3.88 "NCNN 20201218 - Target: CPU - Model: googlenet", Lower Results Are Better "1",31.56,31.48,31.49 "2",31.53,31.48,31.51 "3",31.55,31.51,31.51 "NCNN 20201218 - Target: CPU - Model: vgg16", Lower Results Are Better "1",111.48,111.48,111.15 "2",112.12,111.36,111.4 "3",111.99,111.54,111.23 "NCNN 20201218 - Target: CPU - Model: resnet18", Lower Results Are Better "1",30.74,30.91,30.81 "2",30.78,30.82,30.66 "3",30.66,30.79,30.76 "NCNN 20201218 - Target: CPU - Model: alexnet", Lower Results Are Better "1",24.93,24.93,24.99 "2",24.94,24.94,25.01 "3",25.04,24.85,24.92 "NCNN 20201218 - Target: CPU - Model: resnet50", Lower Results Are Better "1",68.6,68.4,68.4 "2",68.39,68.39,68.48 "3",68.45,68.46,68.36 "NCNN 20201218 - Target: CPU - Model: yolov4-tiny", Lower Results Are Better "1",57.14,57.27,57.1 "2",57.25,57.17,57.26 "3",57.29,57.27,57.21 "NCNN 20201218 - Target: CPU - Model: squeezenet_ssd", Lower Results Are Better "1",47.24,47.03,47.06 "2",47.41,47.18,47.24 "3",47.19,47.15,47.12 "NCNN 20201218 - Target: CPU - Model: regnety_400m", Lower Results Are Better "1",18.63,18.6,18.57 "2",18.66,18.57,18.64 "3",18.63,18.55,18.63 "NCNN 20201218 - Target: Vulkan GPU - Model: mobilenet", Lower Results Are Better "1",43.07,43.08,43.06 "2",43.42,43.1,43.09 "3",43.33,43.36,43.09 "NCNN 20201218 - Target: Vulkan GPU-v2-v2 - Model: mobilenet-v2", Lower Results Are Better "1",10.63,10.62,10.61 "2",10.63,10.62,10.68 "3",10.69,10.64,10.65 "NCNN 20201218 - Target: Vulkan GPU-v3-v3 - Model: mobilenet-v3", Lower Results Are Better "1",9.21,9.16,9.2 "2",9.14,9.17,9.15 "3",9.14,9.15,9.17 "NCNN 20201218 - Target: Vulkan GPU - Model: shufflenet-v2", Lower Results Are Better "1",15.35,15.35,15.29 "2",15.37,15.32,15.27 "3",15.29,15.33,15.34 "NCNN 20201218 - Target: Vulkan GPU - Model: mnasnet", Lower Results Are Better "1",9.84,9.85,9.84 "2",9.87,9.86,9.89 "3",9.9,9.84,9.83 "NCNN 20201218 - Target: Vulkan GPU - Model: efficientnet-b0", Lower Results Are Better "1",15.33,15.32,15.32 "2",15.36,15.4,15.31 "3",15.34,15.4 "NCNN 20201218 - Target: Vulkan GPU - Model: blazeface", Lower Results Are Better "1",3.86,3.87,3.86 "2",3.87,3.89,3.85 "3",3.86,3.87,3.87 "NCNN 20201218 - Target: Vulkan GPU - Model: googlenet", Lower Results Are Better "1",31.55,31.57,31.52 "2",31.5,31.52,31.57 "3",31.43,31.53,31.49 "NCNN 20201218 - Target: Vulkan GPU - Model: vgg16", Lower Results Are Better "1",111.1,111.47,111.31 "2",111.4,111.46,111.11 "3",111.09,111.22,110.95 "NCNN 20201218 - Target: Vulkan GPU - Model: resnet18", Lower Results Are Better "1",30.86,30.67,30.72 "2",30.74,30.75,30.79 "3",30.73,30.75,30.67 "NCNN 20201218 - Target: Vulkan GPU - Model: alexnet", Lower Results Are Better "1",24.95,24.95,24.88 "2",24.88,24.94,24.97 "3",24.86,24.95,24.89 "NCNN 20201218 - Target: Vulkan GPU - Model: resnet50", Lower Results Are Better "1",68.41,68.52,68.35 "2",68.31,68.39,68.39 "3",68.3,68.47,68.5 "NCNN 20201218 - Target: Vulkan GPU - Model: yolov4-tiny", Lower Results Are Better "1",57.16,57.14,57.15 "2",57.27,57.13,57.14 "3",57.18,57.21,57.19 "NCNN 20201218 - Target: Vulkan GPU - Model: squeezenet_ssd", Lower Results Are Better "1",47.13,47.4,47.05 "2",47.45,47.22,47.04 "3",47.32,47.4,47.05 "NCNN 20201218 - Target: Vulkan GPU - Model: regnety_400m", Lower Results Are Better "1",18.6,18.67,18.53 "2",18.69,18.66,18.66 "3",18.61,18.55,18.57 "PHPBench 0.8.1 - PHP Benchmark Suite", Higher Results Are Better "1",659521,658982,655159 "2",660240,655487,658652 "3",657343,658015,653528 "WavPack Audio Encoding 5.3 - WAV To WavPack", Lower Results Are Better "1",16.694,16.698,16.696,16.689,16.69 "2",16.698,16.692,16.694,16.701,16.693 "3",16.775,16.691,16.699,16.695,16.686