Core i3 8100 December, "VkFFT 1.1.1 - ", Higher Results Are Better "1",1362,1369,1369 "2",1370,1371,1367 "3",1369,1366,1369 "Betsy GPU Compressor 1.1 Beta - Codec: ETC1 - Quality: Highest", Lower Results Are Better "1",16.897,11.208,4.314,10.405,11.139,11.067,10.867,11.081,11.094,10.854,11.099,10.845 "2",12.156,11.036,11.092,10.862,11.094,10.84,11.141,11.073,10.846,11.129,10.81,11.101,11.106,10.847,11.098 "3",11.585,3.48,10.483,11.101,10.892,11.055,11.1,10.882,11.069,10.841,11.112,10.843 "Betsy GPU Compressor 1.1 Beta - Codec: ETC2 RGB - Quality: Highest", Lower Results Are Better "1", "VkResample 1.0 - Upscale: 2x - Precision: Double", Lower Results Are Better "1",1011.449,1013.711,1016.321 "2",1005.212,1015.006,1011.269 "3",1003.223,1012.104,1017.688 "VkResample 1.0 - Upscale: 2x - Precision: Single", Lower Results Are Better "1",478.624,478.155,479.721 "2",423.026,421.706,421.95 "3",421.301,422.592,421.011 "VKMark 2020-05-21 - Resolution: 1280 x 1024", Higher Results Are Better "1", "2",971,968,968 "3",959,962,972 "VKMark 2020-05-21 - Resolution: 1920 x 1080", Higher Results Are Better "1",660,654,658 "2", "3",657,659,658 "CLOMP 1.2 - Static OMP Speedup", Higher Results Are Better "1",1.7,1.7,1.7 "2",1.7,1.7,1.7 "3",1.7,1.7,1.7 "Timed HMMer Search 3.3.1 - Pfam Database Search", Lower Results Are Better "1",126.156,126.187,126.127 "2",126.279,126.146,126.168 "3",126.261,126.143,126.057 "Timed MAFFT Alignment 7.471 - Multiple Sequence Alignment - LSU RNA", Lower Results Are Better "1",11.96,11.994,11.864 "2",12.004,11.881,11.882 "3",12.061,12.072,11.858 "simdjson 0.7.1 - Throughput Test: Kostya", Higher Results Are Better "1",0.57,0.58,0.57 "2",0.58,0.57,0.58 "3",0.58,0.57,0.58 "simdjson 0.7.1 - Throughput Test: LargeRandom", Higher Results Are Better "1",0.35,0.35,0.35 "2",0.35,0.35,0.35 "3",0.35,0.35,0.35 "simdjson 0.7.1 - Throughput Test: PartialTweets", Higher Results Are Better "1",0.52,0.52,0.53 "2",0.52,0.53,0.52 "3",0.52,0.52,0.52 "simdjson 0.7.1 - Throughput Test: DistinctUserID", Higher Results Are Better "1",0.54,0.54,0.54 "2",0.54,0.54,0.54 "3",0.54,0.54,0.54 "LZ4 Compression 1.9.3 - Compression Level: 1 - Compression Speed", Higher Results Are Better "1",7611.88,7599.53,7613.44 "2",7635.37,7660.81,7595.51 "3",7599.05,7612.88,7626.51 "LZ4 Compression 1.9.3 - Compression Level: 1 - Decompression Speed", Higher Results Are Better "1",9214.6,9128.6,9261.4 "2",9196.4,9154.9,9285.9 "3",9219.3,9252.7,9178.6 "LZ4 Compression 1.9.3 - Compression Level: 3 - Compression Speed", Higher Results Are Better "1",40.95,40.84,41.13 "2",40.98,40.96,41.12 "3",41.14,40.86,40.96 "LZ4 Compression 1.9.3 - Compression Level: 3 - Decompression Speed", Higher Results Are Better "1",9053.4,9045,9075.5 "2",9054.1,9018.4,9081.4 "3",9061.5,9052.1,9058.4 "LZ4 Compression 1.9.3 - Compression Level: 9 - Compression Speed", Higher Results Are Better "1",39.96,40.13,40.14 "2",39.35,39.97,39.97 "3",39.97,39.99,39.98 "LZ4 Compression 1.9.3 - Compression Level: 9 - Decompression Speed", Higher Results Are Better "1",9058.7,9107.9,9066.2 "2",9076.9,9052,9030.6 "3",9063,9043.9,9093.9 "oneDNN 2.0 - Harness: IP Shapes 1D - Data Type: f32 - Engine: CPU", Lower Results Are Better "1",8.43882,8.48483,8.48815 "2",8.49659,8.47844,8.46461 "3",8.50454,8.45294,8.4406 "oneDNN 2.0 - Harness: IP Shapes 3D - Data Type: f32 - Engine: CPU", Lower Results Are Better "1",9.04292,9.05232,9.08902 "2",9.47589,9.5631,9.54752 "3",9.14634,9.21787,9.20246 "oneDNN 2.0 - Harness: IP Shapes 1D - Data Type: u8s8f32 - Engine: CPU", Lower Results Are Better "1",5.58378,5.58855,5.59395 "2",5.57904,5.58953,5.59156 "3",5.57918,5.57978,5.57978 "oneDNN 2.0 - Harness: IP Shapes 3D - Data Type: u8s8f32 - Engine: CPU", Lower Results Are Better "1",3.61354,3.57756,3.59831 "2",3.69875,3.62252,3.59177 "3",3.62402,3.58365,3.57056 "oneDNN 2.0 - Harness: Convolution Batch Shapes Auto - Data Type: f32 - Engine: CPU", Lower Results Are Better "1",18.5067,18.5814,18.5156 "2",18.7016,18.7674,18.6686 "3",18.5048,18.5807,18.5435 "oneDNN 2.0 - Harness: Deconvolution Batch shapes_1d - Data Type: f32 - Engine: CPU", Lower Results Are Better "1",11.4849,11.4812,11.5859 "2",11.5622,11.4603,11.4759 "3",11.4905,11.4459,11.4825 "oneDNN 2.0 - Harness: Deconvolution Batch shapes_3d - Data Type: f32 - Engine: CPU", Lower Results Are Better "1",14.3213,14.5942,14.4675 "2",14.3458,14.3739,14.3552 "3",14.3503,14.409,14.4842 "oneDNN 2.0 - Harness: Convolution Batch Shapes Auto - Data Type: u8s8f32 - Engine: CPU", Lower Results Are Better "1",17.6817,17.7723,17.6718 "2",17.7834,17.8367,17.8054 "3",17.7666,17.7698,17.7439 "oneDNN 2.0 - Harness: Deconvolution Batch shapes_1d - Data Type: u8s8f32 - Engine: CPU", Lower Results Are Better "1",14.4975,14.596,14.5708 "2",14.5343,14.5181,14.5647 "3",14.5722,14.4881,14.5604 "oneDNN 2.0 - Harness: Deconvolution Batch shapes_3d - Data Type: u8s8f32 - Engine: CPU", Lower Results Are Better "1",11.2336,11.2665,11.2362 "2",11.2299,11.2285,11.2435 "3",11.2181,11.2528,11.2321 "oneDNN 2.0 - Harness: Recurrent Neural Network Training - Data Type: f32 - Engine: CPU", Lower Results Are Better "1",6758.72,6762.66,6757.26 "2",6772.5,6748.09,6764.44 "3",6760.6,6763.04,6761.73 "oneDNN 2.0 - Harness: Recurrent Neural Network Inference - Data Type: f32 - Engine: CPU", Lower Results Are Better "1",3914.83,3852.94,3853.48 "2",3861.37,3861.09,3859.09 "3",3857.12,3853.73,3911.85 "oneDNN 2.0 - Harness: Recurrent Neural Network Training - Data Type: u8s8f32 - Engine: CPU", Lower Results Are Better "1",6743.04,6762.27,6769.45 "2",6757.55,6763.68,6756.53 "3",6770.6,6760.41,6771.15 "oneDNN 2.0 - Harness: Recurrent Neural Network Inference - Data Type: u8s8f32 - Engine: CPU", Lower Results Are Better "1",3864.78,3855.46,3847.12 "2",3856.53,3857.8,3862.63 "3",3854.85,3853.76,3849.79 "oneDNN 2.0 - Harness: Matrix Multiply Batch Shapes Transformer - Data Type: f32 - Engine: CPU", Lower Results Are Better "1",4.70418,4.71308,4.71833 "2",4.71208,4.72185,4.72401 "3",4.72069,4.71886,4.71874 "oneDNN 2.0 - Harness: Recurrent Neural Network Training - Data Type: bf16bf16bf16 - Engine: CPU", Lower Results Are Better "1",6753.67,6774,6748.84 "2",6763.88,6770.91,6878.22 "3",6771.45,6766.65,6754.88 "oneDNN 2.0 - Harness: Recurrent Neural Network Inference - Data Type: bf16bf16bf16 - Engine: CPU", Lower Results Are Better "1",3853.62,3859.47,3855.5 "2",3863.05,3858.85,3858.54 "3",3850.23,3858.31,3857.92 "oneDNN 2.0 - Harness: Matrix Multiply Batch Shapes Transformer - Data Type: u8s8f32 - Engine: CPU", Lower Results Are Better "1",7.48784,7.51475,7.50084 "2",7.49636,7.50607,7.51674 "3",7.49284,7.51633,7.5053 "rav1e 0.4 Alpha - Speed: 1", Higher Results Are Better "1",0.344,0.344,0.344 "2",0.343,0.344,0.346 "3",0.342,0.344,0.343 "rav1e 0.4 Alpha - Speed: 5", Higher Results Are Better "1",0.982,0.984,0.985 "2",0.98,0.987,0.984 "3",0.979,0.986,0.984 "rav1e 0.4 Alpha - Speed: 6", Higher Results Are Better "1",1.307,1.309,1.308 "2",1.307,1.307,1.309 "3",1.307,1.307,1.31 "rav1e 0.4 Alpha - Speed: 10", Higher Results Are Better "1",2.881,2.894,2.894 "2",2.876,2.892,2.894 "3",2.877,2.893,2.896 "Coremark 1.0 - CoreMark Size 666 - Iterations Per Second", Higher Results Are Better "1",92149.974083,104863.022677,90059.664528,100762.012721,90278.16961,106560.10656,94373.009319,100850.92972,93869.169845,102821.155453,105069.608616,95000.593754,98431.251922,96811.278514,99862.688803 "2",107570.256824,106298.166357,98747.14559,105596.620908,106375.905857,92421.441774,88849.400267,94899.169632,98129.408157,106702.234078,95283.468318,100546.722805,95608.007171,104065.04065,105932.20339 "3",87772.23106,95710.952922,89726.334679,94045.729736,92091.631173,90749.248483,95006.234784,90898.761504 "Stockfish 12 - Total Time", Higher Results Are Better "1",6350666,6461077,6558012 "2",6629367,6500126,6526452 "3",6478881,6312827,6563472 "asmFish 2018-07-23 - 1024 Hash Memory, 26 Depth", Higher Results Are Better "1",9136785,8802963,9024316 "2",9147784,8966461,8910895 "3",9001031,8841446,8894896 "Timed FFmpeg Compilation 4.2.2 - Time To Compile", Lower Results Are Better "1",151.747,151.52,151.624 "2",151.658,151.774,151.602 "3",152.018,151.613,151.721 "Build2 0.13 - Time To Compile", Lower Results Are Better "1",338.243,338.174,340.175 "2",338.352,338.186,337.427 "3",338.539,337.815,336.375 "Timed Eigen Compilation 3.3.9 - Time To Compile", Lower Results Are Better "1",93.596,93.387,93.54 "2",93.046,93.131,93.272 "3",93.061,93.214,92.995 "Monkey Audio Encoding 3.99.6 - WAV To APE", Lower Results Are Better "1",13.74,13.552,13.58,13.622,13.628 "2",13.899,13.583,13.629,13.624,13.784 "3",13.715,13.607,13.727,13.575,13.591 "Opus Codec Encoding 1.3.1 - WAV To Opus Encode", Lower Results Are Better "1",10.72,10.643,10.628,10.63,10.619 "2",10.728,10.634,10.627,10.622,10.627 "3",10.724,10.651,10.633,10.623,10.629 "Node.js V8 Web Tooling Benchmark - ", Higher Results Are Better "1",10.23,10.05,10.23 "2",10.39,10.39,10.38 "3",10.18,10.38,10.32 "ASTC Encoder 2.0 - Preset: Fast", Lower Results Are Better "1",5.74,5.78,5.75 "2",5.76,5.74,5.74 "3",5.74,5.74,5.77 "ASTC Encoder 2.0 - Preset: Medium", Lower Results Are Better "1",14.27,14.29,14.28 "2",14.29,14.28,14.31 "3",14.31,14.27,14.29 "ASTC Encoder 2.0 - Preset: Thorough", Lower Results Are Better "1",92.89,92.95,92.93 "2",92.85,92.89,92.9 "3",92.99,92.89,92.98 "ASTC Encoder 2.0 - Preset: Exhaustive", Lower Results Are Better "1",738.12,738.42,738.56 "2",737.92,737.72,737.73 "3",738.21,738.41,738.69 "SQLite Speedtest 3.30 - Timed Time - Size 1,000", Lower Results Are Better "1",79.495,79.386,79.416 "2",79.07,79.653,80.256 "3",79.095,78.765,78.912 "NCNN 20201218 - Target: CPU - Model: mobilenet", Lower Results Are Better "1",28.18,28.14,28.13 "2",28.14,28.17,28.15 "3",28.24,28.13,28.14 "NCNN 20201218 - Target: CPU-v2-v2 - Model: mobilenet-v2", Lower Results Are Better "1",7.12,7.14,7.28 "2",7.13,7.14,7.16 "3",7.12,7.13,7.14 "NCNN 20201218 - Target: CPU-v3-v3 - Model: mobilenet-v3", Lower Results Are Better "1",6.24,6.25,6.23 "2",6.23,6.23,6.29 "3",6.21,6.25,6.26 "NCNN 20201218 - Target: CPU - Model: shufflenet-v2", Lower Results Are Better "1",9.31,9.36,9.35 "2",9.32,9.37,9.34 "3",9.33,9.37,9.37 "NCNN 20201218 - Target: CPU - Model: mnasnet", Lower Results Are Better "1",6.53,6.53,6.58 "2",6.5,6.52,6.52 "3",6.54,6.52,6.52 "NCNN 20201218 - Target: CPU - Model: efficientnet-b0", Lower Results Are Better "1",10.39,10.39,10.38 "2",10.36,10.36,10.36 "3",10.36,10.38,10.36 "NCNN 20201218 - Target: CPU - Model: blazeface", Lower Results Are Better "1",2.36,2.37,2.35 "2",2.36,2.36,2.35 "3",2.36,2.36,2.36 "NCNN 20201218 - Target: CPU - Model: googlenet", Lower Results Are Better "1",21.68,21.73,21.66 "2",21.85,21.71,21.7 "3",21.69,21.68,21.86 "NCNN 20201218 - Target: CPU - Model: vgg16", Lower Results Are Better "1",87.36,87.29,87.4 "2",87.16,87.35,87.45 "3",87.52,87.34,87.15 "NCNN 20201218 - Target: CPU - Model: resnet18", Lower Results Are Better "1",22.56,22.55,22.54 "2",22.53,22.54,22.6 "3",22.52,22.58,22.59 "NCNN 20201218 - Target: CPU - Model: alexnet", Lower Results Are Better "1",19.3,19.32,19.33 "2",19.37,19.32,19.34 "3",19.4,19.29,19.31 "NCNN 20201218 - Target: CPU - Model: resnet50", Lower Results Are Better "1",47.84,47.82,47.82 "2",47.83,48.01,47.86 "3",48.01,47.82,47.81 "NCNN 20201218 - Target: CPU - Model: yolov4-tiny", Lower Results Are Better "1",39.11,38.95,38.91 "2",38.99,38.95,38.97 "3",39.01,38.96,38.93 "NCNN 20201218 - Target: CPU - Model: squeezenet_ssd", Lower Results Are Better "1",40.35,40.42,40.43 "2",40.43,40.42,40.54 "3",40.41,40.47,40.46 "NCNN 20201218 - Target: CPU - Model: regnety_400m", Lower Results Are Better "1",14.55,14.61,14.49 "2",14.44,14.51,14.55 "3",14.52,14.58,14.55 "NCNN 20201218 - Target: Vulkan GPU - Model: mobilenet", Lower Results Are Better "1",28.23,28.13,28.13 "2",28.18,28.18,28.07 "3",28.1,28.12,28.17 "NCNN 20201218 - Target: Vulkan GPU-v2-v2 - Model: mobilenet-v2", Lower Results Are Better "1",7.17,7.15,7.15 "2",7.15,7.15,7.15 "3",7.14,7.15,7.14 "NCNN 20201218 - Target: Vulkan GPU-v3-v3 - Model: mobilenet-v3", Lower Results Are Better "1",6.26,6.26,6.25 "2",6.26,6.25,6.26 "3",6.25,6.24,6.25 "NCNN 20201218 - Target: Vulkan GPU - Model: shufflenet-v2", Lower Results Are Better "1",9.36,9.37,9.35 "2",9.33,9.38,9.39 "3",9.31,9.35,9.35 "NCNN 20201218 - Target: Vulkan GPU - Model: mnasnet", Lower Results Are Better "1",6.55,6.53,6.53 "2",6.54,6.53,6.54 "3",6.52,6.52,6.54 "NCNN 20201218 - Target: Vulkan GPU - Model: efficientnet-b0", Lower Results Are Better "1",10.37,10.39,10.35 "2",10.37,10.37,10.37 "3",10.44,10.39,10.35 "NCNN 20201218 - Target: Vulkan GPU - Model: blazeface", Lower Results Are Better "1",2.36,2.36,2.37 "2",2.36,2.36,2.37 "3",2.37,2.36,2.36 "NCNN 20201218 - Target: Vulkan GPU - Model: googlenet", Lower Results Are Better "1",21.73,21.67,21.65 "2",21.72,21.77,21.67 "3",21.66,21.7,21.72 "NCNN 20201218 - Target: Vulkan GPU - Model: vgg16", Lower Results Are Better "1",87.3,87.26,87.29 "2",87.18,87.41,87.12 "3",87.21,87.25,87.22 "NCNN 20201218 - Target: Vulkan GPU - Model: resnet18", Lower Results Are Better "1",22.46,22.56,22.55 "2",22.55,22.52,22.48 "3",22.54,22.52,22.52 "NCNN 20201218 - Target: Vulkan GPU - Model: alexnet", Lower Results Are Better "1",19.29,19.3,19.26 "2",19.34,19.31,19.27 "3",19.32,19.29,19.28 "NCNN 20201218 - Target: Vulkan GPU - Model: resnet50", Lower Results Are Better "1",47.86,47.85,47.8 "2",47.79,47.74,47.84 "3",47.88,47.77,48.13 "NCNN 20201218 - Target: Vulkan GPU - Model: yolov4-tiny", Lower Results Are Better "1",38.93,39.03,38.95 "2",38.98,39.01,38.89 "3",38.97,38.98,38.88 "NCNN 20201218 - Target: Vulkan GPU - Model: squeezenet_ssd", Lower Results Are Better "1",40.43,40.68,40.45 "2",40.55,40.43,40.4 "3",40.41,40.54,40.37 "NCNN 20201218 - Target: Vulkan GPU - Model: regnety_400m", Lower Results Are Better "1",14.56,14.57,14.52 "2",14.51,14.53,14.55 "3",14.55,14.56,14.58 "OpenVINO 2021.1 - Model: Face Detection 0106 FP16 - Device: CPU", Higher Results Are Better "1",1.16,1.17,1.16 "2",1.16,1.17,1.17 "3",1.16,1.16,1.17 "OpenVINO 2021.1 - Model: Face Detection 0106 FP16 - Device: CPU", Lower Results Are Better "1",3431.68,3425.15,3421.63 "2",3423.44,3426.99,3417.94 "3",3433.89,3427.85,3416.4 "OpenVINO 2021.1 - Model: Face Detection 0106 FP32 - Device: CPU", Higher Results Are Better "1",1.15,1.15,1.15 "2",1.15,1.15,1.15 "3",1.14,1.15,1.15 "OpenVINO 2021.1 - Model: Face Detection 0106 FP32 - Device: CPU", Lower Results Are Better "1",3432.22,3440.83,3436.89 "2",3424.34,3441.24,3444.1 "3",3419.31,3440.93,3451.87 "OpenVINO 2021.1 - Model: Person Detection 0106 FP16 - Device: CPU", Higher Results Are Better "1",0.7,0.71,0.71 "2",0.7,0.71,0.71 "3",0.7,0.71,0.71 "OpenVINO 2021.1 - Model: Person Detection 0106 FP16 - Device: CPU", Lower Results Are Better "1",5646.33,5643.26,5634.26 "2",5646.9,5632.23,5635.82 "3",5649.74,5640.58,5636.64 "OpenVINO 2021.1 - Model: Person Detection 0106 FP32 - Device: CPU", Higher Results Are Better "1",0.71,0.7,0.7 "2",0.71,0.7,0.71 "3",0.7,0.7,0.71 "OpenVINO 2021.1 - Model: Person Detection 0106 FP32 - Device: CPU", Lower Results Are Better "1",5635.96,5647.19,5661.45 "2",5630.51,5649.23,5636.04 "3",5667.91,5644.87,5638.9 "OpenVINO 2021.1 - Model: Age Gender Recognition Retail 0013 FP16 - Device: CPU", Higher Results Are Better "1",2569.6,2544.93,2533.93 "2",2549.24,2161.99,2527.82,2540.4,2542.46,2545.09,2540.14,2566.21,2575.89,2550.72,2554.24,2543.87 "3",2554.8,2534.89,2596.83 "OpenVINO 2021.1 - Model: Age Gender Recognition Retail 0013 FP16 - Device: CPU", Lower Results Are Better "1",1.45,1.45,1.45 "2",1.45,1.46,1.45,1.46,1.46,1.46,1.45,1.45,1.45,1.46,1.45,1.45 "3",1.46,1.46,1.46 "OpenVINO 2021.1 - Model: Age Gender Recognition Retail 0013 FP32 - Device: CPU", Higher Results Are Better "1",2542.09,2536.6,2551.85 "2",2552.77,2546.68,2554.79 "3",2544.16,2548.11,2564.53 "OpenVINO 2021.1 - Model: Age Gender Recognition Retail 0013 FP32 - Device: CPU", Lower Results Are Better "1",1.46,1.46,1.46 "2",1.45,1.46,1.45 "3",1.45,1.45,1.45 "WavPack Audio Encoding 5.3 - WAV To WavPack", Lower Results Are Better "1",17.949,17.942,18.05,17.943,17.941 "2",17.949,17.941,17.94,17.941,17.941 "3",17.951,17.943,17.944,17.941,17.945 "Unpacking Firefox 84.0 - Extracting: firefox-84.0.source.tar.xz", Lower Results Are Better "1",23.779,23.023,23.042,23.179 "2",24.058,23.023,23.457,23.034 "3",24.43,23.733,23.011,23.501 "BRL-CAD 7.30.8 - VGR Performance Metric", Higher Results Are Better "1", "2", "3",