Core i5 10600K 2021 Intel Core i5-10600K testing with a ASUS PRIME Z490M-PLUS (1001 BIOS) and ASUS Intel UHD 630 3GB on Ubuntu 20.04 via the Phoronix Test Suite. Run 1: Processor: Intel Core i5-10600K @ 4.80GHz (6 Cores / 12 Threads), Motherboard: ASUS PRIME Z490M-PLUS (1001 BIOS), Chipset: Intel Comet Lake PCH, Memory: 32GB, Disk: Samsung SSD 970 EVO 500GB, Graphics: ASUS Intel UHD 630 3GB (1200MHz), Audio: Realtek ALC887-VD, Monitor: LG Ultra HD, Network: Intel OS: Ubuntu 20.04, Kernel: 5.9.0-050900daily20201012-generic (x86_64), Desktop: GNOME Shell 3.36.4, Display Server: X Server 1.20.8, Display Driver: modesetting 1.20.8, OpenGL: 4.6 Mesa 20.0.8, Vulkan: 1.2.131, Compiler: GCC 9.3.0, File-System: ext4, Screen Resolution: 3840x2160 Run 2: Processor: Intel Core i5-10600K @ 4.80GHz (6 Cores / 12 Threads), Motherboard: ASUS PRIME Z490M-PLUS (1001 BIOS), Chipset: Intel Comet Lake PCH, Memory: 32GB, Disk: Samsung SSD 970 EVO 500GB, Graphics: ASUS Intel UHD 630 3GB (1200MHz), Audio: Realtek ALC887-VD, Monitor: LG Ultra HD, Network: Intel OS: Ubuntu 20.04, Kernel: 5.9.0-050900daily20201012-generic (x86_64), Desktop: GNOME Shell 3.36.4, Display Server: X Server 1.20.8, Display Driver: modesetting 1.20.8, OpenGL: 4.6 Mesa 20.0.8, Vulkan: 1.2.131, Compiler: GCC 9.3.0, File-System: ext4, Screen Resolution: 3840x2160 Run 3: Processor: Intel Core i5-10600K @ 4.80GHz (6 Cores / 12 Threads), Motherboard: ASUS PRIME Z490M-PLUS (1001 BIOS), Chipset: Intel Comet Lake PCH, Memory: 32GB, Disk: Samsung SSD 970 EVO 500GB, Graphics: ASUS Intel UHD 630 3GB (1200MHz), Audio: Realtek ALC887-VD, Monitor: LG Ultra HD, Network: Intel OS: Ubuntu 20.04, Kernel: 5.9.0-050900daily20201012-generic (x86_64), Desktop: GNOME Shell 3.36.4, Display Server: X Server 1.20.8, Display Driver: modesetting 1.20.8, OpenGL: 4.6 Mesa 20.0.8, Vulkan: 1.2.131, Compiler: GCC 9.3.0, File-System: ext4, Screen Resolution: 3840x2160 Run 4: Processor: Intel Core i5-10600K @ 4.80GHz (6 Cores / 12 Threads), Motherboard: ASUS PRIME Z490M-PLUS (1001 BIOS), Chipset: Intel Comet Lake PCH, Memory: 32GB, Disk: Samsung SSD 970 EVO 500GB, Graphics: ASUS Intel UHD 630 3GB (1200MHz), Audio: Realtek ALC887-VD, Monitor: LG Ultra HD, Network: Intel OS: Ubuntu 20.04, Kernel: 5.9.0-050900daily20201012-generic (x86_64), Desktop: GNOME Shell 3.36.4, Display Server: X Server 1.20.8, Display Driver: modesetting 1.20.8, OpenGL: 4.6 Mesa 20.0.8, Vulkan: 1.2.131, Compiler: GCC 9.3.0, File-System: ext4, Screen Resolution: 3840x2160 Run 5: Processor: Intel Core i5-10600K @ 4.80GHz (6 Cores / 12 Threads), Motherboard: ASUS PRIME Z490M-PLUS (1001 BIOS), Chipset: Intel Comet Lake PCH, Memory: 32GB, Disk: Samsung SSD 970 EVO 500GB, Graphics: ASUS Intel UHD 630 3GB (1200MHz), Audio: Realtek ALC887-VD, Monitor: LG Ultra HD, Network: Intel OS: Ubuntu 20.04, Kernel: 5.9.0-050900daily20201012-generic (x86_64), Desktop: GNOME Shell 3.36.4, Display Server: X Server 1.20.8, Display Driver: modesetting 1.20.8, OpenGL: 4.6 Mesa 20.0.8, Vulkan: 1.2.131, Compiler: GCC 9.3.0, File-System: ext4, Screen Resolution: 3840x2160 VkResample 1.0 Upscale: 2x - Precision: Double ms < Lower Is Better Run 1 . 889.54 |============================================================= Run 2 . 921.46 |=============================================================== Run 3 . 922.85 |=============================================================== Run 4 . 921.74 |=============================================================== Run 5 . 921.46 |=============================================================== VkResample 1.0 Upscale: 2x - Precision: Single ms < Lower Is Better Run 1 . 378.00 |============================================================= Run 2 . 386.44 |=============================================================== Run 3 . 384.60 |============================================================== Run 4 . 386.57 |=============================================================== Run 5 . 388.06 |=============================================================== VKMark 2020-05-21 Resolution: 1920 x 1080 VKMark Score > Higher Is Better Run 1 . 815 |================================================================== Run 2 . 814 |================================================================== Run 3 . 815 |================================================================== Run 4 . 813 |================================================================== Run 5 . 814 |================================================================== VKMark 2020-05-21 Resolution: 1920 x 1200 VKMark Score > Higher Is Better Run 1 . 731 |================================================================== Run 2 . 726 |================================================================== Run 3 . 725 |================================================================= Run 4 . 727 |================================================================== Run 5 . 725 |================================================================= VKMark 2020-05-21 Resolution: 2560 x 1440 VKMark Score > Higher Is Better Run 1 . 476 |================================================================== Run 2 . 474 |================================================================== Run 3 . 473 |================================================================== Run 4 . 474 |================================================================== Run 5 . 473 |================================================================== VKMark 2020-05-21 Resolution: 3840 x 2160 VKMark Score > Higher Is Better Run 1 . 219 |================================================================== Run 2 . 216 |================================================================= Run 3 . 216 |================================================================= Run 4 . 216 |================================================================= Run 5 . 216 |================================================================= CLOMP 1.2 Static OMP Speedup Speedup > Higher Is Better Run 1 . 2.9 |================================================================ Run 2 . 3.0 |================================================================== Run 3 . 2.8 |============================================================== Run 4 . 2.8 |============================================================== Run 5 . 2.9 |================================================================ oneDNN 2.0 Harness: IP Shapes 1D - Data Type: f32 - Engine: CPU ms < Lower Is Better Run 1 . 4.27796 |============================================================== Run 2 . 4.27385 |============================================================== Run 3 . 4.29524 |============================================================== Run 4 . 4.29198 |============================================================== Run 5 . 4.30381 |============================================================== oneDNN 2.0 Harness: IP Shapes 3D - Data Type: f32 - Engine: CPU ms < Lower Is Better Run 1 . 7.46409 |========================================================= Run 2 . 8.16144 |============================================================== Run 3 . 8.09095 |============================================================= Run 4 . 8.06959 |============================================================= Run 5 . 8.07460 |============================================================= oneDNN 2.0 Harness: IP Shapes 1D - Data Type: u8s8f32 - Engine: CPU ms < Lower Is Better Run 1 . 2.01829 |============================================================== Run 2 . 2.01386 |============================================================== Run 3 . 2.02059 |============================================================== Run 4 . 2.02147 |============================================================== Run 5 . 2.01957 |============================================================== oneDNN 2.0 Harness: IP Shapes 3D - Data Type: u8s8f32 - Engine: CPU ms < Lower Is Better Run 1 . 2.31323 |============================================================== Run 2 . 2.31143 |============================================================== Run 3 . 2.31486 |============================================================== Run 4 . 2.32631 |============================================================== Run 5 . 2.32352 |============================================================== oneDNN 2.0 Harness: Convolution Batch Shapes Auto - Data Type: f32 - Engine: CPU ms < Lower Is Better Run 1 . 15.22 |================================================================ Run 2 . 15.31 |================================================================ Run 3 . 15.28 |================================================================ Run 4 . 15.29 |================================================================ Run 5 . 15.32 |================================================================ oneDNN 2.0 Harness: Deconvolution Batch shapes_1d - Data Type: f32 - Engine: CPU ms < Lower Is Better Run 1 . 6.04508 |============================================================== Run 2 . 6.05508 |============================================================== Run 3 . 6.06965 |============================================================== Run 4 . 6.05207 |============================================================== Run 5 . 6.04427 |============================================================== oneDNN 2.0 Harness: Deconvolution Batch shapes_3d - Data Type: f32 - Engine: CPU ms < Lower Is Better Run 1 . 8.45284 |============================================================== Run 2 . 8.44886 |============================================================== Run 3 . 8.44968 |============================================================== Run 4 . 8.45132 |============================================================== Run 5 . 8.44634 |============================================================== oneDNN 2.0 Harness: Convolution Batch Shapes Auto - Data Type: u8s8f32 - Engine: CPU ms < Lower Is Better Run 1 . 13.89 |================================================================ Run 2 . 13.91 |================================================================ Run 3 . 13.89 |================================================================ Run 4 . 13.95 |================================================================ Run 5 . 13.93 |================================================================ oneDNN 2.0 Harness: Deconvolution Batch shapes_1d - Data Type: u8s8f32 - Engine: CPU ms < Lower Is Better Run 1 . 6.06795 |============================================================== Run 2 . 6.04194 |============================================================= Run 3 . 6.06513 |============================================================= Run 4 . 6.11716 |============================================================== Run 5 . 6.08168 |============================================================== oneDNN 2.0 Harness: Deconvolution Batch shapes_3d - Data Type: u8s8f32 - Engine: CPU ms < Lower Is Better Run 1 . 3.99728 |============================================================== Run 2 . 4.00392 |============================================================== Run 3 . 3.99032 |============================================================== Run 4 . 3.99737 |============================================================== Run 5 . 3.99663 |============================================================== oneDNN 2.0 Harness: Recurrent Neural Network Training - Data Type: f32 - Engine: CPU ms < Lower Is Better Run 1 . 3998.24 |============================================================== Run 2 . 4001.98 |============================================================== Run 3 . 4003.53 |============================================================== Run 4 . 4000.59 |============================================================== Run 5 . 4003.73 |============================================================== oneDNN 2.0 Harness: Recurrent Neural Network Inference - Data Type: f32 - Engine: CPU ms < Lower Is Better Run 1 . 2399.13 |============================================================== Run 2 . 2414.27 |============================================================== Run 3 . 2402.06 |============================================================== Run 4 . 2408.34 |============================================================== Run 5 . 2404.06 |============================================================== oneDNN 2.0 Harness: Recurrent Neural Network Training - Data Type: u8s8f32 - Engine: CPU ms < Lower Is Better Run 1 . 3996.33 |============================================================== Run 2 . 4003.51 |============================================================== Run 3 . 4002.93 |============================================================== Run 4 . 4001.98 |============================================================== Run 5 . 4003.17 |============================================================== oneDNN 2.0 Harness: Recurrent Neural Network Inference - Data Type: u8s8f32 - Engine: CPU ms < Lower Is Better Run 1 . 2400.70 |============================================================== Run 2 . 2407.83 |============================================================== Run 3 . 2408.33 |============================================================== Run 4 . 2406.66 |============================================================== Run 5 . 2404.97 |============================================================== oneDNN 2.0 Harness: Matrix Multiply Batch Shapes Transformer - Data Type: f32 - Engine: CPU ms < Lower Is Better Run 1 . 3.43241 |============================================================== Run 2 . 3.43780 |============================================================== Run 3 . 3.43832 |============================================================== Run 4 . 3.44304 |============================================================== Run 5 . 3.43872 |============================================================== oneDNN 2.0 Harness: Recurrent Neural Network Training - Data Type: bf16bf16bf16 - Engine: CPU ms < Lower Is Better Run 1 . 3999.69 |============================================================== Run 2 . 4003.09 |============================================================== Run 3 . 4001.78 |============================================================== Run 4 . 4000.06 |============================================================== Run 5 . 4002.25 |============================================================== oneDNN 2.0 Harness: Recurrent Neural Network Inference - Data Type: bf16bf16bf16 - Engine: CPU ms < Lower Is Better Run 1 . 2400.58 |============================================================== Run 2 . 2408.99 |============================================================== Run 3 . 2409.57 |============================================================== Run 4 . 2410.79 |============================================================== Run 5 . 2412.10 |============================================================== oneDNN 2.0 Harness: Matrix Multiply Batch Shapes Transformer - Data Type: u8s8f32 - Engine: CPU ms < Lower Is Better Run 1 . 2.96337 |============================================================== Run 2 . 2.95600 |============================================================== Run 3 . 2.95629 |============================================================== Run 4 . 2.95899 |============================================================== Run 5 . 2.95866 |============================================================== Timed FFmpeg Compilation 4.2.2 Time To Compile Seconds < Lower Is Better Run 1 . 70.37 |================================================================ Run 2 . 70.26 |================================================================ Run 3 . 70.40 |================================================================ Run 4 . 70.45 |================================================================ Run 5 . 70.31 |================================================================ Build2 0.13 Time To Compile Seconds < Lower Is Better Run 1 . 151.25 |============================================================== Run 2 . 152.43 |============================================================== Run 3 . 153.84 |=============================================================== Run 4 . 152.91 |=============================================================== Timed Eigen Compilation 3.3.9 Time To Compile Seconds < Lower Is Better Run 1 . 68.96 |================================================================ Run 2 . 69.28 |================================================================ Run 3 . 69.19 |================================================================ Run 4 . 68.90 |================================================================ Monkey Audio Encoding 3.99.6 WAV To APE Seconds < Lower Is Better Run 1 . 10.50 |================================================================ Run 2 . 10.52 |================================================================ Run 3 . 10.50 |================================================================ Run 4 . 10.54 |================================================================ Opus Codec Encoding 1.3.1 WAV To Opus Encode Seconds < Lower Is Better Run 1 . 7.714 |================================================================ Run 2 . 7.719 |================================================================ Run 3 . 7.733 |================================================================ Run 4 . 7.720 |================================================================ Cryptsetup PBKDF2-sha512 Iterations Per Second > Higher Is Better Run 1 . 1952660 |============================================================== Run 2 . 1957522 |============================================================== Run 3 . 1958736 |============================================================== Run 4 . 1952709 |============================================================== Cryptsetup PBKDF2-whirlpool Iterations Per Second > Higher Is Better Run 1 . 837967 |=============================================================== Run 2 . 837078 |=============================================================== Run 3 . 837075 |=============================================================== Run 4 . 837967 |=============================================================== Cryptsetup AES-XTS 256b Encryption MiB/s > Higher Is Better Run 1 . 4165.7 |============================================================== Run 2 . 4175.5 |============================================================== Run 3 . 4192.1 |=============================================================== Run 4 . 4219.8 |=============================================================== Cryptsetup AES-XTS 256b Decryption MiB/s > Higher Is Better Run 1 . 4171.6 |============================================================== Run 2 . 4187.4 |============================================================== Run 3 . 4195.7 |=============================================================== Run 4 . 4222.0 |=============================================================== Cryptsetup Serpent-XTS 256b Encryption MiB/s > Higher Is Better Run 1 . 902.9 |================================================================ Run 2 . 905.4 |================================================================ Run 3 . 906.6 |================================================================ Run 4 . 906.7 |================================================================ Cryptsetup Serpent-XTS 256b Decryption MiB/s > Higher Is Better Run 1 . 883.9 |================================================================ Run 2 . 885.3 |================================================================ Run 3 . 885.7 |================================================================ Run 4 . 886.5 |================================================================ Cryptsetup Twofish-XTS 256b Encryption MiB/s > Higher Is Better Run 1 . 496.0 |================================================================ Run 2 . 496.9 |================================================================ Run 3 . 497.0 |================================================================ Run 4 . 497.6 |================================================================ Cryptsetup Twofish-XTS 256b Decryption MiB/s > Higher Is Better Run 1 . 497.7 |================================================================ Run 2 . 497.9 |================================================================ Run 3 . 498.4 |================================================================ Run 4 . 498.6 |================================================================ Cryptsetup AES-XTS 512b Encryption MiB/s > Higher Is Better Run 1 . 3418.4 |============================================================== Run 2 . 3425.2 |=============================================================== Run 3 . 3437.4 |=============================================================== Run 4 . 3446.7 |=============================================================== Cryptsetup AES-XTS 512b Decryption MiB/s > Higher Is Better Run 1 . 3418.0 |============================================================== Run 2 . 3430.0 |=============================================================== Run 3 . 3441.6 |=============================================================== Run 4 . 3453.6 |=============================================================== Cryptsetup Serpent-XTS 512b Encryption MiB/s > Higher Is Better Run 1 . 905.6 |================================================================ Run 2 . 905.5 |================================================================ Run 3 . 904.7 |================================================================ Run 4 . 907.4 |================================================================ Cryptsetup Serpent-XTS 512b Decryption MiB/s > Higher Is Better Run 1 . 884.3 |================================================================ Run 2 . 885.4 |================================================================ Run 3 . 885.7 |================================================================ Run 4 . 886.1 |================================================================ Cryptsetup Twofish-XTS 512b Encryption MiB/s > Higher Is Better Run 1 . 496.3 |================================================================ Run 2 . 496.7 |================================================================ Run 3 . 497.1 |================================================================ Run 4 . 497.4 |================================================================ Cryptsetup Twofish-XTS 512b Decryption MiB/s > Higher Is Better Run 1 . 497.3 |================================================================ Run 2 . 497.7 |================================================================ Run 3 . 498.2 |================================================================ Run 4 . 498.2 |================================================================ NCNN 20201218 Target: CPU - Model: mobilenet ms < Lower Is Better Run 1 . 18.92 |================================================================ Run 2 . 18.83 |================================================================ Run 3 . 18.79 |================================================================ Run 4 . 18.75 |=============================================================== NCNN 20201218 Target: CPU-v2-v2 - Model: mobilenet-v2 ms < Lower Is Better Run 1 . 5.38 |================================================================ Run 2 . 5.42 |================================================================= Run 3 . 5.45 |================================================================= Run 4 . 5.43 |================================================================= NCNN 20201218 Target: CPU-v3-v3 - Model: mobilenet-v3 ms < Lower Is Better Run 1 . 4.33 |================================================================ Run 2 . 4.39 |================================================================= Run 3 . 4.38 |================================================================= Run 4 . 4.40 |================================================================= NCNN 20201218 Target: CPU - Model: shufflenet-v2 ms < Lower Is Better Run 1 . 5.57 |================================================================ Run 2 . 5.59 |================================================================= Run 3 . 5.61 |================================================================= Run 4 . 5.62 |================================================================= NCNN 20201218 Target: CPU - Model: mnasnet ms < Lower Is Better Run 1 . 4.41 |================================================================ Run 2 . 4.42 |================================================================= Run 3 . 4.45 |================================================================= Run 4 . 4.45 |================================================================= NCNN 20201218 Target: CPU - Model: efficientnet-b0 ms < Lower Is Better Run 1 . 6.96 |================================================================ Run 2 . 6.98 |================================================================= Run 3 . 7.01 |================================================================= Run 4 . 7.02 |================================================================= NCNN 20201218 Target: CPU - Model: blazeface ms < Lower Is Better Run 1 . 1.73 |================================================================ Run 2 . 1.75 |================================================================= Run 3 . 1.75 |================================================================= Run 4 . 1.75 |================================================================= NCNN 20201218 Target: CPU - Model: googlenet ms < Lower Is Better Run 1 . 14.67 |================================================================ Run 2 . 14.69 |================================================================ Run 3 . 14.74 |================================================================ Run 4 . 14.68 |================================================================ NCNN 20201218 Target: CPU - Model: vgg16 ms < Lower Is Better Run 1 . 58.61 |================================================================ Run 2 . 58.40 |================================================================ Run 3 . 58.28 |================================================================ Run 4 . 58.32 |================================================================ NCNN 20201218 Target: CPU - Model: resnet18 ms < Lower Is Better Run 1 . 14.73 |================================================================ Run 2 . 14.77 |================================================================ Run 3 . 14.77 |================================================================ Run 4 . 14.79 |================================================================ NCNN 20201218 Target: CPU - Model: alexnet ms < Lower Is Better Run 1 . 12.47 |================================================================ Run 2 . 12.36 |=============================================================== Run 3 . 12.36 |=============================================================== Run 4 . 12.33 |=============================================================== NCNN 20201218 Target: CPU - Model: resnet50 ms < Lower Is Better Run 1 . 29.37 |================================================================ Run 2 . 29.30 |================================================================ Run 3 . 29.31 |================================================================ Run 4 . 29.27 |================================================================ NCNN 20201218 Target: CPU - Model: yolov4-tiny ms < Lower Is Better Run 1 . 27.40 |================================================================ Run 2 . 27.17 |=============================================================== Run 3 . 27.17 |=============================================================== Run 4 . 27.08 |=============================================================== NCNN 20201218 Target: CPU - Model: squeezenet_ssd ms < Lower Is Better Run 1 . 19.77 |================================================================ Run 2 . 19.58 |=============================================================== Run 3 . 19.62 |================================================================ Run 4 . 19.60 |=============================================================== NCNN 20201218 Target: CPU - Model: regnety_400m ms < Lower Is Better Run 1 . 12.50 |=============================================================== Run 2 . 12.60 |=============================================================== Run 3 . 12.70 |================================================================ Run 4 . 12.79 |================================================================ NCNN 20201218 Target: Vulkan GPU - Model: mobilenet ms < Lower Is Better Run 1 . 18.71 |================================================================ Run 2 . 18.68 |================================================================ Run 3 . 18.74 |================================================================ Run 4 . 18.79 |================================================================ NCNN 20201218 Target: Vulkan GPU-v2-v2 - Model: mobilenet-v2 ms < Lower Is Better Run 1 . 5.41 |================================================================= Run 2 . 5.41 |================================================================= Run 3 . 5.41 |================================================================= Run 4 . 5.42 |================================================================= NCNN 20201218 Target: Vulkan GPU-v3-v3 - Model: mobilenet-v3 ms < Lower Is Better Run 1 . 4.36 |================================================================= Run 2 . 4.35 |================================================================= Run 3 . 4.35 |================================================================= Run 4 . 4.34 |================================================================= NCNN 20201218 Target: Vulkan GPU - Model: shufflenet-v2 ms < Lower Is Better Run 1 . 5.61 |================================================================= Run 2 . 5.57 |================================================================= Run 3 . 5.58 |================================================================= Run 4 . 5.57 |================================================================= NCNN 20201218 Target: Vulkan GPU - Model: mnasnet ms < Lower Is Better Run 1 . 4.44 |================================================================= Run 2 . 4.43 |================================================================= Run 3 . 4.40 |================================================================ Run 4 . 4.41 |================================================================= NCNN 20201218 Target: Vulkan GPU - Model: efficientnet-b0 ms < Lower Is Better Run 1 . 6.98 |================================================================= Run 2 . 6.97 |================================================================= Run 3 . 6.98 |================================================================= Run 4 . 6.93 |================================================================= NCNN 20201218 Target: Vulkan GPU - Model: blazeface ms < Lower Is Better Run 1 . 1.75 |================================================================= Run 2 . 1.74 |================================================================= Run 3 . 1.74 |================================================================= Run 4 . 1.74 |================================================================= NCNN 20201218 Target: Vulkan GPU - Model: googlenet ms < Lower Is Better Run 1 . 14.68 |================================================================ Run 2 . 14.66 |================================================================ Run 3 . 14.70 |================================================================ Run 4 . 14.72 |================================================================ NCNN 20201218 Target: Vulkan GPU - Model: vgg16 ms < Lower Is Better Run 1 . 58.33 |================================================================ Run 2 . 58.30 |================================================================ Run 3 . 58.35 |================================================================ Run 4 . 58.32 |================================================================ NCNN 20201218 Target: Vulkan GPU - Model: resnet18 ms < Lower Is Better Run 1 . 14.76 |================================================================ Run 2 . 14.76 |================================================================ Run 3 . 14.76 |================================================================ Run 4 . 14.83 |================================================================ NCNN 20201218 Target: Vulkan GPU - Model: alexnet ms < Lower Is Better Run 1 . 12.36 |================================================================ Run 2 . 12.32 |================================================================ Run 3 . 12.34 |================================================================ Run 4 . 12.36 |================================================================ NCNN 20201218 Target: Vulkan GPU - Model: resnet50 ms < Lower Is Better Run 1 . 29.25 |================================================================ Run 2 . 29.24 |================================================================ Run 3 . 29.27 |================================================================ Run 4 . 29.29 |================================================================ NCNN 20201218 Target: Vulkan GPU - Model: yolov4-tiny ms < Lower Is Better Run 1 . 27.08 |================================================================ Run 2 . 27.05 |================================================================ Run 3 . 27.11 |================================================================ Run 4 . 27.08 |================================================================ NCNN 20201218 Target: Vulkan GPU - Model: squeezenet_ssd ms < Lower Is Better Run 1 . 19.53 |================================================================ Run 2 . 19.55 |================================================================ Run 3 . 19.56 |================================================================ Run 4 . 19.53 |================================================================ NCNN 20201218 Target: Vulkan GPU - Model: regnety_400m ms < Lower Is Better Run 1 . 12.66 |================================================================ Run 2 . 12.56 |=============================================================== Run 3 . 12.63 |================================================================ Run 4 . 12.60 |================================================================ WavPack Audio Encoding 5.3 WAV To WavPack Seconds < Lower Is Better Run 1 . 13.49 |================================================================ Run 2 . 13.51 |================================================================ Run 3 . 13.48 |================================================================ Run 4 . 13.48 |================================================================ Unpacking Firefox 84.0 Extracting: firefox-84.0.source.tar.xz Seconds < Lower Is Better Run 1 . 16.11 |================================================================ Run 2 . 16.03 |================================================================ Run 3 . 16.02 |================================================================ Run 4 . 15.97 |===============================================================