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.
Compare your own system(s) to this result file with the
Phoronix Test Suite by running the command:
phoronix-test-suite benchmark 2103183-IB-10600KPRE35 10600K pre RKL - Phoronix Test Suite 10600K pre RKL 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.
HTML result view exported from: https://openbenchmarking.org/result/2103183-IB-10600KPRE35&grt&rdt&rro .
10600K pre RKL Processor Motherboard Chipset Memory Disk Graphics Audio Monitor Network OS Kernel Desktop Display Server OpenGL Vulkan Compiler File-System Screen Resolution 1 2 3 Intel Core i5-10600K @ 4.80GHz (6 Cores / 12 Threads) ASUS PRIME Z490M-PLUS (1001 BIOS) Intel Comet Lake PCH 32GB Samsung SSD 970 EVO 500GB ASUS Intel UHD 630 3GB (1200MHz) Realtek ALC887-VD LG Ultra HD Intel Ubuntu 20.04 5.9.0-050900daily20201012-generic (x86_64) GNOME Shell 3.36.4 X Server 1.20.9 4.6 Mesa 20.0.8 1.2.131 GCC 9.3.0 ext4 3840x2160 OpenBenchmarking.org Kernel Details - Transparent Huge Pages: madvise Compiler Details - --build=x86_64-linux-gnu --disable-vtable-verify --disable-werror --enable-checking=release --enable-clocale=gnu --enable-default-pie --enable-gnu-unique-object --enable-languages=c,ada,c++,go,brig,d,fortran,objc,obj-c++,gm2 --enable-libstdcxx-debug --enable-libstdcxx-time=yes --enable-multiarch --enable-multilib --enable-nls --enable-objc-gc=auto --enable-offload-targets=nvptx-none=/build/gcc-9-HskZEa/gcc-9-9.3.0/debian/tmp-nvptx/usr,hsa --enable-plugin --enable-shared --enable-threads=posix --host=x86_64-linux-gnu --program-prefix=x86_64-linux-gnu- --target=x86_64-linux-gnu --with-abi=m64 --with-arch-32=i686 --with-default-libstdcxx-abi=new --with-gcc-major-version-only --with-multilib-list=m32,m64,mx32 --with-target-system-zlib=auto --with-tune=generic --without-cuda-driver -v Processor Details - Scaling Governor: intel_pstate powersave - CPU Microcode: 0xe0 Python Details - Python 3.8.5 Security Details - itlb_multihit: KVM: Mitigation of VMX unsupported + l1tf: Not affected + mds: Not affected + meltdown: Not affected + spec_store_bypass: Mitigation of SSB disabled via prctl and seccomp + spectre_v1: Mitigation of usercopy/swapgs barriers and __user pointer sanitization + spectre_v2: Mitigation of Enhanced IBRS IBPB: conditional RSB filling + srbds: Not affected + tsx_async_abort: Not affected
10600K pre RKL aom-av1: Speed 0 Two-Pass aom-av1: Speed 4 Two-Pass aom-av1: Speed 6 Realtime aom-av1: Speed 6 Two-Pass aom-av1: Speed 8 Realtime astcenc: Medium astcenc: Thorough astcenc: Exhaustive basis: ETC1S basis: UASTC Level 0 basis: UASTC Level 2 basis: UASTC Level 3 mnn: SqueezeNetV1.0 mnn: resnet-v2-50 mnn: MobileNetV2_224 mnn: mobilenet-v1-1.0 mnn: inception-v3 onednn: IP Shapes 1D - f32 - CPU onednn: IP Shapes 3D - f32 - CPU onednn: IP Shapes 1D - u8s8f32 - CPU onednn: IP Shapes 3D - u8s8f32 - CPU onednn: Convolution Batch Shapes Auto - f32 - CPU onednn: Deconvolution Batch shapes_1d - f32 - CPU onednn: Deconvolution Batch shapes_3d - f32 - CPU onednn: Convolution Batch Shapes Auto - u8s8f32 - CPU onednn: Deconvolution Batch shapes_1d - u8s8f32 - CPU onednn: Deconvolution Batch shapes_3d - u8s8f32 - CPU onednn: Recurrent Neural Network Training - f32 - CPU onednn: Recurrent Neural Network Inference - f32 - CPU onednn: Recurrent Neural Network Training - u8s8f32 - CPU onednn: Recurrent Neural Network Inference - u8s8f32 - CPU onednn: Matrix Multiply Batch Shapes Transformer - f32 - CPU onednn: Recurrent Neural Network Training - bf16bf16bf16 - CPU onednn: Recurrent Neural Network Inference - bf16bf16bf16 - CPU onednn: Matrix Multiply Batch Shapes Transformer - u8s8f32 - CPU simdjson: Kostya simdjson: LargeRand simdjson: PartialTweets simdjson: DistinctUserID svt-hevc: 1 - Bosphorus 1080p svt-hevc: 7 - Bosphorus 1080p svt-hevc: 10 - Bosphorus 1080p svt-vp9: VMAF Optimized - Bosphorus 1080p svt-vp9: PSNR/SSIM Optimized - Bosphorus 1080p svt-vp9: Visual Quality Optimized - Bosphorus 1080p sysbench: RAM / Memory sysbench: CPU build-mesa: Time To Compile build-nodejs: Time To Compile incompact3d: input.i3d 129 Cells Per Direction incompact3d: input.i3d 193 Cells Per Direction 1 2 3 0.23 5.96 20.83 17.05 96.50 6.0128 18.3302 144.6340 25.519 7.600 41.225 79.667 4.514 28.545 2.546 3.260 33.770 4.32120 7.66238 2.04154 2.39200 15.1117 10.04714 8.51089 13.7279 2.66876 5.36600 3990.01 2379.62 3992.29 2381.10 3.38413 4002.18 2382.71 3.46010 3.06 1.1 4.30 4.92 5.43 86.08 185.05 149.76 152.32 119.95 26132.76 14374.26 69.654 596.491 37.2945633 131.975932 0.23 5.97 20.67 17.09 96.22 6.0240 18.3402 144.5918 25.514 7.601 41.210 79.679 4.508 28.576 2.549 3.240 33.980 4.31466 7.73529 2.03699 2.38521 15.1207 10.0807 8.51927 13.8142 2.65983 5.31671 3998.99 2403.36 3996.07 2394.46 3.37849 3995.94 2397.83 3.47494 3.05 1.1 4.29 4.92 5.44 86.61 185.25 149.49 151.96 120.03 25903.89 14373.47 69.689 596.970 38.2099012 131.818481 0.23 5.97 20.75 17.06 96.59 6.0152 18.2889 143.5319 25.365 7.603 41.221 79.662 4.452 28.471 2.559 3.231 33.928 4.28025 7.47684 2.01397 2.39279 15.0783 9.98148 8.52282 13.8421 2.65906 5.36398 3986.56 2374.75 3987.23 2372.73 3.39558 3987.15 2372.19 3.46459 3.05 1.1 4.29 4.92 5.44 86.69 184.69 149.77 152.34 120.00 26135.31 14375.35 69.808 597.216 37.7690824 132.997213 OpenBenchmarking.org
AOM AV1 Encoder Mode: Speed 0 Two-Pass OpenBenchmarking.org Frames Per Second, More Is Better AOM AV1 2.1-rc Encoder Mode: Speed 0 Two-Pass 3 2 1 0.0518 0.1036 0.1554 0.2072 0.259 SE +/- 0.00, N = 3 SE +/- 0.00, N = 3 SE +/- 0.00, N = 3 0.23 0.23 0.23 1. (CXX) g++ options: -O3 -std=c++11 -U_FORTIFY_SOURCE -lm -lpthread
AOM AV1 Encoder Mode: Speed 4 Two-Pass OpenBenchmarking.org Frames Per Second, More Is Better AOM AV1 2.1-rc Encoder Mode: Speed 4 Two-Pass 3 2 1 1.3433 2.6866 4.0299 5.3732 6.7165 SE +/- 0.01, N = 3 SE +/- 0.02, N = 3 SE +/- 0.00, N = 3 5.97 5.97 5.96 1. (CXX) g++ options: -O3 -std=c++11 -U_FORTIFY_SOURCE -lm -lpthread
AOM AV1 Encoder Mode: Speed 6 Realtime OpenBenchmarking.org Frames Per Second, More Is Better AOM AV1 2.1-rc Encoder Mode: Speed 6 Realtime 3 2 1 5 10 15 20 25 SE +/- 0.11, N = 3 SE +/- 0.15, N = 3 SE +/- 0.08, N = 3 20.75 20.67 20.83 1. (CXX) g++ options: -O3 -std=c++11 -U_FORTIFY_SOURCE -lm -lpthread
AOM AV1 Encoder Mode: Speed 6 Two-Pass OpenBenchmarking.org Frames Per Second, More Is Better AOM AV1 2.1-rc Encoder Mode: Speed 6 Two-Pass 3 2 1 4 8 12 16 20 SE +/- 0.03, N = 3 SE +/- 0.00, N = 3 SE +/- 0.03, N = 3 17.06 17.09 17.05 1. (CXX) g++ options: -O3 -std=c++11 -U_FORTIFY_SOURCE -lm -lpthread
AOM AV1 Encoder Mode: Speed 8 Realtime OpenBenchmarking.org Frames Per Second, More Is Better AOM AV1 2.1-rc Encoder Mode: Speed 8 Realtime 3 2 1 20 40 60 80 100 SE +/- 0.08, N = 3 SE +/- 0.18, N = 3 SE +/- 0.17, N = 3 96.59 96.22 96.50 1. (CXX) g++ options: -O3 -std=c++11 -U_FORTIFY_SOURCE -lm -lpthread
ASTC Encoder Preset: Medium OpenBenchmarking.org Seconds, Fewer Is Better ASTC Encoder 2.4 Preset: Medium 3 2 1 2 4 6 8 10 SE +/- 0.0018, N = 3 SE +/- 0.0013, N = 3 SE +/- 0.0064, N = 3 6.0152 6.0240 6.0128 1. (CXX) g++ options: -O3 -flto -pthread
ASTC Encoder Preset: Thorough OpenBenchmarking.org Seconds, Fewer Is Better ASTC Encoder 2.4 Preset: Thorough 3 2 1 5 10 15 20 25 SE +/- 0.00, N = 3 SE +/- 0.03, N = 3 SE +/- 0.02, N = 3 18.29 18.34 18.33 1. (CXX) g++ options: -O3 -flto -pthread
ASTC Encoder Preset: Exhaustive OpenBenchmarking.org Seconds, Fewer Is Better ASTC Encoder 2.4 Preset: Exhaustive 3 2 1 30 60 90 120 150 SE +/- 0.30, N = 3 SE +/- 0.26, N = 3 SE +/- 0.22, N = 3 143.53 144.59 144.63 1. (CXX) g++ options: -O3 -flto -pthread
Basis Universal Settings: ETC1S OpenBenchmarking.org Seconds, Fewer Is Better Basis Universal 1.13 Settings: ETC1S 3 2 1 6 12 18 24 30 SE +/- 0.04, N = 3 SE +/- 0.03, N = 3 SE +/- 0.03, N = 3 25.37 25.51 25.52 1. (CXX) g++ options: -std=c++11 -fvisibility=hidden -fPIC -fno-strict-aliasing -O3 -rdynamic -lm -lpthread
Basis Universal Settings: UASTC Level 0 OpenBenchmarking.org Seconds, Fewer Is Better Basis Universal 1.13 Settings: UASTC Level 0 3 2 1 2 4 6 8 10 SE +/- 0.004, N = 3 SE +/- 0.004, N = 3 SE +/- 0.004, N = 3 7.603 7.601 7.600 1. (CXX) g++ options: -std=c++11 -fvisibility=hidden -fPIC -fno-strict-aliasing -O3 -rdynamic -lm -lpthread
Basis Universal Settings: UASTC Level 2 OpenBenchmarking.org Seconds, Fewer Is Better Basis Universal 1.13 Settings: UASTC Level 2 3 2 1 9 18 27 36 45 SE +/- 0.01, N = 3 SE +/- 0.00, N = 3 SE +/- 0.01, N = 3 41.22 41.21 41.23 1. (CXX) g++ options: -std=c++11 -fvisibility=hidden -fPIC -fno-strict-aliasing -O3 -rdynamic -lm -lpthread
Basis Universal Settings: UASTC Level 3 OpenBenchmarking.org Seconds, Fewer Is Better Basis Universal 1.13 Settings: UASTC Level 3 3 2 1 20 40 60 80 100 SE +/- 0.00, N = 3 SE +/- 0.01, N = 3 SE +/- 0.00, N = 3 79.66 79.68 79.67 1. (CXX) g++ options: -std=c++11 -fvisibility=hidden -fPIC -fno-strict-aliasing -O3 -rdynamic -lm -lpthread
Mobile Neural Network Model: SqueezeNetV1.0 OpenBenchmarking.org ms, Fewer Is Better Mobile Neural Network 1.1.3 Model: SqueezeNetV1.0 3 2 1 1.0157 2.0314 3.0471 4.0628 5.0785 SE +/- 0.004, N = 3 SE +/- 0.007, N = 3 SE +/- 0.010, N = 3 4.452 4.508 4.514 MIN: 4.37 / MAX: 7.17 MIN: 4.45 / MAX: 5.33 MIN: 4.43 / MAX: 7.13 1. (CXX) g++ options: -std=c++11 -O3 -fvisibility=hidden -fomit-frame-pointer -fstrict-aliasing -ffunction-sections -fdata-sections -ffast-math -fno-rtti -fno-exceptions -rdynamic -pthread -ldl
Mobile Neural Network Model: resnet-v2-50 OpenBenchmarking.org ms, Fewer Is Better Mobile Neural Network 1.1.3 Model: resnet-v2-50 3 2 1 7 14 21 28 35 SE +/- 0.04, N = 3 SE +/- 0.06, N = 3 SE +/- 0.10, N = 3 28.47 28.58 28.55 MIN: 28.25 / MAX: 40.28 MIN: 28.26 / MAX: 40.34 MIN: 28.18 / MAX: 40.29 1. (CXX) g++ options: -std=c++11 -O3 -fvisibility=hidden -fomit-frame-pointer -fstrict-aliasing -ffunction-sections -fdata-sections -ffast-math -fno-rtti -fno-exceptions -rdynamic -pthread -ldl
Mobile Neural Network Model: MobileNetV2_224 OpenBenchmarking.org ms, Fewer Is Better Mobile Neural Network 1.1.3 Model: MobileNetV2_224 3 2 1 0.5758 1.1516 1.7274 2.3032 2.879 SE +/- 0.018, N = 3 SE +/- 0.011, N = 3 SE +/- 0.012, N = 3 2.559 2.549 2.546 MIN: 2.5 / MAX: 33.31 MIN: 2.51 / MAX: 5.08 MIN: 2.51 / MAX: 3.35 1. (CXX) g++ options: -std=c++11 -O3 -fvisibility=hidden -fomit-frame-pointer -fstrict-aliasing -ffunction-sections -fdata-sections -ffast-math -fno-rtti -fno-exceptions -rdynamic -pthread -ldl
Mobile Neural Network Model: mobilenet-v1-1.0 OpenBenchmarking.org ms, Fewer Is Better Mobile Neural Network 1.1.3 Model: mobilenet-v1-1.0 3 2 1 0.7335 1.467 2.2005 2.934 3.6675 SE +/- 0.017, N = 3 SE +/- 0.002, N = 3 SE +/- 0.011, N = 3 3.231 3.240 3.260 MIN: 3.19 / MAX: 3.46 MIN: 3.2 / MAX: 4.08 MIN: 3.22 / MAX: 4.01 1. (CXX) g++ options: -std=c++11 -O3 -fvisibility=hidden -fomit-frame-pointer -fstrict-aliasing -ffunction-sections -fdata-sections -ffast-math -fno-rtti -fno-exceptions -rdynamic -pthread -ldl
Mobile Neural Network Model: inception-v3 OpenBenchmarking.org ms, Fewer Is Better Mobile Neural Network 1.1.3 Model: inception-v3 3 2 1 8 16 24 32 40 SE +/- 0.19, N = 3 SE +/- 0.16, N = 3 SE +/- 0.04, N = 3 33.93 33.98 33.77 MIN: 33.53 / MAX: 46.76 MIN: 33.58 / MAX: 47.6 MIN: 33.53 / MAX: 46.55 1. (CXX) g++ options: -std=c++11 -O3 -fvisibility=hidden -fomit-frame-pointer -fstrict-aliasing -ffunction-sections -fdata-sections -ffast-math -fno-rtti -fno-exceptions -rdynamic -pthread -ldl
oneDNN Harness: IP Shapes 1D - Data Type: f32 - Engine: CPU OpenBenchmarking.org ms, Fewer Is Better oneDNN 2.1.2 Harness: IP Shapes 1D - Data Type: f32 - Engine: CPU 3 2 1 0.9723 1.9446 2.9169 3.8892 4.8615 SE +/- 0.01808, N = 3 SE +/- 0.01586, N = 3 SE +/- 0.00877, N = 3 4.28025 4.31466 4.32120 MIN: 4.19 MIN: 4.18 MIN: 4.19 1. (CXX) g++ options: -O3 -march=native -std=c++11 -fopenmp -msse4.1 -fPIC -pie -lpthread -ldl
oneDNN Harness: IP Shapes 3D - Data Type: f32 - Engine: CPU OpenBenchmarking.org ms, Fewer Is Better oneDNN 2.1.2 Harness: IP Shapes 3D - Data Type: f32 - Engine: CPU 3 2 1 2 4 6 8 10 SE +/- 0.01643, N = 3 SE +/- 0.01377, N = 3 SE +/- 0.01852, N = 3 7.47684 7.73529 7.66238 MIN: 7.35 MIN: 7.59 MIN: 7.54 1. (CXX) g++ options: -O3 -march=native -std=c++11 -fopenmp -msse4.1 -fPIC -pie -lpthread -ldl
oneDNN Harness: IP Shapes 1D - Data Type: u8s8f32 - Engine: CPU OpenBenchmarking.org ms, Fewer Is Better oneDNN 2.1.2 Harness: IP Shapes 1D - Data Type: u8s8f32 - Engine: CPU 3 2 1 0.4593 0.9186 1.3779 1.8372 2.2965 SE +/- 0.00640, N = 3 SE +/- 0.01080, N = 3 SE +/- 0.00826, N = 3 2.01397 2.03699 2.04154 MIN: 1.98 MIN: 1.99 MIN: 1.98 1. (CXX) g++ options: -O3 -march=native -std=c++11 -fopenmp -msse4.1 -fPIC -pie -lpthread -ldl
oneDNN Harness: IP Shapes 3D - Data Type: u8s8f32 - Engine: CPU OpenBenchmarking.org ms, Fewer Is Better oneDNN 2.1.2 Harness: IP Shapes 3D - Data Type: u8s8f32 - Engine: CPU 3 2 1 0.5384 1.0768 1.6152 2.1536 2.692 SE +/- 0.01182, N = 3 SE +/- 0.00590, N = 3 SE +/- 0.00743, N = 3 2.39279 2.38521 2.39200 MIN: 2.33 MIN: 2.31 MIN: 2.34 1. (CXX) g++ options: -O3 -march=native -std=c++11 -fopenmp -msse4.1 -fPIC -pie -lpthread -ldl
oneDNN Harness: Convolution Batch Shapes Auto - Data Type: f32 - Engine: CPU OpenBenchmarking.org ms, Fewer Is Better oneDNN 2.1.2 Harness: Convolution Batch Shapes Auto - Data Type: f32 - Engine: CPU 3 2 1 4 8 12 16 20 SE +/- 0.05, N = 3 SE +/- 0.05, N = 3 SE +/- 0.05, N = 3 15.08 15.12 15.11 MIN: 14.97 MIN: 15.01 MIN: 15.01 1. (CXX) g++ options: -O3 -march=native -std=c++11 -fopenmp -msse4.1 -fPIC -pie -lpthread -ldl
oneDNN Harness: Deconvolution Batch shapes_1d - Data Type: f32 - Engine: CPU OpenBenchmarking.org ms, Fewer Is Better oneDNN 2.1.2 Harness: Deconvolution Batch shapes_1d - Data Type: f32 - Engine: CPU 3 2 1 3 6 9 12 15 SE +/- 0.01007, N = 3 SE +/- 0.02946, N = 3 SE +/- 0.04868, N = 3 9.98148 10.08070 10.04714 MIN: 6.26 MIN: 6.13 MIN: 6.15 1. (CXX) g++ options: -O3 -march=native -std=c++11 -fopenmp -msse4.1 -fPIC -pie -lpthread -ldl
oneDNN Harness: Deconvolution Batch shapes_3d - Data Type: f32 - Engine: CPU OpenBenchmarking.org ms, Fewer Is Better oneDNN 2.1.2 Harness: Deconvolution Batch shapes_3d - Data Type: f32 - Engine: CPU 3 2 1 2 4 6 8 10 SE +/- 0.00862, N = 3 SE +/- 0.00726, N = 3 SE +/- 0.00717, N = 3 8.52282 8.51927 8.51089 MIN: 8.48 MIN: 8.48 MIN: 8.48 1. (CXX) g++ options: -O3 -march=native -std=c++11 -fopenmp -msse4.1 -fPIC -pie -lpthread -ldl
oneDNN Harness: Convolution Batch Shapes Auto - Data Type: u8s8f32 - Engine: CPU OpenBenchmarking.org ms, Fewer Is Better oneDNN 2.1.2 Harness: Convolution Batch Shapes Auto - Data Type: u8s8f32 - Engine: CPU 3 2 1 4 8 12 16 20 SE +/- 0.08, N = 3 SE +/- 0.05, N = 3 SE +/- 0.07, N = 3 13.84 13.81 13.73 MIN: 13.46 MIN: 13.46 MIN: 13.46 1. (CXX) g++ options: -O3 -march=native -std=c++11 -fopenmp -msse4.1 -fPIC -pie -lpthread -ldl
oneDNN Harness: Deconvolution Batch shapes_1d - Data Type: u8s8f32 - Engine: CPU OpenBenchmarking.org ms, Fewer Is Better oneDNN 2.1.2 Harness: Deconvolution Batch shapes_1d - Data Type: u8s8f32 - Engine: CPU 3 2 1 0.6005 1.201 1.8015 2.402 3.0025 SE +/- 0.00456, N = 3 SE +/- 0.00545, N = 3 SE +/- 0.01467, N = 3 2.65906 2.65983 2.66876 MIN: 2.63 MIN: 2.63 MIN: 2.63 1. (CXX) g++ options: -O3 -march=native -std=c++11 -fopenmp -msse4.1 -fPIC -pie -lpthread -ldl
oneDNN Harness: Deconvolution Batch shapes_3d - Data Type: u8s8f32 - Engine: CPU OpenBenchmarking.org ms, Fewer Is Better oneDNN 2.1.2 Harness: Deconvolution Batch shapes_3d - Data Type: u8s8f32 - Engine: CPU 3 2 1 1.2074 2.4148 3.6222 4.8296 6.037 SE +/- 0.00867, N = 3 SE +/- 0.01565, N = 3 SE +/- 0.01215, N = 3 5.36398 5.31671 5.36600 MIN: 5.32 MIN: 5.27 MIN: 5.32 1. (CXX) g++ options: -O3 -march=native -std=c++11 -fopenmp -msse4.1 -fPIC -pie -lpthread -ldl
oneDNN Harness: Recurrent Neural Network Training - Data Type: f32 - Engine: CPU OpenBenchmarking.org ms, Fewer Is Better oneDNN 2.1.2 Harness: Recurrent Neural Network Training - Data Type: f32 - Engine: CPU 3 2 1 900 1800 2700 3600 4500 SE +/- 1.26, N = 3 SE +/- 2.93, N = 3 SE +/- 0.55, N = 3 3986.56 3998.99 3990.01 MIN: 3980.86 MIN: 3992.8 MIN: 3986.86 1. (CXX) g++ options: -O3 -march=native -std=c++11 -fopenmp -msse4.1 -fPIC -pie -lpthread -ldl
oneDNN Harness: Recurrent Neural Network Inference - Data Type: f32 - Engine: CPU OpenBenchmarking.org ms, Fewer Is Better oneDNN 2.1.2 Harness: Recurrent Neural Network Inference - Data Type: f32 - Engine: CPU 3 2 1 500 1000 1500 2000 2500 SE +/- 1.89, N = 3 SE +/- 4.31, N = 3 SE +/- 2.92, N = 3 2374.75 2403.36 2379.62 MIN: 2367.87 MIN: 2396.19 MIN: 2374.18 1. (CXX) g++ options: -O3 -march=native -std=c++11 -fopenmp -msse4.1 -fPIC -pie -lpthread -ldl
oneDNN Harness: Recurrent Neural Network Training - Data Type: u8s8f32 - Engine: CPU OpenBenchmarking.org ms, Fewer Is Better oneDNN 2.1.2 Harness: Recurrent Neural Network Training - Data Type: u8s8f32 - Engine: CPU 3 2 1 900 1800 2700 3600 4500 SE +/- 1.71, N = 3 SE +/- 1.10, N = 3 SE +/- 0.57, N = 3 3987.23 3996.07 3992.29 MIN: 3981.34 MIN: 3991.93 MIN: 3987.88 1. (CXX) g++ options: -O3 -march=native -std=c++11 -fopenmp -msse4.1 -fPIC -pie -lpthread -ldl
oneDNN Harness: Recurrent Neural Network Inference - Data Type: u8s8f32 - Engine: CPU OpenBenchmarking.org ms, Fewer Is Better oneDNN 2.1.2 Harness: Recurrent Neural Network Inference - Data Type: u8s8f32 - Engine: CPU 3 2 1 500 1000 1500 2000 2500 SE +/- 1.29, N = 3 SE +/- 0.97, N = 3 SE +/- 2.74, N = 3 2372.73 2394.46 2381.10 MIN: 2366.08 MIN: 2391.28 MIN: 2375.91 1. (CXX) g++ options: -O3 -march=native -std=c++11 -fopenmp -msse4.1 -fPIC -pie -lpthread -ldl
oneDNN Harness: Matrix Multiply Batch Shapes Transformer - Data Type: f32 - Engine: CPU OpenBenchmarking.org ms, Fewer Is Better oneDNN 2.1.2 Harness: Matrix Multiply Batch Shapes Transformer - Data Type: f32 - Engine: CPU 3 2 1 0.764 1.528 2.292 3.056 3.82 SE +/- 0.00477, N = 3 SE +/- 0.00806, N = 3 SE +/- 0.00246, N = 3 3.39558 3.37849 3.38413 MIN: 3.33 MIN: 3.31 MIN: 3.33 1. (CXX) g++ options: -O3 -march=native -std=c++11 -fopenmp -msse4.1 -fPIC -pie -lpthread -ldl
oneDNN Harness: Recurrent Neural Network Training - Data Type: bf16bf16bf16 - Engine: CPU OpenBenchmarking.org ms, Fewer Is Better oneDNN 2.1.2 Harness: Recurrent Neural Network Training - Data Type: bf16bf16bf16 - Engine: CPU 3 2 1 900 1800 2700 3600 4500 SE +/- 1.18, N = 3 SE +/- 1.20, N = 3 SE +/- 9.00, N = 3 3987.15 3995.94 4002.18 MIN: 3982.67 MIN: 3991.84 MIN: 3990.27 1. (CXX) g++ options: -O3 -march=native -std=c++11 -fopenmp -msse4.1 -fPIC -pie -lpthread -ldl
oneDNN Harness: Recurrent Neural Network Inference - Data Type: bf16bf16bf16 - Engine: CPU OpenBenchmarking.org ms, Fewer Is Better oneDNN 2.1.2 Harness: Recurrent Neural Network Inference - Data Type: bf16bf16bf16 - Engine: CPU 3 2 1 500 1000 1500 2000 2500 SE +/- 1.46, N = 3 SE +/- 1.16, N = 3 SE +/- 1.67, N = 3 2372.19 2397.83 2382.71 MIN: 2367.54 MIN: 2393.33 MIN: 2377.54 1. (CXX) g++ options: -O3 -march=native -std=c++11 -fopenmp -msse4.1 -fPIC -pie -lpthread -ldl
oneDNN Harness: Matrix Multiply Batch Shapes Transformer - Data Type: u8s8f32 - Engine: CPU OpenBenchmarking.org ms, Fewer Is Better oneDNN 2.1.2 Harness: Matrix Multiply Batch Shapes Transformer - Data Type: u8s8f32 - Engine: CPU 3 2 1 0.7819 1.5638 2.3457 3.1276 3.9095 SE +/- 0.00212, N = 3 SE +/- 0.00087, N = 3 SE +/- 0.01319, N = 3 3.46459 3.47494 3.46010 MIN: 3.27 MIN: 3.28 MIN: 3.26 1. (CXX) g++ options: -O3 -march=native -std=c++11 -fopenmp -msse4.1 -fPIC -pie -lpthread -ldl
simdjson Throughput Test: Kostya OpenBenchmarking.org GB/s, More Is Better simdjson 0.8.2 Throughput Test: Kostya 3 2 1 0.6885 1.377 2.0655 2.754 3.4425 SE +/- 0.00, N = 3 SE +/- 0.00, N = 3 SE +/- 0.00, N = 3 3.05 3.05 3.06 1. (CXX) g++ options: -O3 -pthread
simdjson Throughput Test: LargeRandom OpenBenchmarking.org GB/s, More Is Better simdjson 0.8.2 Throughput Test: LargeRandom 3 2 1 0.2475 0.495 0.7425 0.99 1.2375 SE +/- 0.00, N = 3 SE +/- 0.00, N = 3 SE +/- 0.00, N = 3 1.1 1.1 1.1 1. (CXX) g++ options: -O3 -pthread
simdjson Throughput Test: PartialTweets OpenBenchmarking.org GB/s, More Is Better simdjson 0.8.2 Throughput Test: PartialTweets 3 2 1 0.9675 1.935 2.9025 3.87 4.8375 SE +/- 0.00, N = 3 SE +/- 0.01, N = 3 SE +/- 0.00, N = 3 4.29 4.29 4.30 1. (CXX) g++ options: -O3 -pthread
simdjson Throughput Test: DistinctUserID OpenBenchmarking.org GB/s, More Is Better simdjson 0.8.2 Throughput Test: DistinctUserID 3 2 1 1.107 2.214 3.321 4.428 5.535 SE +/- 0.00, N = 3 SE +/- 0.01, N = 3 SE +/- 0.01, N = 3 4.92 4.92 4.92 1. (CXX) g++ options: -O3 -pthread
SVT-HEVC Tuning: 1 - Input: Bosphorus 1080p OpenBenchmarking.org Frames Per Second, More Is Better SVT-HEVC 1.5.0 Tuning: 1 - Input: Bosphorus 1080p 3 2 1 1.224 2.448 3.672 4.896 6.12 SE +/- 0.02, N = 3 SE +/- 0.01, N = 3 SE +/- 0.01, N = 3 5.44 5.44 5.43 1. (CC) gcc options: -fPIE -fPIC -O3 -O2 -pie -rdynamic -lpthread -lrt
SVT-HEVC Tuning: 7 - Input: Bosphorus 1080p OpenBenchmarking.org Frames Per Second, More Is Better SVT-HEVC 1.5.0 Tuning: 7 - Input: Bosphorus 1080p 3 2 1 20 40 60 80 100 SE +/- 0.04, N = 3 SE +/- 0.05, N = 3 SE +/- 0.07, N = 3 86.69 86.61 86.08 1. (CC) gcc options: -fPIE -fPIC -O3 -O2 -pie -rdynamic -lpthread -lrt
SVT-HEVC Tuning: 10 - Input: Bosphorus 1080p OpenBenchmarking.org Frames Per Second, More Is Better SVT-HEVC 1.5.0 Tuning: 10 - Input: Bosphorus 1080p 3 2 1 40 80 120 160 200 SE +/- 0.38, N = 3 SE +/- 0.38, N = 3 SE +/- 0.05, N = 3 184.69 185.25 185.05 1. (CC) gcc options: -fPIE -fPIC -O3 -O2 -pie -rdynamic -lpthread -lrt
SVT-VP9 Tuning: VMAF Optimized - Input: Bosphorus 1080p OpenBenchmarking.org Frames Per Second, More Is Better SVT-VP9 0.3 Tuning: VMAF Optimized - Input: Bosphorus 1080p 3 2 1 30 60 90 120 150 SE +/- 0.12, N = 3 SE +/- 0.06, N = 3 SE +/- 0.29, N = 3 149.77 149.49 149.76 1. (CC) gcc options: -O3 -fcommon -fPIE -fPIC -fvisibility=hidden -pie -rdynamic -lpthread -lrt -lm
SVT-VP9 Tuning: PSNR/SSIM Optimized - Input: Bosphorus 1080p OpenBenchmarking.org Frames Per Second, More Is Better SVT-VP9 0.3 Tuning: PSNR/SSIM Optimized - Input: Bosphorus 1080p 3 2 1 30 60 90 120 150 SE +/- 0.29, N = 3 SE +/- 0.11, N = 3 SE +/- 0.28, N = 3 152.34 151.96 152.32 1. (CC) gcc options: -O3 -fcommon -fPIE -fPIC -fvisibility=hidden -pie -rdynamic -lpthread -lrt -lm
SVT-VP9 Tuning: Visual Quality Optimized - Input: Bosphorus 1080p OpenBenchmarking.org Frames Per Second, More Is Better SVT-VP9 0.3 Tuning: Visual Quality Optimized - Input: Bosphorus 1080p 3 2 1 30 60 90 120 150 SE +/- 0.23, N = 3 SE +/- 0.14, N = 3 SE +/- 0.13, N = 3 120.00 120.03 119.95 1. (CC) gcc options: -O3 -fcommon -fPIE -fPIC -fvisibility=hidden -pie -rdynamic -lpthread -lrt -lm
Sysbench Test: RAM / Memory OpenBenchmarking.org MiB/sec, More Is Better Sysbench 1.0.20 Test: RAM / Memory 3 2 1 6K 12K 18K 24K 30K SE +/- 185.77, N = 3 SE +/- 44.57, N = 3 SE +/- 182.62, N = 3 26135.31 25903.89 26132.76 1. (CC) gcc options: -pthread -O2 -funroll-loops -rdynamic -ldl -laio -lm
Sysbench Test: CPU OpenBenchmarking.org Events Per Second, More Is Better Sysbench 1.0.20 Test: CPU 3 2 1 3K 6K 9K 12K 15K SE +/- 0.21, N = 3 SE +/- 1.54, N = 3 SE +/- 1.10, N = 3 14375.35 14373.47 14374.26 1. (CC) gcc options: -pthread -O2 -funroll-loops -rdynamic -ldl -laio -lm
Timed Mesa Compilation Time To Compile OpenBenchmarking.org Seconds, Fewer Is Better Timed Mesa Compilation 21.0 Time To Compile 3 2 1 16 32 48 64 80 SE +/- 0.01, N = 3 SE +/- 0.06, N = 3 SE +/- 0.18, N = 3 69.81 69.69 69.65
Timed Node.js Compilation Time To Compile OpenBenchmarking.org Seconds, Fewer Is Better Timed Node.js Compilation 15.11 Time To Compile 3 2 1 130 260 390 520 650 SE +/- 0.12, N = 3 SE +/- 0.25, N = 3 SE +/- 0.12, N = 3 597.22 596.97 596.49
Xcompact3d Incompact3d Input: input.i3d 129 Cells Per Direction OpenBenchmarking.org Seconds, Fewer Is Better Xcompact3d Incompact3d 2021-03-11 Input: input.i3d 129 Cells Per Direction 3 2 1 9 18 27 36 45 SE +/- 0.35, N = 3 SE +/- 0.07, N = 3 SE +/- 0.36, N = 3 37.77 38.21 37.29 1. (F9X) gfortran options: -cpp -O2 -funroll-loops -floop-optimize -fcray-pointer -fbacktrace -pthread -lmpi_usempif08 -lmpi_mpifh -lmpi
Xcompact3d Incompact3d Input: input.i3d 193 Cells Per Direction OpenBenchmarking.org Seconds, Fewer Is Better Xcompact3d Incompact3d 2021-03-11 Input: input.i3d 193 Cells Per Direction 3 2 1 30 60 90 120 150 SE +/- 0.15, N = 3 SE +/- 1.01, N = 3 SE +/- 1.07, N = 3 133.00 131.82 131.98 1. (F9X) gfortran options: -cpp -O2 -funroll-loops -floop-optimize -fcray-pointer -fbacktrace -pthread -lmpi_usempif08 -lmpi_mpifh -lmpi
Phoronix Test Suite v10.8.4