Intel Core i5-8400 testing with a MSI Z370M MORTAR (MS-7B54) v1.0 (1.80 BIOS) and MSI Intel UHD 630 3GB on Ubuntu 20.04 via the Phoronix Test Suite.
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phoronix-test-suite benchmark 2103223-IB-8400M557504 8400 m - Phoronix Test Suite 8400 m Intel Core i5-8400 testing with a MSI Z370M MORTAR (MS-7B54) v1.0 (1.80 BIOS) and MSI Intel UHD 630 3GB on Ubuntu 20.04 via the Phoronix Test Suite.
HTML result view exported from: https://openbenchmarking.org/result/2103223-IB-8400M557504&gru&rdt .
8400 m Processor Motherboard Chipset Memory Disk Graphics Audio Monitor Network OS Kernel Desktop Display Server OpenGL Compiler File-System Screen Resolution 1 2 3 Intel Core i5-8400 @ 4.00GHz (6 Cores) MSI Z370M MORTAR (MS-7B54) v1.0 (1.80 BIOS) Intel 8th Gen Core 8GB 512GB INTEL SSDPEKNW512G8 MSI Intel UHD 630 3GB (1050MHz) Realtek ALC892 DELL S2409W Intel I219-V Ubuntu 20.04 5.9.0-050900rc7daily20200929-generic (x86_64) 20200928 GNOME Shell 3.36.4 X Server 1.20.9 4.6 Mesa 20.0.8 GCC 9.3.0 ext4 1920x1080 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: 0xde - Thermald 1.9.1 Python Details - Python 3.8.5 Security Details - itlb_multihit: KVM: Mitigation of VMX disabled + l1tf: Mitigation of PTE Inversion; VMX: conditional cache flushes SMT disabled + mds: Mitigation of Clear buffers; SMT disabled + meltdown: Mitigation of PTI + 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 Full generic retpoline IBPB: conditional IBRS_FW STIBP: disabled RSB filling + srbds: Mitigation of Microcode + tsx_async_abort: Not affected
8400 m sysbench: CPU 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 stockfish: Total Time 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 incompact3d: input.i3d 129 Cells Per Direction incompact3d: input.i3d 193 Cells Per Direction build-mesa: Time To Compile build-nodejs: Time To Compile 1 2 3 8027.05 4.31 63.17 132.86 116.51 117.74 94.87 12559.86 12423645 5.38261 10.5166 3.32381 2.14099 20.5263 7.38112 9.41175 15.8780 3.16664 6.34104 4629.05 2569.74 4618.45 2557.47 3.75357 4548.60 2615.31 4.19566 43.8697395 150.887232 96.022 868.883 8031.24 4.32 63.20 132.44 116.36 117.96 94.91 12654.75 12462066 5.41408 10.3376 3.32302 2.14355 20.5156 7.36038 9.43695 15.8402 3.17003 6.34022 4526.88 2556.44 4653.17 2601.07 3.75446 4647.00 2598.32 4.18604 43.0112292 149.555781 95.821 869.018 8033.66 4.28 63.33 133.08 116.64 117.88 94.55 12635.66 12596102 5.35508 10.5981 3.32685 2.13409 20.5318 7.35392 9.42173 15.8777 3.17132 6.36246 4560.44 2560.05 4629.21 2568.63 3.75387 4588.83 2621.26 4.18462 43.8241310 150.497513 95.943 869.258 OpenBenchmarking.org
Sysbench Test: CPU OpenBenchmarking.org Events Per Second, More Is Better Sysbench 1.0.20 Test: CPU 1 2 3 2K 4K 6K 8K 10K SE +/- 3.68, N = 3 SE +/- 1.68, N = 3 SE +/- 0.35, N = 3 8027.05 8031.24 8033.66 1. (CC) gcc options: -pthread -O2 -funroll-loops -rdynamic -ldl -laio -lm
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 1 2 3 0.972 1.944 2.916 3.888 4.86 SE +/- 0.01, N = 3 SE +/- 0.01, N = 3 SE +/- 0.02, N = 3 4.31 4.32 4.28 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 1 2 3 14 28 42 56 70 SE +/- 0.01, N = 3 SE +/- 0.10, N = 3 SE +/- 0.08, N = 3 63.17 63.20 63.33 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 1 2 3 30 60 90 120 150 SE +/- 0.21, N = 3 SE +/- 0.12, N = 3 SE +/- 0.28, N = 3 132.86 132.44 133.08 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 1 2 3 30 60 90 120 150 SE +/- 1.20, N = 3 SE +/- 0.82, N = 3 SE +/- 0.89, N = 3 116.51 116.36 116.64 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 1 2 3 30 60 90 120 150 SE +/- 0.20, N = 3 SE +/- 0.04, N = 3 SE +/- 0.25, N = 3 117.74 117.96 117.88 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 1 2 3 20 40 60 80 100 SE +/- 0.27, N = 3 SE +/- 0.16, N = 3 SE +/- 0.17, N = 3 94.87 94.91 94.55 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 1 2 3 3K 6K 9K 12K 15K SE +/- 59.06, N = 3 SE +/- 68.62, N = 3 SE +/- 94.65, N = 3 12559.86 12654.75 12635.66 1. (CC) gcc options: -pthread -O2 -funroll-loops -rdynamic -ldl -laio -lm
Stockfish Total Time OpenBenchmarking.org Nodes Per Second, More Is Better Stockfish 13 Total Time 1 2 3 3M 6M 9M 12M 15M SE +/- 30828.18, N = 3 SE +/- 19387.12, N = 3 SE +/- 55803.38, N = 3 12423645 12462066 12596102 1. (CXX) g++ options: -lgcov -m64 -lpthread -fno-exceptions -std=c++17 -fprofile-use -fno-peel-loops -fno-tracer -pedantic -O3 -msse -msse3 -mpopcnt -mavx2 -msse4.1 -mssse3 -msse2 -mbmi2 -flto -flto=jobserver
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 1 2 3 1.2182 2.4364 3.6546 4.8728 6.091 SE +/- 0.03869, N = 3 SE +/- 0.03388, N = 3 SE +/- 0.00843, N = 3 5.38261 5.41408 5.35508 MIN: 5.29 MIN: 5.28 MIN: 5.29 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 1 2 3 3 6 9 12 15 SE +/- 0.02, N = 3 SE +/- 0.01, N = 3 SE +/- 0.03, N = 3 10.52 10.34 10.60 MIN: 10.39 MIN: 10.22 MIN: 10.46 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 1 2 3 0.7485 1.497 2.2455 2.994 3.7425 SE +/- 0.00143, N = 3 SE +/- 0.00484, N = 3 SE +/- 0.00512, N = 3 3.32381 3.32302 3.32685 MIN: 3.3 MIN: 3.3 MIN: 3.3 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 1 2 3 0.4823 0.9646 1.4469 1.9292 2.4115 SE +/- 0.01543, N = 3 SE +/- 0.00480, N = 3 SE +/- 0.00779, N = 3 2.14099 2.14355 2.13409 MIN: 2.09 MIN: 2.1 MIN: 2.09 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 1 2 3 5 10 15 20 25 SE +/- 0.02, N = 3 SE +/- 0.01, N = 3 SE +/- 0.02, N = 3 20.53 20.52 20.53 MIN: 20.45 MIN: 20.43 MIN: 20.46 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: f32 - Engine: CPU OpenBenchmarking.org ms, Fewer Is Better oneDNN 2.1.2 Harness: Deconvolution Batch shapes_1d - Data Type: f32 - Engine: CPU 1 2 3 2 4 6 8 10 SE +/- 0.03024, N = 3 SE +/- 0.00323, N = 3 SE +/- 0.00600, N = 3 7.38112 7.36038 7.35392 MIN: 7.28 MIN: 7.29 MIN: 7.28 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 1 2 3 3 6 9 12 15 SE +/- 0.03594, N = 3 SE +/- 0.00908, N = 3 SE +/- 0.01321, N = 3 9.41175 9.43695 9.42173 MIN: 9.31 MIN: 9.39 MIN: 9.36 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 1 2 3 4 8 12 16 20 SE +/- 0.02, N = 3 SE +/- 0.03, N = 3 SE +/- 0.01, N = 3 15.88 15.84 15.88 MIN: 15.61 MIN: 15.56 MIN: 15.65 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 1 2 3 0.7135 1.427 2.1405 2.854 3.5675 SE +/- 0.00040, N = 3 SE +/- 0.00367, N = 3 SE +/- 0.00322, N = 3 3.16664 3.17003 3.17132 MIN: 3.15 MIN: 3.16 MIN: 3.15 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: u8s8f32 - Engine: CPU OpenBenchmarking.org ms, Fewer Is Better oneDNN 2.1.2 Harness: Deconvolution Batch shapes_3d - Data Type: u8s8f32 - Engine: CPU 1 2 3 2 4 6 8 10 SE +/- 0.01367, N = 3 SE +/- 0.01774, N = 3 SE +/- 0.00393, N = 3 6.34104 6.34022 6.36246 MIN: 6.3 MIN: 6.29 MIN: 6.34 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 1 2 3 1000 2000 3000 4000 5000 SE +/- 64.56, N = 4 SE +/- 65.83, N = 4 SE +/- 76.24, N = 3 4629.05 4526.88 4560.44 MIN: 4369.13 MIN: 4352.66 MIN: 4359.42 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 1 2 3 600 1200 1800 2400 3000 SE +/- 28.26, N = 3 SE +/- 19.07, N = 3 SE +/- 20.05, N = 3 2569.74 2556.44 2560.05 MIN: 2535.13 MIN: 2533.01 MIN: 2534.6 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 1 2 3 1000 2000 3000 4000 5000 SE +/- 59.35, N = 3 SE +/- 72.81, N = 3 SE +/- 57.69, N = 3 4618.45 4653.17 4629.21 MIN: 4468.76 MIN: 4471.26 MIN: 4445.97 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 1 2 3 600 1200 1800 2400 3000 SE +/- 30.85, N = 3 SE +/- 37.01, N = 3 SE +/- 17.62, N = 3 2557.47 2601.07 2568.63 MIN: 2499.68 MIN: 2532.97 MIN: 2535.83 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 1 2 3 0.8448 1.6896 2.5344 3.3792 4.224 SE +/- 0.00276, N = 3 SE +/- 0.00001, N = 3 SE +/- 0.00133, N = 3 3.75357 3.75446 3.75387 MIN: 3.7 MIN: 3.71 MIN: 3.7 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 1 2 3 1000 2000 3000 4000 5000 SE +/- 17.83, N = 3 SE +/- 70.95, N = 3 SE +/- 8.80, N = 3 4548.60 4647.00 4588.83 MIN: 4424.13 MIN: 4418.38 MIN: 4444.6 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 1 2 3 600 1200 1800 2400 3000 SE +/- 29.19, N = 3 SE +/- 20.36, N = 15 SE +/- 39.37, N = 3 2615.31 2598.32 2621.26 MIN: 2557.11 MIN: 2532.11 MIN: 2560.3 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 1 2 3 0.944 1.888 2.832 3.776 4.72 SE +/- 0.00754, N = 3 SE +/- 0.00107, N = 3 SE +/- 0.00174, N = 3 4.19566 4.18604 4.18462 MIN: 4.16 MIN: 4.16 MIN: 4.16 1. (CXX) g++ options: -O3 -march=native -std=c++11 -fopenmp -msse4.1 -fPIC -pie -lpthread -ldl
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 1 2 3 10 20 30 40 50 SE +/- 0.06, N = 3 SE +/- 0.38, N = 3 SE +/- 0.04, N = 3 43.87 43.01 43.82 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 1 2 3 30 60 90 120 150 SE +/- 0.26, N = 3 SE +/- 0.06, N = 3 SE +/- 0.06, N = 3 150.89 149.56 150.50 1. (F9X) gfortran options: -cpp -O2 -funroll-loops -floop-optimize -fcray-pointer -fbacktrace -pthread -lmpi_usempif08 -lmpi_mpifh -lmpi
Timed Mesa Compilation Time To Compile OpenBenchmarking.org Seconds, Fewer Is Better Timed Mesa Compilation 21.0 Time To Compile 1 2 3 20 40 60 80 100 SE +/- 0.16, N = 3 SE +/- 0.11, N = 3 SE +/- 0.06, N = 3 96.02 95.82 95.94
Timed Node.js Compilation Time To Compile OpenBenchmarking.org Seconds, Fewer Is Better Timed Node.js Compilation 15.11 Time To Compile 1 2 3 200 400 600 800 1000 SE +/- 0.27, N = 3 SE +/- 0.34, N = 3 SE +/- 0.25, N = 3 868.88 869.02 869.26
Phoronix Test Suite v10.8.4