3800XT Xmas AMD Ryzen 7 3800XT 8-Core testing with a MSI X370 XPOWER GAMING TITANIUM (MS-7A31) v1.0 (1.MS BIOS) and Sapphire AMD Radeon HD 4650 on Debian 10 via the Phoronix Test Suite.
HTML result view exported from: https://openbenchmarking.org/result/2012220-HA-3800XTXMA77&sor .
3800XT Xmas Processor Motherboard Chipset Memory Disk Graphics Audio Network OS Kernel Display Server Display Driver Compiler File-System Screen Resolution 1 2 3 AMD Ryzen 7 3800XT 8-Core @ 3.90GHz (8 Cores / 16 Threads) MSI X370 XPOWER GAMING TITANIUM (MS-7A31) v1.0 (1.MS BIOS) AMD Starship/Matisse 16GB 128GB INTEL SSDPEKKW128G7 Sapphire AMD Radeon HD 4650 AMD RV710/730 Intel I211 Debian 10 4.19.0-13-amd64 (x86_64) X Server 1.20.4 modesetting 1.20.4 GCC 8.3.0 ext4 1024x768 OpenBenchmarking.org Compiler Details - --build=x86_64-linux-gnu --disable-vtable-verify --disable-werror --enable-bootstrap --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++ --enable-libmpx --enable-libstdcxx-debug --enable-libstdcxx-time=yes --enable-multiarch --enable-multilib --enable-nls --enable-objc-gc=auto --enable-offload-targets=nvptx-none --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 --with-tune=generic --without-cuda-driver -v Processor Details - Scaling Governor: acpi-cpufreq ondemand (Boost: Enabled) - CPU Microcode: 0x8701021 Security Details - itlb_multihit: Not affected + 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 Full AMD retpoline IBPB: conditional STIBP: conditional RSB filling + srbds: Not affected + tsx_async_abort: Not affected
3800XT Xmas clomp: Static OMP Speedup simdjson: Kostya simdjson: LargeRand simdjson: PartialTweets simdjson: DistinctUserID 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 build2: Time To Compile build-eigen: Time To Compile encode-ape: WAV To APE encode-opus: WAV To Opus Encode node-web-tooling: ncnn: CPU - mobilenet ncnn: CPU-v2-v2 - mobilenet-v2 ncnn: CPU-v3-v3 - mobilenet-v3 ncnn: CPU - shufflenet-v2 ncnn: CPU - mnasnet ncnn: CPU - efficientnet-b0 ncnn: CPU - blazeface ncnn: CPU - googlenet ncnn: CPU - vgg16 ncnn: CPU - resnet18 ncnn: CPU - alexnet ncnn: CPU - resnet50 ncnn: CPU - yolov4-tiny ncnn: CPU - squeezenet_ssd ncnn: CPU - regnety_400m encode-wavpack: WAV To WavPack 1 2 3 24.6 0.79 0.52 0.87 0.91 4.48738 8.51187 2.54343 2.24794 22.4927 4.89338 6.46084 19.9432 6.08209 5.04369 3738.79 2559.41 3737.84 2539.97 4.88553 3748.94 2545.13 2.77016 91.947 53.636 10.880 6.672 11.67 17.71 5.65 4.75 6.53 4.55 7.71 2.20 15.80 65.01 17.06 13.35 29.89 27.55 22.34 16.91 11.613 24.3 0.77 0.52 0.87 0.93 4.48906 8.62804 2.51638 2.24690 22.3600 4.92244 6.52103 20.0053 6.20820 5.05767 3744.57 2599.00 3729.25 2548.96 4.92836 3760.66 2589.72 2.80307 92.305 53.608 10.901 6.843 11.85 17.96 5.75 4.89 6.75 4.59 7.60 2.20 15.90 64.95 17.35 13.59 29.40 27.02 22.47 17.11 11.863 24.1 0.77 0.50 0.87 0.94 4.48307 8.52628 2.53349 2.21311 22.4369 4.92300 6.54317 19.9962 6.11717 5.03873 3746.85 2562.58 3754.88 2549.09 4.98457 3729.32 2535.92 2.79235 91.555 54.143 10.937 6.868 11.77 17.75 5.74 4.82 6.56 4.59 7.59 2.21 15.88 65.73 17.15 13.72 29.56 27.50 22.70 17.15 11.863 OpenBenchmarking.org
CLOMP Static OMP Speedup OpenBenchmarking.org Speedup, More Is Better CLOMP 1.2 Static OMP Speedup 1 2 3 6 12 18 24 30 SE +/- 0.06, N = 3 SE +/- 0.24, N = 9 SE +/- 0.23, N = 3 24.6 24.3 24.1 1. (CC) gcc options: -fopenmp -O3 -lm
simdjson Throughput Test: Kostya OpenBenchmarking.org GB/s, More Is Better simdjson 0.7.1 Throughput Test: Kostya 1 3 2 0.1778 0.3556 0.5334 0.7112 0.889 SE +/- 0.01, N = 3 SE +/- 0.01, N = 3 SE +/- 0.01, N = 3 0.79 0.77 0.77 1. (CXX) g++ options: -O3 -pthread
simdjson Throughput Test: LargeRandom OpenBenchmarking.org GB/s, More Is Better simdjson 0.7.1 Throughput Test: LargeRandom 2 1 3 0.117 0.234 0.351 0.468 0.585 SE +/- 0.00, N = 3 SE +/- 0.00, N = 3 SE +/- 0.00, N = 3 0.52 0.52 0.50 1. (CXX) g++ options: -O3 -pthread
simdjson Throughput Test: PartialTweets OpenBenchmarking.org GB/s, More Is Better simdjson 0.7.1 Throughput Test: PartialTweets 3 2 1 0.1958 0.3916 0.5874 0.7832 0.979 SE +/- 0.01, N = 3 SE +/- 0.00, N = 3 SE +/- 0.00, N = 3 0.87 0.87 0.87 1. (CXX) g++ options: -O3 -pthread
simdjson Throughput Test: DistinctUserID OpenBenchmarking.org GB/s, More Is Better simdjson 0.7.1 Throughput Test: DistinctUserID 3 2 1 0.2115 0.423 0.6345 0.846 1.0575 SE +/- 0.00, N = 3 SE +/- 0.01, N = 3 SE +/- 0.00, N = 3 0.94 0.93 0.91 1. (CXX) g++ options: -O3 -pthread
oneDNN Harness: IP Shapes 1D - Data Type: f32 - Engine: CPU OpenBenchmarking.org ms, Fewer Is Better oneDNN 2.0 Harness: IP Shapes 1D - Data Type: f32 - Engine: CPU 3 1 2 1.01 2.02 3.03 4.04 5.05 SE +/- 0.00136, N = 3 SE +/- 0.00749, N = 3 SE +/- 0.00920, N = 3 4.48307 4.48738 4.48906 MIN: 4.38 MIN: 4.37 MIN: 4.36 1. (CXX) g++ options: -O3 -std=c++11 -fopenmp -msse4.1 -fPIC -pie -lpthread
oneDNN Harness: IP Shapes 3D - Data Type: f32 - Engine: CPU OpenBenchmarking.org ms, Fewer Is Better oneDNN 2.0 Harness: IP Shapes 3D - Data Type: f32 - Engine: CPU 1 3 2 2 4 6 8 10 SE +/- 0.00466, N = 3 SE +/- 0.00758, N = 3 SE +/- 0.09156, N = 3 8.51187 8.52628 8.62804 MIN: 8.22 MIN: 8.24 MIN: 8.19 1. (CXX) g++ options: -O3 -std=c++11 -fopenmp -msse4.1 -fPIC -pie -lpthread
oneDNN Harness: IP Shapes 1D - Data Type: u8s8f32 - Engine: CPU OpenBenchmarking.org ms, Fewer Is Better oneDNN 2.0 Harness: IP Shapes 1D - Data Type: u8s8f32 - Engine: CPU 2 3 1 0.5723 1.1446 1.7169 2.2892 2.8615 SE +/- 0.01254, N = 3 SE +/- 0.02535, N = 3 SE +/- 0.03478, N = 3 2.51638 2.53349 2.54343 MIN: 2.46 MIN: 2.47 MIN: 2.46 1. (CXX) g++ options: -O3 -std=c++11 -fopenmp -msse4.1 -fPIC -pie -lpthread
oneDNN Harness: IP Shapes 3D - Data Type: u8s8f32 - Engine: CPU OpenBenchmarking.org ms, Fewer Is Better oneDNN 2.0 Harness: IP Shapes 3D - Data Type: u8s8f32 - Engine: CPU 3 2 1 0.5058 1.0116 1.5174 2.0232 2.529 SE +/- 0.00052, N = 3 SE +/- 0.03512, N = 3 SE +/- 0.03602, N = 3 2.21311 2.24690 2.24794 MIN: 2.15 MIN: 2.15 MIN: 2.1 1. (CXX) g++ options: -O3 -std=c++11 -fopenmp -msse4.1 -fPIC -pie -lpthread
oneDNN Harness: Convolution Batch Shapes Auto - Data Type: f32 - Engine: CPU OpenBenchmarking.org ms, Fewer Is Better oneDNN 2.0 Harness: Convolution Batch Shapes Auto - Data Type: f32 - Engine: CPU 2 3 1 5 10 15 20 25 SE +/- 0.07, N = 3 SE +/- 0.17, N = 3 SE +/- 0.22, N = 3 22.36 22.44 22.49 MIN: 22.04 MIN: 21.94 MIN: 22.02 1. (CXX) g++ options: -O3 -std=c++11 -fopenmp -msse4.1 -fPIC -pie -lpthread
oneDNN Harness: Deconvolution Batch shapes_1d - Data Type: f32 - Engine: CPU OpenBenchmarking.org ms, Fewer Is Better oneDNN 2.0 Harness: Deconvolution Batch shapes_1d - Data Type: f32 - Engine: CPU 1 2 3 1.1077 2.2154 3.3231 4.4308 5.5385 SE +/- 0.01359, N = 3 SE +/- 0.00927, N = 3 SE +/- 0.03107, N = 3 4.89338 4.92244 4.92300 MIN: 4.77 MIN: 4.8 MIN: 4.8 1. (CXX) g++ options: -O3 -std=c++11 -fopenmp -msse4.1 -fPIC -pie -lpthread
oneDNN Harness: Deconvolution Batch shapes_3d - Data Type: f32 - Engine: CPU OpenBenchmarking.org ms, Fewer Is Better oneDNN 2.0 Harness: Deconvolution Batch shapes_3d - Data Type: f32 - Engine: CPU 1 2 3 2 4 6 8 10 SE +/- 0.00198, N = 3 SE +/- 0.05128, N = 3 SE +/- 0.06875, N = 3 6.46084 6.52103 6.54317 MIN: 6.26 MIN: 6.26 MIN: 6.29 1. (CXX) g++ options: -O3 -std=c++11 -fopenmp -msse4.1 -fPIC -pie -lpthread
oneDNN Harness: Convolution Batch Shapes Auto - Data Type: u8s8f32 - Engine: CPU OpenBenchmarking.org ms, Fewer Is Better oneDNN 2.0 Harness: Convolution Batch Shapes Auto - Data Type: u8s8f32 - Engine: CPU 1 3 2 5 10 15 20 25 SE +/- 0.05, N = 3 SE +/- 0.06, N = 3 SE +/- 0.07, N = 3 19.94 20.00 20.01 MIN: 19.55 MIN: 19.58 MIN: 19.49 1. (CXX) g++ options: -O3 -std=c++11 -fopenmp -msse4.1 -fPIC -pie -lpthread
oneDNN Harness: Deconvolution Batch shapes_1d - Data Type: u8s8f32 - Engine: CPU OpenBenchmarking.org ms, Fewer Is Better oneDNN 2.0 Harness: Deconvolution Batch shapes_1d - Data Type: u8s8f32 - Engine: CPU 1 3 2 2 4 6 8 10 SE +/- 0.01646, N = 3 SE +/- 0.05490, N = 3 SE +/- 0.02186, N = 3 6.08209 6.11717 6.20820 MIN: 5.82 MIN: 5.82 MIN: 5.92 1. (CXX) g++ options: -O3 -std=c++11 -fopenmp -msse4.1 -fPIC -pie -lpthread
oneDNN Harness: Deconvolution Batch shapes_3d - Data Type: u8s8f32 - Engine: CPU OpenBenchmarking.org ms, Fewer Is Better oneDNN 2.0 Harness: Deconvolution Batch shapes_3d - Data Type: u8s8f32 - Engine: CPU 3 1 2 1.138 2.276 3.414 4.552 5.69 SE +/- 0.01014, N = 3 SE +/- 0.01222, N = 3 SE +/- 0.00496, N = 3 5.03873 5.04369 5.05767 MIN: 4.88 MIN: 4.89 MIN: 4.87 1. (CXX) g++ options: -O3 -std=c++11 -fopenmp -msse4.1 -fPIC -pie -lpthread
oneDNN Harness: Recurrent Neural Network Training - Data Type: f32 - Engine: CPU OpenBenchmarking.org ms, Fewer Is Better oneDNN 2.0 Harness: Recurrent Neural Network Training - Data Type: f32 - Engine: CPU 1 2 3 800 1600 2400 3200 4000 SE +/- 16.31, N = 3 SE +/- 7.38, N = 3 SE +/- 19.25, N = 3 3738.79 3744.57 3746.85 MIN: 3697.6 MIN: 3709.08 MIN: 3689.7 1. (CXX) g++ options: -O3 -std=c++11 -fopenmp -msse4.1 -fPIC -pie -lpthread
oneDNN Harness: Recurrent Neural Network Inference - Data Type: f32 - Engine: CPU OpenBenchmarking.org ms, Fewer Is Better oneDNN 2.0 Harness: Recurrent Neural Network Inference - Data Type: f32 - Engine: CPU 1 3 2 600 1200 1800 2400 3000 SE +/- 21.19, N = 3 SE +/- 18.04, N = 3 SE +/- 16.17, N = 3 2559.41 2562.58 2599.00 MIN: 2519.59 MIN: 2513.45 MIN: 2537.71 1. (CXX) g++ options: -O3 -std=c++11 -fopenmp -msse4.1 -fPIC -pie -lpthread
oneDNN Harness: Recurrent Neural Network Training - Data Type: u8s8f32 - Engine: CPU OpenBenchmarking.org ms, Fewer Is Better oneDNN 2.0 Harness: Recurrent Neural Network Training - Data Type: u8s8f32 - Engine: CPU 2 1 3 800 1600 2400 3200 4000 SE +/- 7.73, N = 3 SE +/- 11.79, N = 3 SE +/- 1.39, N = 3 3729.25 3737.84 3754.88 MIN: 3691.59 MIN: 3715.9 MIN: 3710.36 1. (CXX) g++ options: -O3 -std=c++11 -fopenmp -msse4.1 -fPIC -pie -lpthread
oneDNN Harness: Recurrent Neural Network Inference - Data Type: u8s8f32 - Engine: CPU OpenBenchmarking.org ms, Fewer Is Better oneDNN 2.0 Harness: Recurrent Neural Network Inference - Data Type: u8s8f32 - Engine: CPU 1 2 3 500 1000 1500 2000 2500 SE +/- 10.45, N = 3 SE +/- 18.64, N = 3 SE +/- 16.36, N = 3 2539.97 2548.96 2549.09 MIN: 2503.75 MIN: 2516.55 MIN: 2510.5 1. (CXX) g++ options: -O3 -std=c++11 -fopenmp -msse4.1 -fPIC -pie -lpthread
oneDNN Harness: Matrix Multiply Batch Shapes Transformer - Data Type: f32 - Engine: CPU OpenBenchmarking.org ms, Fewer Is Better oneDNN 2.0 Harness: Matrix Multiply Batch Shapes Transformer - Data Type: f32 - Engine: CPU 1 2 3 1.1215 2.243 3.3645 4.486 5.6075 SE +/- 0.00771, N = 3 SE +/- 0.02985, N = 3 SE +/- 0.06118, N = 3 4.88553 4.92836 4.98457 MIN: 4.71 MIN: 4.62 MIN: 4.58 1. (CXX) g++ options: -O3 -std=c++11 -fopenmp -msse4.1 -fPIC -pie -lpthread
oneDNN Harness: Recurrent Neural Network Training - Data Type: bf16bf16bf16 - Engine: CPU OpenBenchmarking.org ms, Fewer Is Better oneDNN 2.0 Harness: Recurrent Neural Network Training - Data Type: bf16bf16bf16 - Engine: CPU 3 1 2 800 1600 2400 3200 4000 SE +/- 16.79, N = 3 SE +/- 15.88, N = 3 SE +/- 20.09, N = 3 3729.32 3748.94 3760.66 MIN: 3692.62 MIN: 3715.22 MIN: 3711.31 1. (CXX) g++ options: -O3 -std=c++11 -fopenmp -msse4.1 -fPIC -pie -lpthread
oneDNN Harness: Recurrent Neural Network Inference - Data Type: bf16bf16bf16 - Engine: CPU OpenBenchmarking.org ms, Fewer Is Better oneDNN 2.0 Harness: Recurrent Neural Network Inference - Data Type: bf16bf16bf16 - Engine: CPU 3 1 2 600 1200 1800 2400 3000 SE +/- 3.65, N = 3 SE +/- 16.39, N = 3 SE +/- 34.23, N = 3 2535.92 2545.13 2589.72 MIN: 2518.96 MIN: 2520.36 MIN: 2517.27 1. (CXX) g++ options: -O3 -std=c++11 -fopenmp -msse4.1 -fPIC -pie -lpthread
oneDNN Harness: Matrix Multiply Batch Shapes Transformer - Data Type: u8s8f32 - Engine: CPU OpenBenchmarking.org ms, Fewer Is Better oneDNN 2.0 Harness: Matrix Multiply Batch Shapes Transformer - Data Type: u8s8f32 - Engine: CPU 1 3 2 0.6307 1.2614 1.8921 2.5228 3.1535 SE +/- 0.00210, N = 3 SE +/- 0.01553, N = 3 SE +/- 0.02928, N = 3 2.77016 2.79235 2.80307 MIN: 2.64 MIN: 2.67 MIN: 2.66 1. (CXX) g++ options: -O3 -std=c++11 -fopenmp -msse4.1 -fPIC -pie -lpthread
Build2 Time To Compile OpenBenchmarking.org Seconds, Fewer Is Better Build2 0.13 Time To Compile 3 1 2 20 40 60 80 100 SE +/- 0.95, N = 3 SE +/- 1.24, N = 4 SE +/- 0.97, N = 15 91.56 91.95 92.31
Timed Eigen Compilation Time To Compile OpenBenchmarking.org Seconds, Fewer Is Better Timed Eigen Compilation 3.3.9 Time To Compile 2 1 3 12 24 36 48 60 SE +/- 0.07, N = 3 SE +/- 0.08, N = 3 SE +/- 0.28, N = 3 53.61 53.64 54.14
Monkey Audio Encoding WAV To APE OpenBenchmarking.org Seconds, Fewer Is Better Monkey Audio Encoding 3.99.6 WAV To APE 1 2 3 3 6 9 12 15 SE +/- 0.03, N = 5 SE +/- 0.02, N = 5 SE +/- 0.01, N = 5 10.88 10.90 10.94 1. (CXX) g++ options: -O3 -pedantic -rdynamic -lrt
Opus Codec Encoding WAV To Opus Encode OpenBenchmarking.org Seconds, Fewer Is Better Opus Codec Encoding 1.3.1 WAV To Opus Encode 1 2 3 2 4 6 8 10 SE +/- 0.051, N = 5 SE +/- 0.002, N = 5 SE +/- 0.002, N = 5 6.672 6.843 6.868 1. (CXX) g++ options: -fvisibility=hidden -logg -lm
Node.js V8 Web Tooling Benchmark OpenBenchmarking.org runs/s, More Is Better Node.js V8 Web Tooling Benchmark 2 3 1 3 6 9 12 15 SE +/- 0.03, N = 3 SE +/- 0.09, N = 3 SE +/- 0.08, N = 3 11.85 11.77 11.67 1. Nodejs
v10.21.0
NCNN Target: CPU - Model: mobilenet OpenBenchmarking.org ms, Fewer Is Better NCNN 20201218 Target: CPU - Model: mobilenet 1 3 2 4 8 12 16 20 SE +/- 0.15, N = 3 SE +/- 0.11, N = 3 SE +/- 0.28, N = 3 17.71 17.75 17.96 MIN: 17.21 / MAX: 37.89 MIN: 17.4 / MAX: 18.27 MIN: 17.32 / MAX: 22.66 1. (CXX) g++ options: -O3 -rdynamic -lgomp -lpthread
NCNN Target: CPU-v2-v2 - Model: mobilenet-v2 OpenBenchmarking.org ms, Fewer Is Better NCNN 20201218 Target: CPU-v2-v2 - Model: mobilenet-v2 1 3 2 1.2938 2.5876 3.8814 5.1752 6.469 SE +/- 0.05, N = 3 SE +/- 0.01, N = 3 SE +/- 0.01, N = 3 5.65 5.74 5.75 MIN: 5.5 / MAX: 5.81 MIN: 5.68 / MAX: 5.92 MIN: 5.67 / MAX: 8.44 1. (CXX) g++ options: -O3 -rdynamic -lgomp -lpthread
NCNN Target: CPU-v3-v3 - Model: mobilenet-v3 OpenBenchmarking.org ms, Fewer Is Better NCNN 20201218 Target: CPU-v3-v3 - Model: mobilenet-v3 1 3 2 1.1003 2.2006 3.3009 4.4012 5.5015 SE +/- 0.04, N = 3 SE +/- 0.01, N = 3 SE +/- 0.07, N = 3 4.75 4.82 4.89 MIN: 4.65 / MAX: 4.95 MIN: 4.75 / MAX: 4.88 MIN: 4.76 / MAX: 9.52 1. (CXX) g++ options: -O3 -rdynamic -lgomp -lpthread
NCNN Target: CPU - Model: shufflenet-v2 OpenBenchmarking.org ms, Fewer Is Better NCNN 20201218 Target: CPU - Model: shufflenet-v2 1 3 2 2 4 6 8 10 SE +/- 0.02, N = 3 SE +/- 0.02, N = 3 SE +/- 0.22, N = 3 6.53 6.56 6.75 MIN: 6.43 / MAX: 6.87 MIN: 6.47 / MAX: 6.9 MIN: 6.47 / MAX: 11.37 1. (CXX) g++ options: -O3 -rdynamic -lgomp -lpthread
NCNN Target: CPU - Model: mnasnet OpenBenchmarking.org ms, Fewer Is Better NCNN 20201218 Target: CPU - Model: mnasnet 1 2 3 1.0328 2.0656 3.0984 4.1312 5.164 SE +/- 0.02, N = 3 SE +/- 0.02, N = 3 SE +/- 0.01, N = 3 4.55 4.59 4.59 MIN: 4.48 / MAX: 4.77 MIN: 4.52 / MAX: 4.79 MIN: 4.54 / MAX: 4.73 1. (CXX) g++ options: -O3 -rdynamic -lgomp -lpthread
NCNN Target: CPU - Model: efficientnet-b0 OpenBenchmarking.org ms, Fewer Is Better NCNN 20201218 Target: CPU - Model: efficientnet-b0 3 2 1 2 4 6 8 10 SE +/- 0.00, N = 3 SE +/- 0.02, N = 3 SE +/- 0.18, N = 3 7.59 7.60 7.71 MIN: 7.52 / MAX: 7.78 MIN: 7.5 / MAX: 7.99 MIN: 7.32 / MAX: 12.06 1. (CXX) g++ options: -O3 -rdynamic -lgomp -lpthread
NCNN Target: CPU - Model: blazeface OpenBenchmarking.org ms, Fewer Is Better NCNN 20201218 Target: CPU - Model: blazeface 1 2 3 0.4973 0.9946 1.4919 1.9892 2.4865 SE +/- 0.01, N = 3 SE +/- 0.00, N = 3 SE +/- 0.00, N = 3 2.20 2.20 2.21 MIN: 2.17 / MAX: 2.24 MIN: 2.18 / MAX: 2.23 MIN: 2.19 / MAX: 2.25 1. (CXX) g++ options: -O3 -rdynamic -lgomp -lpthread
NCNN Target: CPU - Model: googlenet OpenBenchmarking.org ms, Fewer Is Better NCNN 20201218 Target: CPU - Model: googlenet 1 3 2 4 8 12 16 20 SE +/- 0.08, N = 3 SE +/- 0.13, N = 3 SE +/- 0.12, N = 3 15.80 15.88 15.90 MIN: 15.55 / MAX: 17.96 MIN: 15.59 / MAX: 16.98 MIN: 15.65 / MAX: 16.3 1. (CXX) g++ options: -O3 -rdynamic -lgomp -lpthread
NCNN Target: CPU - Model: vgg16 OpenBenchmarking.org ms, Fewer Is Better NCNN 20201218 Target: CPU - Model: vgg16 2 1 3 15 30 45 60 75 SE +/- 0.12, N = 3 SE +/- 0.25, N = 3 SE +/- 0.76, N = 3 64.95 65.01 65.73 MIN: 64.42 / MAX: 67.23 MIN: 64.47 / MAX: 75.95 MIN: 64.66 / MAX: 94.99 1. (CXX) g++ options: -O3 -rdynamic -lgomp -lpthread
NCNN Target: CPU - Model: resnet18 OpenBenchmarking.org ms, Fewer Is Better NCNN 20201218 Target: CPU - Model: resnet18 1 3 2 4 8 12 16 20 SE +/- 0.03, N = 3 SE +/- 0.11, N = 3 SE +/- 0.18, N = 3 17.06 17.15 17.35 MIN: 16.88 / MAX: 17.3 MIN: 16.88 / MAX: 17.52 MIN: 16.91 / MAX: 22 1. (CXX) g++ options: -O3 -rdynamic -lgomp -lpthread
NCNN Target: CPU - Model: alexnet OpenBenchmarking.org ms, Fewer Is Better NCNN 20201218 Target: CPU - Model: alexnet 1 2 3 4 8 12 16 20 SE +/- 0.04, N = 3 SE +/- 0.18, N = 3 SE +/- 0.26, N = 3 13.35 13.59 13.72 MIN: 13.15 / MAX: 14.36 MIN: 13.2 / MAX: 21.81 MIN: 13.3 / MAX: 18.46 1. (CXX) g++ options: -O3 -rdynamic -lgomp -lpthread
NCNN Target: CPU - Model: resnet50 OpenBenchmarking.org ms, Fewer Is Better NCNN 20201218 Target: CPU - Model: resnet50 2 3 1 7 14 21 28 35 SE +/- 0.19, N = 3 SE +/- 0.11, N = 3 SE +/- 0.48, N = 3 29.40 29.56 29.89 MIN: 28.96 / MAX: 31.7 MIN: 29.23 / MAX: 29.88 MIN: 29.04 / MAX: 36.56 1. (CXX) g++ options: -O3 -rdynamic -lgomp -lpthread
NCNN Target: CPU - Model: yolov4-tiny OpenBenchmarking.org ms, Fewer Is Better NCNN 20201218 Target: CPU - Model: yolov4-tiny 2 3 1 6 12 18 24 30 SE +/- 0.37, N = 3 SE +/- 0.41, N = 3 SE +/- 0.45, N = 3 27.02 27.50 27.55 MIN: 26.54 / MAX: 28.2 MIN: 26.6 / MAX: 28.39 MIN: 26.59 / MAX: 33.15 1. (CXX) g++ options: -O3 -rdynamic -lgomp -lpthread
NCNN Target: CPU - Model: squeezenet_ssd OpenBenchmarking.org ms, Fewer Is Better NCNN 20201218 Target: CPU - Model: squeezenet_ssd 1 2 3 5 10 15 20 25 SE +/- 0.08, N = 3 SE +/- 0.02, N = 3 SE +/- 0.23, N = 3 22.34 22.47 22.70 MIN: 22.05 / MAX: 25.42 MIN: 22.25 / MAX: 22.78 MIN: 22.29 / MAX: 27.66 1. (CXX) g++ options: -O3 -rdynamic -lgomp -lpthread
NCNN Target: CPU - Model: regnety_400m OpenBenchmarking.org ms, Fewer Is Better NCNN 20201218 Target: CPU - Model: regnety_400m 1 2 3 4 8 12 16 20 SE +/- 0.10, N = 3 SE +/- 0.01, N = 3 SE +/- 0.01, N = 3 16.91 17.11 17.15 MIN: 16.65 / MAX: 18.74 MIN: 16.88 / MAX: 18.83 MIN: 16.99 / MAX: 17.41 1. (CXX) g++ options: -O3 -rdynamic -lgomp -lpthread
WavPack Audio Encoding WAV To WavPack OpenBenchmarking.org Seconds, Fewer Is Better WavPack Audio Encoding 5.3 WAV To WavPack 1 2 3 3 6 9 12 15 SE +/- 0.04, N = 5 SE +/- 0.00, N = 5 SE +/- 0.02, N = 5 11.61 11.86 11.86 1. (CXX) g++ options: -rdynamic
Phoronix Test Suite v10.8.4