AMD EPYC 7601 Xmas 2020

AMD EPYC 7601 32-Core testing with a TYAN B8026T70AE24HR (V1.02.B10 BIOS) and llvmpipe 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 2012222-HA-AMDEPYC7628
Jump To Table - Results

View

Do Not Show Noisy Results
Do Not Show Results With Incomplete Data
Do Not Show Results With Little Change/Spread
List Notable Results
Show Result Confidence Charts

Limit displaying results to tests within:

Audio Encoding 3 Tests
Bioinformatics 2 Tests
Timed Code Compilation 3 Tests
C/C++ Compiler Tests 5 Tests
CPU Massive 4 Tests
Creator Workloads 4 Tests
Encoding 3 Tests
HPC - High Performance Computing 4 Tests
Machine Learning 2 Tests
Multi-Core 5 Tests
Programmer / Developer System Benchmarks 6 Tests
Scientific Computing 2 Tests
Server 3 Tests

Statistics

Show Overall Harmonic Mean(s)
Show Overall Geometric Mean
Show Geometric Means Per-Suite/Category
Show Wins / Losses Counts (Pie Chart)
Normalize Results
Remove Outliers Before Calculating Averages

Graph Settings

Force Line Graphs Where Applicable
Convert To Scalar Where Applicable
Prefer Vertical Bar Graphs

Multi-Way Comparison

Condense Multi-Option Tests Into Single Result Graphs

Table

Show Detailed System Result Table

Run Management

Highlight
Result
Hide
Result
Result
Identifier
View Logs
Performance Per
Dollar
Date
Run
  Test
  Duration
Run 1
December 21 2020
  11 Hours, 33 Minutes
Run 2
December 21 2020
  11 Hours, 37 Minutes
Run 3
December 22 2020
  10 Hours, 48 Minutes
Invert Hiding All Results Option
  11 Hours, 19 Minutes

Only show results where is faster than
Only show results matching title/arguments (delimit multiple options with a comma):
Do not show results matching title/arguments (delimit multiple options with a comma):


AMD EPYC 7601 Xmas 2020OpenBenchmarking.orgPhoronix Test SuiteAMD EPYC 7601 32-Core @ 2.20GHz (32 Cores / 64 Threads)TYAN B8026T70AE24HR (V1.02.B10 BIOS)AMD 17h126GB280GB INTEL SSDPE21D280GAllvmpipeVE2282 x Broadcom NetXtreme BCM5720 2-port PCIeUbuntu 20.045.4.0-53-generic (x86_64)GNOME Shell 3.36.4X Server 1.20.8modesetting 1.20.83.3 Mesa 20.0.8 (LLVM 10.0.0 128 bits)GCC 9.3.0ext41920x1080ProcessorMotherboardChipsetMemoryDiskGraphicsMonitorNetworkOSKernelDesktopDisplay ServerDisplay DriverOpenGLCompilerFile-SystemScreen ResolutionAMD EPYC 7601 Xmas 2020 BenchmarksSystem Logs- --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 - Scaling Governor: acpi-cpufreq ondemand (Boost: Enabled) - CPU Microcode: 0x8001250 - 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: disabled RSB filling + srbds: Not affected + tsx_async_abort: Not affected

Run 1Run 2Run 3Result OverviewPhoronix Test Suite100%100%101%101%102%Node.js V8 Web Tooling BenchmarkoneDNNCLOMPTimed MAFFT AlignmentTimed HMMer SearchMonkey Audio EncodingBuild2NCNNSQLite SpeedtestCoremarkOpus Codec EncodingTimed FFmpeg CompilationWavPack Audio EncodingTimed Eigen Compilationsimdjson

AMD EPYC 7601 Xmas 2020clomp: Static OMP Speedupencode-ape: WAV To APEencode-opus: WAV To Opus Encodeencode-wavpack: WAV To WavPackhmmer: Pfam Database Searchmafft: Multiple Sequence Alignment - LSU RNAncnn: CPU - mobilenetncnn: CPU-v2-v2 - mobilenet-v2ncnn: CPU-v3-v3 - mobilenet-v3ncnn: CPU - shufflenet-v2ncnn: CPU - mnasnetncnn: CPU - efficientnet-b0ncnn: CPU - blazefacencnn: CPU - googlenetncnn: CPU - vgg16ncnn: CPU - resnet18ncnn: CPU - alexnetncnn: CPU - resnet50ncnn: CPU - yolov4-tinyncnn: CPU - squeezenet_ssdncnn: CPU - regnety_400monednn: IP Shapes 1D - f32 - CPUonednn: IP Shapes 3D - f32 - CPUonednn: IP Shapes 1D - u8s8f32 - CPUonednn: IP Shapes 3D - u8s8f32 - CPUonednn: Convolution Batch Shapes Auto - f32 - CPUonednn: Deconvolution Batch shapes_1d - f32 - CPUonednn: Deconvolution Batch shapes_3d - f32 - CPUonednn: Convolution Batch Shapes Auto - u8s8f32 - CPUonednn: Deconvolution Batch shapes_1d - u8s8f32 - CPUonednn: Deconvolution Batch shapes_3d - u8s8f32 - CPUonednn: Recurrent Neural Network Training - f32 - CPUonednn: Recurrent Neural Network Inference - f32 - CPUonednn: Recurrent Neural Network Training - u8s8f32 - CPUonednn: Recurrent Neural Network Inference - u8s8f32 - CPUonednn: Matrix Multiply Batch Shapes Transformer - f32 - CPUonednn: Recurrent Neural Network Training - bf16bf16bf16 - CPUonednn: Recurrent Neural Network Inference - bf16bf16bf16 - CPUonednn: Matrix Multiply Batch Shapes Transformer - u8s8f32 - CPUcoremark: CoreMark Size 666 - Iterations Per Secondbuild-ffmpeg: Time To Compilebuild2: Time To Compilebuild-eigen: Time To Compilesqlite-speedtest: Timed Time - Size 1,000node-web-tooling: simdjson: Kostyasimdjson: LargeRandsimdjson: PartialTweetssimdjson: DistinctUserIDRun 1Run 2Run 357.118.34610.18717.319200.29515.01843.1017.4216.3017.5116.1722.197.7948.06100.7241.8333.2060.7857.9946.68117.025.3477112.41772.679373.5651118.51284.032819.0443923.30304.602484.4131410732.733293.4910583.103300.071.7122010689.163332.791.78892879248.02263839.094102.295120.01690.1166.780.330.280.360.3757.718.33210.21517.312199.70815.14741.8419.4217.4817.3515.7622.247.8946.9994.3345.7030.1959.2455.8046.89119.234.4914811.76992.685113.5597018.68004.007139.0389322.45764.714734.3709710747.53322.6810647.603434.141.7405610915.653312.301.77953879237.12207839.108102.588119.98190.3206.740.330.280.360.3757.818.41610.19517.292200.75315.02343.2618.2216.9116.9416.2623.227.9049.8188.5543.6431.9259.4956.5244.81118.484.3351912.08562.665093.5715318.65564.018279.0876723.21204.228414.4004910314.223393.8210812.543327.911.6651211077.93405.821.79366876909.95000139.189102.354120.19190.1076.850.330.280.360.37OpenBenchmarking.org

CLOMP

CLOMP is the C version of the Livermore OpenMP benchmark developed to measure OpenMP overheads and other performance impacts due to threading in order to influence future system designs. This particular test profile configuration is currently set to look at the OpenMP static schedule speed-up across all available CPU cores using the recommended test configuration. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgSpeedup, More Is BetterCLOMP 1.2Static OMP SpeedupRun 1Run 2Run 31326395265SE +/- 0.32, N = 3SE +/- 0.70, N = 3SE +/- 0.43, N = 357.157.757.81. (CC) gcc options: -fopenmp -O3 -lm

Monkey Audio Encoding

This test times how long it takes to encode a sample WAV file to Monkey's Audio APE format. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgSeconds, Fewer Is BetterMonkey Audio Encoding 3.99.6WAV To APERun 1Run 2Run 3510152025SE +/- 0.01, N = 5SE +/- 0.01, N = 5SE +/- 0.08, N = 518.3518.3318.421. (CXX) g++ options: -O3 -pedantic -rdynamic -lrt

Opus Codec Encoding

Opus is an open audio codec. Opus is a lossy audio compression format designed primarily for interactive real-time applications over the Internet. This test uses Opus-Tools and measures the time required to encode a WAV file to Opus. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgSeconds, Fewer Is BetterOpus Codec Encoding 1.3.1WAV To Opus EncodeRun 1Run 2Run 33691215SE +/- 0.00, N = 5SE +/- 0.01, N = 5SE +/- 0.01, N = 510.1910.2210.201. (CXX) g++ options: -fvisibility=hidden -logg -lm

WavPack Audio Encoding

This test times how long it takes to encode a sample WAV file to WavPack format with very high quality settings. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgSeconds, Fewer Is BetterWavPack Audio Encoding 5.3WAV To WavPackRun 1Run 2Run 348121620SE +/- 0.02, N = 5SE +/- 0.02, N = 5SE +/- 0.00, N = 517.3217.3117.291. (CXX) g++ options: -rdynamic

Timed HMMer Search

This test searches through the Pfam database of profile hidden markov models. The search finds the domain structure of Drosophila Sevenless protein. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgSeconds, Fewer Is BetterTimed HMMer Search 3.3.1Pfam Database SearchRun 1Run 2Run 34080120160200SE +/- 0.06, N = 3SE +/- 0.82, N = 3SE +/- 0.16, N = 3200.30199.71200.751. (CC) gcc options: -O3 -pthread -lhmmer -leasel -lm

Timed MAFFT Alignment

This test performs an alignment of 100 pyruvate decarboxylase sequences. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgSeconds, Fewer Is BetterTimed MAFFT Alignment 7.471Multiple Sequence Alignment - LSU RNARun 1Run 2Run 348121620SE +/- 0.03, N = 3SE +/- 0.11, N = 3SE +/- 0.04, N = 315.0215.1515.021. (CC) gcc options: -std=c99 -O3 -lm -lpthread

NCNN

NCNN is a high performance neural network inference framework optimized for mobile and other platforms developed by Tencent. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgms, Fewer Is BetterNCNN 20201218Target: CPU - Model: mobilenetRun 1Run 2Run 31020304050SE +/- 1.57, N = 12SE +/- 1.10, N = 12SE +/- 1.07, N = 1243.1041.8443.26MIN: 35.09 / MAX: 501.41MIN: 35.73 / MAX: 496.11MIN: 34.82 / MAX: 511.891. (CXX) g++ options: -O3 -rdynamic -lgomp -lpthread

OpenBenchmarking.orgms, Fewer Is BetterNCNN 20201218Target: CPU-v2-v2 - Model: mobilenet-v2Run 1Run 2Run 3510152025SE +/- 0.22, N = 12SE +/- 1.19, N = 12SE +/- 0.54, N = 1217.4219.4218.22MIN: 15.79 / MAX: 249.25MIN: 15.84 / MAX: 439.61MIN: 15.35 / MAX: 435.271. (CXX) g++ options: -O3 -rdynamic -lgomp -lpthread

OpenBenchmarking.orgms, Fewer Is BetterNCNN 20201218Target: CPU-v3-v3 - Model: mobilenet-v3Run 1Run 2Run 348121620SE +/- 0.56, N = 12SE +/- 0.96, N = 12SE +/- 0.59, N = 1216.3017.4816.91MIN: 14.83 / MAX: 444.14MIN: 14.75 / MAX: 525.02MIN: 14.94 / MAX: 447.341. (CXX) g++ options: -O3 -rdynamic -lgomp -lpthread

OpenBenchmarking.orgms, Fewer Is BetterNCNN 20201218Target: CPU - Model: shufflenet-v2Run 1Run 2Run 348121620SE +/- 0.42, N = 12SE +/- 0.51, N = 12SE +/- 0.13, N = 1217.5117.3516.94MIN: 15.95 / MAX: 355.59MIN: 16 / MAX: 357.5MIN: 16.11 / MAX: 120.461. (CXX) g++ options: -O3 -rdynamic -lgomp -lpthread

OpenBenchmarking.orgms, Fewer Is BetterNCNN 20201218Target: CPU - Model: mnasnetRun 1Run 2Run 348121620SE +/- 0.48, N = 12SE +/- 0.24, N = 12SE +/- 0.43, N = 1216.1715.7616.26MIN: 14.62 / MAX: 428.63MIN: 14.78 / MAX: 415.5MIN: 14.79 / MAX: 427.391. (CXX) g++ options: -O3 -rdynamic -lgomp -lpthread

OpenBenchmarking.orgms, Fewer Is BetterNCNN 20201218Target: CPU - Model: efficientnet-b0Run 1Run 2Run 3612182430SE +/- 0.37, N = 12SE +/- 0.31, N = 12SE +/- 0.56, N = 1222.1922.2423.22MIN: 20.26 / MAX: 496.03MIN: 20.84 / MAX: 524.85MIN: 20.7 / MAX: 525.921. (CXX) g++ options: -O3 -rdynamic -lgomp -lpthread

OpenBenchmarking.orgms, Fewer Is BetterNCNN 20201218Target: CPU - Model: blazefaceRun 1Run 2Run 3246810SE +/- 0.06, N = 12SE +/- 0.06, N = 12SE +/- 0.09, N = 127.797.897.90MIN: 7.48 / MAX: 49.5MIN: 7.55 / MAX: 80.4MIN: 7.46 / MAX: 59.211. (CXX) g++ options: -O3 -rdynamic -lgomp -lpthread

OpenBenchmarking.orgms, Fewer Is BetterNCNN 20201218Target: CPU - Model: googlenetRun 1Run 2Run 31122334455SE +/- 2.27, N = 12SE +/- 2.77, N = 12SE +/- 2.45, N = 1248.0646.9949.81MIN: 32.75 / MAX: 604.8MIN: 33.26 / MAX: 605.84MIN: 32.24 / MAX: 613.181. (CXX) g++ options: -O3 -rdynamic -lgomp -lpthread

OpenBenchmarking.orgms, Fewer Is BetterNCNN 20201218Target: CPU - Model: vgg16Run 1Run 2Run 320406080100SE +/- 5.01, N = 12SE +/- 3.64, N = 12SE +/- 3.70, N = 12100.7294.3388.55MIN: 45.51 / MAX: 338.45MIN: 47.38 / MAX: 304.01MIN: 43.77 / MAX: 279.551. (CXX) g++ options: -O3 -rdynamic -lgomp -lpthread

OpenBenchmarking.orgms, Fewer Is BetterNCNN 20201218Target: CPU - Model: resnet18Run 1Run 2Run 31020304050SE +/- 1.98, N = 12SE +/- 3.66, N = 12SE +/- 2.71, N = 1241.8345.7043.64MIN: 23.36 / MAX: 249.26MIN: 27.44 / MAX: 248.59MIN: 27.63 / MAX: 246.761. (CXX) g++ options: -O3 -rdynamic -lgomp -lpthread

OpenBenchmarking.orgms, Fewer Is BetterNCNN 20201218Target: CPU - Model: alexnetRun 1Run 2Run 3816243240SE +/- 1.65, N = 12SE +/- 1.11, N = 12SE +/- 1.62, N = 1233.2030.1931.92MIN: 18.26 / MAX: 171.51MIN: 16.07 / MAX: 156.27MIN: 16.26 / MAX: 163.341. (CXX) g++ options: -O3 -rdynamic -lgomp -lpthread

OpenBenchmarking.orgms, Fewer Is BetterNCNN 20201218Target: CPU - Model: resnet50Run 1Run 2Run 31428425670SE +/- 2.69, N = 12SE +/- 1.83, N = 12SE +/- 3.15, N = 1260.7859.2459.49MIN: 38.67 / MAX: 633.7MIN: 38.46 / MAX: 770.44MIN: 38.42 / MAX: 662.241. (CXX) g++ options: -O3 -rdynamic -lgomp -lpthread

OpenBenchmarking.orgms, Fewer Is BetterNCNN 20201218Target: CPU - Model: yolov4-tinyRun 1Run 2Run 31326395265SE +/- 1.01, N = 12SE +/- 0.72, N = 12SE +/- 0.57, N = 1257.9955.8056.52MIN: 46.53 / MAX: 296.18MIN: 46.04 / MAX: 269.61MIN: 44.78 / MAX: 275.311. (CXX) g++ options: -O3 -rdynamic -lgomp -lpthread

OpenBenchmarking.orgms, Fewer Is BetterNCNN 20201218Target: CPU - Model: squeezenet_ssdRun 1Run 2Run 31122334455SE +/- 1.46, N = 12SE +/- 1.43, N = 12SE +/- 1.26, N = 1246.6846.8944.81MIN: 37.34 / MAX: 524.93MIN: 37.8 / MAX: 531.21MIN: 37.3 / MAX: 531.471. (CXX) g++ options: -O3 -rdynamic -lgomp -lpthread

OpenBenchmarking.orgms, Fewer Is BetterNCNN 20201218Target: CPU - Model: regnety_400mRun 1Run 2Run 3306090120150SE +/- 1.56, N = 12SE +/- 2.16, N = 12SE +/- 1.61, N = 12117.02119.23118.48MIN: 109.2 / MAX: 1631.71MIN: 109.72 / MAX: 3748.32MIN: 109.05 / MAX: 2000.571. (CXX) g++ options: -O3 -rdynamic -lgomp -lpthread

oneDNN

This is a test of the Intel oneDNN as an Intel-optimized library for Deep Neural Networks and making use of its built-in benchdnn functionality. The result is the total perf time reported. Intel oneDNN was formerly known as DNNL (Deep Neural Network Library) and MKL-DNN before being rebranded as part of the Intel oneAPI initiative. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgms, Fewer Is BetteroneDNN 2.0Harness: IP Shapes 1D - Data Type: f32 - Engine: CPURun 1Run 2Run 31.20322.40643.60964.81286.016SE +/- 0.52810, N = 15SE +/- 0.07284, N = 15SE +/- 0.13685, N = 125.347714.491484.33519MIN: 2.82MIN: 2.85MIN: 2.851. (CXX) g++ options: -O3 -std=c++11 -fopenmp -msse4.1 -fPIC -pie -lpthread

OpenBenchmarking.orgms, Fewer Is BetteroneDNN 2.0Harness: IP Shapes 3D - Data Type: f32 - Engine: CPURun 1Run 2Run 33691215SE +/- 0.32, N = 15SE +/- 0.25, N = 15SE +/- 0.23, N = 1512.4211.7712.09MIN: 3.03MIN: 3.13MIN: 3.141. (CXX) g++ options: -O3 -std=c++11 -fopenmp -msse4.1 -fPIC -pie -lpthread

OpenBenchmarking.orgms, Fewer Is BetteroneDNN 2.0Harness: IP Shapes 1D - Data Type: u8s8f32 - Engine: CPURun 1Run 2Run 30.60411.20821.81232.41643.0205SE +/- 0.01516, N = 3SE +/- 0.00743, N = 3SE +/- 0.00279, N = 32.679372.685112.66509MIN: 2.56MIN: 2.55MIN: 2.551. (CXX) g++ options: -O3 -std=c++11 -fopenmp -msse4.1 -fPIC -pie -lpthread

OpenBenchmarking.orgms, Fewer Is BetteroneDNN 2.0Harness: IP Shapes 3D - Data Type: u8s8f32 - Engine: CPURun 1Run 2Run 30.80361.60722.41083.21444.018SE +/- 0.01645, N = 3SE +/- 0.02517, N = 3SE +/- 0.00955, N = 33.565113.559703.57153MIN: 1.9MIN: 1.89MIN: 1.891. (CXX) g++ options: -O3 -std=c++11 -fopenmp -msse4.1 -fPIC -pie -lpthread

OpenBenchmarking.orgms, Fewer Is BetteroneDNN 2.0Harness: Convolution Batch Shapes Auto - Data Type: f32 - Engine: CPURun 1Run 2Run 3510152025SE +/- 0.19, N = 3SE +/- 0.29, N = 3SE +/- 0.25, N = 318.5118.6818.66MIN: 17.06MIN: 17.2MIN: 17.141. (CXX) g++ options: -O3 -std=c++11 -fopenmp -msse4.1 -fPIC -pie -lpthread

OpenBenchmarking.orgms, Fewer Is BetteroneDNN 2.0Harness: Deconvolution Batch shapes_1d - Data Type: f32 - Engine: CPURun 1Run 2Run 30.90741.81482.72223.62964.537SE +/- 0.02609, N = 3SE +/- 0.02054, N = 3SE +/- 0.03270, N = 34.032814.007134.01827MIN: 3.67MIN: 3.65MIN: 3.671. (CXX) g++ options: -O3 -std=c++11 -fopenmp -msse4.1 -fPIC -pie -lpthread

OpenBenchmarking.orgms, Fewer Is BetteroneDNN 2.0Harness: Deconvolution Batch shapes_3d - Data Type: f32 - Engine: CPURun 1Run 2Run 33691215SE +/- 0.10760, N = 15SE +/- 0.11235, N = 3SE +/- 0.11809, N = 159.044399.038939.08767MIN: 6.91MIN: 6.98MIN: 6.991. (CXX) g++ options: -O3 -std=c++11 -fopenmp -msse4.1 -fPIC -pie -lpthread

OpenBenchmarking.orgms, Fewer Is BetteroneDNN 2.0Harness: Convolution Batch Shapes Auto - Data Type: u8s8f32 - Engine: CPURun 1Run 2Run 3612182430SE +/- 0.12, N = 3SE +/- 0.45, N = 12SE +/- 0.12, N = 323.3022.4623.21MIN: 21.63MIN: 11.33MIN: 20.941. (CXX) g++ options: -O3 -std=c++11 -fopenmp -msse4.1 -fPIC -pie -lpthread

OpenBenchmarking.orgms, Fewer Is BetteroneDNN 2.0Harness: Deconvolution Batch shapes_1d - Data Type: u8s8f32 - Engine: CPURun 1Run 2Run 31.06082.12163.18244.24325.304SE +/- 0.17305, N = 15SE +/- 0.12692, N = 15SE +/- 0.04344, N = 34.602484.714734.22841MIN: 3.92MIN: 3.93MIN: 3.961. (CXX) g++ options: -O3 -std=c++11 -fopenmp -msse4.1 -fPIC -pie -lpthread

OpenBenchmarking.orgms, Fewer Is BetteroneDNN 2.0Harness: Deconvolution Batch shapes_3d - Data Type: u8s8f32 - Engine: CPURun 1Run 2Run 30.9931.9862.9793.9724.965SE +/- 0.05240, N = 6SE +/- 0.06219, N = 3SE +/- 0.06103, N = 44.413144.370974.40049MIN: 4.07MIN: 4.07MIN: 4.061. (CXX) g++ options: -O3 -std=c++11 -fopenmp -msse4.1 -fPIC -pie -lpthread

OpenBenchmarking.orgms, Fewer Is BetteroneDNN 2.0Harness: Recurrent Neural Network Training - Data Type: f32 - Engine: CPURun 1Run 2Run 32K4K6K8K10KSE +/- 164.15, N = 12SE +/- 128.18, N = 12SE +/- 184.49, N = 1310732.7310747.5010314.22MIN: 8370.79MIN: 9600.6MIN: 7551.611. (CXX) g++ options: -O3 -std=c++11 -fopenmp -msse4.1 -fPIC -pie -lpthread

OpenBenchmarking.orgms, Fewer Is BetteroneDNN 2.0Harness: Recurrent Neural Network Inference - Data Type: f32 - Engine: CPURun 1Run 2Run 37001400210028003500SE +/- 45.21, N = 15SE +/- 38.80, N = 15SE +/- 11.78, N = 33293.493322.683393.82MIN: 2548MIN: 2956.39MIN: 3348.851. (CXX) g++ options: -O3 -std=c++11 -fopenmp -msse4.1 -fPIC -pie -lpthread

OpenBenchmarking.orgms, Fewer Is BetteroneDNN 2.0Harness: Recurrent Neural Network Training - Data Type: u8s8f32 - Engine: CPURun 1Run 2Run 32K4K6K8K10KSE +/- 206.22, N = 10SE +/- 204.17, N = 12SE +/- 330.55, N = 1210583.1010647.6010812.54MIN: 9226.33MIN: 8942.86MIN: 8507.261. (CXX) g++ options: -O3 -std=c++11 -fopenmp -msse4.1 -fPIC -pie -lpthread

OpenBenchmarking.orgms, Fewer Is BetteroneDNN 2.0Harness: Recurrent Neural Network Inference - Data Type: u8s8f32 - Engine: CPURun 1Run 2Run 37001400210028003500SE +/- 44.01, N = 15SE +/- 41.23, N = 6SE +/- 46.22, N = 153300.073434.143327.91MIN: 2751.78MIN: 3003.06MIN: 2885.531. (CXX) g++ options: -O3 -std=c++11 -fopenmp -msse4.1 -fPIC -pie -lpthread

OpenBenchmarking.orgms, Fewer Is BetteroneDNN 2.0Harness: Matrix Multiply Batch Shapes Transformer - Data Type: f32 - Engine: CPURun 1Run 2Run 30.39160.78321.17481.56641.958SE +/- 0.06136, N = 15SE +/- 0.05674, N = 12SE +/- 0.06598, N = 151.712201.740561.66512MIN: 1.12MIN: 1.11MIN: 0.981. (CXX) g++ options: -O3 -std=c++11 -fopenmp -msse4.1 -fPIC -pie -lpthread

OpenBenchmarking.orgms, Fewer Is BetteroneDNN 2.0Harness: Recurrent Neural Network Training - Data Type: bf16bf16bf16 - Engine: CPURun 1Run 2Run 32K4K6K8K10KSE +/- 258.76, N = 9SE +/- 182.83, N = 12SE +/- 137.39, N = 410689.1610915.6511077.90MIN: 9144.24MIN: 8687.22MIN: 10188.81. (CXX) g++ options: -O3 -std=c++11 -fopenmp -msse4.1 -fPIC -pie -lpthread

OpenBenchmarking.orgms, Fewer Is BetteroneDNN 2.0Harness: Recurrent Neural Network Inference - Data Type: bf16bf16bf16 - Engine: CPURun 1Run 2Run 37001400210028003500SE +/- 31.60, N = 10SE +/- 58.86, N = 15SE +/- 51.82, N = 33332.793312.303405.82MIN: 2567.62MIN: 2572.81MIN: 3281.71. (CXX) g++ options: -O3 -std=c++11 -fopenmp -msse4.1 -fPIC -pie -lpthread

OpenBenchmarking.orgms, Fewer Is BetteroneDNN 2.0Harness: Matrix Multiply Batch Shapes Transformer - Data Type: u8s8f32 - Engine: CPURun 1Run 2Run 30.40360.80721.21081.61442.018SE +/- 0.01884, N = 3SE +/- 0.01534, N = 15SE +/- 0.01875, N = 31.788921.779531.79366MIN: 1.66MIN: 1.57MIN: 1.661. (CXX) g++ options: -O3 -std=c++11 -fopenmp -msse4.1 -fPIC -pie -lpthread

Coremark

This is a test of EEMBC CoreMark processor benchmark. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgIterations/Sec, More Is BetterCoremark 1.0CoreMark Size 666 - Iterations Per SecondRun 1Run 2Run 3200K400K600K800K1000KSE +/- 5683.14, N = 3SE +/- 1976.60, N = 3SE +/- 2175.03, N = 3879248.02879237.12876909.951. (CC) gcc options: -O2 -lrt" -lrt

Timed FFmpeg Compilation

This test times how long it takes to build the FFmpeg multimedia library. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgSeconds, Fewer Is BetterTimed FFmpeg Compilation 4.2.2Time To CompileRun 1Run 2Run 3918273645SE +/- 0.05, N = 3SE +/- 0.09, N = 3SE +/- 0.14, N = 339.0939.1139.19

Build2

This test profile measures the time to bootstrap/install the build2 C++ build toolchain from source. Build2 is a cross-platform build toolchain for C/C++ code and features Cargo-like features. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgSeconds, Fewer Is BetterBuild2 0.13Time To CompileRun 1Run 2Run 320406080100SE +/- 0.36, N = 3SE +/- 0.14, N = 3SE +/- 0.04, N = 3102.30102.59102.35

Timed Eigen Compilation

This test times how long it takes to build all Eigen examples. The Eigen examples are compiled serially. Eigen is a C++ template library for linear algebra. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgSeconds, Fewer Is BetterTimed Eigen Compilation 3.3.9Time To CompileRun 1Run 2Run 3306090120150SE +/- 0.02, N = 3SE +/- 0.02, N = 3SE +/- 0.17, N = 3120.02119.98120.19

SQLite Speedtest

This is a benchmark of SQLite's speedtest1 benchmark program with an increased problem size of 1,000. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgSeconds, Fewer Is BetterSQLite Speedtest 3.30Timed Time - Size 1,000Run 1Run 2Run 320406080100SE +/- 0.01, N = 3SE +/- 0.98, N = 3SE +/- 0.17, N = 390.1290.3290.111. (CC) gcc options: -O2 -ldl -lz -lpthread

Node.js V8 Web Tooling Benchmark

Running the V8 project's Web-Tooling-Benchmark under Node.js. The Web-Tooling-Benchmark stresses JavaScript-related workloads common to web developers like Babel and TypeScript and Babylon. This test profile can test the system's JavaScript performance with Node.js. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgruns/s, More Is BetterNode.js V8 Web Tooling BenchmarkRun 1Run 2Run 3246810SE +/- 0.08, N = 3SE +/- 0.01, N = 3SE +/- 0.04, N = 36.786.746.851. Nodejs v10.19.0

simdjson

This is a benchmark of SIMDJSON, a high performance JSON parser. SIMDJSON aims to be the fastest JSON parser and is used by projects like Microsoft FishStore, Yandex ClickHouse, Shopify, and others. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgGB/s, More Is Bettersimdjson 0.7.1Throughput Test: KostyaRun 1Run 2Run 30.07430.14860.22290.29720.3715SE +/- 0.00, N = 3SE +/- 0.00, N = 3SE +/- 0.00, N = 30.330.330.331. (CXX) g++ options: -O3 -pthread

OpenBenchmarking.orgGB/s, More Is Bettersimdjson 0.7.1Throughput Test: LargeRandomRun 1Run 2Run 30.0630.1260.1890.2520.315SE +/- 0.00, N = 3SE +/- 0.00, N = 3SE +/- 0.00, N = 30.280.280.281. (CXX) g++ options: -O3 -pthread

OpenBenchmarking.orgGB/s, More Is Bettersimdjson 0.7.1Throughput Test: PartialTweetsRun 1Run 2Run 30.0810.1620.2430.3240.405SE +/- 0.00, N = 3SE +/- 0.00, N = 3SE +/- 0.00, N = 30.360.360.361. (CXX) g++ options: -O3 -pthread

OpenBenchmarking.orgGB/s, More Is Bettersimdjson 0.7.1Throughput Test: DistinctUserIDRun 1Run 2Run 30.08330.16660.24990.33320.4165SE +/- 0.00, N = 3SE +/- 0.00, N = 3SE +/- 0.00, N = 30.370.370.371. (CXX) g++ options: -O3 -pthread