Xeon E3 1280 v5 m

Intel Xeon E3-1280 v5 testing with a MSI Z170A SLI PLUS (MS-7998) v1.0 (2.A0 BIOS) and ASUS AMD Radeon HD 7850 / R7 265 R9 270 1024SP 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 2103199-IB-XEONE312846
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Xeon E3 1280 v5 mProcessorMotherboardChipsetMemoryDiskGraphicsAudioMonitorNetworkOSKernelDesktopDisplay ServerOpenGLCompilerFile-SystemScreen Resolution123Intel Xeon E3-1280 v5 @ 4.00GHz (4 Cores / 8 Threads)MSI Z170A SLI PLUS (MS-7998) v1.0 (2.A0 BIOS)Intel Xeon E3-1200 v5/E3-150032GB256GB TOSHIBA RD400ASUS AMD Radeon HD 7850 / R7 265 R9 270 1024SPRealtek ALC1150VA2431Intel I219-VUbuntu 20.045.9.0-050900rc2daily20200826-generic (x86_64) 20200825GNOME Shell 3.36.4X Server 1.20.94.5 Mesa 20.0.8 (LLVM 10.0.0)GCC 9.3.0ext41920x1080OpenBenchmarking.orgKernel Details- Transparent Huge Pages: madviseCompiler 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: 0xe2 - Thermald 1.9.1 Python Details- Python 3.8.5Security Details- itlb_multihit: KVM: Mitigation of VMX disabled + l1tf: Mitigation of PTE Inversion; VMX: conditional cache flushes SMT vulnerable + mds: Mitigation of Clear buffers; SMT vulnerable + 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: conditional RSB filling + srbds: Mitigation of Microcode + tsx_async_abort: Mitigation of Clear buffers; SMT vulnerable

123Result OverviewPhoronix Test Suite100%100%100%101%Mobile Neural NetworkStockfishSysbenchoneDNNTimed Mesa CompilationXcompact3d Incompact3dsimdjsonAOM AV1SVT-HEVCASTC EncoderSVT-VP9Timed Node.js CompilationBasis Universal

Xeon E3 1280 v5 mincompact3d: input.i3d 129 Cells Per Directionincompact3d: input.i3d 193 Cells Per Directionsimdjson: Kostyasimdjson: LargeRandsimdjson: PartialTweetssimdjson: DistinctUserIDaom-av1: Speed 0 Two-Passaom-av1: Speed 4 Two-Passaom-av1: Speed 6 Realtimeaom-av1: Speed 6 Two-Passaom-av1: Speed 8 Realtimesvt-hevc: 1 - Bosphorus 1080psvt-hevc: 7 - Bosphorus 1080psvt-hevc: 10 - Bosphorus 1080psvt-vp9: VMAF Optimized - Bosphorus 1080psvt-vp9: PSNR/SSIM Optimized - Bosphorus 1080psvt-vp9: Visual Quality Optimized - Bosphorus 1080pbuild-mesa: Time To Compilebuild-nodejs: Time To Compileonednn: 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 - CPUastcenc: Mediumastcenc: Thoroughastcenc: Exhaustivebasis: ETC1Sbasis: UASTC Level 0basis: UASTC Level 2basis: UASTC Level 3mnn: SqueezeNetV1.0mnn: resnet-v2-50mnn: MobileNetV2_224mnn: mobilenet-v1-1.0mnn: inception-v3sysbench: RAM / Memorysysbench: CPUstockfish: Total Time12359.7731183203.0885112.360.883.523.990.163.7912.319.8762.443.0847.85101.8587.8588.0169.82126.2631106.5027.9894812.27533.657023.2894220.902014.455214.401020.49764.778718.075197395.553948.987393.223952.655.428177395.133955.375.917068.918033.0108256.213536.77411.00672.898144.1697.55045.7144.0334.57755.42516690.547854.281034384159.8612671202.9322152.360.883.533.980.163.7912.339.8662.543.0847.78101.8587.6688.0470.00126.1861106.6368.0129812.10133.661323.2809120.933314.401414.510820.52334.763448.101927399.683955.177401.563952.085.421017396.463954.965.906368.938032.9899256.091836.83510.99772.911144.0797.47945.3544.0114.54554.83516726.667845.281033853159.8264809203.1359912.360.883.523.980.163.8012.359.8462.453.0847.79101.9887.7488.0669.87126.3861106.6827.9786212.05873.659563.2039920.903114.429614.464120.51504.785768.084237394.303951.907396.593955.005.388177408.913957.845.907098.929633.0202256.171636.83910.99272.894144.0797.45845.2804.0014.53455.04216845.497843.3410254227OpenBenchmarking.org

Xcompact3d Incompact3d

Xcompact3d Incompact3d is a Fortran-MPI based, finite difference high-performance code for solving the incompressible Navier-Stokes equation and as many as you need scalar transport equations. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgSeconds, Fewer Is BetterXcompact3d Incompact3d 2021-03-11Input: input.i3d 129 Cells Per Direction3211326395265SE +/- 0.02, N = 3SE +/- 0.02, N = 3SE +/- 0.01, N = 359.8359.8659.771. (F9X) gfortran options: -cpp -O2 -funroll-loops -floop-optimize -fcray-pointer -fbacktrace -pthread -lmpi_usempif08 -lmpi_mpifh -lmpi

OpenBenchmarking.orgSeconds, Fewer Is BetterXcompact3d Incompact3d 2021-03-11Input: input.i3d 193 Cells Per Direction3214080120160200SE +/- 0.13, N = 3SE +/- 0.09, N = 3SE +/- 0.09, N = 3203.14202.93203.091. (F9X) gfortran options: -cpp -O2 -funroll-loops -floop-optimize -fcray-pointer -fbacktrace -pthread -lmpi_usempif08 -lmpi_mpifh -lmpi

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 0.8.2Throughput Test: Kostya3210.5311.0621.5932.1242.655SE +/- 0.00, N = 3SE +/- 0.00, N = 3SE +/- 0.00, N = 32.362.362.361. (CXX) g++ options: -O3 -pthread

OpenBenchmarking.orgGB/s, More Is Bettersimdjson 0.8.2Throughput Test: LargeRandom3210.1980.3960.5940.7920.99SE +/- 0.00, N = 3SE +/- 0.00, N = 3SE +/- 0.00, N = 30.880.880.881. (CXX) g++ options: -O3 -pthread

OpenBenchmarking.orgGB/s, More Is Bettersimdjson 0.8.2Throughput Test: PartialTweets3210.79431.58862.38293.17723.9715SE +/- 0.00, N = 3SE +/- 0.00, N = 3SE +/- 0.00, N = 33.523.533.521. (CXX) g++ options: -O3 -pthread

OpenBenchmarking.orgGB/s, More Is Bettersimdjson 0.8.2Throughput Test: DistinctUserID3210.89781.79562.69343.59124.489SE +/- 0.00, N = 3SE +/- 0.01, N = 3SE +/- 0.00, N = 33.983.983.991. (CXX) g++ options: -O3 -pthread

AOM AV1

This is a test of the AOMedia AV1 encoder (libaom) run on the CPU with a sample 1080p video file. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgFrames Per Second, More Is BetterAOM AV1 2.1-rcEncoder Mode: Speed 0 Two-Pass3210.0360.0720.1080.1440.18SE +/- 0.00, N = 8SE +/- 0.00, N = 3SE +/- 0.00, N = 30.160.160.161. (CXX) g++ options: -O3 -std=c++11 -U_FORTIFY_SOURCE -lm -lpthread

OpenBenchmarking.orgFrames Per Second, More Is BetterAOM AV1 2.1-rcEncoder Mode: Speed 4 Two-Pass3210.8551.712.5653.424.275SE +/- 0.00, N = 3SE +/- 0.01, N = 3SE +/- 0.00, N = 33.803.793.791. (CXX) g++ options: -O3 -std=c++11 -U_FORTIFY_SOURCE -lm -lpthread

OpenBenchmarking.orgFrames Per Second, More Is BetterAOM AV1 2.1-rcEncoder Mode: Speed 6 Realtime3213691215SE +/- 0.02, N = 3SE +/- 0.01, N = 3SE +/- 0.01, N = 312.3512.3312.311. (CXX) g++ options: -O3 -std=c++11 -U_FORTIFY_SOURCE -lm -lpthread

OpenBenchmarking.orgFrames Per Second, More Is BetterAOM AV1 2.1-rcEncoder Mode: Speed 6 Two-Pass3213691215SE +/- 0.01, N = 3SE +/- 0.00, N = 3SE +/- 0.01, N = 39.849.869.871. (CXX) g++ options: -O3 -std=c++11 -U_FORTIFY_SOURCE -lm -lpthread

OpenBenchmarking.orgFrames Per Second, More Is BetterAOM AV1 2.1-rcEncoder Mode: Speed 8 Realtime3211428425670SE +/- 0.08, N = 3SE +/- 0.14, N = 3SE +/- 0.16, N = 362.4562.5462.441. (CXX) g++ options: -O3 -std=c++11 -U_FORTIFY_SOURCE -lm -lpthread

SVT-HEVC

This is a test of the Intel Open Visual Cloud Scalable Video Technology SVT-HEVC CPU-based multi-threaded video encoder for the HEVC / H.265 video format with a sample 1080p YUV video file. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgFrames Per Second, More Is BetterSVT-HEVC 1.5.0Tuning: 1 - Input: Bosphorus 1080p3210.6931.3862.0792.7723.465SE +/- 0.00, N = 3SE +/- 0.00, N = 3SE +/- 0.00, N = 33.083.083.081. (CC) gcc options: -fPIE -fPIC -O3 -O2 -pie -rdynamic -lpthread -lrt

OpenBenchmarking.orgFrames Per Second, More Is BetterSVT-HEVC 1.5.0Tuning: 7 - Input: Bosphorus 1080p3211122334455SE +/- 0.08, N = 3SE +/- 0.02, N = 3SE +/- 0.03, N = 347.7947.7847.851. (CC) gcc options: -fPIE -fPIC -O3 -O2 -pie -rdynamic -lpthread -lrt

OpenBenchmarking.orgFrames Per Second, More Is BetterSVT-HEVC 1.5.0Tuning: 10 - Input: Bosphorus 1080p32120406080100SE +/- 0.10, N = 3SE +/- 0.10, N = 3SE +/- 0.14, N = 3101.98101.85101.851. (CC) gcc options: -fPIE -fPIC -O3 -O2 -pie -rdynamic -lpthread -lrt

SVT-VP9

This is a test of the Intel Open Visual Cloud Scalable Video Technology SVT-VP9 CPU-based multi-threaded video encoder for the VP9 video format with a sample YUV input video file. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgFrames Per Second, More Is BetterSVT-VP9 0.3Tuning: VMAF Optimized - Input: Bosphorus 1080p32120406080100SE +/- 0.04, N = 3SE +/- 0.11, N = 3SE +/- 0.10, N = 387.7487.6687.851. (CC) gcc options: -O3 -fcommon -fPIE -fPIC -fvisibility=hidden -pie -rdynamic -lpthread -lrt -lm

OpenBenchmarking.orgFrames Per Second, More Is BetterSVT-VP9 0.3Tuning: PSNR/SSIM Optimized - Input: Bosphorus 1080p32120406080100SE +/- 0.17, N = 3SE +/- 0.06, N = 3SE +/- 0.02, N = 388.0688.0488.011. (CC) gcc options: -O3 -fcommon -fPIE -fPIC -fvisibility=hidden -pie -rdynamic -lpthread -lrt -lm

OpenBenchmarking.orgFrames Per Second, More Is BetterSVT-VP9 0.3Tuning: Visual Quality Optimized - Input: Bosphorus 1080p3211632486480SE +/- 0.05, N = 3SE +/- 0.07, N = 3SE +/- 0.01, N = 369.8770.0069.821. (CC) gcc options: -O3 -fcommon -fPIE -fPIC -fvisibility=hidden -pie -rdynamic -lpthread -lrt -lm

Timed Mesa Compilation

This test profile times how long it takes to compile Mesa with Meson/Ninja. For minimizing build dependencies and avoid versioning conflicts, test this is just the core Mesa build without LLVM or the extra Gallium3D/Mesa drivers enabled. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgSeconds, Fewer Is BetterTimed Mesa Compilation 21.0Time To Compile321306090120150SE +/- 0.09, N = 3SE +/- 0.05, N = 3SE +/- 0.14, N = 3126.39126.19126.26

Timed Node.js Compilation

This test profile times how long it takes to build/compile Node.js itself from source. Node.js is a JavaScript run-time built from the Chrome V8 JavaScript engine while itself is written in C/C++. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgSeconds, Fewer Is BetterTimed Node.js Compilation 15.11Time To Compile3212004006008001000SE +/- 0.28, N = 3SE +/- 0.31, N = 3SE +/- 0.06, N = 31106.681106.641106.50

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 2.1.2Harness: IP Shapes 1D - Data Type: f32 - Engine: CPU321246810SE +/- 0.00688, N = 3SE +/- 0.02581, N = 3SE +/- 0.01467, N = 37.978628.012987.98948MIN: 7.79MIN: 7.85MIN: 7.811. (CXX) g++ options: -O3 -march=native -std=c++11 -fopenmp -msse4.1 -fPIC -pie -lpthread -ldl

OpenBenchmarking.orgms, Fewer Is BetteroneDNN 2.1.2Harness: IP Shapes 3D - Data Type: f32 - Engine: CPU3213691215SE +/- 0.01, N = 3SE +/- 0.02, N = 3SE +/- 0.01, N = 312.0612.1012.28MIN: 11.91MIN: 11.78MIN: 12.091. (CXX) g++ options: -O3 -march=native -std=c++11 -fopenmp -msse4.1 -fPIC -pie -lpthread -ldl

OpenBenchmarking.orgms, Fewer Is BetteroneDNN 2.1.2Harness: IP Shapes 1D - Data Type: u8s8f32 - Engine: CPU3210.82381.64762.47143.29524.119SE +/- 0.00493, N = 3SE +/- 0.00209, N = 3SE +/- 0.00650, N = 33.659563.661323.65702MIN: 3.62MIN: 3.61MIN: 3.611. (CXX) g++ options: -O3 -march=native -std=c++11 -fopenmp -msse4.1 -fPIC -pie -lpthread -ldl

OpenBenchmarking.orgms, Fewer Is BetteroneDNN 2.1.2Harness: IP Shapes 3D - Data Type: u8s8f32 - Engine: CPU3210.74011.48022.22032.96043.7005SE +/- 0.00597, N = 3SE +/- 0.01431, N = 3SE +/- 0.00631, N = 33.203993.280913.28942MIN: 3.13MIN: 3.2MIN: 3.221. (CXX) g++ options: -O3 -march=native -std=c++11 -fopenmp -msse4.1 -fPIC -pie -lpthread -ldl

OpenBenchmarking.orgms, Fewer Is BetteroneDNN 2.1.2Harness: Convolution Batch Shapes Auto - Data Type: f32 - Engine: CPU321510152025SE +/- 0.01, N = 3SE +/- 0.04, N = 3SE +/- 0.01, N = 320.9020.9320.90MIN: 20.81MIN: 20.82MIN: 20.841. (CXX) g++ options: -O3 -march=native -std=c++11 -fopenmp -msse4.1 -fPIC -pie -lpthread -ldl

OpenBenchmarking.orgms, Fewer Is BetteroneDNN 2.1.2Harness: Deconvolution Batch shapes_1d - Data Type: f32 - Engine: CPU32148121620SE +/- 0.02, N = 3SE +/- 0.05, N = 3SE +/- 0.04, N = 314.4314.4014.46MIN: 10.61MIN: 10.62MIN: 10.631. (CXX) g++ options: -O3 -march=native -std=c++11 -fopenmp -msse4.1 -fPIC -pie -lpthread -ldl

OpenBenchmarking.orgms, Fewer Is BetteroneDNN 2.1.2Harness: Deconvolution Batch shapes_3d - Data Type: f32 - Engine: CPU32148121620SE +/- 0.02, N = 3SE +/- 0.03, N = 3SE +/- 0.02, N = 314.4614.5114.40MIN: 14.29MIN: 14.31MIN: 14.251. (CXX) g++ options: -O3 -march=native -std=c++11 -fopenmp -msse4.1 -fPIC -pie -lpthread -ldl

OpenBenchmarking.orgms, Fewer Is BetteroneDNN 2.1.2Harness: Convolution Batch Shapes Auto - Data Type: u8s8f32 - Engine: CPU321510152025SE +/- 0.02, N = 3SE +/- 0.02, N = 3SE +/- 0.01, N = 320.5220.5220.50MIN: 20.32MIN: 20.29MIN: 20.321. (CXX) g++ options: -O3 -march=native -std=c++11 -fopenmp -msse4.1 -fPIC -pie -lpthread -ldl

OpenBenchmarking.orgms, Fewer Is BetteroneDNN 2.1.2Harness: Deconvolution Batch shapes_1d - Data Type: u8s8f32 - Engine: CPU3211.07682.15363.23044.30725.384SE +/- 0.01370, N = 3SE +/- 0.00463, N = 3SE +/- 0.01143, N = 34.785764.763444.77871MIN: 4.73MIN: 4.73MIN: 4.731. (CXX) g++ options: -O3 -march=native -std=c++11 -fopenmp -msse4.1 -fPIC -pie -lpthread -ldl

OpenBenchmarking.orgms, Fewer Is BetteroneDNN 2.1.2Harness: Deconvolution Batch shapes_3d - Data Type: u8s8f32 - Engine: CPU321246810SE +/- 0.01391, N = 3SE +/- 0.01834, N = 3SE +/- 0.01132, N = 38.084238.101928.07519MIN: 8.03MIN: 8.04MIN: 8.011. (CXX) g++ options: -O3 -march=native -std=c++11 -fopenmp -msse4.1 -fPIC -pie -lpthread -ldl

OpenBenchmarking.orgms, Fewer Is BetteroneDNN 2.1.2Harness: Recurrent Neural Network Training - Data Type: f32 - Engine: CPU32116003200480064008000SE +/- 2.94, N = 3SE +/- 4.06, N = 3SE +/- 4.38, N = 37394.307399.687395.55MIN: 7382.12MIN: 7381.45MIN: 7383.321. (CXX) g++ options: -O3 -march=native -std=c++11 -fopenmp -msse4.1 -fPIC -pie -lpthread -ldl

OpenBenchmarking.orgms, Fewer Is BetteroneDNN 2.1.2Harness: Recurrent Neural Network Inference - Data Type: f32 - Engine: CPU3218001600240032004000SE +/- 1.51, N = 3SE +/- 7.15, N = 3SE +/- 1.93, N = 33951.903955.173948.98MIN: 3944.83MIN: 3940.03MIN: 3941.231. (CXX) g++ options: -O3 -march=native -std=c++11 -fopenmp -msse4.1 -fPIC -pie -lpthread -ldl

OpenBenchmarking.orgms, Fewer Is BetteroneDNN 2.1.2Harness: Recurrent Neural Network Training - Data Type: u8s8f32 - Engine: CPU32116003200480064008000SE +/- 3.85, N = 3SE +/- 2.46, N = 3SE +/- 1.70, N = 37396.597401.567393.22MIN: 7381.63MIN: 7389.32MIN: 7380.821. (CXX) g++ options: -O3 -march=native -std=c++11 -fopenmp -msse4.1 -fPIC -pie -lpthread -ldl

OpenBenchmarking.orgms, Fewer Is BetteroneDNN 2.1.2Harness: Recurrent Neural Network Inference - Data Type: u8s8f32 - Engine: CPU3218001600240032004000SE +/- 2.54, N = 3SE +/- 2.76, N = 3SE +/- 2.90, N = 33955.003952.083952.65MIN: 3946.66MIN: 3941.26MIN: 3942.221. (CXX) g++ options: -O3 -march=native -std=c++11 -fopenmp -msse4.1 -fPIC -pie -lpthread -ldl

OpenBenchmarking.orgms, Fewer Is BetteroneDNN 2.1.2Harness: Matrix Multiply Batch Shapes Transformer - Data Type: f32 - Engine: CPU3211.22132.44263.66394.88526.1065SE +/- 0.00691, N = 3SE +/- 0.00660, N = 3SE +/- 0.00412, N = 35.388175.421015.42817MIN: 5.33MIN: 5.36MIN: 5.361. (CXX) g++ options: -O3 -march=native -std=c++11 -fopenmp -msse4.1 -fPIC -pie -lpthread -ldl

OpenBenchmarking.orgms, Fewer Is BetteroneDNN 2.1.2Harness: Recurrent Neural Network Training - Data Type: bf16bf16bf16 - Engine: CPU32116003200480064008000SE +/- 15.57, N = 3SE +/- 5.16, N = 3SE +/- 2.52, N = 37408.917396.467395.13MIN: 7383.82MIN: 7381.2MIN: 7381.081. (CXX) g++ options: -O3 -march=native -std=c++11 -fopenmp -msse4.1 -fPIC -pie -lpthread -ldl

OpenBenchmarking.orgms, Fewer Is BetteroneDNN 2.1.2Harness: Recurrent Neural Network Inference - Data Type: bf16bf16bf16 - Engine: CPU3218001600240032004000SE +/- 4.66, N = 3SE +/- 0.47, N = 3SE +/- 2.53, N = 33957.843954.963955.37MIN: 3944.06MIN: 3947.75MIN: 3945.551. (CXX) g++ options: -O3 -march=native -std=c++11 -fopenmp -msse4.1 -fPIC -pie -lpthread -ldl

OpenBenchmarking.orgms, Fewer Is BetteroneDNN 2.1.2Harness: Matrix Multiply Batch Shapes Transformer - Data Type: u8s8f32 - Engine: CPU3211.33132.66263.99395.32526.6565SE +/- 0.00186, N = 3SE +/- 0.00128, N = 3SE +/- 0.00433, N = 35.907095.906365.91706MIN: 5.87MIN: 5.87MIN: 5.871. (CXX) g++ options: -O3 -march=native -std=c++11 -fopenmp -msse4.1 -fPIC -pie -lpthread -ldl

ASTC Encoder

ASTC Encoder (astcenc) is for the Adaptive Scalable Texture Compression (ASTC) format commonly used with OpenGL, OpenGL ES, and Vulkan graphics APIs. This test profile does a coding test of both compression/decompression. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgSeconds, Fewer Is BetterASTC Encoder 2.4Preset: Medium321246810SE +/- 0.0096, N = 3SE +/- 0.0040, N = 3SE +/- 0.0175, N = 38.92968.93808.91801. (CXX) g++ options: -O3 -flto -pthread

OpenBenchmarking.orgSeconds, Fewer Is BetterASTC Encoder 2.4Preset: Thorough321816243240SE +/- 0.01, N = 3SE +/- 0.01, N = 3SE +/- 0.01, N = 333.0232.9933.011. (CXX) g++ options: -O3 -flto -pthread

OpenBenchmarking.orgSeconds, Fewer Is BetterASTC Encoder 2.4Preset: Exhaustive32160120180240300SE +/- 0.05, N = 3SE +/- 0.00, N = 3SE +/- 0.05, N = 3256.17256.09256.211. (CXX) g++ options: -O3 -flto -pthread

Basis Universal

Basis Universal is a GPU texture codec. This test times how long it takes to convert sRGB PNGs into Basis Univeral assets with various settings. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgSeconds, Fewer Is BetterBasis Universal 1.13Settings: ETC1S321816243240SE +/- 0.04, N = 3SE +/- 0.05, N = 3SE +/- 0.03, N = 336.8436.8436.771. (CXX) g++ options: -std=c++11 -fvisibility=hidden -fPIC -fno-strict-aliasing -O3 -rdynamic -lm -lpthread

OpenBenchmarking.orgSeconds, Fewer Is BetterBasis Universal 1.13Settings: UASTC Level 03213691215SE +/- 0.01, N = 3SE +/- 0.01, N = 3SE +/- 0.02, N = 310.9911.0011.011. (CXX) g++ options: -std=c++11 -fvisibility=hidden -fPIC -fno-strict-aliasing -O3 -rdynamic -lm -lpthread

OpenBenchmarking.orgSeconds, Fewer Is BetterBasis Universal 1.13Settings: UASTC Level 23211632486480SE +/- 0.01, N = 3SE +/- 0.00, N = 3SE +/- 0.02, N = 372.8972.9172.901. (CXX) g++ options: -std=c++11 -fvisibility=hidden -fPIC -fno-strict-aliasing -O3 -rdynamic -lm -lpthread

OpenBenchmarking.orgSeconds, Fewer Is BetterBasis Universal 1.13Settings: UASTC Level 3321306090120150SE +/- 0.02, N = 3SE +/- 0.00, N = 3SE +/- 0.02, N = 3144.08144.08144.171. (CXX) g++ options: -std=c++11 -fvisibility=hidden -fPIC -fno-strict-aliasing -O3 -rdynamic -lm -lpthread

Mobile Neural Network

MNN is the Mobile Neural Network as a highly efficient, lightweight deep learning framework developed by Alibaba. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgms, Fewer Is BetterMobile Neural Network 1.1.3Model: SqueezeNetV1.0321246810SE +/- 0.011, N = 3SE +/- 0.012, N = 3SE +/- 0.015, N = 37.4587.4797.550MIN: 7.38 / MAX: 29.38MIN: 7.4 / MAX: 11.93MIN: 7.38 / MAX: 30.781. (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

OpenBenchmarking.orgms, Fewer Is BetterMobile Neural Network 1.1.3Model: resnet-v2-503211020304050SE +/- 0.14, N = 3SE +/- 0.09, N = 3SE +/- 0.15, N = 345.2845.3545.71MIN: 44.97 / MAX: 67.28MIN: 45.03 / MAX: 69.72MIN: 44.4 / MAX: 74.551. (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

OpenBenchmarking.orgms, Fewer Is BetterMobile Neural Network 1.1.3Model: MobileNetV2_2243210.90741.81482.72223.62964.537SE +/- 0.018, N = 3SE +/- 0.012, N = 3SE +/- 0.014, N = 34.0014.0114.033MIN: 3.91 / MAX: 27.34MIN: 3.92 / MAX: 27.37MIN: 3.94 / MAX: 25.541. (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

OpenBenchmarking.orgms, Fewer Is BetterMobile Neural Network 1.1.3Model: mobilenet-v1-1.03211.02982.05963.08944.11925.149SE +/- 0.005, N = 3SE +/- 0.006, N = 3SE +/- 0.013, N = 34.5344.5454.577MIN: 4.49 / MAX: 8.91MIN: 4.48 / MAX: 28.03MIN: 4.48 / MAX: 26.261. (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

OpenBenchmarking.orgms, Fewer Is BetterMobile Neural Network 1.1.3Model: inception-v33211224364860SE +/- 0.56, N = 3SE +/- 0.49, N = 3SE +/- 0.21, N = 355.0454.8455.43MIN: 53.69 / MAX: 79.04MIN: 53.62 / MAX: 78.53MIN: 54.13 / MAX: 79.11. (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

Sysbench

This is a benchmark of Sysbench with the built-in CPU and memory sub-tests. Sysbench is a scriptable multi-threaded benchmark tool based on LuaJIT. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgMiB/sec, More Is BetterSysbench 1.0.20Test: RAM / Memory3214K8K12K16K20KSE +/- 83.93, N = 3SE +/- 70.80, N = 3SE +/- 100.94, N = 316845.4916726.6616690.541. (CC) gcc options: -pthread -O2 -funroll-loops -rdynamic -ldl -laio -lm

OpenBenchmarking.orgEvents Per Second, More Is BetterSysbench 1.0.20Test: CPU3212K4K6K8K10KSE +/- 0.29, N = 3SE +/- 0.62, N = 3SE +/- 0.37, N = 37843.347845.287854.281. (CC) gcc options: -pthread -O2 -funroll-loops -rdynamic -ldl -laio -lm

Stockfish

This is a test of Stockfish, an advanced open-source C++11 chess benchmark that can scale up to 512 CPU threads. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgNodes Per Second, More Is BetterStockfish 13Total Time3212M4M6M8M10MSE +/- 48708.15, N = 3SE +/- 5126.49, N = 3SE +/- 62662.98, N = 31025422710338531103438411. (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

52 Results Shown

Xcompact3d Incompact3d:
  input.i3d 129 Cells Per Direction
  input.i3d 193 Cells Per Direction
simdjson:
  Kostya
  LargeRand
  PartialTweets
  DistinctUserID
AOM AV1:
  Speed 0 Two-Pass
  Speed 4 Two-Pass
  Speed 6 Realtime
  Speed 6 Two-Pass
  Speed 8 Realtime
SVT-HEVC:
  1 - Bosphorus 1080p
  7 - Bosphorus 1080p
  10 - Bosphorus 1080p
SVT-VP9:
  VMAF Optimized - Bosphorus 1080p
  PSNR/SSIM Optimized - Bosphorus 1080p
  Visual Quality Optimized - Bosphorus 1080p
Timed Mesa Compilation
Timed Node.js Compilation
oneDNN:
  IP Shapes 1D - f32 - CPU
  IP Shapes 3D - f32 - CPU
  IP Shapes 1D - u8s8f32 - CPU
  IP Shapes 3D - u8s8f32 - CPU
  Convolution Batch Shapes Auto - f32 - CPU
  Deconvolution Batch shapes_1d - f32 - CPU
  Deconvolution Batch shapes_3d - f32 - CPU
  Convolution Batch Shapes Auto - u8s8f32 - CPU
  Deconvolution Batch shapes_1d - u8s8f32 - CPU
  Deconvolution Batch shapes_3d - u8s8f32 - CPU
  Recurrent Neural Network Training - f32 - CPU
  Recurrent Neural Network Inference - f32 - CPU
  Recurrent Neural Network Training - u8s8f32 - CPU
  Recurrent Neural Network Inference - u8s8f32 - CPU
  Matrix Multiply Batch Shapes Transformer - f32 - CPU
  Recurrent Neural Network Training - bf16bf16bf16 - CPU
  Recurrent Neural Network Inference - bf16bf16bf16 - CPU
  Matrix Multiply Batch Shapes Transformer - u8s8f32 - CPU
ASTC Encoder:
  Medium
  Thorough
  Exhaustive
Basis Universal:
  ETC1S
  UASTC Level 0
  UASTC Level 2
  UASTC Level 3
Mobile Neural Network:
  SqueezeNetV1.0
  resnet-v2-50
  MobileNetV2_224
  mobilenet-v1-1.0
  inception-v3
Sysbench:
  RAM / Memory
  CPU
Stockfish