7950x3d

AMD Ryzen 9 7950X3D 16-Core testing with a ASRockRack B650D4U-2L2T/BCM (2.09 BIOS) and ASPEED 512MB on Ubuntu 22.04 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 2311220-NE-7950X3D3814
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November 21 2023
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November 21 2023
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November 22 2023
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7950x3dOpenBenchmarking.orgPhoronix Test SuiteAMD Ryzen 9 7950X3D 16-Core @ 5.76GHz (16 Cores / 32 Threads)ASRockRack B650D4U-2L2T/BCM (2.09 BIOS)AMD Device 14d82 x 32 GB DDR5-4800MT/s MTC20C2085S1EC48BA13201GB Micron_7450_MTFDKCC3T2TFS + 0GB Virtual HDisk0 + 0GB Virtual HDisk1 + 0GB Virtual HDisk2 + 0GB Virtual HDisk3ASPEED 512MBAMD Device 1640VA24312 x Intel I210 + 2 x Broadcom BCM57416 NetXtreme-E Dual-Media 10G RDMAUbuntu 22.046.6.0-rc4-phx-amd-pref-core (x86_64)GNOME Shell 42.9X Server1.3.238GCC 11.4.0ext41920x1200ProcessorMotherboardChipsetMemoryDiskGraphicsAudioMonitorNetworkOSKernelDesktopDisplay ServerVulkanCompilerFile-SystemScreen Resolution7950x3d BenchmarksSystem Logs- Transparent Huge Pages: madvise- --build=x86_64-linux-gnu --disable-vtable-verify --disable-werror --enable-bootstrap --enable-cet --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++,m2 --enable-libphobos-checking=release --enable-libstdcxx-debug --enable-libstdcxx-time=yes --enable-link-serialization=2 --enable-multiarch --enable-multilib --enable-nls --enable-objc-gc=auto --enable-offload-targets=nvptx-none=/build/gcc-11-XeT9lY/gcc-11-11.4.0/debian/tmp-nvptx/usr,amdgcn-amdhsa=/build/gcc-11-XeT9lY/gcc-11-11.4.0/debian/tmp-gcn/usr --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-build-config=bootstrap-lto-lean --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: amd-pstate-epp performance (EPP: performance) - CPU Microcode: 0xa601203- OpenJDK Runtime Environment (build 11.0.20+8-post-Ubuntu-1ubuntu122.04)- Python 3.10.12- gather_data_sampling: Not affected + itlb_multihit: Not affected + l1tf: Not affected + mds: Not affected + meltdown: Not affected + mmio_stale_data: Not affected + retbleed: Not affected + spec_rstack_overflow: Mitigation of safe RET no microcode + spec_store_bypass: Mitigation of SSB disabled via prctl + spectre_v1: Mitigation of usercopy/swapgs barriers and __user pointer sanitization + spectre_v2: Mitigation of Enhanced / Automatic IBRS IBPB: conditional STIBP: always-on RSB filling PBRSB-eIBRS: Not affected + srbds: Not affected + tsx_async_abort: Not affected

abcdResult OverviewPhoronix Test Suite100%101%101%102%102%easyWaveTimed Gem5 CompilationWebP2 Image EncodePyTorchQuantLibQMCPACKTimed FFmpeg CompilationoneDNNCpuminer-OptFFmpegCloverLeafOpenVKLEmbreeOpenSSLOpenVINODaCapo BenchmarkIntel Open Image DenoiseOSPRay Studio

7950x3dquantlib: Multi-Threadedquantlib: Single-Threadedcloverleaf: clover_bmcloverleaf: clover_bm16cloverleaf: clover_bm64_shortqmcpack: H4_aeqmcpack: Li2_STO_aeqmcpack: LiH_ae_MSDqmcpack: simple-H2Oqmcpack: O_ae_pyscf_UHFqmcpack: FeCO6_b3lyp_gmsffmpeg: libx264 - Liveffmpeg: libx265 - Liveffmpeg: libx264 - Uploadffmpeg: libx265 - Uploadffmpeg: libx264 - Platformffmpeg: libx265 - Platformffmpeg: libx264 - Video On Demandffmpeg: libx265 - Video On Demanddacapobench: Jythondacapobench: Eclipsedacapobench: GraphChidacapobench: Tradesoapdacapobench: Tradebeansdacapobench: Spring Bootdacapobench: Apache Kafkadacapobench: Apache Tomcatdacapobench: jMonkeyEnginedacapobench: Apache Cassandradacapobench: Apache Xalan XSLTdacapobench: Batik SVG Toolkitdacapobench: H2 Database Enginedacapobench: FOP Print Formatterdacapobench: PMD Source Code Analyzerdacapobench: Apache Lucene Search Indexdacapobench: Apache Lucene Search Enginedacapobench: Avrora AVR Simulation Frameworkdacapobench: BioJava Biological Data Frameworkdacapobench: Zxing 1D/2D Barcode Image Processingdacapobench: H2O In-Memory Platform For Machine Learningwebp2: Defaultwebp2: Quality 75, Compression Effort 7webp2: Quality 95, Compression Effort 7webp2: Quality 100, Compression Effort 5webp2: Quality 100, Lossless Compressioneasywave: e2Asean Grid + BengkuluSept2007 Source - 240easywave: e2Asean Grid + BengkuluSept2007 Source - 1200embree: Pathtracer - Crownembree: Pathtracer ISPC - Crownembree: Pathtracer - Asian Dragonembree: Pathtracer - Asian Dragon Objembree: Pathtracer ISPC - Asian Dragonembree: Pathtracer ISPC - Asian Dragon Objoidn: RT.hdr_alb_nrm.3840x2160 - CPU-Onlyoidn: RT.ldr_alb_nrm.3840x2160 - CPU-Onlyoidn: RTLightmap.hdr.4096x4096 - CPU-Onlyopenvkl: vklBenchmarkCPU ISPCopenvkl: vklBenchmarkCPU Scalarbuild-ffmpeg: Time To Compilebuild-gem5: Time To Compileonednn: IP Shapes 1D - f32 - CPUonednn: IP Shapes 3D - f32 - CPUonednn: IP Shapes 1D - u8s8f32 - CPUonednn: IP Shapes 3D - u8s8f32 - CPUonednn: IP Shapes 1D - bf16bf16bf16 - CPUonednn: IP Shapes 3D - bf16bf16bf16 - 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: Convolution Batch Shapes Auto - bf16bf16bf16 - CPUonednn: Deconvolution Batch shapes_1d - bf16bf16bf16 - CPUonednn: Deconvolution Batch shapes_3d - bf16bf16bf16 - CPUonednn: Recurrent Neural Network Inference - u8s8f32 - CPUonednn: Recurrent Neural Network Training - bf16bf16bf16 - CPUonednn: Recurrent Neural Network Inference - bf16bf16bf16 - CPUospray-studio: 1 - 4K - 1 - Path Tracer - CPUospray-studio: 2 - 4K - 1 - Path Tracer - CPUospray-studio: 3 - 4K - 1 - Path Tracer - CPUospray-studio: 1 - 4K - 16 - Path Tracer - CPUospray-studio: 1 - 4K - 32 - Path Tracer - CPUospray-studio: 2 - 4K - 16 - Path Tracer - CPUospray-studio: 2 - 4K - 32 - Path Tracer - CPUospray-studio: 3 - 4K - 16 - Path Tracer - CPUospray-studio: 3 - 4K - 32 - Path Tracer - CPUospray-studio: 1 - 1080p - 1 - Path Tracer - CPUospray-studio: 2 - 1080p - 1 - Path Tracer - CPUospray-studio: 3 - 1080p - 1 - Path Tracer - CPUospray-studio: 1 - 1080p - 16 - Path Tracer - CPUospray-studio: 1 - 1080p - 32 - Path Tracer - CPUospray-studio: 2 - 1080p - 16 - Path Tracer - CPUospray-studio: 2 - 1080p - 32 - Path Tracer - CPUospray-studio: 3 - 1080p - 16 - Path Tracer - CPUospray-studio: 3 - 1080p - 32 - Path Tracer - CPUcpuminer-opt: Magicpuminer-opt: scryptcpuminer-opt: Deepcoincpuminer-opt: Ringcoincpuminer-opt: Blake-2 Scpuminer-opt: Garlicoincpuminer-opt: Skeincoincpuminer-opt: Myriad-Groestlcpuminer-opt: LBC, LBRY Creditscpuminer-opt: Quad SHA-256, Pyritecpuminer-opt: Triple SHA-256, Onecoinopenssl: SHA256openssl: SHA512openssl: RSA4096openssl: RSA4096openssl: ChaCha20openssl: AES-128-GCMopenssl: AES-256-GCMopenssl: ChaCha20-Poly1305pytorch: CPU - 1 - ResNet-50pytorch: CPU - 1 - ResNet-152pytorch: CPU - 16 - ResNet-50pytorch: CPU - 32 - ResNet-50pytorch: CPU - 64 - ResNet-50pytorch: CPU - 16 - ResNet-152pytorch: CPU - 256 - ResNet-50pytorch: CPU - 32 - ResNet-152pytorch: CPU - 512 - ResNet-50pytorch: CPU - 64 - ResNet-152pytorch: CPU - 256 - ResNet-152pytorch: CPU - 512 - ResNet-152pytorch: CPU - 1 - Efficientnet_v2_lpytorch: CPU - 16 - Efficientnet_v2_lpytorch: CPU - 32 - Efficientnet_v2_lpytorch: CPU - 64 - Efficientnet_v2_lpytorch: CPU - 256 - Efficientnet_v2_lpytorch: CPU - 512 - Efficientnet_v2_lopenvino: Face Detection FP16 - CPUopenvino: Face Detection FP16 - CPUopenvino: Person Detection FP16 - CPUopenvino: Person Detection FP16 - CPUopenvino: Person Detection FP32 - CPUopenvino: Person Detection FP32 - CPUopenvino: Vehicle Detection FP16 - CPUopenvino: Vehicle Detection FP16 - CPUopenvino: Face Detection FP16-INT8 - CPUopenvino: Face Detection FP16-INT8 - CPUopenvino: Face Detection Retail FP16 - CPUopenvino: Face Detection Retail FP16 - CPUopenvino: Road Segmentation ADAS FP16 - CPUopenvino: Road Segmentation ADAS FP16 - CPUopenvino: Vehicle Detection FP16-INT8 - CPUopenvino: Vehicle Detection FP16-INT8 - CPUopenvino: Weld Porosity Detection FP16 - CPUopenvino: Weld Porosity Detection FP16 - CPUopenvino: Face Detection Retail FP16-INT8 - CPUopenvino: Face Detection Retail FP16-INT8 - CPUopenvino: Road Segmentation ADAS FP16-INT8 - CPUopenvino: Road Segmentation ADAS FP16-INT8 - CPUopenvino: Machine Translation EN To DE FP16 - CPUopenvino: Machine Translation EN To DE FP16 - CPUopenvino: Weld Porosity Detection FP16-INT8 - CPUopenvino: Weld Porosity Detection FP16-INT8 - CPUopenvino: Person Vehicle Bike Detection FP16 - CPUopenvino: Person Vehicle Bike Detection FP16 - CPUopenvino: Handwritten English Recognition FP16 - CPUopenvino: Handwritten English Recognition FP16 - CPUopenvino: Age Gender Recognition Retail 0013 FP16 - CPUopenvino: Age Gender Recognition Retail 0013 FP16 - CPUopenvino: Handwritten English Recognition FP16-INT8 - CPUopenvino: Handwritten English Recognition FP16-INT8 - CPUopenvino: Age Gender Recognition Retail 0013 FP16-INT8 - CPUopenvino: Age Gender Recognition Retail 0013 FP16-INT8 - CPUabcd82133.53980.331.841496.78175.9112.16135.673.46818.239132.77125.46282.96179.5516.9033.5463.9868.3964.1668.4842587923232828083912152350953432681254805261104185541412442842133125484946612259213.510.310.158.730.032.14881.62530.495831.919530.933327.578333.778428.6080.810.810.3960324221.91284.151.893792.801830.5236590.2629560.6942961.237124.017812.985362.598963.767790.4555310.647551227.58620.7141231.931.094252.343291.48385633.911236.29632.072425143035025716051399567311214155084397165253106910831267171163849917266388522014844670640.3304.467978.243455.061346601796.713444011440158506208010588032631708710106384699605501.2358677.512548865201098960081440924807869808946150223069.4126.9945.7044.9745.4518.1345.0918.0446.3117.8017.9618.3014.2010.6210.8110.8610.8410.9313.41595.5594.284.8394.0584.991034.257.7125.52313.053070.772.49439.7518.161613.224.921353.9111.794527.763.44524.5815.23130.0561.382608.396.11572.385.06739.5621.6133511.790.43584.127.3647376.590.2982020.04042.631.791495.65175.9212.51135.9574.10218.433131.36125.49282.92180.0616.6733.5363.8568.3663.7868.5741477872238327143865166050913424681555485221092185341711762798132028014935616259513.050.310.158.730.032.08981.03030.448431.965330.887427.516633.727228.70740.810.810.3960324221.895283.2151.940872.817370.4987410.2791280.6931231.185584.034183.010992.598383.716500.4563470.6468661229.80636.4971236.681.097602.341251.48496635.3001231.68633.611426743235027723461403427281514177384660165034106910831266171163827917316387402022644437635.66304.627965.213355.731341771783.763444011490157836212710589732907394910106358355305508.4359044.212512743096098958335180925126926308958268839070.3926.7346.7345.9847.0118.0246.2918.0646.3618.0718.1117.8114.1210.8610.8910.9310.9311.0413.38595.3693.9585.0794.6684.431032.487.7325.56312.533063.552.5435.7718.321617.794.911352.8911.84537.363.43522.6415.28130.9560.982604.126.111587.745.02731.4221.8533483.530.43585.5527.2947316.170.29819584025.432.021494.53175.9212.63135.673.60118.387129.98124.98284.24180.0216.8133.4663.6968.2964.1468.1440817747241126993824162250983438681155545281086184045512072689129528384794606259113.380.320.158.720.032.10180.87330.391631.704730.831627.540333.651628.64440.810.810.3960424221.918284.0431.925662.803770.5345760.2487880.6953391.183724.011143.009062.598353.727810.456250.6462231234.14632.3941236.281.099422.339221.48752624.1381228.25628.308423943165035725901401197288814169884786164625106910831265170973844817235387982018644682636.52305.227982.943367.451348001783.943443011400157906208010589032833153190106490755005468.4358701.312533858004098987719340924793156908947892825069.0527.0245.9445.9146.1018.0346.1618.0546.4117.7518.1118.1614.0110.7210.8710.8210.8810.8513.33597.294.2984.7493.7685.2710327.7325.56312.483067.522.5437.7618.241617.824.91353.6211.794512.343.44532.9414.99130.0661.382609.576.11591.845733.8121.7733482.540.43587.4727.2147255.360.382159.4403332.061496.30175.8612.62135.0273.48818.297129.65125.13276.55179.2916.6433.5763.7568.6364.2668.7141367773238727783920165750943437681555705241101185943011862683130125374930611270913.710.310.158.750.032.0980.09830.511231.853530.826327.531633.724828.70190.810.810.3960324122.012288.1591.935182.818730.5205750.2569620.6951711.176684.043192.987852.598863.761920.4555530.6452311224625.5041224.111.097822.34111.48153634.6631234.57635.305425142975042718021396317276214136084573164645106810851264170753851217289390622013944177635.79305.367973.873350.861352001844.593447011390157806205010586032930127410106392313705500.8358447.112527706385099011030490924791346508948840393068.9927.6345.1647.7045.4318.0247.0618.1446.9318.1918.1917.9514.2510.9710.9210.9010.7910.9413.39594.9894.9984.1494.2884.741033.337.7225.5313.253069.352.49434.9818.361619.164.91351.1711.814544.573.42521.4615.32131.0960.942603.356.111572.565.06733.3621.7933491.830.43579.5627.5747453.430.29OpenBenchmarking.org

QuantLib

QuantLib is an open-source library/framework around quantitative finance for modeling, trading and risk management scenarios. QuantLib is written in C++ with Boost and its built-in benchmark used reports the QuantLib Benchmark Index benchmark score. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgMFLOPS, More Is BetterQuantLib 1.32Configuration: Multi-Threadeddcba20K40K60K80K100KSE +/- 83.63, N = 382159.481958.082020.082133.51. (CXX) g++ options: -O3 -march=native -fPIE -pie

OpenBenchmarking.orgMFLOPS, More Is BetterQuantLib 1.32Configuration: Single-Threadeddcba9001800270036004500SE +/- 9.84, N = 34033.04025.44042.63980.31. (CXX) g++ options: -O3 -march=native -fPIE -pie

CloverLeaf

CloverLeaf is a Lagrangian-Eulerian hydrodynamics benchmark. This test profile currently makes use of CloverLeaf's OpenMP version. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgSeconds, Fewer Is BetterCloverLeaf 1.3Input: clover_bmdcba714212835SE +/- 0.08, N = 332.0632.0231.7931.841. (F9X) gfortran options: -O3 -march=native -funroll-loops -fopenmp

OpenBenchmarking.orgSeconds, Fewer Is BetterCloverLeaf 1.3Input: clover_bm16dcba30060090012001500SE +/- 0.59, N = 31496.301494.531495.651496.781. (F9X) gfortran options: -O3 -march=native -funroll-loops -fopenmp

OpenBenchmarking.orgSeconds, Fewer Is BetterCloverLeaf 1.3Input: clover_bm64_shortdcba4080120160200SE +/- 0.02, N = 3175.86175.92175.92175.911. (F9X) gfortran options: -O3 -march=native -funroll-loops -fopenmp

QMCPACK

QMCPACK is a modern high-performance open-source Quantum Monte Carlo (QMC) simulation code making use of MPI for this benchmark of the H20 example code. QMCPACK is an open-source production level many-body ab initio Quantum Monte Carlo code for computing the electronic structure of atoms, molecules, and solids. QMCPACK is supported by the U.S. Department of Energy. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgTotal Execution Time - Seconds, Fewer Is BetterQMCPACK 3.17.1Input: H4_aedcba3691215SE +/- 0.09, N = 1512.6212.6312.5112.161. (CXX) g++ options: -fopenmp -foffload=disable -finline-limit=1000 -fstrict-aliasing -funroll-all-loops -ffast-math -march=native -O3 -lm -ldl

OpenBenchmarking.orgTotal Execution Time - Seconds, Fewer Is BetterQMCPACK 3.17.1Input: Li2_STO_aedcba306090120150SE +/- 1.12, N = 3135.02135.60135.95135.601. (CXX) g++ options: -fopenmp -foffload=disable -finline-limit=1000 -fstrict-aliasing -funroll-all-loops -ffast-math -march=native -O3 -lm -ldl

OpenBenchmarking.orgTotal Execution Time - Seconds, Fewer Is BetterQMCPACK 3.17.1Input: LiH_ae_MSDdcba1632486480SE +/- 0.40, N = 373.4973.6074.1073.471. (CXX) g++ options: -fopenmp -foffload=disable -finline-limit=1000 -fstrict-aliasing -funroll-all-loops -ffast-math -march=native -O3 -lm -ldl

OpenBenchmarking.orgTotal Execution Time - Seconds, Fewer Is BetterQMCPACK 3.17.1Input: simple-H2Odcba510152025SE +/- 0.03, N = 318.3018.3918.4318.241. (CXX) g++ options: -fopenmp -foffload=disable -finline-limit=1000 -fstrict-aliasing -funroll-all-loops -ffast-math -march=native -O3 -lm -ldl

OpenBenchmarking.orgTotal Execution Time - Seconds, Fewer Is BetterQMCPACK 3.17.1Input: O_ae_pyscf_UHFdcba306090120150SE +/- 1.01, N = 3129.65129.98131.36132.771. (CXX) g++ options: -fopenmp -foffload=disable -finline-limit=1000 -fstrict-aliasing -funroll-all-loops -ffast-math -march=native -O3 -lm -ldl

OpenBenchmarking.orgTotal Execution Time - Seconds, Fewer Is BetterQMCPACK 3.17.1Input: FeCO6_b3lyp_gmsdcba306090120150SE +/- 0.20, N = 3125.13124.98125.49125.461. (CXX) g++ options: -fopenmp -foffload=disable -finline-limit=1000 -fstrict-aliasing -funroll-all-loops -ffast-math -march=native -O3 -lm -ldl

FFmpeg

This is a benchmark of the FFmpeg multimedia framework. The FFmpeg test profile is making use of a modified version of vbench from Columbia University's Architecture and Design Lab (ARCADE) [http://arcade.cs.columbia.edu/vbench/] that is a benchmark for video-as-a-service workloads. The test profile offers the options of a range of vbench scenarios based on freely distributable video content and offers the options of using the x264 or x265 video encoders for transcoding. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgFPS, More Is BetterFFmpeg 6.1Encoder: libx264 - Scenario: Livedcba60120180240300SE +/- 1.97, N = 3276.55284.24282.92282.961. (CXX) g++ options: -O3 -rdynamic -lpthread -lrt -ldl -lnuma

OpenBenchmarking.orgFPS, More Is BetterFFmpeg 6.1Encoder: libx265 - Scenario: Livedcba4080120160200SE +/- 0.76, N = 3179.29180.02180.06179.551. (CXX) g++ options: -O3 -rdynamic -lpthread -lrt -ldl -lnuma

OpenBenchmarking.orgFPS, More Is BetterFFmpeg 6.1Encoder: libx264 - Scenario: Uploaddcba48121620SE +/- 0.14, N = 316.6416.8116.6716.901. (CXX) g++ options: -O3 -rdynamic -lpthread -lrt -ldl -lnuma

OpenBenchmarking.orgFPS, More Is BetterFFmpeg 6.1Encoder: libx265 - Scenario: Uploaddcba816243240SE +/- 0.08, N = 333.5733.4633.5333.541. (CXX) g++ options: -O3 -rdynamic -lpthread -lrt -ldl -lnuma

OpenBenchmarking.orgFPS, More Is BetterFFmpeg 6.1Encoder: libx264 - Scenario: Platformdcba1428425670SE +/- 0.08, N = 363.7563.6963.8563.981. (CXX) g++ options: -O3 -rdynamic -lpthread -lrt -ldl -lnuma

OpenBenchmarking.orgFPS, More Is BetterFFmpeg 6.1Encoder: libx265 - Scenario: Platformdcba1530456075SE +/- 0.09, N = 368.6368.2968.3668.391. (CXX) g++ options: -O3 -rdynamic -lpthread -lrt -ldl -lnuma

OpenBenchmarking.orgFPS, More Is BetterFFmpeg 6.1Encoder: libx264 - Scenario: Video On Demanddcba1428425670SE +/- 0.11, N = 364.2664.1463.7864.161. (CXX) g++ options: -O3 -rdynamic -lpthread -lrt -ldl -lnuma

OpenBenchmarking.orgFPS, More Is BetterFFmpeg 6.1Encoder: libx265 - Scenario: Video On Demanddcba1530456075SE +/- 0.07, N = 368.7168.1468.5768.481. (CXX) g++ options: -O3 -rdynamic -lpthread -lrt -ldl -lnuma

DaCapo Benchmark

This test runs the DaCapo Benchmarks written in Java and intended to test system/CPU performance of various popular real-world Java workloads. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgmsec, Fewer Is BetterDaCapo Benchmark 23.11Java Test: Jythondcba9001800270036004500SE +/- 38.35, N = 34136408141474258

OpenBenchmarking.orgmsec, Fewer Is BetterDaCapo Benchmark 23.11Java Test: Eclipsedcba2K4K6K8K10KSE +/- 58.05, N = 37773774778727923

OpenBenchmarking.orgmsec, Fewer Is BetterDaCapo Benchmark 23.11Java Test: GraphChidcba5001000150020002500SE +/- 9.87, N = 32387241123832328

OpenBenchmarking.orgmsec, Fewer Is BetterDaCapo Benchmark 23.11Java Test: Tradesoapdcba6001200180024003000SE +/- 19.80, N = 32778269927142808

OpenBenchmarking.orgmsec, Fewer Is BetterDaCapo Benchmark 23.11Java Test: Tradebeansdcba8001600240032004000SE +/- 47.36, N = 33920382438653912

OpenBenchmarking.orgmsec, Fewer Is BetterDaCapo Benchmark 23.11Java Test: Spring Bootdcba400800120016002000SE +/- 9.84, N = 31657162216601523

OpenBenchmarking.orgmsec, Fewer Is BetterDaCapo Benchmark 23.11Java Test: Apache Kafkadcba11002200330044005500SE +/- 0.88, N = 35094509850915095

OpenBenchmarking.orgmsec, Fewer Is BetterDaCapo Benchmark 23.11Java Test: Apache Tomcatdcba7001400210028003500SE +/- 3.51, N = 33437343834243432

OpenBenchmarking.orgmsec, Fewer Is BetterDaCapo Benchmark 23.11Java Test: jMonkeyEnginedcba15003000450060007500SE +/- 0.88, N = 36815681168156812

OpenBenchmarking.orgmsec, Fewer Is BetterDaCapo Benchmark 23.11Java Test: Apache Cassandradcba12002400360048006000SE +/- 47.51, N = 35570555455485480

OpenBenchmarking.orgmsec, Fewer Is BetterDaCapo Benchmark 23.11Java Test: Apache Xalan XSLTdcba110220330440550SE +/- 1.00, N = 3524528522526

OpenBenchmarking.orgmsec, Fewer Is BetterDaCapo Benchmark 23.11Java Test: Batik SVG Toolkitdcba2004006008001000SE +/- 15.43, N = 31101108610921104

OpenBenchmarking.orgmsec, Fewer Is BetterDaCapo Benchmark 23.11Java Test: H2 Database Enginedcba400800120016002000SE +/- 9.96, N = 31859184018531855

OpenBenchmarking.orgmsec, Fewer Is BetterDaCapo Benchmark 23.11Java Test: FOP Print Formatterdcba100200300400500SE +/- 7.98, N = 15430455417414

OpenBenchmarking.orgmsec, Fewer Is BetterDaCapo Benchmark 23.11Java Test: PMD Source Code Analyzerdcba30060090012001500SE +/- 5.04, N = 31186120711761244

OpenBenchmarking.orgmsec, Fewer Is BetterDaCapo Benchmark 23.11Java Test: Apache Lucene Search Indexdcba6001200180024003000SE +/- 6.81, N = 32683268927982842

OpenBenchmarking.orgmsec, Fewer Is BetterDaCapo Benchmark 23.11Java Test: Apache Lucene Search Enginedcba30060090012001500SE +/- 10.95, N = 91301129513201331

OpenBenchmarking.orgmsec, Fewer Is BetterDaCapo Benchmark 23.11Java Test: Avrora AVR Simulation Frameworkdcba6001200180024003000SE +/- 25.80, N = 152537283828012548

OpenBenchmarking.orgmsec, Fewer Is BetterDaCapo Benchmark 23.11Java Test: BioJava Biological Data Frameworkdcba11002200330044005500SE +/- 70.68, N = 34930479449354946

OpenBenchmarking.orgmsec, Fewer Is BetterDaCapo Benchmark 23.11Java Test: Zxing 1D/2D Barcode Image Processingdcba130260390520650SE +/- 8.14, N = 3611606616612

OpenBenchmarking.orgmsec, Fewer Is BetterDaCapo Benchmark 23.11Java Test: H2O In-Memory Platform For Machine Learningdcba6001200180024003000SE +/- 1.45, N = 32709259125952592

WebP2 Image Encode

This is a test of Google's libwebp2 library with the WebP2 image encode utility and using a sample 6000x4000 pixel JPEG image as the input, similar to the WebP/libwebp test profile. WebP2 is currently experimental and under heavy development as ultimately the successor to WebP. WebP2 supports 10-bit HDR, more efficienct lossy compression, improved lossless compression, animation support, and full multi-threading support compared to WebP. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgMP/s, More Is BetterWebP2 Image Encode 20220823Encode Settings: Defaultdcba48121620SE +/- 0.18, N = 313.7113.3813.0513.511. (CXX) g++ options: -msse4.2 -fno-rtti -O3 -ldl

OpenBenchmarking.orgMP/s, More Is BetterWebP2 Image Encode 20220823Encode Settings: Quality 75, Compression Effort 7dcba0.0720.1440.2160.2880.36SE +/- 0.00, N = 30.310.320.310.311. (CXX) g++ options: -msse4.2 -fno-rtti -O3 -ldl

OpenBenchmarking.orgMP/s, More Is BetterWebP2 Image Encode 20220823Encode Settings: Quality 95, Compression Effort 7dcba0.03380.06760.10140.13520.169SE +/- 0.00, N = 30.150.150.150.151. (CXX) g++ options: -msse4.2 -fno-rtti -O3 -ldl

OpenBenchmarking.orgMP/s, More Is BetterWebP2 Image Encode 20220823Encode Settings: Quality 100, Compression Effort 5dcba246810SE +/- 0.01, N = 38.758.728.738.731. (CXX) g++ options: -msse4.2 -fno-rtti -O3 -ldl

OpenBenchmarking.orgMP/s, More Is BetterWebP2 Image Encode 20220823Encode Settings: Quality 100, Lossless Compressiondcba0.00680.01360.02040.02720.034SE +/- 0.00, N = 30.030.030.030.031. (CXX) g++ options: -msse4.2 -fno-rtti -O3 -ldl

easyWave

The easyWave software allows simulating tsunami generation and propagation in the context of early warning systems. EasyWave supports making use of OpenMP for CPU multi-threading and there are also GPU ports available but not currently incorporated as part of this test profile. The easyWave tsunami generation software is run with one of the example/reference input files for measuring the CPU execution time. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgSeconds, Fewer Is BettereasyWave r34Input: e2Asean Grid + BengkuluSept2007 Source - Time: 240dcba0.48330.96661.44991.93322.4165SE +/- 0.004, N = 32.0902.1012.0892.1481. (CXX) g++ options: -O3 -fopenmp

OpenBenchmarking.orgSeconds, Fewer Is BettereasyWave r34Input: e2Asean Grid + BengkuluSept2007 Source - Time: 1200dcba20406080100SE +/- 0.33, N = 380.1080.8781.0381.631. (CXX) g++ options: -O3 -fopenmp

Embree

Intel Embree is a collection of high-performance ray-tracing kernels for execution on CPUs (and GPUs via SYCL) and supporting instruction sets such as SSE, AVX, AVX2, and AVX-512. Embree also supports making use of the Intel SPMD Program Compiler (ISPC). Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgFrames Per Second, More Is BetterEmbree 4.3Binary: Pathtracer - Model: Crowndcba714212835SE +/- 0.06, N = 330.5130.3930.4530.50MIN: 30.28 / MAX: 31.02MIN: 30.17 / MAX: 30.88MIN: 30.1 / MAX: 31.05MIN: 30.29 / MAX: 31

OpenBenchmarking.orgFrames Per Second, More Is BetterEmbree 4.3Binary: Pathtracer ISPC - Model: Crowndcba714212835SE +/- 0.04, N = 331.8531.7031.9731.92MIN: 31.57 / MAX: 32.5MIN: 31.4 / MAX: 32.36MIN: 31.62 / MAX: 32.67MIN: 31.66 / MAX: 32.67

OpenBenchmarking.orgFrames Per Second, More Is BetterEmbree 4.3Binary: Pathtracer - Model: Asian Dragondcba714212835SE +/- 0.06, N = 330.8330.8330.8930.93MIN: 30.69 / MAX: 31.27MIN: 30.69 / MAX: 31.19MIN: 30.64 / MAX: 31.42MIN: 30.8 / MAX: 31.38

OpenBenchmarking.orgFrames Per Second, More Is BetterEmbree 4.3Binary: Pathtracer - Model: Asian Dragon Objdcba612182430SE +/- 0.04, N = 327.5327.5427.5227.58MIN: 27.38 / MAX: 27.96MIN: 27.35 / MAX: 27.99MIN: 27.3 / MAX: 28.13MIN: 27.4 / MAX: 28.05

OpenBenchmarking.orgFrames Per Second, More Is BetterEmbree 4.3Binary: Pathtracer ISPC - Model: Asian Dragondcba816243240SE +/- 0.07, N = 333.7233.6533.7333.78MIN: 33.46 / MAX: 34.55MIN: 33.44 / MAX: 34.17MIN: 33.38 / MAX: 34.7MIN: 33.54 / MAX: 34.43

OpenBenchmarking.orgFrames Per Second, More Is BetterEmbree 4.3Binary: Pathtracer ISPC - Model: Asian Dragon Objdcba714212835SE +/- 0.05, N = 328.7028.6428.7128.61MIN: 28.49 / MAX: 29.4MIN: 28.43 / MAX: 29.3MIN: 28.44 / MAX: 29.67MIN: 28.41 / MAX: 29.24

Intel Open Image Denoise

OpenBenchmarking.orgImages / Sec, More Is BetterIntel Open Image Denoise 2.1Run: RT.hdr_alb_nrm.3840x2160 - Device: CPU-Onlydcba0.18230.36460.54690.72920.9115SE +/- 0.00, N = 30.810.810.810.81

OpenBenchmarking.orgImages / Sec, More Is BetterIntel Open Image Denoise 2.1Run: RT.ldr_alb_nrm.3840x2160 - Device: CPU-Onlydcba0.18230.36460.54690.72920.9115SE +/- 0.00, N = 30.810.810.810.81

OpenBenchmarking.orgImages / Sec, More Is BetterIntel Open Image Denoise 2.1Run: RTLightmap.hdr.4096x4096 - Device: CPU-Onlydcba0.08780.17560.26340.35120.439SE +/- 0.00, N = 30.390.390.390.39

OpenVKL

OpenVKL is the Intel Open Volume Kernel Library that offers high-performance volume computation kernels and part of the Intel oneAPI rendering toolkit. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgItems / Sec, More Is BetterOpenVKL 2.0.0Benchmark: vklBenchmarkCPU ISPCdcba130260390520650SE +/- 0.00, N = 3603604603603MIN: 46 / MAX: 8277MIN: 46 / MAX: 8291MIN: 46 / MAX: 8279MIN: 46 / MAX: 8290

OpenBenchmarking.orgItems / Sec, More Is BetterOpenVKL 2.0.0Benchmark: vklBenchmarkCPU Scalardcba50100150200250SE +/- 0.67, N = 3241242242242MIN: 16 / MAX: 4419MIN: 17 / MAX: 4423MIN: 16 / MAX: 4422MIN: 17 / MAX: 4418

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 6.1Time To Compiledcba510152025SE +/- 0.01, N = 322.0121.9221.9021.91

Timed Gem5 Compilation

This test times how long it takes to compile Gem5. Gem5 is a simulator for computer system architecture research. Gem5 is widely used for computer architecture research within the industry, academia, and more. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgSeconds, Fewer Is BetterTimed Gem5 Compilation 23.0.1Time To Compiledcba60120180240300SE +/- 3.14, N = 3288.16284.04283.22284.15

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 toolkit. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgms, Fewer Is BetteroneDNN 3.3Harness: IP Shapes 1D - Data Type: f32 - Engine: CPUdcba0.43670.87341.31011.74682.1835SE +/- 0.02190, N = 31.935181.925661.940871.89379MIN: 1.72MIN: 1.71MIN: 1.73MIN: 1.71. (CXX) g++ options: -O3 -march=native -fopenmp -msse4.1 -fPIC -pie -ldl

OpenBenchmarking.orgms, Fewer Is BetteroneDNN 3.3Harness: IP Shapes 3D - Data Type: f32 - Engine: CPUdcba0.63421.26841.90262.53683.171SE +/- 0.01747, N = 32.818732.803772.817372.80183MIN: 2.78MIN: 2.76MIN: 2.75MIN: 2.761. (CXX) g++ options: -O3 -march=native -fopenmp -msse4.1 -fPIC -pie -ldl

OpenBenchmarking.orgms, Fewer Is BetteroneDNN 3.3Harness: IP Shapes 1D - Data Type: u8s8f32 - Engine: CPUdcba0.12030.24060.36090.48120.6015SE +/- 0.010372, N = 150.5205750.5345760.4987410.523659MIN: 0.43MIN: 0.43MIN: 0.39MIN: 0.431. (CXX) g++ options: -O3 -march=native -fopenmp -msse4.1 -fPIC -pie -ldl

OpenBenchmarking.orgms, Fewer Is BetteroneDNN 3.3Harness: IP Shapes 3D - Data Type: u8s8f32 - Engine: CPUdcba0.06280.12560.18840.25120.314SE +/- 0.003205, N = 130.2569620.2487880.2791280.262956MIN: 0.24MIN: 0.24MIN: 0.24MIN: 0.251. (CXX) g++ options: -O3 -march=native -fopenmp -msse4.1 -fPIC -pie -ldl

OpenBenchmarking.orgms, Fewer Is BetteroneDNN 3.3Harness: IP Shapes 1D - Data Type: bf16bf16bf16 - Engine: CPUdcba0.15650.3130.46950.6260.7825SE +/- 0.002235, N = 30.6951710.6953390.6931230.694296MIN: 0.65MIN: 0.65MIN: 0.64MIN: 0.651. (CXX) g++ options: -O3 -march=native -fopenmp -msse4.1 -fPIC -pie -ldl

OpenBenchmarking.orgms, Fewer Is BetteroneDNN 3.3Harness: IP Shapes 3D - Data Type: bf16bf16bf16 - Engine: CPUdcba0.27840.55680.83521.11361.392SE +/- 0.01251, N = 51.176681.183721.185581.23712MIN: 1.1MIN: 1.11MIN: 1.08MIN: 1.171. (CXX) g++ options: -O3 -march=native -fopenmp -msse4.1 -fPIC -pie -ldl

OpenBenchmarking.orgms, Fewer Is BetteroneDNN 3.3Harness: Convolution Batch Shapes Auto - Data Type: f32 - Engine: CPUdcba0.90971.81942.72913.63884.5485SE +/- 0.00942, N = 34.043194.011144.034184.01781MIN: 3.98MIN: 3.96MIN: 3.94MIN: 3.961. (CXX) g++ options: -O3 -march=native -fopenmp -msse4.1 -fPIC -pie -ldl

OpenBenchmarking.orgms, Fewer Is BetteroneDNN 3.3Harness: Deconvolution Batch shapes_1d - Data Type: f32 - Engine: CPUdcba0.67751.3552.03252.713.3875SE +/- 0.00759, N = 32.987853.009063.010992.98536MIN: 2.51MIN: 2.51MIN: 2.51MIN: 2.511. (CXX) g++ options: -O3 -march=native -fopenmp -msse4.1 -fPIC -pie -ldl

OpenBenchmarking.orgms, Fewer Is BetteroneDNN 3.3Harness: Deconvolution Batch shapes_3d - Data Type: f32 - Engine: CPUdcba0.58481.16961.75442.33922.924SE +/- 0.00014, N = 32.598862.598352.598382.59896MIN: 2.59MIN: 2.59MIN: 2.59MIN: 2.591. (CXX) g++ options: -O3 -march=native -fopenmp -msse4.1 -fPIC -pie -ldl

OpenBenchmarking.orgms, Fewer Is BetteroneDNN 3.3Harness: Convolution Batch Shapes Auto - Data Type: u8s8f32 - Engine: CPUdcba0.84781.69562.54343.39124.239SE +/- 0.01733, N = 33.761923.727813.716503.76779MIN: 3.67MIN: 3.66MIN: 3.63MIN: 3.681. (CXX) g++ options: -O3 -march=native -fopenmp -msse4.1 -fPIC -pie -ldl

OpenBenchmarking.orgms, Fewer Is BetteroneDNN 3.3Harness: Deconvolution Batch shapes_1d - Data Type: u8s8f32 - Engine: CPUdcba0.10270.20540.30810.41080.5135SE +/- 0.000061, N = 30.4555530.4562500.4563470.455531MIN: 0.44MIN: 0.44MIN: 0.44MIN: 0.441. (CXX) g++ options: -O3 -march=native -fopenmp -msse4.1 -fPIC -pie -ldl

OpenBenchmarking.orgms, Fewer Is BetteroneDNN 3.3Harness: Deconvolution Batch shapes_3d - Data Type: u8s8f32 - Engine: CPUdcba0.14570.29140.43710.58280.7285SE +/- 0.000222, N = 30.6452310.6462230.6468660.647550MIN: 0.64MIN: 0.64MIN: 0.64MIN: 0.641. (CXX) g++ options: -O3 -march=native -fopenmp -msse4.1 -fPIC -pie -ldl

OpenBenchmarking.orgms, Fewer Is BetteroneDNN 3.3Harness: Recurrent Neural Network Training - Data Type: f32 - Engine: CPUdcba30060090012001500SE +/- 0.51, N = 31224.001234.141229.801227.58MIN: 1220.91MIN: 1229.87MIN: 1224.55MIN: 1224.621. (CXX) g++ options: -O3 -march=native -fopenmp -msse4.1 -fPIC -pie -ldl

OpenBenchmarking.orgms, Fewer Is BetteroneDNN 3.3Harness: Recurrent Neural Network Inference - Data Type: f32 - Engine: CPUdcba140280420560700SE +/- 0.32, N = 3625.50632.39636.50620.71MIN: 622.67MIN: 629.36MIN: 632.82MIN: 617.841. (CXX) g++ options: -O3 -march=native -fopenmp -msse4.1 -fPIC -pie -ldl

OpenBenchmarking.orgms, Fewer Is BetteroneDNN 3.3Harness: Recurrent Neural Network Training - Data Type: u8s8f32 - Engine: CPUdcba30060090012001500SE +/- 0.95, N = 31224.111236.281236.681231.93MIN: 1220.23MIN: 1233.21MIN: 1230.73MIN: 1227.811. (CXX) g++ options: -O3 -march=native -fopenmp -msse4.1 -fPIC -pie -ldl

OpenBenchmarking.orgms, Fewer Is BetteroneDNN 3.3Harness: Convolution Batch Shapes Auto - Data Type: bf16bf16bf16 - Engine: CPUdcba0.24740.49480.74220.98961.237SE +/- 0.00130, N = 31.097821.099421.097601.09425MIN: 1.07MIN: 1.07MIN: 1.07MIN: 1.071. (CXX) g++ options: -O3 -march=native -fopenmp -msse4.1 -fPIC -pie -ldl

OpenBenchmarking.orgms, Fewer Is BetteroneDNN 3.3Harness: Deconvolution Batch shapes_1d - Data Type: bf16bf16bf16 - Engine: CPUdcba0.52721.05441.58162.10882.636SE +/- 0.00064, N = 32.341102.339222.341252.34329MIN: 2.3MIN: 2.31MIN: 2.31MIN: 2.311. (CXX) g++ options: -O3 -march=native -fopenmp -msse4.1 -fPIC -pie -ldl

OpenBenchmarking.orgms, Fewer Is BetteroneDNN 3.3Harness: Deconvolution Batch shapes_3d - Data Type: bf16bf16bf16 - Engine: CPUdcba0.33470.66941.00411.33881.6735SE +/- 0.00176, N = 31.481531.487521.484961.48385MIN: 1.47MIN: 1.48MIN: 1.47MIN: 1.471. (CXX) g++ options: -O3 -march=native -fopenmp -msse4.1 -fPIC -pie -ldl

OpenBenchmarking.orgms, Fewer Is BetteroneDNN 3.3Harness: Recurrent Neural Network Inference - Data Type: u8s8f32 - Engine: CPUdcba140280420560700SE +/- 1.22, N = 3634.66624.14635.30633.91MIN: 631.75MIN: 621.15MIN: 629.42MIN: 629.41. (CXX) g++ options: -O3 -march=native -fopenmp -msse4.1 -fPIC -pie -ldl

OpenBenchmarking.orgms, Fewer Is BetteroneDNN 3.3Harness: Recurrent Neural Network Training - Data Type: bf16bf16bf16 - Engine: CPUdcba30060090012001500SE +/- 2.80, N = 31234.571228.251231.681236.29MIN: 1231MIN: 1224.56MIN: 1222.84MIN: 1232.21. (CXX) g++ options: -O3 -march=native -fopenmp -msse4.1 -fPIC -pie -ldl

OpenBenchmarking.orgms, Fewer Is BetteroneDNN 3.3Harness: Recurrent Neural Network Inference - Data Type: bf16bf16bf16 - Engine: CPUdcba140280420560700SE +/- 2.14, N = 3635.31628.31633.61632.07MIN: 632.15MIN: 625.84MIN: 626.34MIN: 628.151. (CXX) g++ options: -O3 -march=native -fopenmp -msse4.1 -fPIC -pie -ldl

OSPRay Studio

Intel OSPRay Studio is an open-source, interactive visualization and ray-tracing software package. OSPRay Studio makes use of Intel OSPRay, a portable ray-tracing engine for high-performance, high-fidelity visualizations. OSPRay builds off Intel's Embree and Intel SPMD Program Compiler (ISPC) components as part of the oneAPI rendering toolkit. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgms, Fewer Is BetterOSPRay Studio 0.13Camera: 1 - Resolution: 4K - Samples Per Pixel: 1 - Renderer: Path Tracer - Acceleration: CPUdcba9001800270036004500SE +/- 3.51, N = 34251423942674251

OpenBenchmarking.orgms, Fewer Is BetterOSPRay Studio 0.13Camera: 2 - Resolution: 4K - Samples Per Pixel: 1 - Renderer: Path Tracer - Acceleration: CPUdcba9001800270036004500SE +/- 4.41, N = 34297431643234303

OpenBenchmarking.orgms, Fewer Is BetterOSPRay Studio 0.13Camera: 3 - Resolution: 4K - Samples Per Pixel: 1 - Renderer: Path Tracer - Acceleration: CPUdcba11002200330044005500SE +/- 4.26, N = 35042503550275025

OpenBenchmarking.orgms, Fewer Is BetterOSPRay Studio 0.13Camera: 1 - Resolution: 4K - Samples Per Pixel: 16 - Renderer: Path Tracer - Acceleration: CPUdcba16K32K48K64K80KSE +/- 88.19, N = 371802725907234671605

OpenBenchmarking.orgms, Fewer Is BetterOSPRay Studio 0.13Camera: 1 - Resolution: 4K - Samples Per Pixel: 32 - Renderer: Path Tracer - Acceleration: CPUdcba30K60K90K120K150KSE +/- 200.00, N = 3139631140119140342139956

OpenBenchmarking.orgms, Fewer Is BetterOSPRay Studio 0.13Camera: 2 - Resolution: 4K - Samples Per Pixel: 16 - Renderer: Path Tracer - Acceleration: CPUdcba16K32K48K64K80KSE +/- 124.54, N = 372762728887281573112

OpenBenchmarking.orgms, Fewer Is BetterOSPRay Studio 0.13Camera: 2 - Resolution: 4K - Samples Per Pixel: 32 - Renderer: Path Tracer - Acceleration: CPUdcba30K60K90K120K150KSE +/- 201.33, N = 3141360141698141773141550

OpenBenchmarking.orgms, Fewer Is BetterOSPRay Studio 0.13Camera: 3 - Resolution: 4K - Samples Per Pixel: 16 - Renderer: Path Tracer - Acceleration: CPUdcba20K40K60K80K100KSE +/- 192.43, N = 384573847868466084397

OpenBenchmarking.orgms, Fewer Is BetterOSPRay Studio 0.13Camera: 3 - Resolution: 4K - Samples Per Pixel: 32 - Renderer: Path Tracer - Acceleration: CPUdcba40K80K120K160K200KSE +/- 70.29, N = 3164645164625165034165253

OpenBenchmarking.orgms, Fewer Is BetterOSPRay Studio 0.13Camera: 1 - Resolution: 1080p - Samples Per Pixel: 1 - Renderer: Path Tracer - Acceleration: CPUdcba2004006008001000SE +/- 0.58, N = 31068106910691069

OpenBenchmarking.orgms, Fewer Is BetterOSPRay Studio 0.13Camera: 2 - Resolution: 1080p - Samples Per Pixel: 1 - Renderer: Path Tracer - Acceleration: CPUdcba2004006008001000SE +/- 0.58, N = 31085108310831083

OpenBenchmarking.orgms, Fewer Is BetterOSPRay Studio 0.13Camera: 3 - Resolution: 1080p - Samples Per Pixel: 1 - Renderer: Path Tracer - Acceleration: CPUdcba30060090012001500SE +/- 2.65, N = 31264126512661267

OpenBenchmarking.orgms, Fewer Is BetterOSPRay Studio 0.13Camera: 1 - Resolution: 1080p - Samples Per Pixel: 16 - Renderer: Path Tracer - Acceleration: CPUdcba4K8K12K16K20KSE +/- 12.41, N = 317075170971711617116

OpenBenchmarking.orgms, Fewer Is BetterOSPRay Studio 0.13Camera: 1 - Resolution: 1080p - Samples Per Pixel: 32 - Renderer: Path Tracer - Acceleration: CPUdcba8K16K24K32K40KSE +/- 262.57, N = 338512384483827938499

OpenBenchmarking.orgms, Fewer Is BetterOSPRay Studio 0.13Camera: 2 - Resolution: 1080p - Samples Per Pixel: 16 - Renderer: Path Tracer - Acceleration: CPUdcba4K8K12K16K20KSE +/- 12.45, N = 317289172351731617266

OpenBenchmarking.orgms, Fewer Is BetterOSPRay Studio 0.13Camera: 2 - Resolution: 1080p - Samples Per Pixel: 32 - Renderer: Path Tracer - Acceleration: CPUdcba8K16K24K32K40KSE +/- 34.12, N = 339062387983874038852

OpenBenchmarking.orgms, Fewer Is BetterOSPRay Studio 0.13Camera: 3 - Resolution: 1080p - Samples Per Pixel: 16 - Renderer: Path Tracer - Acceleration: CPUdcba4K8K12K16K20KSE +/- 20.65, N = 320139201862022620148

OpenBenchmarking.orgms, Fewer Is BetterOSPRay Studio 0.13Camera: 3 - Resolution: 1080p - Samples Per Pixel: 32 - Renderer: Path Tracer - Acceleration: CPUdcba10K20K30K40K50KSE +/- 116.17, N = 344177446824443744670

Cpuminer-Opt

Cpuminer-Opt is a fork of cpuminer-multi that carries a wide range of CPU performance optimizations for measuring the potential cryptocurrency mining performance of the CPU/processor with a wide variety of cryptocurrencies. The benchmark reports the hash speed for the CPU mining performance for the selected cryptocurrency. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgkH/s, More Is BetterCpuminer-Opt 23.5Algorithm: Magidcba140280420560700SE +/- 0.61, N = 3635.79636.52635.66640.301. (CXX) g++ options: -O2 -lcurl -lz -lpthread -lssl -lcrypto -lgmp

OpenBenchmarking.orgkH/s, More Is BetterCpuminer-Opt 23.5Algorithm: scryptdcba70140210280350SE +/- 0.25, N = 3305.36305.22304.62304.461. (CXX) g++ options: -O2 -lcurl -lz -lpthread -lssl -lcrypto -lgmp

OpenBenchmarking.orgkH/s, More Is BetterCpuminer-Opt 23.5Algorithm: Deepcoindcba2K4K6K8K10KSE +/- 21.85, N = 37973.877982.947965.217978.241. (CXX) g++ options: -O2 -lcurl -lz -lpthread -lssl -lcrypto -lgmp

OpenBenchmarking.orgkH/s, More Is BetterCpuminer-Opt 23.5Algorithm: Ringcoindcba7001400210028003500SE +/- 2.45, N = 33350.863367.453355.733455.061. (CXX) g++ options: -O2 -lcurl -lz -lpthread -lssl -lcrypto -lgmp

OpenBenchmarking.orgkH/s, More Is BetterCpuminer-Opt 23.5Algorithm: Blake-2 Sdcba30K60K90K120K150KSE +/- 3.33, N = 31352001348001341771346601. (CXX) g++ options: -O2 -lcurl -lz -lpthread -lssl -lcrypto -lgmp

OpenBenchmarking.orgkH/s, More Is BetterCpuminer-Opt 23.5Algorithm: Garlicoindcba400800120016002000SE +/- 2.78, N = 31844.591783.941783.761796.711. (CXX) g++ options: -O2 -lcurl -lz -lpthread -lssl -lcrypto -lgmp

OpenBenchmarking.orgkH/s, More Is BetterCpuminer-Opt 23.5Algorithm: Skeincoindcba7K14K21K28K35KSE +/- 5.77, N = 3344703443034440344401. (CXX) g++ options: -O2 -lcurl -lz -lpthread -lssl -lcrypto -lgmp

OpenBenchmarking.orgkH/s, More Is BetterCpuminer-Opt 23.5Algorithm: Myriad-Groestldcba2K4K6K8K10KSE +/- 50.00, N = 3113901140011490114401. (CXX) g++ options: -O2 -lcurl -lz -lpthread -lssl -lcrypto -lgmp

OpenBenchmarking.orgkH/s, More Is BetterCpuminer-Opt 23.5Algorithm: LBC, LBRY Creditsdcba3K6K9K12K15KSE +/- 3.33, N = 3157801579015783158501. (CXX) g++ options: -O2 -lcurl -lz -lpthread -lssl -lcrypto -lgmp

OpenBenchmarking.orgkH/s, More Is BetterCpuminer-Opt 23.5Algorithm: Quad SHA-256, Pyritedcba13K26K39K52K65KSE +/- 16.67, N = 3620506208062127620801. (CXX) g++ options: -O2 -lcurl -lz -lpthread -lssl -lcrypto -lgmp

OpenBenchmarking.orgkH/s, More Is BetterCpuminer-Opt 23.5Algorithm: Triple SHA-256, Onecoindcba20K40K60K80K100KSE +/- 3.33, N = 31058601058901058971058801. (CXX) g++ options: -O2 -lcurl -lz -lpthread -lssl -lcrypto -lgmp

OpenSSL

OpenSSL is an open-source toolkit that implements SSL (Secure Sockets Layer) and TLS (Transport Layer Security) protocols. The system/openssl test profiles relies on benchmarking the system/OS-supplied openssl binary rather than the pts/openssl test profile that uses the locally-built OpenSSL for benchmarking. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgbyte/s, More Is BetterOpenSSLAlgorithm: SHA256dcba7000M14000M21000M28000M35000M329301274103283315319032907394910326317087101. OpenSSL 3.0.2 15 Mar 2022 (Library: OpenSSL 3.0.2 15 Mar 2022)

OpenBenchmarking.orgbyte/s, More Is BetterOpenSSLAlgorithm: SHA512dcba2000M4000M6000M8000M10000M106392313701064907550010635835530106384699601. OpenSSL 3.0.2 15 Mar 2022 (Library: OpenSSL 3.0.2 15 Mar 2022)

OpenBenchmarking.orgsign/s, More Is BetterOpenSSLAlgorithm: RSA4096dcba120024003600480060005500.85468.45508.45501.21. OpenSSL 3.0.2 15 Mar 2022 (Library: OpenSSL 3.0.2 15 Mar 2022)

OpenBenchmarking.orgverify/s, More Is BetterOpenSSLAlgorithm: RSA4096dcba80K160K240K320K400K358447.1358701.3359044.2358677.51. OpenSSL 3.0.2 15 Mar 2022 (Library: OpenSSL 3.0.2 15 Mar 2022)

OpenBenchmarking.orgbyte/s, More Is BetterOpenSSLAlgorithm: ChaCha20dcba30000M60000M90000M120000M150000M1252770638501253385800401251274309601254886520101. OpenSSL 3.0.2 15 Mar 2022 (Library: OpenSSL 3.0.2 15 Mar 2022)

OpenBenchmarking.orgbyte/s, More Is BetterOpenSSLAlgorithm: AES-128-GCMdcba20000M40000M60000M80000M100000M990110304909898771934098958335180989600814401. OpenSSL 3.0.2 15 Mar 2022 (Library: OpenSSL 3.0.2 15 Mar 2022)

OpenBenchmarking.orgbyte/s, More Is BetterOpenSSLAlgorithm: AES-256-GCMdcba20000M40000M60000M80000M100000M924791346509247931569092512692630924807869801. OpenSSL 3.0.2 15 Mar 2022 (Library: OpenSSL 3.0.2 15 Mar 2022)

OpenBenchmarking.orgbyte/s, More Is BetterOpenSSLAlgorithm: ChaCha20-Poly1305dcba20000M40000M60000M80000M100000M894884039308947892825089582688390894615022301. OpenSSL 3.0.2 15 Mar 2022 (Library: OpenSSL 3.0.2 15 Mar 2022)

RabbitMQ

RabbitMQ is an open-source message broker. This test profile makes use of the RabbitMQ PerfTest with the RabbitMQ server and PerfTest client running on the same host namely as a system/CPU performance benchmark. Learn more via the OpenBenchmarking.org test page.

Scenario: Simple 2 Publishers + 4 Consumers

a: The test quit with a non-zero exit status. E: java.net.ConnectException: Connection refused (Connection refused)

b: The test quit with a non-zero exit status. E: java.net.ConnectException: Connection refused (Connection refused)

c: The test quit with a non-zero exit status. E: java.net.ConnectException: Connection refused (Connection refused)

d: The test quit with a non-zero exit status. E: java.net.ConnectException: Connection refused (Connection refused)

Scenario: 10 Queues, 100 Producers, 100 Consumers

a: The test quit with a non-zero exit status. E: java.net.ConnectException: Connection refused (Connection refused)

b: The test quit with a non-zero exit status. E: java.net.ConnectException: Connection refused (Connection refused)

c: The test quit with a non-zero exit status. E: java.net.ConnectException: Connection refused (Connection refused)

d: The test quit with a non-zero exit status. E: java.net.ConnectException: Connection refused (Connection refused)

Scenario: 60 Queues, 100 Producers, 100 Consumers

a: The test quit with a non-zero exit status. E: java.net.ConnectException: Connection refused (Connection refused)

b: The test quit with a non-zero exit status. E: java.net.ConnectException: Connection refused (Connection refused)

c: The test quit with a non-zero exit status. E: java.net.ConnectException: Connection refused (Connection refused)

d: The test quit with a non-zero exit status. E: java.net.ConnectException: Connection refused (Connection refused)

Scenario: 120 Queues, 400 Producers, 400 Consumers

a: The test quit with a non-zero exit status. E: java.net.ConnectException: Connection refused (Connection refused)

b: The test quit with a non-zero exit status. E: java.net.ConnectException: Connection refused (Connection refused)

c: The test quit with a non-zero exit status. E: java.net.ConnectException: Connection refused (Connection refused)

d: The test quit with a non-zero exit status. E: java.net.ConnectException: Connection refused (Connection refused)

Scenario: 200 Queues, 400 Producers, 400 Consumers

a: The test quit with a non-zero exit status. E: java.net.ConnectException: Connection refused (Connection refused)

b: The test quit with a non-zero exit status. E: java.net.ConnectException: Connection refused (Connection refused)

c: The test quit with a non-zero exit status. E: java.net.ConnectException: Connection refused (Connection refused)

d: The test quit with a non-zero exit status. E: java.net.ConnectException: Connection refused (Connection refused)

PyTorch

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.1Device: CPU - Batch Size: 1 - Model: ResNet-50dcba163248648068.9969.0570.3969.41MIN: 65.18 / MAX: 70.36MIN: 64.46 / MAX: 70.37MIN: 65.98 / MAX: 71.59MIN: 64.47 / MAX: 71.04

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.1Device: CPU - Batch Size: 1 - Model: ResNet-152dcba71421283527.6327.0226.7326.99MIN: 26.37 / MAX: 27.91MIN: 26.41 / MAX: 27.29MIN: 25.73 / MAX: 27.4MIN: 25.92 / MAX: 27.21

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.1Device: CPU - Batch Size: 16 - Model: ResNet-50dcba112233445545.1645.9446.7345.70MIN: 42.72 / MAX: 46.38MIN: 36.22 / MAX: 46.45MIN: 43.51 / MAX: 47.16MIN: 43.16 / MAX: 46.31

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.1Device: CPU - Batch Size: 32 - Model: ResNet-50dcba112233445547.7045.9145.9844.97MIN: 44.77 / MAX: 48.1MIN: 41.91 / MAX: 46.67MIN: 43.4 / MAX: 46.68MIN: 42.18 / MAX: 46.53

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.1Device: CPU - Batch Size: 64 - Model: ResNet-50dcba112233445545.4346.1047.0145.45MIN: 43.43 / MAX: 46.04MIN: 35.44 / MAX: 46.83MIN: 42.75 / MAX: 47.57MIN: 34.94 / MAX: 45.89

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.1Device: CPU - Batch Size: 16 - Model: ResNet-152dcba4812162018.0218.0318.0218.13MIN: 17.66 / MAX: 18.18MIN: 17.54 / MAX: 18.23MIN: 17.53 / MAX: 18.23MIN: 17.59 / MAX: 18.32

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.1Device: CPU - Batch Size: 256 - Model: ResNet-50dcba112233445547.0646.1646.2945.09MIN: 42.87 / MAX: 47.87MIN: 42.11 / MAX: 46.89MIN: 42.39 / MAX: 46.81MIN: 43.25 / MAX: 45.61

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.1Device: CPU - Batch Size: 32 - Model: ResNet-152dcba4812162018.1418.0518.0618.04MIN: 17.74 / MAX: 18.22MIN: 17.55 / MAX: 18.12MIN: 17.57 / MAX: 18.26MIN: 17.52 / MAX: 18.19

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.1Device: CPU - Batch Size: 512 - Model: ResNet-50dcba112233445546.9346.4146.3646.31MIN: 44.02 / MAX: 47.5MIN: 43.7 / MAX: 46.95MIN: 42.96 / MAX: 47.26MIN: 43.53 / MAX: 47.23

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.1Device: CPU - Batch Size: 64 - Model: ResNet-152dcba4812162018.1917.7518.0717.80MIN: 17.82 / MAX: 18.26MIN: 17.45 / MAX: 17.89MIN: 16.99 / MAX: 18.18MIN: 17.33 / MAX: 18.03

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.1Device: CPU - Batch Size: 256 - Model: ResNet-152dcba4812162018.1918.1118.1117.96MIN: 14.43 / MAX: 18.68MIN: 17.68 / MAX: 18.22MIN: 17.67 / MAX: 18.23MIN: 17.36 / MAX: 18.16

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.1Device: CPU - Batch Size: 512 - Model: ResNet-152dcba51015202517.9518.1617.8118.30MIN: 17.53 / MAX: 18.17MIN: 17.66 / MAX: 18.27MIN: 17.54 / MAX: 18.01MIN: 17.67 / MAX: 18.39

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.1Device: CPU - Batch Size: 1 - Model: Efficientnet_v2_ldcba4812162014.2514.0114.1214.20MIN: 14.08 / MAX: 14.36MIN: 13.86 / MAX: 14.16MIN: 13.18 / MAX: 14.23MIN: 14.07 / MAX: 14.34

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.1Device: CPU - Batch Size: 16 - Model: Efficientnet_v2_ldcba369121510.9710.7210.8610.62MIN: 9.39 / MAX: 11.28MIN: 9.34 / MAX: 10.88MIN: 9.5 / MAX: 11.07MIN: 9.39 / MAX: 10.82

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.1Device: CPU - Batch Size: 32 - Model: Efficientnet_v2_ldcba369121510.9210.8710.8910.81MIN: 9.26 / MAX: 11.09MIN: 9.55 / MAX: 11.02MIN: 9.54 / MAX: 11.07MIN: 9.24 / MAX: 10.96

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.1Device: CPU - Batch Size: 64 - Model: Efficientnet_v2_ldcba369121510.9010.8210.9310.86MIN: 9.57 / MAX: 11.05MIN: 9.26 / MAX: 10.96MIN: 8.84 / MAX: 11.11MIN: 9.49 / MAX: 11

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.1Device: CPU - Batch Size: 256 - Model: Efficientnet_v2_ldcba369121510.7910.8810.9310.84MIN: 9.49 / MAX: 10.96MIN: 9.61 / MAX: 11.08MIN: 9.59 / MAX: 11.11MIN: 9.5 / MAX: 10.98

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.1Device: CPU - Batch Size: 512 - Model: Efficientnet_v2_ldcba369121510.9410.8511.0410.93MIN: 9.62 / MAX: 11.08MIN: 9.35 / MAX: 11.06MIN: 9.87 / MAX: 11.21MIN: 9.18 / MAX: 11.07

OpenVINO

This is a test of the Intel OpenVINO, a toolkit around neural networks, using its built-in benchmarking support and analyzing the throughput and latency for various models. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgFPS, More Is BetterOpenVINO 2023.2.devModel: Face Detection FP16 - Device: CPUdcba369121513.3913.3313.3813.411. (CXX) g++ options: -fPIC -fsigned-char -ffunction-sections -fdata-sections -O3 -fno-strict-overflow -fwrapv -shared -ldl

OpenBenchmarking.orgms, Fewer Is BetterOpenVINO 2023.2.devModel: Face Detection FP16 - Device: CPUdcba130260390520650594.98597.20595.36595.55MIN: 577.06 / MAX: 624.47MIN: 574.49 / MAX: 623.82MIN: 575.04 / MAX: 623.57MIN: 576.09 / MAX: 622.51. (CXX) g++ options: -fPIC -fsigned-char -ffunction-sections -fdata-sections -O3 -fno-strict-overflow -fwrapv -shared -ldl

OpenBenchmarking.orgFPS, More Is BetterOpenVINO 2023.2.devModel: Person Detection FP16 - Device: CPUdcba2040608010094.9994.2993.9594.201. (CXX) g++ options: -fPIC -fsigned-char -ffunction-sections -fdata-sections -O3 -fno-strict-overflow -fwrapv -shared -ldl

OpenBenchmarking.orgms, Fewer Is BetterOpenVINO 2023.2.devModel: Person Detection FP16 - Device: CPUdcba2040608010084.1484.7485.0784.83MIN: 49.25 / MAX: 110.52MIN: 44.18 / MAX: 109.72MIN: 55.85 / MAX: 113.02MIN: 51.55 / MAX: 110.451. (CXX) g++ options: -fPIC -fsigned-char -ffunction-sections -fdata-sections -O3 -fno-strict-overflow -fwrapv -shared -ldl

OpenBenchmarking.orgFPS, More Is BetterOpenVINO 2023.2.devModel: Person Detection FP32 - Device: CPUdcba2040608010094.2893.7694.6694.051. (CXX) g++ options: -fPIC -fsigned-char -ffunction-sections -fdata-sections -O3 -fno-strict-overflow -fwrapv -shared -ldl

OpenBenchmarking.orgms, Fewer Is BetterOpenVINO 2023.2.devModel: Person Detection FP32 - Device: CPUdcba2040608010084.7485.2784.4384.99MIN: 43.16 / MAX: 116.66MIN: 56.98 / MAX: 111.16MIN: 38.96 / MAX: 118.46MIN: 54.5 / MAX: 109.881. (CXX) g++ options: -fPIC -fsigned-char -ffunction-sections -fdata-sections -O3 -fno-strict-overflow -fwrapv -shared -ldl

OpenBenchmarking.orgFPS, More Is BetterOpenVINO 2023.2.devModel: Vehicle Detection FP16 - Device: CPUdcba20040060080010001033.331032.001032.481034.251. (CXX) g++ options: -fPIC -fsigned-char -ffunction-sections -fdata-sections -O3 -fno-strict-overflow -fwrapv -shared -ldl

OpenBenchmarking.orgms, Fewer Is BetterOpenVINO 2023.2.devModel: Vehicle Detection FP16 - Device: CPUdcba2468107.727.737.737.71MIN: 4.51 / MAX: 13.75MIN: 4.84 / MAX: 13.08MIN: 4.78 / MAX: 16.94MIN: 4.99 / MAX: 14.681. (CXX) g++ options: -fPIC -fsigned-char -ffunction-sections -fdata-sections -O3 -fno-strict-overflow -fwrapv -shared -ldl

OpenBenchmarking.orgFPS, More Is BetterOpenVINO 2023.2.devModel: Face Detection FP16-INT8 - Device: CPUdcba61218243025.5025.5625.5625.521. (CXX) g++ options: -fPIC -fsigned-char -ffunction-sections -fdata-sections -O3 -fno-strict-overflow -fwrapv -shared -ldl

OpenBenchmarking.orgms, Fewer Is BetterOpenVINO 2023.2.devModel: Face Detection FP16-INT8 - Device: CPUdcba70140210280350313.25312.48312.53313.05MIN: 299.83 / MAX: 323.76MIN: 296.91 / MAX: 323.74MIN: 300.51 / MAX: 321.6MIN: 299.21 / MAX: 324.171. (CXX) g++ options: -fPIC -fsigned-char -ffunction-sections -fdata-sections -O3 -fno-strict-overflow -fwrapv -shared -ldl

OpenBenchmarking.orgFPS, More Is BetterOpenVINO 2023.2.devModel: Face Detection Retail FP16 - Device: CPUdcba70014002100280035003069.353067.523063.553070.771. (CXX) g++ options: -fPIC -fsigned-char -ffunction-sections -fdata-sections -O3 -fno-strict-overflow -fwrapv -shared -ldl

OpenBenchmarking.orgms, Fewer Is BetterOpenVINO 2023.2.devModel: Face Detection Retail FP16 - Device: CPUdcba0.56251.1251.68752.252.81252.492.502.502.49MIN: 1.35 / MAX: 9.24MIN: 1.34 / MAX: 9.59MIN: 1.34 / MAX: 9.48MIN: 1.35 / MAX: 6.31. (CXX) g++ options: -fPIC -fsigned-char -ffunction-sections -fdata-sections -O3 -fno-strict-overflow -fwrapv -shared -ldl

OpenBenchmarking.orgFPS, More Is BetterOpenVINO 2023.2.devModel: Road Segmentation ADAS FP16 - Device: CPUdcba100200300400500434.98437.76435.77439.751. (CXX) g++ options: -fPIC -fsigned-char -ffunction-sections -fdata-sections -O3 -fno-strict-overflow -fwrapv -shared -ldl

OpenBenchmarking.orgms, Fewer Is BetterOpenVINO 2023.2.devModel: Road Segmentation ADAS FP16 - Device: CPUdcba51015202518.3618.2418.3218.16MIN: 9.65 / MAX: 27.17MIN: 12.24 / MAX: 26.29MIN: 12.74 / MAX: 30.01MIN: 9.71 / MAX: 27.641. (CXX) g++ options: -fPIC -fsigned-char -ffunction-sections -fdata-sections -O3 -fno-strict-overflow -fwrapv -shared -ldl

OpenBenchmarking.orgFPS, More Is BetterOpenVINO 2023.2.devModel: Vehicle Detection FP16-INT8 - Device: CPUdcba300600900120015001619.161617.821617.791613.221. (CXX) g++ options: -fPIC -fsigned-char -ffunction-sections -fdata-sections -O3 -fno-strict-overflow -fwrapv -shared -ldl

OpenBenchmarking.orgms, Fewer Is BetterOpenVINO 2023.2.devModel: Vehicle Detection FP16-INT8 - Device: CPUdcba1.1072.2143.3214.4285.5354.904.904.914.92MIN: 2.75 / MAX: 9.12MIN: 2.76 / MAX: 13.8MIN: 2.77 / MAX: 14.1MIN: 2.75 / MAX: 10.581. (CXX) g++ options: -fPIC -fsigned-char -ffunction-sections -fdata-sections -O3 -fno-strict-overflow -fwrapv -shared -ldl

OpenBenchmarking.orgFPS, More Is BetterOpenVINO 2023.2.devModel: Weld Porosity Detection FP16 - Device: CPUdcba300600900120015001351.171353.621352.891353.911. (CXX) g++ options: -fPIC -fsigned-char -ffunction-sections -fdata-sections -O3 -fno-strict-overflow -fwrapv -shared -ldl

OpenBenchmarking.orgms, Fewer Is BetterOpenVINO 2023.2.devModel: Weld Porosity Detection FP16 - Device: CPUdcba369121511.8111.7911.8011.79MIN: 6.78 / MAX: 18.07MIN: 6.2 / MAX: 21.55MIN: 7.57 / MAX: 15.99MIN: 6.37 / MAX: 23.31. (CXX) g++ options: -fPIC -fsigned-char -ffunction-sections -fdata-sections -O3 -fno-strict-overflow -fwrapv -shared -ldl

OpenBenchmarking.orgFPS, More Is BetterOpenVINO 2023.2.devModel: Face Detection Retail FP16-INT8 - Device: CPUdcba100020003000400050004544.574512.344537.364527.761. (CXX) g++ options: -fPIC -fsigned-char -ffunction-sections -fdata-sections -O3 -fno-strict-overflow -fwrapv -shared -ldl

OpenBenchmarking.orgms, Fewer Is BetterOpenVINO 2023.2.devModel: Face Detection Retail FP16-INT8 - Device: CPUdcba0.7741.5482.3223.0963.873.423.443.433.44MIN: 1.94 / MAX: 6.89MIN: 1.94 / MAX: 11.06MIN: 1.96 / MAX: 8.28MIN: 1.95 / MAX: 10.991. (CXX) g++ options: -fPIC -fsigned-char -ffunction-sections -fdata-sections -O3 -fno-strict-overflow -fwrapv -shared -ldl

OpenBenchmarking.orgFPS, More Is BetterOpenVINO 2023.2.devModel: Road Segmentation ADAS FP16-INT8 - Device: CPUdcba120240360480600521.46532.94522.64524.581. (CXX) g++ options: -fPIC -fsigned-char -ffunction-sections -fdata-sections -O3 -fno-strict-overflow -fwrapv -shared -ldl

OpenBenchmarking.orgms, Fewer Is BetterOpenVINO 2023.2.devModel: Road Segmentation ADAS FP16-INT8 - Device: CPUdcba4812162015.3214.9915.2815.23MIN: 12.62 / MAX: 21MIN: 11.64 / MAX: 20.21MIN: 9.17 / MAX: 19.71MIN: 11.89 / MAX: 21.111. (CXX) g++ options: -fPIC -fsigned-char -ffunction-sections -fdata-sections -O3 -fno-strict-overflow -fwrapv -shared -ldl

OpenBenchmarking.orgFPS, More Is BetterOpenVINO 2023.2.devModel: Machine Translation EN To DE FP16 - Device: CPUdcba306090120150131.09130.06130.95130.051. (CXX) g++ options: -fPIC -fsigned-char -ffunction-sections -fdata-sections -O3 -fno-strict-overflow -fwrapv -shared -ldl

OpenBenchmarking.orgms, Fewer Is BetterOpenVINO 2023.2.devModel: Machine Translation EN To DE FP16 - Device: CPUdcba142842567060.9461.3860.9861.38MIN: 46.99 / MAX: 72.58MIN: 44.4 / MAX: 70.65MIN: 27.92 / MAX: 70.86MIN: 46.13 / MAX: 71.271. (CXX) g++ options: -fPIC -fsigned-char -ffunction-sections -fdata-sections -O3 -fno-strict-overflow -fwrapv -shared -ldl

OpenBenchmarking.orgFPS, More Is BetterOpenVINO 2023.2.devModel: Weld Porosity Detection FP16-INT8 - Device: CPUdcba60012001800240030002603.352609.572604.122608.391. (CXX) g++ options: -fPIC -fsigned-char -ffunction-sections -fdata-sections -O3 -fno-strict-overflow -fwrapv -shared -ldl

OpenBenchmarking.orgms, Fewer Is BetterOpenVINO 2023.2.devModel: Weld Porosity Detection FP16-INT8 - Device: CPUdcba2468106.116.106.116.10MIN: 3.18 / MAX: 11.79MIN: 3.18 / MAX: 11.91MIN: 3.19 / MAX: 13.98MIN: 3.19 / MAX: 11.011. (CXX) g++ options: -fPIC -fsigned-char -ffunction-sections -fdata-sections -O3 -fno-strict-overflow -fwrapv -shared -ldl

OpenBenchmarking.orgFPS, More Is BetterOpenVINO 2023.2.devModel: Person Vehicle Bike Detection FP16 - Device: CPUdcba300600900120015001572.561591.841587.741572.381. (CXX) g++ options: -fPIC -fsigned-char -ffunction-sections -fdata-sections -O3 -fno-strict-overflow -fwrapv -shared -ldl

OpenBenchmarking.orgms, Fewer Is BetterOpenVINO 2023.2.devModel: Person Vehicle Bike Detection FP16 - Device: CPUdcba1.13852.2773.41554.5545.69255.065.005.025.06MIN: 3.24 / MAX: 9.55MIN: 3.63 / MAX: 11.88MIN: 3.6 / MAX: 10.68MIN: 3.62 / MAX: 13.341. (CXX) g++ options: -fPIC -fsigned-char -ffunction-sections -fdata-sections -O3 -fno-strict-overflow -fwrapv -shared -ldl

OpenBenchmarking.orgFPS, More Is BetterOpenVINO 2023.2.devModel: Handwritten English Recognition FP16 - Device: CPUdcba160320480640800733.36733.81731.42739.561. (CXX) g++ options: -fPIC -fsigned-char -ffunction-sections -fdata-sections -O3 -fno-strict-overflow -fwrapv -shared -ldl

OpenBenchmarking.orgms, Fewer Is BetterOpenVINO 2023.2.devModel: Handwritten English Recognition FP16 - Device: CPUdcba51015202521.7921.7721.8521.61MIN: 14.67 / MAX: 31.51MIN: 17.91 / MAX: 28.95MIN: 14.62 / MAX: 38.4MIN: 15.02 / MAX: 30.511. (CXX) g++ options: -fPIC -fsigned-char -ffunction-sections -fdata-sections -O3 -fno-strict-overflow -fwrapv -shared -ldl

OpenBenchmarking.orgFPS, More Is BetterOpenVINO 2023.2.devModel: Age Gender Recognition Retail 0013 FP16 - Device: CPUdcba7K14K21K28K35K33491.8333482.5433483.5333511.791. (CXX) g++ options: -fPIC -fsigned-char -ffunction-sections -fdata-sections -O3 -fno-strict-overflow -fwrapv -shared -ldl

OpenBenchmarking.orgms, Fewer Is BetterOpenVINO 2023.2.devModel: Age Gender Recognition Retail 0013 FP16 - Device: CPUdcba0.09680.19360.29040.38720.4840.430.430.430.43MIN: 0.22 / MAX: 5.02MIN: 0.22 / MAX: 7.73MIN: 0.22 / MAX: 4.19MIN: 0.22 / MAX: 4.21. (CXX) g++ options: -fPIC -fsigned-char -ffunction-sections -fdata-sections -O3 -fno-strict-overflow -fwrapv -shared -ldl

OpenBenchmarking.orgFPS, More Is BetterOpenVINO 2023.2.devModel: Handwritten English Recognition FP16-INT8 - Device: CPUdcba130260390520650579.56587.47585.55584.101. (CXX) g++ options: -fPIC -fsigned-char -ffunction-sections -fdata-sections -O3 -fno-strict-overflow -fwrapv -shared -ldl

OpenBenchmarking.orgms, Fewer Is BetterOpenVINO 2023.2.devModel: Handwritten English Recognition FP16-INT8 - Device: CPUdcba61218243027.5727.2127.2927.36MIN: 20.3 / MAX: 33.35MIN: 22.22 / MAX: 34.96MIN: 21.85 / MAX: 35.83MIN: 19.64 / MAX: 35.391. (CXX) g++ options: -fPIC -fsigned-char -ffunction-sections -fdata-sections -O3 -fno-strict-overflow -fwrapv -shared -ldl

OpenBenchmarking.orgFPS, More Is BetterOpenVINO 2023.2.devModel: Age Gender Recognition Retail 0013 FP16-INT8 - Device: CPUdcba10K20K30K40K50K47453.4347255.3647316.1747376.591. (CXX) g++ options: -fPIC -fsigned-char -ffunction-sections -fdata-sections -O3 -fno-strict-overflow -fwrapv -shared -ldl

OpenBenchmarking.orgms, Fewer Is BetterOpenVINO 2023.2.devModel: Age Gender Recognition Retail 0013 FP16-INT8 - Device: CPUdcba0.06750.1350.20250.270.33750.290.300.290.29MIN: 0.17 / MAX: 7.66MIN: 0.17 / MAX: 7.08MIN: 0.17 / MAX: 7.59MIN: 0.17 / MAX: 7.871. (CXX) g++ options: -fPIC -fsigned-char -ffunction-sections -fdata-sections -O3 -fno-strict-overflow -fwrapv -shared -ldl

172 Results Shown

QuantLib:
  Multi-Threaded
  Single-Threaded
CloverLeaf:
  clover_bm
  clover_bm16
  clover_bm64_short
QMCPACK:
  H4_ae
  Li2_STO_ae
  LiH_ae_MSD
  simple-H2O
  O_ae_pyscf_UHF
  FeCO6_b3lyp_gms
FFmpeg:
  libx264 - Live
  libx265 - Live
  libx264 - Upload
  libx265 - Upload
  libx264 - Platform
  libx265 - Platform
  libx264 - Video On Demand
  libx265 - Video On Demand
DaCapo Benchmark:
  Jython
  Eclipse
  GraphChi
  Tradesoap
  Tradebeans
  Spring Boot
  Apache Kafka
  Apache Tomcat
  jMonkeyEngine
  Apache Cassandra
  Apache Xalan XSLT
  Batik SVG Toolkit
  H2 Database Engine
  FOP Print Formatter
  PMD Source Code Analyzer
  Apache Lucene Search Index
  Apache Lucene Search Engine
  Avrora AVR Simulation Framework
  BioJava Biological Data Framework
  Zxing 1D/2D Barcode Image Processing
  H2O In-Memory Platform For Machine Learning
WebP2 Image Encode:
  Default
  Quality 75, Compression Effort 7
  Quality 95, Compression Effort 7
  Quality 100, Compression Effort 5
  Quality 100, Lossless Compression
easyWave:
  e2Asean Grid + BengkuluSept2007 Source - 240
  e2Asean Grid + BengkuluSept2007 Source - 1200
Embree:
  Pathtracer - Crown
  Pathtracer ISPC - Crown
  Pathtracer - Asian Dragon
  Pathtracer - Asian Dragon Obj
  Pathtracer ISPC - Asian Dragon
  Pathtracer ISPC - Asian Dragon Obj
Intel Open Image Denoise:
  RT.hdr_alb_nrm.3840x2160 - CPU-Only
  RT.ldr_alb_nrm.3840x2160 - CPU-Only
  RTLightmap.hdr.4096x4096 - CPU-Only
OpenVKL:
  vklBenchmarkCPU ISPC
  vklBenchmarkCPU Scalar
Timed FFmpeg Compilation
Timed Gem5 Compilation
oneDNN:
  IP Shapes 1D - f32 - CPU
  IP Shapes 3D - f32 - CPU
  IP Shapes 1D - u8s8f32 - CPU
  IP Shapes 3D - u8s8f32 - CPU
  IP Shapes 1D - bf16bf16bf16 - CPU
  IP Shapes 3D - bf16bf16bf16 - 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
  Convolution Batch Shapes Auto - bf16bf16bf16 - CPU
  Deconvolution Batch shapes_1d - bf16bf16bf16 - CPU
  Deconvolution Batch shapes_3d - bf16bf16bf16 - CPU
  Recurrent Neural Network Inference - u8s8f32 - CPU
  Recurrent Neural Network Training - bf16bf16bf16 - CPU
  Recurrent Neural Network Inference - bf16bf16bf16 - CPU
OSPRay Studio:
  1 - 4K - 1 - Path Tracer - CPU
  2 - 4K - 1 - Path Tracer - CPU
  3 - 4K - 1 - Path Tracer - CPU
  1 - 4K - 16 - Path Tracer - CPU
  1 - 4K - 32 - Path Tracer - CPU
  2 - 4K - 16 - Path Tracer - CPU
  2 - 4K - 32 - Path Tracer - CPU
  3 - 4K - 16 - Path Tracer - CPU
  3 - 4K - 32 - Path Tracer - CPU
  1 - 1080p - 1 - Path Tracer - CPU
  2 - 1080p - 1 - Path Tracer - CPU
  3 - 1080p - 1 - Path Tracer - CPU
  1 - 1080p - 16 - Path Tracer - CPU
  1 - 1080p - 32 - Path Tracer - CPU
  2 - 1080p - 16 - Path Tracer - CPU
  2 - 1080p - 32 - Path Tracer - CPU
  3 - 1080p - 16 - Path Tracer - CPU
  3 - 1080p - 32 - Path Tracer - CPU
Cpuminer-Opt:
  Magi
  scrypt
  Deepcoin
  Ringcoin
  Blake-2 S
  Garlicoin
  Skeincoin
  Myriad-Groestl
  LBC, LBRY Credits
  Quad SHA-256, Pyrite
  Triple SHA-256, Onecoin
OpenSSL:
  SHA256
  SHA512
  RSA4096
  RSA4096
  ChaCha20
  AES-128-GCM
  AES-256-GCM
  ChaCha20-Poly1305
PyTorch:
  CPU - 1 - ResNet-50
  CPU - 1 - ResNet-152
  CPU - 16 - ResNet-50
  CPU - 32 - ResNet-50
  CPU - 64 - ResNet-50
  CPU - 16 - ResNet-152
  CPU - 256 - ResNet-50
  CPU - 32 - ResNet-152
  CPU - 512 - ResNet-50
  CPU - 64 - ResNet-152
  CPU - 256 - ResNet-152
  CPU - 512 - ResNet-152
  CPU - 1 - Efficientnet_v2_l
  CPU - 16 - Efficientnet_v2_l
  CPU - 32 - Efficientnet_v2_l
  CPU - 64 - Efficientnet_v2_l
  CPU - 256 - Efficientnet_v2_l
  CPU - 512 - Efficientnet_v2_l
OpenVINO:
  Face Detection FP16 - CPU:
    FPS
    ms
  Person Detection FP16 - CPU:
    FPS
    ms
  Person Detection FP32 - CPU:
    FPS
    ms
  Vehicle Detection FP16 - CPU:
    FPS
    ms
  Face Detection FP16-INT8 - CPU:
    FPS
    ms
  Face Detection Retail FP16 - CPU:
    FPS
    ms
  Road Segmentation ADAS FP16 - CPU:
    FPS
    ms
  Vehicle Detection FP16-INT8 - CPU:
    FPS
    ms
  Weld Porosity Detection FP16 - CPU:
    FPS
    ms
  Face Detection Retail FP16-INT8 - CPU:
    FPS
    ms
  Road Segmentation ADAS FP16-INT8 - CPU:
    FPS
    ms
  Machine Translation EN To DE FP16 - CPU:
    FPS
    ms
  Weld Porosity Detection FP16-INT8 - CPU:
    FPS
    ms
  Person Vehicle Bike Detection FP16 - CPU:
    FPS
    ms
  Handwritten English Recognition FP16 - CPU:
    FPS
    ms
  Age Gender Recognition Retail 0013 FP16 - CPU:
    FPS
    ms
  Handwritten English Recognition FP16-INT8 - CPU:
    FPS
    ms
  Age Gender Recognition Retail 0013 FP16-INT8 - CPU:
    FPS
    ms