eps

2 x AMD EPYC 9684X 96-Core testing with a AMD Titanite_4G (RTI1007B BIOS) and ASPEED on Ubuntu 23.10 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 2312241-NE-EPS60637430
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a
December 24 2023
  1 Day, 26 Minutes
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December 25 2023
  7 Hours, 39 Minutes
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epsOpenBenchmarking.orgPhoronix Test Suite2 x AMD EPYC 9684X 96-Core @ 2.55GHz (192 Cores / 384 Threads)AMD Titanite_4G (RTI1007B BIOS)AMD Device 14a41520GB3201GB Micron_7450_MTFDKCB3T2TFSASPEEDBroadcom NetXtreme BCM5720 PCIeUbuntu 23.106.5.0-13-generic (x86_64)GCC 13.2.0ext4800x600ProcessorMotherboardChipsetMemoryDiskGraphicsNetworkOSKernelCompilerFile-SystemScreen ResolutionEps PerformanceSystem 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,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-defaulted --enable-offload-targets=nvptx-none=/build/gcc-13-XYspKM/gcc-13-13.2.0/debian/tmp-nvptx/usr,amdgcn-amdhsa=/build/gcc-13-XYspKM/gcc-13-13.2.0/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: acpi-cpufreq performance (Boost: Enabled) - CPU Microcode: 0xa10113e - OpenJDK Runtime Environment (build 11.0.21+9-post-Ubuntu-0ubuntu123.10)- Python 3.11.6- 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 + 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

a vs. b ComparisonPhoronix Test SuiteBaseline+7.7%+7.7%+15.4%+15.4%+23.1%+23.1%+30.8%+30.8%7.7%5.3%4.3%4.3%2.7%2.1%13.1%2.3%3.1%9.6%2%2.4%6.7%7.4%2.5%2.7%6.6%10.5%9.6%4.1%9.7%2.7%11.7%3.4%30.8%11.9%4.6%CPU - 256 - ResNet-152CPU - 1 - Efficientnet_v2_lPreset 13 - Bosphorus 4KPreset 12 - Bosphorus 4KQ.1.C.E.53.7%CPU - 256 - ResNet-503.3%CPU - 1 - ResNet-152BLAS50 - Q2150 - Q1915.6%50 - Q1850 - Q165.3%50 - Q1550 - Q132.2%50 - Q1250 - Q1150 - Q074%50 - Q054.6%50 - Q043.9%50 - Q0313.4%50 - Q017.2%10 - Q1910 - Q1810 - Q1510 - Q1410 - Q137.6%10 - Q113.4%10 - Q1010 - Q092.8%10 - Q0810 - Q0610 - Q0514.7%10 - Q0410 - Q032.3%10 - Q011 - Q225.9%1 - Q198.5%1 - Q181 - Q171 - Q169.9%1 - Q153.4%1 - Q147.1%1 - Q139.6%1 - Q124.2%1 - Q111 - Q093.3%1 - Q071 - Q061 - Q051 - Q041 - Q012.9%PyTorchPyTorchSVT-AV1SVT-AV1WebP2 Image EncodePyTorchPyTorchLeelaChessZeroApache Spark TPC-HApache Spark TPC-HApache Spark TPC-HApache Spark TPC-HApache Spark TPC-HApache Spark TPC-HApache Spark TPC-HApache Spark TPC-HApache Spark TPC-HApache Spark TPC-HApache Spark TPC-HApache Spark TPC-HApache Spark TPC-HApache Spark TPC-HApache Spark TPC-HApache Spark TPC-HApache Spark TPC-HApache Spark TPC-HApache Spark TPC-HApache Spark TPC-HApache Spark TPC-HApache Spark TPC-HApache Spark TPC-HApache Spark TPC-HApache Spark TPC-HApache Spark TPC-HApache Spark TPC-HApache Spark TPC-HApache Spark TPC-HApache Spark TPC-HApache Spark TPC-HApache Spark TPC-HApache Spark TPC-HApache Spark TPC-HApache Spark TPC-HApache Spark TPC-HApache Spark TPC-HApache Spark TPC-HApache Spark TPC-HApache Spark TPC-HApache Spark TPC-HApache Spark TPC-HApache Spark TPC-Hab

epslczero: BLASlczero: Eigenpytorch: CPU - 256 - Efficientnet_v2_lpytorch: CPU - 16 - Efficientnet_v2_lpytorch: CPU - 32 - Efficientnet_v2_lspark-tpch: 50 - Q22spark-tpch: 50 - Q21spark-tpch: 50 - Q20spark-tpch: 50 - Q19spark-tpch: 50 - Q18spark-tpch: 50 - Q17spark-tpch: 50 - Q16spark-tpch: 50 - Q15spark-tpch: 50 - Q14spark-tpch: 50 - Q13spark-tpch: 50 - Q12spark-tpch: 50 - Q11spark-tpch: 50 - Q10spark-tpch: 50 - Q09spark-tpch: 50 - Q08spark-tpch: 50 - Q07spark-tpch: 50 - Q06spark-tpch: 50 - Q05spark-tpch: 50 - Q04spark-tpch: 50 - Q03spark-tpch: 50 - Q02spark-tpch: 50 - Q01spark-tpch: 50 - Geometric Mean Of All Queriesspark-tpch: 10 - Q22spark-tpch: 10 - Q21spark-tpch: 10 - Q20spark-tpch: 10 - Q19spark-tpch: 10 - Q18spark-tpch: 10 - Q17spark-tpch: 10 - Q16spark-tpch: 10 - Q15spark-tpch: 10 - Q14spark-tpch: 10 - Q13spark-tpch: 10 - Q12spark-tpch: 10 - Q11spark-tpch: 10 - Q10spark-tpch: 10 - Q09spark-tpch: 10 - Q08spark-tpch: 10 - Q07spark-tpch: 10 - Q06spark-tpch: 10 - Q05spark-tpch: 10 - Q04spark-tpch: 10 - Q03spark-tpch: 10 - Q02spark-tpch: 10 - Q01spark-tpch: 10 - Geometric Mean Of All Queriespytorch: CPU - 32 - ResNet-152pytorch: CPU - 16 - ResNet-152pytorch: CPU - 256 - ResNet-152webp2: Quality 100, Lossless Compressionpytorch: CPU - 1 - ResNet-50openssl: SHA512openssl: SHA256pytorch: CPU - 1 - Efficientnet_v2_lpytorch: CPU - 1 - ResNet-152pytorch: CPU - 256 - ResNet-50pytorch: CPU - 32 - ResNet-50pytorch: CPU - 16 - ResNet-50deepsparse: BERT-Large, NLP Question Answering - Synchronous Single-Streamdeepsparse: BERT-Large, NLP Question Answering - Synchronous Single-Streamdeepsparse: BERT-Large, NLP Question Answering - Asynchronous Multi-Streamdeepsparse: BERT-Large, NLP Question Answering - Asynchronous Multi-Streamspark-tpch: 1 - Q22spark-tpch: 1 - Q21spark-tpch: 1 - Q20spark-tpch: 1 - Q19spark-tpch: 1 - Q18spark-tpch: 1 - Q17spark-tpch: 1 - Q16spark-tpch: 1 - Q15spark-tpch: 1 - Q14spark-tpch: 1 - Q13spark-tpch: 1 - Q12spark-tpch: 1 - Q11spark-tpch: 1 - Q10spark-tpch: 1 - Q09spark-tpch: 1 - Q08spark-tpch: 1 - Q07spark-tpch: 1 - Q06spark-tpch: 1 - Q05spark-tpch: 1 - Q04spark-tpch: 1 - Q03spark-tpch: 1 - Q02spark-tpch: 1 - Q01spark-tpch: 1 - Geometric Mean Of All Queriesopenssl: RSA4096openssl: RSA4096webp2: Quality 95, Compression Effort 7deepsparse: NLP Text Classification, BERT base uncased SST2, Sparse INT8 - Synchronous Single-Streamdeepsparse: NLP Text Classification, BERT base uncased SST2, Sparse INT8 - Synchronous Single-Streamdeepsparse: NLP Document Classification, oBERT base uncased on IMDB - Asynchronous Multi-Streamdeepsparse: NLP Document Classification, oBERT base uncased on IMDB - Asynchronous Multi-Streamdeepsparse: BERT-Large, NLP Question Answering, Sparse INT8 - Asynchronous Multi-Streamdeepsparse: BERT-Large, NLP Question Answering, Sparse INT8 - Asynchronous Multi-Streamdeepsparse: NLP Token Classification, BERT base uncased conll2003 - Asynchronous Multi-Streamdeepsparse: NLP Token Classification, BERT base uncased conll2003 - Asynchronous Multi-Streamdeepsparse: NLP Text Classification, BERT base uncased SST2, Sparse INT8 - Asynchronous Multi-Streamdeepsparse: NLP Text Classification, BERT base uncased SST2, Sparse INT8 - Asynchronous Multi-Streamdeepsparse: NLP Token Classification, BERT base uncased conll2003 - Synchronous Single-Streamdeepsparse: NLP Token Classification, BERT base uncased conll2003 - Synchronous Single-Streamdeepsparse: BERT-Large, NLP Question Answering, Sparse INT8 - Synchronous Single-Streamdeepsparse: BERT-Large, NLP Question Answering, Sparse INT8 - Synchronous Single-Streamdeepsparse: NLP Document Classification, oBERT base uncased on IMDB - Synchronous Single-Streamdeepsparse: NLP Document Classification, oBERT base uncased on IMDB - Synchronous Single-Streamdeepsparse: CV Segmentation, 90% Pruned YOLACT Pruned - Asynchronous Multi-Streamdeepsparse: CV Segmentation, 90% Pruned YOLACT Pruned - Asynchronous Multi-Streamdeepsparse: NLP Text Classification, DistilBERT mnli - Asynchronous Multi-Streamdeepsparse: NLP Text Classification, DistilBERT mnli - Asynchronous Multi-Streamdeepsparse: CV Segmentation, 90% Pruned YOLACT Pruned - Synchronous Single-Streamdeepsparse: CV Segmentation, 90% Pruned YOLACT Pruned - Synchronous Single-Streamdeepsparse: NLP Text Classification, DistilBERT mnli - Synchronous Single-Streamdeepsparse: NLP Text Classification, DistilBERT mnli - Synchronous Single-Streamdeepsparse: CV Detection, YOLOv5s COCO - Asynchronous Multi-Streamdeepsparse: CV Detection, YOLOv5s COCO - Asynchronous Multi-Streamdeepsparse: CV Detection, YOLOv5s COCO, Sparse INT8 - Asynchronous Multi-Streamdeepsparse: CV Detection, YOLOv5s COCO, Sparse INT8 - Asynchronous Multi-Streamdeepsparse: ResNet-50, Baseline - Asynchronous Multi-Streamdeepsparse: ResNet-50, Baseline - Asynchronous Multi-Streamdeepsparse: ResNet-50, Sparse INT8 - Synchronous Single-Streamdeepsparse: ResNet-50, Sparse INT8 - Synchronous Single-Streamdeepsparse: ResNet-50, Sparse INT8 - Asynchronous Multi-Streamdeepsparse: ResNet-50, Sparse INT8 - Asynchronous Multi-Streamdeepsparse: CV Classification, ResNet-50 ImageNet - Asynchronous Multi-Streamdeepsparse: CV Classification, ResNet-50 ImageNet - Asynchronous Multi-Streamdeepsparse: CV Detection, YOLOv5s COCO - Synchronous Single-Streamdeepsparse: CV Detection, YOLOv5s COCO - Synchronous Single-Streamdeepsparse: CV Detection, YOLOv5s COCO, Sparse INT8 - Synchronous Single-Streamdeepsparse: CV Detection, YOLOv5s COCO, Sparse INT8 - Synchronous Single-Streamdeepsparse: CV Classification, ResNet-50 ImageNet - Synchronous Single-Streamdeepsparse: CV Classification, ResNet-50 ImageNet - Synchronous Single-Streamdeepsparse: ResNet-50, Baseline - Synchronous Single-Streamdeepsparse: ResNet-50, Baseline - Synchronous Single-Streamsvt-av1: Preset 13 - Bosphorus 4Kxmrig: GhostRider - 1Mwebp2: Quality 75, Compression Effort 7java-scimark2: Compositesvt-av1: Preset 4 - Bosphorus 4Ksvt-av1: Preset 4 - Bosphorus 1080psvt-av1: Preset 8 - Bosphorus 4Kxmrig: CryptoNight-Heavy - 1Mxmrig: CryptoNight-Femto UPX2 - 1Mxmrig: Monero - 1Mxmrig: KawPow - 1Mxmrig: Wownero - 1Msvt-av1: Preset 12 - Bosphorus 4Ksvt-av1: Preset 8 - Bosphorus 1080pwebp2: Quality 100, Compression Effort 5webp2: Defaultsvt-av1: Preset 12 - Bosphorus 1080psvt-av1: Preset 13 - Bosphorus 1080pjava-scimark2: Jacobi Successive Over-Relaxationjava-scimark2: Dense LU Matrix Factorizationjava-scimark2: Sparse Matrix Multiplyjava-scimark2: Fast Fourier Transformjava-scimark2: Monte Carloab8537042.322.322.3210.6932563887.8952891020.7987613710.4528725934.5130564324.3092791214.215703979.7773386612.7045501112.7590141319.4053777113.5802825324.3600374836.6645851126.7353528324.857111615.9030920729.8362789120.9959831226.1878871914.2548720012.0079561919.587458076.0541189532.9071502711.435608236.2067783718.4697119412.770445506.871312945.841380767.076223697.377283739.944004388.0029234915.1748809821.9067020415.5182476114.652009332.0510474516.4436562912.3457120313.973087637.431042837.5888915110.721502088.908.938.960.1123.57916309254732818698957606.4010.1621.2921.0021.1631.215432.0229607.5664156.41591.007690479.645312313.057396170.790923955.628538452.959939241.381472592.501859662.064853311.588159362.175426481.273381353.813596655.709694072.655846444.010448060.468229154.131221613.925257453.864421842.061790714.320060812.449649163244390.398622.00.455.2377190.7999715.0362132.658036.75082608.0090719.2814132.048517.30235540.626820.615748.491714.642268.265520.634548.4476383.2004248.577084.25191136.710515.318365.20704.4503224.5798122.0312784.5178120.2065796.071354.50641758.59311.2413804.17845.595517108.463454.40971761.40414.7188211.74484.7126212.09554.8022208.12004.7637209.7998176.67031859.70.833984.628.24821.42486.434123041.6123199.0123352.8123558.6131141.9178.910165.1046.519.48571.875635.8101703.4213358.532809.01420.741631.428717152.282.342.3210.8741006977.7067565921.0538444512.0859279633.7419815124.5578899414.975358019.4828777312.5676708213.0449647917.7000179313.3120002724.6858558736.6652679426.6290950825.860551835.8838248331.2005977621.816757229.6859054614.5304679912.8683500319.564756586.0443091432.7015495311.539661416.060416717.3137016313.013741496.952706815.438705926.906023037.9408378610.038290028.2781429314.7771949822.5255279514.5576934814.896059041.855959318.8612918911.2624216114.289846427.392459877.2882671410.657939428.988.979.650.1123.12918359614702822111754006.7410.4320.6021.0921.5731.257531.9795607.5735156.42831.066792139.559095383.050016880.857975965.131711482.883481981.517799142.587141752.211469651.740741612.266416071.139986873.812455425.897758482.609078173.877902750.358015573.692176343.754272463.866108182.082242014.446579462.495177473243345.298528.80.455.2296191.0971717.5936132.271936.91462596.0961717.9791132.421917.30195540.51720.683748.33214.642668.263620.68648.3264382.5561249.498384.24911136.643915.365365.00794.4341225.4047121.6067786.8905120.0373797.412454.55461756.55691.2404804.75285.615917047.63954.48591759.07464.718211.77294.7117212.13054.7775209.19554.829206.969184.34731728.90.823996.768.20821.31386.841123777.7122070.3122971123411.1131613.6186.609162.5616.289.63569.955639.0881703.2513434.092792.09421.911632.45OpenBenchmarking.org

LeelaChessZero

LeelaChessZero (lc0 / lczero) is a chess engine automated vian neural networks. This test profile can be used for OpenCL, CUDA + cuDNN, and BLAS (CPU-based) benchmarking. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgNodes Per Second, More Is BetterLeelaChessZero 0.30Backend: BLASba2004006008001000SE +/- 18.54, N = 98718531. (CXX) g++ options: -flto -pthread
OpenBenchmarking.orgNodes Per Second, More Is BetterLeelaChessZero 0.30Backend: BLASba150300450600750Min: 755 / Avg: 852.78 / Max: 9491. (CXX) g++ options: -flto -pthread

OpenBenchmarking.orgNodes Per Second, More Is BetterLeelaChessZero 0.30Backend: Eigenba150300450600750SE +/- 17.59, N = 87157041. (CXX) g++ options: -flto -pthread
OpenBenchmarking.orgNodes Per Second, More Is BetterLeelaChessZero 0.30Backend: Eigenba130260390520650Min: 624 / Avg: 704 / Max: 7751. (CXX) g++ options: -flto -pthread

PyTorch

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.1Device: CPU - Batch Size: 256 - Model: Efficientnet_v2_lab0.5221.0441.5662.0882.61SE +/- 0.00, N = 32.322.28MIN: 1.83 / MAX: 2.8MIN: 1.71 / MAX: 2.84
OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.1Device: CPU - Batch Size: 256 - Model: Efficientnet_v2_lab246810Min: 2.31 / Avg: 2.32 / Max: 2.32

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.1Device: CPU - Batch Size: 16 - Model: Efficientnet_v2_lba0.52651.0531.57952.1062.6325SE +/- 0.01, N = 32.342.32MIN: 1.78 / MAX: 2.78MIN: 1.77 / MAX: 2.81
OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.1Device: CPU - Batch Size: 16 - Model: Efficientnet_v2_lba246810Min: 2.31 / Avg: 2.32 / Max: 2.33

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.1Device: CPU - Batch Size: 32 - Model: Efficientnet_v2_lba0.5221.0441.5662.0882.61SE +/- 0.01, N = 32.322.32MIN: 1.93 / MAX: 2.71MIN: 1.86 / MAX: 2.8
OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.1Device: CPU - Batch Size: 32 - Model: Efficientnet_v2_lba246810Min: 2.31 / Avg: 2.32 / Max: 2.34

Apache Spark TPC-H

This is a benchmark of Apache Spark using TPC-H data-set. Apache Spark is an open-source unified analytics engine for large-scale data processing and dealing with big data. This test profile benchmarks the Apache Spark in a single-system configuration using spark-submit. The test makes use of https://github.com/ssavvides/tpch-spark/ for facilitating the TPC-H benchmark. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgSeconds, Fewer Is BetterApache Spark TPC-H 3.5Scale Factor: 50 - Q22ab3691215SE +/- 0.12, N = 310.6910.87
OpenBenchmarking.orgSeconds, Fewer Is BetterApache Spark TPC-H 3.5Scale Factor: 50 - Q22ab3691215Min: 10.5 / Avg: 10.69 / Max: 10.92

OpenBenchmarking.orgSeconds, Fewer Is BetterApache Spark TPC-H 3.5Scale Factor: 50 - Q21ba20406080100SE +/- 7.93, N = 377.7187.90
OpenBenchmarking.orgSeconds, Fewer Is BetterApache Spark TPC-H 3.5Scale Factor: 50 - Q21ba20406080100Min: 78.37 / Avg: 87.9 / Max: 103.64

OpenBenchmarking.orgSeconds, Fewer Is BetterApache Spark TPC-H 3.5Scale Factor: 50 - Q20ab510152025SE +/- 0.10, N = 320.8021.05
OpenBenchmarking.orgSeconds, Fewer Is BetterApache Spark TPC-H 3.5Scale Factor: 50 - Q20ab510152025Min: 20.61 / Avg: 20.8 / Max: 20.9

OpenBenchmarking.orgSeconds, Fewer Is BetterApache Spark TPC-H 3.5Scale Factor: 50 - Q19ab3691215SE +/- 0.12, N = 310.4512.09
OpenBenchmarking.orgSeconds, Fewer Is BetterApache Spark TPC-H 3.5Scale Factor: 50 - Q19ab48121620Min: 10.29 / Avg: 10.45 / Max: 10.7

OpenBenchmarking.orgSeconds, Fewer Is BetterApache Spark TPC-H 3.5Scale Factor: 50 - Q18ba816243240SE +/- 0.33, N = 333.7434.51
OpenBenchmarking.orgSeconds, Fewer Is BetterApache Spark TPC-H 3.5Scale Factor: 50 - Q18ba714212835Min: 34 / Avg: 34.51 / Max: 35.13

OpenBenchmarking.orgSeconds, Fewer Is BetterApache Spark TPC-H 3.5Scale Factor: 50 - Q17ab612182430SE +/- 0.55, N = 324.3124.56
OpenBenchmarking.orgSeconds, Fewer Is BetterApache Spark TPC-H 3.5Scale Factor: 50 - Q17ab612182430Min: 23.46 / Avg: 24.31 / Max: 25.35

OpenBenchmarking.orgSeconds, Fewer Is BetterApache Spark TPC-H 3.5Scale Factor: 50 - Q16ab48121620SE +/- 0.26, N = 314.2214.98
OpenBenchmarking.orgSeconds, Fewer Is BetterApache Spark TPC-H 3.5Scale Factor: 50 - Q16ab48121620Min: 13.89 / Avg: 14.22 / Max: 14.72

OpenBenchmarking.orgSeconds, Fewer Is BetterApache Spark TPC-H 3.5Scale Factor: 50 - Q15ba3691215SE +/- 0.05343306, N = 39.482877739.77733866
OpenBenchmarking.orgSeconds, Fewer Is BetterApache Spark TPC-H 3.5Scale Factor: 50 - Q15ba3691215Min: 9.71 / Avg: 9.78 / Max: 9.88

OpenBenchmarking.orgSeconds, Fewer Is BetterApache Spark TPC-H 3.5Scale Factor: 50 - Q14ba3691215SE +/- 0.22, N = 312.5712.70
OpenBenchmarking.orgSeconds, Fewer Is BetterApache Spark TPC-H 3.5Scale Factor: 50 - Q14ba48121620Min: 12.34 / Avg: 12.7 / Max: 13.1

OpenBenchmarking.orgSeconds, Fewer Is BetterApache Spark TPC-H 3.5Scale Factor: 50 - Q13ab3691215SE +/- 0.08, N = 312.7613.04
OpenBenchmarking.orgSeconds, Fewer Is BetterApache Spark TPC-H 3.5Scale Factor: 50 - Q13ab48121620Min: 12.6 / Avg: 12.76 / Max: 12.85

OpenBenchmarking.orgSeconds, Fewer Is BetterApache Spark TPC-H 3.5Scale Factor: 50 - Q12ba510152025SE +/- 1.19, N = 317.7019.41
OpenBenchmarking.orgSeconds, Fewer Is BetterApache Spark TPC-H 3.5Scale Factor: 50 - Q12ba510152025Min: 17.49 / Avg: 19.41 / Max: 21.59

OpenBenchmarking.orgSeconds, Fewer Is BetterApache Spark TPC-H 3.5Scale Factor: 50 - Q11ba3691215SE +/- 0.32, N = 313.3113.58
OpenBenchmarking.orgSeconds, Fewer Is BetterApache Spark TPC-H 3.5Scale Factor: 50 - Q11ba48121620Min: 13.06 / Avg: 13.58 / Max: 14.17

OpenBenchmarking.orgSeconds, Fewer Is BetterApache Spark TPC-H 3.5Scale Factor: 50 - Q10ab612182430SE +/- 0.32, N = 324.3624.69
OpenBenchmarking.orgSeconds, Fewer Is BetterApache Spark TPC-H 3.5Scale Factor: 50 - Q10ab612182430Min: 23.74 / Avg: 24.36 / Max: 24.8

OpenBenchmarking.orgSeconds, Fewer Is BetterApache Spark TPC-H 3.5Scale Factor: 50 - Q09ab816243240SE +/- 0.34, N = 336.6636.67
OpenBenchmarking.orgSeconds, Fewer Is BetterApache Spark TPC-H 3.5Scale Factor: 50 - Q09ab816243240Min: 36.17 / Avg: 36.66 / Max: 37.31

OpenBenchmarking.orgSeconds, Fewer Is BetterApache Spark TPC-H 3.5Scale Factor: 50 - Q08ba612182430SE +/- 0.26, N = 326.6326.74
OpenBenchmarking.orgSeconds, Fewer Is BetterApache Spark TPC-H 3.5Scale Factor: 50 - Q08ba612182430Min: 26.39 / Avg: 26.74 / Max: 27.24

OpenBenchmarking.orgSeconds, Fewer Is BetterApache Spark TPC-H 3.5Scale Factor: 50 - Q07ab612182430SE +/- 0.23, N = 324.8625.86
OpenBenchmarking.orgSeconds, Fewer Is BetterApache Spark TPC-H 3.5Scale Factor: 50 - Q07ab612182430Min: 24.48 / Avg: 24.86 / Max: 25.28

OpenBenchmarking.orgSeconds, Fewer Is BetterApache Spark TPC-H 3.5Scale Factor: 50 - Q06ba1.32822.65643.98465.31286.641SE +/- 0.04522799, N = 35.883824835.90309207
OpenBenchmarking.orgSeconds, Fewer Is BetterApache Spark TPC-H 3.5Scale Factor: 50 - Q06ba246810Min: 5.82 / Avg: 5.9 / Max: 5.98

OpenBenchmarking.orgSeconds, Fewer Is BetterApache Spark TPC-H 3.5Scale Factor: 50 - Q05ab714212835SE +/- 0.67, N = 329.8431.20
OpenBenchmarking.orgSeconds, Fewer Is BetterApache Spark TPC-H 3.5Scale Factor: 50 - Q05ab714212835Min: 29.14 / Avg: 29.84 / Max: 31.17

OpenBenchmarking.orgSeconds, Fewer Is BetterApache Spark TPC-H 3.5Scale Factor: 50 - Q04ab510152025SE +/- 0.46, N = 321.0021.82
OpenBenchmarking.orgSeconds, Fewer Is BetterApache Spark TPC-H 3.5Scale Factor: 50 - Q04ab510152025Min: 20.09 / Avg: 21 / Max: 21.56

OpenBenchmarking.orgSeconds, Fewer Is BetterApache Spark TPC-H 3.5Scale Factor: 50 - Q03ab714212835SE +/- 0.94, N = 326.1929.69
OpenBenchmarking.orgSeconds, Fewer Is BetterApache Spark TPC-H 3.5Scale Factor: 50 - Q03ab714212835Min: 24.85 / Avg: 26.19 / Max: 28

OpenBenchmarking.orgSeconds, Fewer Is BetterApache Spark TPC-H 3.5Scale Factor: 50 - Q02ab48121620SE +/- 0.35, N = 314.2514.53
OpenBenchmarking.orgSeconds, Fewer Is BetterApache Spark TPC-H 3.5Scale Factor: 50 - Q02ab48121620Min: 13.66 / Avg: 14.25 / Max: 14.86

OpenBenchmarking.orgSeconds, Fewer Is BetterApache Spark TPC-H 3.5Scale Factor: 50 - Q01ab3691215SE +/- 0.21, N = 312.0112.87
OpenBenchmarking.orgSeconds, Fewer Is BetterApache Spark TPC-H 3.5Scale Factor: 50 - Q01ab48121620Min: 11.59 / Avg: 12.01 / Max: 12.24

OpenBenchmarking.orgSeconds, Fewer Is BetterApache Spark TPC-H 3.5Scale Factor: 50 - Geometric Mean Of All Queriesba510152025SE +/- 0.05, N = 319.5619.59MIN: 9.48 / MAX: 77.71MIN: 9.71 / MAX: 103.64
OpenBenchmarking.orgSeconds, Fewer Is BetterApache Spark TPC-H 3.5Scale Factor: 50 - Geometric Mean Of All Queriesba510152025Min: 19.5 / Avg: 19.59 / Max: 19.68

OpenBenchmarking.orgSeconds, Fewer Is BetterApache Spark TPC-H 3.5Scale Factor: 10 - Q22ba246810SE +/- 0.13164085, N = 36.044309146.05411895
OpenBenchmarking.orgSeconds, Fewer Is BetterApache Spark TPC-H 3.5Scale Factor: 10 - Q22ba246810Min: 5.82 / Avg: 6.05 / Max: 6.28

OpenBenchmarking.orgSeconds, Fewer Is BetterApache Spark TPC-H 3.5Scale Factor: 10 - Q21ba816243240SE +/- 0.11, N = 332.7032.91
OpenBenchmarking.orgSeconds, Fewer Is BetterApache Spark TPC-H 3.5Scale Factor: 10 - Q21ba714212835Min: 32.7 / Avg: 32.91 / Max: 33.03

OpenBenchmarking.orgSeconds, Fewer Is BetterApache Spark TPC-H 3.5Scale Factor: 10 - Q20ab3691215SE +/- 0.14, N = 311.4411.54
OpenBenchmarking.orgSeconds, Fewer Is BetterApache Spark TPC-H 3.5Scale Factor: 10 - Q20ab3691215Min: 11.15 / Avg: 11.44 / Max: 11.6

OpenBenchmarking.orgSeconds, Fewer Is BetterApache Spark TPC-H 3.5Scale Factor: 10 - Q19ba246810SE +/- 0.15363169, N = 36.060416706.20677837
OpenBenchmarking.orgSeconds, Fewer Is BetterApache Spark TPC-H 3.5Scale Factor: 10 - Q19ba246810Min: 6.03 / Avg: 6.21 / Max: 6.51

OpenBenchmarking.orgSeconds, Fewer Is BetterApache Spark TPC-H 3.5Scale Factor: 10 - Q18ba510152025SE +/- 0.50, N = 317.3118.47
OpenBenchmarking.orgSeconds, Fewer Is BetterApache Spark TPC-H 3.5Scale Factor: 10 - Q18ba510152025Min: 17.58 / Avg: 18.47 / Max: 19.32

OpenBenchmarking.orgSeconds, Fewer Is BetterApache Spark TPC-H 3.5Scale Factor: 10 - Q17ab3691215SE +/- 0.07, N = 312.7713.01
OpenBenchmarking.orgSeconds, Fewer Is BetterApache Spark TPC-H 3.5Scale Factor: 10 - Q17ab48121620Min: 12.67 / Avg: 12.77 / Max: 12.91

OpenBenchmarking.orgSeconds, Fewer Is BetterApache Spark TPC-H 3.5Scale Factor: 10 - Q16ab246810SE +/- 0.33462632, N = 36.871312946.95270681
OpenBenchmarking.orgSeconds, Fewer Is BetterApache Spark TPC-H 3.5Scale Factor: 10 - Q16ab3691215Min: 6.24 / Avg: 6.87 / Max: 7.38

OpenBenchmarking.orgSeconds, Fewer Is BetterApache Spark TPC-H 3.5Scale Factor: 10 - Q15ba1.31432.62863.94295.25726.5715SE +/- 0.10221447, N = 35.438705925.84138076
OpenBenchmarking.orgSeconds, Fewer Is BetterApache Spark TPC-H 3.5Scale Factor: 10 - Q15ba246810Min: 5.7 / Avg: 5.84 / Max: 6.04

OpenBenchmarking.orgSeconds, Fewer Is BetterApache Spark TPC-H 3.5Scale Factor: 10 - Q14ba246810SE +/- 0.33271668, N = 36.906023037.07622369
OpenBenchmarking.orgSeconds, Fewer Is BetterApache Spark TPC-H 3.5Scale Factor: 10 - Q14ba3691215Min: 6.63 / Avg: 7.08 / Max: 7.73

OpenBenchmarking.orgSeconds, Fewer Is BetterApache Spark TPC-H 3.5Scale Factor: 10 - Q13ab246810SE +/- 0.09689769, N = 37.377283737.94083786
OpenBenchmarking.orgSeconds, Fewer Is BetterApache Spark TPC-H 3.5Scale Factor: 10 - Q13ab3691215Min: 7.2 / Avg: 7.38 / Max: 7.54

OpenBenchmarking.orgSeconds, Fewer Is BetterApache Spark TPC-H 3.5Scale Factor: 10 - Q12ab3691215SE +/- 0.16460967, N = 39.9440043810.03829002
OpenBenchmarking.orgSeconds, Fewer Is BetterApache Spark TPC-H 3.5Scale Factor: 10 - Q12ab3691215Min: 9.67 / Avg: 9.94 / Max: 10.24

OpenBenchmarking.orgSeconds, Fewer Is BetterApache Spark TPC-H 3.5Scale Factor: 10 - Q11ab246810SE +/- 0.04584382, N = 38.002923498.27814293
OpenBenchmarking.orgSeconds, Fewer Is BetterApache Spark TPC-H 3.5Scale Factor: 10 - Q11ab3691215Min: 7.95 / Avg: 8 / Max: 8.09

OpenBenchmarking.orgSeconds, Fewer Is BetterApache Spark TPC-H 3.5Scale Factor: 10 - Q10ba48121620SE +/- 0.31, N = 314.7815.17
OpenBenchmarking.orgSeconds, Fewer Is BetterApache Spark TPC-H 3.5Scale Factor: 10 - Q10ba48121620Min: 14.55 / Avg: 15.17 / Max: 15.51

OpenBenchmarking.orgSeconds, Fewer Is BetterApache Spark TPC-H 3.5Scale Factor: 10 - Q09ab510152025SE +/- 0.51, N = 321.9122.53
OpenBenchmarking.orgSeconds, Fewer Is BetterApache Spark TPC-H 3.5Scale Factor: 10 - Q09ab510152025Min: 21.28 / Avg: 21.91 / Max: 22.91

OpenBenchmarking.orgSeconds, Fewer Is BetterApache Spark TPC-H 3.5Scale Factor: 10 - Q08ba48121620SE +/- 0.41, N = 314.5615.52
OpenBenchmarking.orgSeconds, Fewer Is BetterApache Spark TPC-H 3.5Scale Factor: 10 - Q08ba48121620Min: 14.72 / Avg: 15.52 / Max: 16.06

OpenBenchmarking.orgSeconds, Fewer Is BetterApache Spark TPC-H 3.5Scale Factor: 10 - Q07ab48121620SE +/- 0.33, N = 314.6514.90
OpenBenchmarking.orgSeconds, Fewer Is BetterApache Spark TPC-H 3.5Scale Factor: 10 - Q07ab48121620Min: 14.01 / Avg: 14.65 / Max: 15.07

OpenBenchmarking.orgSeconds, Fewer Is BetterApache Spark TPC-H 3.5Scale Factor: 10 - Q06ba0.46150.9231.38451.8462.3075SE +/- 0.23574646, N = 31.855959302.05104745
OpenBenchmarking.orgSeconds, Fewer Is BetterApache Spark TPC-H 3.5Scale Factor: 10 - Q06ba246810Min: 1.72 / Avg: 2.05 / Max: 2.51

OpenBenchmarking.orgSeconds, Fewer Is BetterApache Spark TPC-H 3.5Scale Factor: 10 - Q05ab510152025SE +/- 0.48, N = 316.4418.86
OpenBenchmarking.orgSeconds, Fewer Is BetterApache Spark TPC-H 3.5Scale Factor: 10 - Q05ab510152025Min: 15.72 / Avg: 16.44 / Max: 17.34

OpenBenchmarking.orgSeconds, Fewer Is BetterApache Spark TPC-H 3.5Scale Factor: 10 - Q04ba3691215SE +/- 0.21, N = 311.2612.35
OpenBenchmarking.orgSeconds, Fewer Is BetterApache Spark TPC-H 3.5Scale Factor: 10 - Q04ba48121620Min: 11.97 / Avg: 12.35 / Max: 12.71

OpenBenchmarking.orgSeconds, Fewer Is BetterApache Spark TPC-H 3.5Scale Factor: 10 - Q03ab48121620SE +/- 0.31, N = 313.9714.29
OpenBenchmarking.orgSeconds, Fewer Is BetterApache Spark TPC-H 3.5Scale Factor: 10 - Q03ab48121620Min: 13.43 / Avg: 13.97 / Max: 14.49

OpenBenchmarking.orgSeconds, Fewer Is BetterApache Spark TPC-H 3.5Scale Factor: 10 - Q02ba246810SE +/- 0.13824959, N = 37.392459877.43104283
OpenBenchmarking.orgSeconds, Fewer Is BetterApache Spark TPC-H 3.5Scale Factor: 10 - Q02ba3691215Min: 7.22 / Avg: 7.43 / Max: 7.69

OpenBenchmarking.orgSeconds, Fewer Is BetterApache Spark TPC-H 3.5Scale Factor: 10 - Q01ba246810SE +/- 0.23898111, N = 37.288267147.58889151
OpenBenchmarking.orgSeconds, Fewer Is BetterApache Spark TPC-H 3.5Scale Factor: 10 - Q01ba3691215Min: 7.28 / Avg: 7.59 / Max: 8.06

OpenBenchmarking.orgSeconds, Fewer Is BetterApache Spark TPC-H 3.5Scale Factor: 10 - Geometric Mean Of All Queriesba3691215SE +/- 0.02, N = 310.6610.72MIN: 5.44 / MAX: 32.7MIN: 5.7 / MAX: 33.03
OpenBenchmarking.orgSeconds, Fewer Is BetterApache Spark TPC-H 3.5Scale Factor: 10 - Geometric Mean Of All Queriesba3691215Min: 10.7 / Avg: 10.72 / Max: 10.76

PyTorch

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.1Device: CPU - Batch Size: 32 - Model: ResNet-152ba3691215SE +/- 0.10, N = 38.988.90MIN: 5.1 / MAX: 9.29MIN: 4.8 / MAX: 9.23
OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.1Device: CPU - Batch Size: 32 - Model: ResNet-152ba3691215Min: 8.76 / Avg: 8.9 / Max: 9.09

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.1Device: CPU - Batch Size: 16 - Model: ResNet-152ba3691215SE +/- 0.10, N = 38.978.93MIN: 4.96 / MAX: 9.11MIN: 4.75 / MAX: 9.39
OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.1Device: CPU - Batch Size: 16 - Model: ResNet-152ba3691215Min: 8.79 / Avg: 8.93 / Max: 9.13

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.1Device: CPU - Batch Size: 256 - Model: ResNet-152ba3691215SE +/- 0.05, N = 39.658.96MIN: 4.98 / MAX: 9.85MIN: 4.84 / MAX: 9.24
OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.1Device: CPU - Batch Size: 256 - Model: ResNet-152ba3691215Min: 8.87 / Avg: 8.96 / Max: 9.06

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: Quality 100, Lossless Compressionba0.02480.04960.07440.09920.124SE +/- 0.00, N = 30.110.111. (CXX) g++ options: -msse4.2 -fno-rtti -O3 -ldl
OpenBenchmarking.orgMP/s, More Is BetterWebP2 Image Encode 20220823Encode Settings: Quality 100, Lossless Compressionba12345Min: 0.11 / Avg: 0.11 / Max: 0.111. (CXX) g++ options: -msse4.2 -fno-rtti -O3 -ldl

PyTorch

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.1Device: CPU - Batch Size: 1 - Model: ResNet-50ab612182430SE +/- 0.19, N = 1523.5723.12MIN: 11.38 / MAX: 25.62MIN: 12.17 / MAX: 24.33
OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.1Device: CPU - Batch Size: 1 - Model: ResNet-50ab612182430Min: 21.87 / Avg: 23.57 / Max: 24.85

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.

Algorithm: AES-256-GCM

a: The test run did not produce a result. E: 40270E64087F0000:error:1C800066:Provider routines:ossl_gcm_stream_update:cipher operation failed:../providers/implementations/ciphers/ciphercommon_gcm.c:320:

b: The test run did not produce a result. E: 408712FE017F0000:error:1C800066:Provider routines:ossl_gcm_stream_update:cipher operation failed:../providers/implementations/ciphers/ciphercommon_gcm.c:320:

Algorithm: AES-128-GCM

a: The test run did not produce a result. E: 4097A6F7B77F0000:error:1C800066:Provider routines:ossl_gcm_stream_update:cipher operation failed:../providers/implementations/ciphers/ciphercommon_gcm.c:320:

b: The test run did not produce a result. E: 40B7EFA3BE7F0000:error:1C800066:Provider routines:ossl_gcm_stream_update:cipher operation failed:../providers/implementations/ciphers/ciphercommon_gcm.c:320:

OpenBenchmarking.orgbyte/s, More Is BetterOpenSSLAlgorithm: SHA512ba20000M40000M60000M80000M100000MSE +/- 191332047.54, N = 391835961470916309254731. OpenSSL 3.0.10 1 Aug 2023 (Library: OpenSSL 3.0.10 1 Aug 2023)
OpenBenchmarking.orgbyte/s, More Is BetterOpenSSLAlgorithm: SHA512ba16000M32000M48000M64000M80000MMin: 91369558010 / Avg: 91630925473.33 / Max: 920036611501. OpenSSL 3.0.10 1 Aug 2023 (Library: OpenSSL 3.0.10 1 Aug 2023)

Algorithm: ChaCha20-Poly1305

a: The test run did not produce a result.

b: The test run did not produce a result.

Algorithm: ChaCha20

a: The test run did not produce a result.

b: The test run did not produce a result.

OpenBenchmarking.orgbyte/s, More Is BetterOpenSSLAlgorithm: SHA256ba60000M120000M180000M240000M300000MSE +/- 548972949.20, N = 32822111754002818698957601. OpenSSL 3.0.10 1 Aug 2023 (Library: OpenSSL 3.0.10 1 Aug 2023)
OpenBenchmarking.orgbyte/s, More Is BetterOpenSSLAlgorithm: SHA256ba50000M100000M150000M200000M250000MMin: 281109203760 / Avg: 281869895760 / Max: 2829358981301. OpenSSL 3.0.10 1 Aug 2023 (Library: OpenSSL 3.0.10 1 Aug 2023)

PyTorch

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.1Device: CPU - Batch Size: 1 - Model: Efficientnet_v2_lba246810SE +/- 0.05, N = 36.746.40MIN: 3.48 / MAX: 6.89MIN: 2.93 / MAX: 6.73
OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.1Device: CPU - Batch Size: 1 - Model: Efficientnet_v2_lba3691215Min: 6.35 / Avg: 6.4 / Max: 6.5

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.1Device: CPU - Batch Size: 1 - Model: ResNet-152ba3691215SE +/- 0.08, N = 310.4310.16MIN: 4.8 / MAX: 11.36MIN: 4.56 / MAX: 10.94
OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.1Device: CPU - Batch Size: 1 - Model: ResNet-152ba3691215Min: 10.01 / Avg: 10.16 / Max: 10.28

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.1Device: CPU - Batch Size: 256 - Model: ResNet-50ab510152025SE +/- 0.31, N = 321.2920.60MIN: 13.22 / MAX: 22.39MIN: 13.89 / MAX: 21.35
OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.1Device: CPU - Batch Size: 256 - Model: ResNet-50ab510152025Min: 20.78 / Avg: 21.29 / Max: 21.84

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.1Device: CPU - Batch Size: 32 - Model: ResNet-50ba510152025SE +/- 0.20, N = 321.0921.00MIN: 13.93 / MAX: 21.71MIN: 11.39 / MAX: 21.87
OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.1Device: CPU - Batch Size: 32 - Model: ResNet-50ba510152025Min: 20.62 / Avg: 21 / Max: 21.31

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.1Device: CPU - Batch Size: 16 - Model: ResNet-50ba510152025SE +/- 0.25, N = 321.5721.16MIN: 14.06 / MAX: 22.29MIN: 12.26 / MAX: 22.24
OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.1Device: CPU - Batch Size: 16 - Model: ResNet-50ba510152025Min: 20.71 / Avg: 21.16 / Max: 21.58

Neural Magic DeepSparse

This is a benchmark of Neural Magic's DeepSparse using its built-in deepsparse.benchmark utility and various models from their SparseZoo (https://sparsezoo.neuralmagic.com/). Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgms/batch, Fewer Is BetterNeural Magic DeepSparse 1.6Model: BERT-Large, NLP Question Answering - Scenario: Synchronous Single-Streamab714212835SE +/- 0.03, N = 331.2231.26
OpenBenchmarking.orgms/batch, Fewer Is BetterNeural Magic DeepSparse 1.6Model: BERT-Large, NLP Question Answering - Scenario: Synchronous Single-Streamab714212835Min: 31.16 / Avg: 31.22 / Max: 31.25

OpenBenchmarking.orgitems/sec, More Is BetterNeural Magic DeepSparse 1.6Model: BERT-Large, NLP Question Answering - Scenario: Synchronous Single-Streamab714212835SE +/- 0.03, N = 332.0231.98
OpenBenchmarking.orgitems/sec, More Is BetterNeural Magic DeepSparse 1.6Model: BERT-Large, NLP Question Answering - Scenario: Synchronous Single-Streamab714212835Min: 31.99 / Avg: 32.02 / Max: 32.07

OpenBenchmarking.orgms/batch, Fewer Is BetterNeural Magic DeepSparse 1.6Model: BERT-Large, NLP Question Answering - Scenario: Asynchronous Multi-Streamab130260390520650SE +/- 0.37, N = 3607.57607.57
OpenBenchmarking.orgms/batch, Fewer Is BetterNeural Magic DeepSparse 1.6Model: BERT-Large, NLP Question Answering - Scenario: Asynchronous Multi-Streamab110220330440550Min: 607.06 / Avg: 607.57 / Max: 608.29

OpenBenchmarking.orgitems/sec, More Is BetterNeural Magic DeepSparse 1.6Model: BERT-Large, NLP Question Answering - Scenario: Asynchronous Multi-Streamba306090120150SE +/- 0.02, N = 3156.43156.42
OpenBenchmarking.orgitems/sec, More Is BetterNeural Magic DeepSparse 1.6Model: BERT-Large, NLP Question Answering - Scenario: Asynchronous Multi-Streamba306090120150Min: 156.39 / Avg: 156.42 / Max: 156.46

Apache Spark TPC-H

This is a benchmark of Apache Spark using TPC-H data-set. Apache Spark is an open-source unified analytics engine for large-scale data processing and dealing with big data. This test profile benchmarks the Apache Spark in a single-system configuration using spark-submit. The test makes use of https://github.com/ssavvides/tpch-spark/ for facilitating the TPC-H benchmark. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgSeconds, Fewer Is BetterApache Spark TPC-H 3.5Scale Factor: 1 - Q22ab0.240.480.720.961.2SE +/- 0.03222070, N = 31.007690471.06679213
OpenBenchmarking.orgSeconds, Fewer Is BetterApache Spark TPC-H 3.5Scale Factor: 1 - Q22ab246810Min: 0.97 / Avg: 1.01 / Max: 1.07

OpenBenchmarking.orgSeconds, Fewer Is BetterApache Spark TPC-H 3.5Scale Factor: 1 - Q21ba3691215SE +/- 0.26119238, N = 39.559095389.64531231
OpenBenchmarking.orgSeconds, Fewer Is BetterApache Spark TPC-H 3.5Scale Factor: 1 - Q21ba3691215Min: 9.15 / Avg: 9.65 / Max: 10.03

OpenBenchmarking.orgSeconds, Fewer Is BetterApache Spark TPC-H 3.5Scale Factor: 1 - Q20ba0.68791.37582.06372.75163.4395SE +/- 0.12035470, N = 33.050016883.05739617
OpenBenchmarking.orgSeconds, Fewer Is BetterApache Spark TPC-H 3.5Scale Factor: 1 - Q20ba246810Min: 2.84 / Avg: 3.06 / Max: 3.26

OpenBenchmarking.orgSeconds, Fewer Is BetterApache Spark TPC-H 3.5Scale Factor: 1 - Q19ab0.1930.3860.5790.7720.965SE +/- 0.03922839, N = 30.790923950.85797596
OpenBenchmarking.orgSeconds, Fewer Is BetterApache Spark TPC-H 3.5Scale Factor: 1 - Q19ab246810Min: 0.73 / Avg: 0.79 / Max: 0.86

OpenBenchmarking.orgSeconds, Fewer Is BetterApache Spark TPC-H 3.5Scale Factor: 1 - Q18ba1.26642.53283.79925.06566.332SE +/- 0.11078356, N = 35.131711485.62853845
OpenBenchmarking.orgSeconds, Fewer Is BetterApache Spark TPC-H 3.5Scale Factor: 1 - Q18ba246810Min: 5.47 / Avg: 5.63 / Max: 5.84

OpenBenchmarking.orgSeconds, Fewer Is BetterApache Spark TPC-H 3.5Scale Factor: 1 - Q17ba0.6661.3321.9982.6643.33SE +/- 0.10612827, N = 32.883481982.95993924
OpenBenchmarking.orgSeconds, Fewer Is BetterApache Spark TPC-H 3.5Scale Factor: 1 - Q17ba246810Min: 2.76 / Avg: 2.96 / Max: 3.11

OpenBenchmarking.orgSeconds, Fewer Is BetterApache Spark TPC-H 3.5Scale Factor: 1 - Q16ab0.34150.6831.02451.3661.7075SE +/- 0.06760680, N = 31.381472591.51779914
OpenBenchmarking.orgSeconds, Fewer Is BetterApache Spark TPC-H 3.5Scale Factor: 1 - Q16ab246810Min: 1.31 / Avg: 1.38 / Max: 1.52

OpenBenchmarking.orgSeconds, Fewer Is BetterApache Spark TPC-H 3.5Scale Factor: 1 - Q15ab0.58211.16421.74632.32842.9105SE +/- 0.11136502, N = 32.501859662.58714175
OpenBenchmarking.orgSeconds, Fewer Is BetterApache Spark TPC-H 3.5Scale Factor: 1 - Q15ab246810Min: 2.38 / Avg: 2.5 / Max: 2.72

OpenBenchmarking.orgSeconds, Fewer Is BetterApache Spark TPC-H 3.5Scale Factor: 1 - Q14ab0.49760.99521.49281.99042.488SE +/- 0.16557850, N = 32.064853312.21146965
OpenBenchmarking.orgSeconds, Fewer Is BetterApache Spark TPC-H 3.5Scale Factor: 1 - Q14ab246810Min: 1.89 / Avg: 2.06 / Max: 2.4

OpenBenchmarking.orgSeconds, Fewer Is BetterApache Spark TPC-H 3.5Scale Factor: 1 - Q13ab0.39170.78341.17511.56681.9585SE +/- 0.15789062, N = 31.588159361.74074161
OpenBenchmarking.orgSeconds, Fewer Is BetterApache Spark TPC-H 3.5Scale Factor: 1 - Q13ab246810Min: 1.33 / Avg: 1.59 / Max: 1.88

OpenBenchmarking.orgSeconds, Fewer Is BetterApache Spark TPC-H 3.5Scale Factor: 1 - Q12ab0.50991.01981.52972.03962.5495SE +/- 0.15180813, N = 32.175426482.26641607
OpenBenchmarking.orgSeconds, Fewer Is BetterApache Spark TPC-H 3.5Scale Factor: 1 - Q12ab246810Min: 1.94 / Avg: 2.18 / Max: 2.46

OpenBenchmarking.orgSeconds, Fewer Is BetterApache Spark TPC-H 3.5Scale Factor: 1 - Q11ba0.28650.5730.85951.1461.4325SE +/- 0.06007206, N = 31.139986871.27338135
OpenBenchmarking.orgSeconds, Fewer Is BetterApache Spark TPC-H 3.5Scale Factor: 1 - Q11ba246810Min: 1.21 / Avg: 1.27 / Max: 1.39

OpenBenchmarking.orgSeconds, Fewer Is BetterApache Spark TPC-H 3.5Scale Factor: 1 - Q10ba0.85811.71622.57433.43244.2905SE +/- 0.13264795, N = 33.812455423.81359665
OpenBenchmarking.orgSeconds, Fewer Is BetterApache Spark TPC-H 3.5Scale Factor: 1 - Q10ba246810Min: 3.56 / Avg: 3.81 / Max: 4.01

OpenBenchmarking.orgSeconds, Fewer Is BetterApache Spark TPC-H 3.5Scale Factor: 1 - Q09ab1.3272.6543.9815.3086.635SE +/- 0.08828966, N = 35.709694075.89775848
OpenBenchmarking.orgSeconds, Fewer Is BetterApache Spark TPC-H 3.5Scale Factor: 1 - Q09ab246810Min: 5.53 / Avg: 5.71 / Max: 5.82

OpenBenchmarking.orgSeconds, Fewer Is BetterApache Spark TPC-H 3.5Scale Factor: 1 - Q08ba0.59761.19521.79282.39042.988SE +/- 0.02941830, N = 32.609078172.65584644
OpenBenchmarking.orgSeconds, Fewer Is BetterApache Spark TPC-H 3.5Scale Factor: 1 - Q08ba246810Min: 2.61 / Avg: 2.66 / Max: 2.71

OpenBenchmarking.orgSeconds, Fewer Is BetterApache Spark TPC-H 3.5Scale Factor: 1 - Q07ba0.90241.80482.70723.60964.512SE +/- 0.02085439, N = 33.877902754.01044806
OpenBenchmarking.orgSeconds, Fewer Is BetterApache Spark TPC-H 3.5Scale Factor: 1 - Q07ba246810Min: 3.98 / Avg: 4.01 / Max: 4.05

OpenBenchmarking.orgSeconds, Fewer Is BetterApache Spark TPC-H 3.5Scale Factor: 1 - Q06ba0.10540.21080.31620.42160.527SE +/- 0.03244463, N = 30.358015570.46822915
OpenBenchmarking.orgSeconds, Fewer Is BetterApache Spark TPC-H 3.5Scale Factor: 1 - Q06ba12345Min: 0.42 / Avg: 0.47 / Max: 0.53

OpenBenchmarking.orgSeconds, Fewer Is BetterApache Spark TPC-H 3.5Scale Factor: 1 - Q05ba0.92951.8592.78853.7184.6475SE +/- 0.18898243, N = 33.692176344.13122161
OpenBenchmarking.orgSeconds, Fewer Is BetterApache Spark TPC-H 3.5Scale Factor: 1 - Q05ba246810Min: 3.84 / Avg: 4.13 / Max: 4.48

OpenBenchmarking.orgSeconds, Fewer Is BetterApache Spark TPC-H 3.5Scale Factor: 1 - Q04ba0.88321.76642.64963.53284.416SE +/- 0.09899955, N = 33.754272463.92525745
OpenBenchmarking.orgSeconds, Fewer Is BetterApache Spark TPC-H 3.5Scale Factor: 1 - Q04ba246810Min: 3.73 / Avg: 3.93 / Max: 4.03

OpenBenchmarking.orgSeconds, Fewer Is BetterApache Spark TPC-H 3.5Scale Factor: 1 - Q03ab0.86991.73982.60973.47964.3495SE +/- 0.11371323, N = 33.864421843.86610818
OpenBenchmarking.orgSeconds, Fewer Is BetterApache Spark TPC-H 3.5Scale Factor: 1 - Q03ab246810Min: 3.68 / Avg: 3.86 / Max: 4.07

OpenBenchmarking.orgSeconds, Fewer Is BetterApache Spark TPC-H 3.5Scale Factor: 1 - Q02ab0.46850.9371.40551.8742.3425SE +/- 0.02016184, N = 32.061790712.08224201
OpenBenchmarking.orgSeconds, Fewer Is BetterApache Spark TPC-H 3.5Scale Factor: 1 - Q02ab246810Min: 2.02 / Avg: 2.06 / Max: 2.09

OpenBenchmarking.orgSeconds, Fewer Is BetterApache Spark TPC-H 3.5Scale Factor: 1 - Q01ab1.00052.0013.00154.0025.0025SE +/- 0.17358727, N = 34.320060814.44657946
OpenBenchmarking.orgSeconds, Fewer Is BetterApache Spark TPC-H 3.5Scale Factor: 1 - Q01ab246810Min: 3.99 / Avg: 4.32 / Max: 4.57

OpenBenchmarking.orgSeconds, Fewer Is BetterApache Spark TPC-H 3.5Scale Factor: 1 - Geometric Mean Of All Queriesab0.56141.12281.68422.24562.807SE +/- 0.02040294, N = 32.449649162.49517747MIN: 0.73 / MAX: 10.03MIN: 0.86 / MAX: 9.56
OpenBenchmarking.orgSeconds, Fewer Is BetterApache Spark TPC-H 3.5Scale Factor: 1 - Geometric Mean Of All Queriesab246810Min: 2.42 / Avg: 2.45 / Max: 2.49

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.orgverify/s, More Is BetterOpenSSLAlgorithm: RSA4096ab700K1400K2100K2800K3500KSE +/- 1292.47, N = 33244390.33243345.21. OpenSSL 3.0.10 1 Aug 2023 (Library: OpenSSL 3.0.10 1 Aug 2023)
OpenBenchmarking.orgverify/s, More Is BetterOpenSSLAlgorithm: RSA4096ab600K1200K1800K2400K3000KMin: 3242079.1 / Avg: 3244390.3 / Max: 3246548.51. OpenSSL 3.0.10 1 Aug 2023 (Library: OpenSSL 3.0.10 1 Aug 2023)

OpenBenchmarking.orgsign/s, More Is BetterOpenSSLAlgorithm: RSA4096ab20K40K60K80K100KSE +/- 53.45, N = 398622.098528.81. OpenSSL 3.0.10 1 Aug 2023 (Library: OpenSSL 3.0.10 1 Aug 2023)
OpenBenchmarking.orgsign/s, More Is BetterOpenSSLAlgorithm: RSA4096ab20K40K60K80K100KMin: 98556.9 / Avg: 98622.03 / Max: 987281. OpenSSL 3.0.10 1 Aug 2023 (Library: OpenSSL 3.0.10 1 Aug 2023)

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: Quality 95, Compression Effort 7ba0.10130.20260.30390.40520.5065SE +/- 0.00, N = 30.450.451. (CXX) g++ options: -msse4.2 -fno-rtti -O3 -ldl
OpenBenchmarking.orgMP/s, More Is BetterWebP2 Image Encode 20220823Encode Settings: Quality 95, Compression Effort 7ba12345Min: 0.45 / Avg: 0.45 / Max: 0.461. (CXX) g++ options: -msse4.2 -fno-rtti -O3 -ldl

Neural Magic DeepSparse

This is a benchmark of Neural Magic's DeepSparse using its built-in deepsparse.benchmark utility and various models from their SparseZoo (https://sparsezoo.neuralmagic.com/). Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgms/batch, Fewer Is BetterNeural Magic DeepSparse 1.6Model: NLP Text Classification, BERT base uncased SST2, Sparse INT8 - Scenario: Synchronous Single-Streamba1.17852.3573.53554.7145.8925SE +/- 0.0015, N = 35.22965.2377
OpenBenchmarking.orgms/batch, Fewer Is BetterNeural Magic DeepSparse 1.6Model: NLP Text Classification, BERT base uncased SST2, Sparse INT8 - Scenario: Synchronous Single-Streamba246810Min: 5.24 / Avg: 5.24 / Max: 5.24

OpenBenchmarking.orgitems/sec, More Is BetterNeural Magic DeepSparse 1.6Model: NLP Text Classification, BERT base uncased SST2, Sparse INT8 - Scenario: Synchronous Single-Streamba4080120160200SE +/- 0.06, N = 3191.10190.80
OpenBenchmarking.orgitems/sec, More Is BetterNeural Magic DeepSparse 1.6Model: NLP Text Classification, BERT base uncased SST2, Sparse INT8 - Scenario: Synchronous Single-Streamba4080120160200Min: 190.7 / Avg: 190.8 / Max: 190.9

OpenBenchmarking.orgms/batch, Fewer Is BetterNeural Magic DeepSparse 1.6Model: NLP Document Classification, oBERT base uncased on IMDB - Scenario: Asynchronous Multi-Streamab150300450600750SE +/- 4.21, N = 3715.04717.59
OpenBenchmarking.orgms/batch, Fewer Is BetterNeural Magic DeepSparse 1.6Model: NLP Document Classification, oBERT base uncased on IMDB - Scenario: Asynchronous Multi-Streamab130260390520650Min: 706.95 / Avg: 715.04 / Max: 721.12

OpenBenchmarking.orgitems/sec, More Is BetterNeural Magic DeepSparse 1.6Model: NLP Document Classification, oBERT base uncased on IMDB - Scenario: Asynchronous Multi-Streamab306090120150SE +/- 0.66, N = 3132.66132.27
OpenBenchmarking.orgitems/sec, More Is BetterNeural Magic DeepSparse 1.6Model: NLP Document Classification, oBERT base uncased on IMDB - Scenario: Asynchronous Multi-Streamab20406080100Min: 131.62 / Avg: 132.66 / Max: 133.87

OpenBenchmarking.orgms/batch, Fewer Is BetterNeural Magic DeepSparse 1.6Model: BERT-Large, NLP Question Answering, Sparse INT8 - Scenario: Asynchronous Multi-Streamab816243240SE +/- 0.09, N = 336.7536.91
OpenBenchmarking.orgms/batch, Fewer Is BetterNeural Magic DeepSparse 1.6Model: BERT-Large, NLP Question Answering, Sparse INT8 - Scenario: Asynchronous Multi-Streamab816243240Min: 36.58 / Avg: 36.75 / Max: 36.85

OpenBenchmarking.orgitems/sec, More Is BetterNeural Magic DeepSparse 1.6Model: BERT-Large, NLP Question Answering, Sparse INT8 - Scenario: Asynchronous Multi-Streamab6001200180024003000SE +/- 6.37, N = 32608.012596.10
OpenBenchmarking.orgitems/sec, More Is BetterNeural Magic DeepSparse 1.6Model: BERT-Large, NLP Question Answering, Sparse INT8 - Scenario: Asynchronous Multi-Streamab5001000150020002500Min: 2601.01 / Avg: 2608.01 / Max: 2620.73

OpenBenchmarking.orgms/batch, Fewer Is BetterNeural Magic DeepSparse 1.6Model: NLP Token Classification, BERT base uncased conll2003 - Scenario: Asynchronous Multi-Streamba160320480640800SE +/- 1.53, N = 3717.98719.28
OpenBenchmarking.orgms/batch, Fewer Is BetterNeural Magic DeepSparse 1.6Model: NLP Token Classification, BERT base uncased conll2003 - Scenario: Asynchronous Multi-Streamba130260390520650Min: 716.33 / Avg: 719.28 / Max: 721.5

OpenBenchmarking.orgitems/sec, More Is BetterNeural Magic DeepSparse 1.6Model: NLP Token Classification, BERT base uncased conll2003 - Scenario: Asynchronous Multi-Streamba306090120150SE +/- 0.03, N = 3132.42132.05
OpenBenchmarking.orgitems/sec, More Is BetterNeural Magic DeepSparse 1.6Model: NLP Token Classification, BERT base uncased conll2003 - Scenario: Asynchronous Multi-Streamba20406080100Min: 132.01 / Avg: 132.05 / Max: 132.11

OpenBenchmarking.orgms/batch, Fewer Is BetterNeural Magic DeepSparse 1.6Model: NLP Text Classification, BERT base uncased SST2, Sparse INT8 - Scenario: Asynchronous Multi-Streamba48121620SE +/- 0.01, N = 317.3017.30
OpenBenchmarking.orgms/batch, Fewer Is BetterNeural Magic DeepSparse 1.6Model: NLP Text Classification, BERT base uncased SST2, Sparse INT8 - Scenario: Asynchronous Multi-Streamba48121620Min: 17.27 / Avg: 17.3 / Max: 17.32

OpenBenchmarking.orgitems/sec, More Is BetterNeural Magic DeepSparse 1.6Model: NLP Text Classification, BERT base uncased SST2, Sparse INT8 - Scenario: Asynchronous Multi-Streamab12002400360048006000SE +/- 5.02, N = 35540.635540.52
OpenBenchmarking.orgitems/sec, More Is BetterNeural Magic DeepSparse 1.6Model: NLP Text Classification, BERT base uncased SST2, Sparse INT8 - Scenario: Asynchronous Multi-Streamab10002000300040005000Min: 5535.01 / Avg: 5540.63 / Max: 5550.65

OpenBenchmarking.orgms/batch, Fewer Is BetterNeural Magic DeepSparse 1.6Model: NLP Token Classification, BERT base uncased conll2003 - Scenario: Synchronous Single-Streamab510152025SE +/- 0.02, N = 320.6220.68
OpenBenchmarking.orgms/batch, Fewer Is BetterNeural Magic DeepSparse 1.6Model: NLP Token Classification, BERT base uncased conll2003 - Scenario: Synchronous Single-Streamab510152025Min: 20.58 / Avg: 20.62 / Max: 20.66

OpenBenchmarking.orgitems/sec, More Is BetterNeural Magic DeepSparse 1.6Model: NLP Token Classification, BERT base uncased conll2003 - Scenario: Synchronous Single-Streamab1122334455SE +/- 0.05, N = 348.4948.33
OpenBenchmarking.orgitems/sec, More Is BetterNeural Magic DeepSparse 1.6Model: NLP Token Classification, BERT base uncased conll2003 - Scenario: Synchronous Single-Streamab1020304050Min: 48.4 / Avg: 48.49 / Max: 48.58

OpenBenchmarking.orgms/batch, Fewer Is BetterNeural Magic DeepSparse 1.6Model: BERT-Large, NLP Question Answering, Sparse INT8 - Scenario: Synchronous Single-Streamab48121620SE +/- 0.02, N = 314.6414.64
OpenBenchmarking.orgms/batch, Fewer Is BetterNeural Magic DeepSparse 1.6Model: BERT-Large, NLP Question Answering, Sparse INT8 - Scenario: Synchronous Single-Streamab48121620Min: 14.6 / Avg: 14.64 / Max: 14.67

OpenBenchmarking.orgitems/sec, More Is BetterNeural Magic DeepSparse 1.6Model: BERT-Large, NLP Question Answering, Sparse INT8 - Scenario: Synchronous Single-Streamab1530456075SE +/- 0.11, N = 368.2768.26
OpenBenchmarking.orgitems/sec, More Is BetterNeural Magic DeepSparse 1.6Model: BERT-Large, NLP Question Answering, Sparse INT8 - Scenario: Synchronous Single-Streamab1326395265Min: 68.13 / Avg: 68.27 / Max: 68.47

OpenBenchmarking.orgms/batch, Fewer Is BetterNeural Magic DeepSparse 1.6Model: NLP Document Classification, oBERT base uncased on IMDB - Scenario: Synchronous Single-Streamab510152025SE +/- 0.01, N = 320.6320.69
OpenBenchmarking.orgms/batch, Fewer Is BetterNeural Magic DeepSparse 1.6Model: NLP Document Classification, oBERT base uncased on IMDB - Scenario: Synchronous Single-Streamab510152025Min: 20.62 / Avg: 20.63 / Max: 20.65

OpenBenchmarking.orgitems/sec, More Is BetterNeural Magic DeepSparse 1.6Model: NLP Document Classification, oBERT base uncased on IMDB - Scenario: Synchronous Single-Streamab1122334455SE +/- 0.02, N = 348.4548.33
OpenBenchmarking.orgitems/sec, More Is BetterNeural Magic DeepSparse 1.6Model: NLP Document Classification, oBERT base uncased on IMDB - Scenario: Synchronous Single-Streamab1020304050Min: 48.41 / Avg: 48.45 / Max: 48.47

OpenBenchmarking.orgms/batch, Fewer Is BetterNeural Magic DeepSparse 1.6Model: CV Segmentation, 90% Pruned YOLACT Pruned - Scenario: Asynchronous Multi-Streamba80160240320400SE +/- 0.61, N = 3382.56383.20
OpenBenchmarking.orgms/batch, Fewer Is BetterNeural Magic DeepSparse 1.6Model: CV Segmentation, 90% Pruned YOLACT Pruned - Scenario: Asynchronous Multi-Streamba70140210280350Min: 382.13 / Avg: 383.2 / Max: 384.26

OpenBenchmarking.orgitems/sec, More Is BetterNeural Magic DeepSparse 1.6Model: CV Segmentation, 90% Pruned YOLACT Pruned - Scenario: Asynchronous Multi-Streamba50100150200250SE +/- 0.41, N = 3249.50248.58
OpenBenchmarking.orgitems/sec, More Is BetterNeural Magic DeepSparse 1.6Model: CV Segmentation, 90% Pruned YOLACT Pruned - Scenario: Asynchronous Multi-Streamba50100150200250Min: 247.78 / Avg: 248.58 / Max: 249.1

OpenBenchmarking.orgms/batch, Fewer Is BetterNeural Magic DeepSparse 1.6Model: NLP Text Classification, DistilBERT mnli - Scenario: Asynchronous Multi-Streamba20406080100SE +/- 0.19, N = 384.2584.25
OpenBenchmarking.orgms/batch, Fewer Is BetterNeural Magic DeepSparse 1.6Model: NLP Text Classification, DistilBERT mnli - Scenario: Asynchronous Multi-Streamba1632486480Min: 83.89 / Avg: 84.25 / Max: 84.54

OpenBenchmarking.orgitems/sec, More Is BetterNeural Magic DeepSparse 1.6Model: NLP Text Classification, DistilBERT mnli - Scenario: Asynchronous Multi-Streamab2004006008001000SE +/- 2.45, N = 31136.711136.64
OpenBenchmarking.orgitems/sec, More Is BetterNeural Magic DeepSparse 1.6Model: NLP Text Classification, DistilBERT mnli - Scenario: Asynchronous Multi-Streamab2004006008001000Min: 1133.13 / Avg: 1136.71 / Max: 1141.4

OpenBenchmarking.orgms/batch, Fewer Is BetterNeural Magic DeepSparse 1.6Model: CV Segmentation, 90% Pruned YOLACT Pruned - Scenario: Synchronous Single-Streamab48121620SE +/- 0.01, N = 315.3215.37
OpenBenchmarking.orgms/batch, Fewer Is BetterNeural Magic DeepSparse 1.6Model: CV Segmentation, 90% Pruned YOLACT Pruned - Scenario: Synchronous Single-Streamab48121620Min: 15.3 / Avg: 15.32 / Max: 15.33

OpenBenchmarking.orgitems/sec, More Is BetterNeural Magic DeepSparse 1.6Model: CV Segmentation, 90% Pruned YOLACT Pruned - Scenario: Synchronous Single-Streamab1530456075SE +/- 0.04, N = 365.2165.01
OpenBenchmarking.orgitems/sec, More Is BetterNeural Magic DeepSparse 1.6Model: CV Segmentation, 90% Pruned YOLACT Pruned - Scenario: Synchronous Single-Streamab1326395265Min: 65.15 / Avg: 65.21 / Max: 65.29

OpenBenchmarking.orgms/batch, Fewer Is BetterNeural Magic DeepSparse 1.6Model: NLP Text Classification, DistilBERT mnli - Scenario: Synchronous Single-Streamba1.00132.00263.00394.00525.0065SE +/- 0.0001, N = 34.43414.4503
OpenBenchmarking.orgms/batch, Fewer Is BetterNeural Magic DeepSparse 1.6Model: NLP Text Classification, DistilBERT mnli - Scenario: Synchronous Single-Streamba246810Min: 4.45 / Avg: 4.45 / Max: 4.45

OpenBenchmarking.orgitems/sec, More Is BetterNeural Magic DeepSparse 1.6Model: NLP Text Classification, DistilBERT mnli - Scenario: Synchronous Single-Streamba50100150200250SE +/- 0.01, N = 3225.40224.58
OpenBenchmarking.orgitems/sec, More Is BetterNeural Magic DeepSparse 1.6Model: NLP Text Classification, DistilBERT mnli - Scenario: Synchronous Single-Streamba4080120160200Min: 224.57 / Avg: 224.58 / Max: 224.59

OpenBenchmarking.orgms/batch, Fewer Is BetterNeural Magic DeepSparse 1.6Model: CV Detection, YOLOv5s COCO - Scenario: Asynchronous Multi-Streamba306090120150SE +/- 0.25, N = 3121.61122.03
OpenBenchmarking.orgms/batch, Fewer Is BetterNeural Magic DeepSparse 1.6Model: CV Detection, YOLOv5s COCO - Scenario: Asynchronous Multi-Streamba20406080100Min: 121.55 / Avg: 122.03 / Max: 122.38

OpenBenchmarking.orgitems/sec, More Is BetterNeural Magic DeepSparse 1.6Model: CV Detection, YOLOv5s COCO - Scenario: Asynchronous Multi-Streamba2004006008001000SE +/- 1.42, N = 3786.89784.52
OpenBenchmarking.orgitems/sec, More Is BetterNeural Magic DeepSparse 1.6Model: CV Detection, YOLOv5s COCO - Scenario: Asynchronous Multi-Streamba140280420560700Min: 782.64 / Avg: 784.52 / Max: 787.31

OpenBenchmarking.orgms/batch, Fewer Is BetterNeural Magic DeepSparse 1.6Model: CV Detection, YOLOv5s COCO, Sparse INT8 - Scenario: Asynchronous Multi-Streamba306090120150SE +/- 0.24, N = 3120.04120.21
OpenBenchmarking.orgms/batch, Fewer Is BetterNeural Magic DeepSparse 1.6Model: CV Detection, YOLOv5s COCO, Sparse INT8 - Scenario: Asynchronous Multi-Streamba20406080100Min: 119.9 / Avg: 120.21 / Max: 120.68

OpenBenchmarking.orgitems/sec, More Is BetterNeural Magic DeepSparse 1.6Model: CV Detection, YOLOv5s COCO, Sparse INT8 - Scenario: Asynchronous Multi-Streamba2004006008001000SE +/- 1.54, N = 3797.41796.07
OpenBenchmarking.orgitems/sec, More Is BetterNeural Magic DeepSparse 1.6Model: CV Detection, YOLOv5s COCO, Sparse INT8 - Scenario: Asynchronous Multi-Streamba140280420560700Min: 793.01 / Avg: 796.07 / Max: 797.9

OpenBenchmarking.orgms/batch, Fewer Is BetterNeural Magic DeepSparse 1.6Model: ResNet-50, Baseline - Scenario: Asynchronous Multi-Streamab1224364860SE +/- 0.06, N = 354.5154.55
OpenBenchmarking.orgms/batch, Fewer Is BetterNeural Magic DeepSparse 1.6Model: ResNet-50, Baseline - Scenario: Asynchronous Multi-Streamab1122334455Min: 54.41 / Avg: 54.51 / Max: 54.61

OpenBenchmarking.orgitems/sec, More Is BetterNeural Magic DeepSparse 1.6Model: ResNet-50, Baseline - Scenario: Asynchronous Multi-Streamab400800120016002000SE +/- 1.91, N = 31758.591756.56
OpenBenchmarking.orgitems/sec, More Is BetterNeural Magic DeepSparse 1.6Model: ResNet-50, Baseline - Scenario: Asynchronous Multi-Streamab30060090012001500Min: 1755.4 / Avg: 1758.59 / Max: 1762

OpenBenchmarking.orgms/batch, Fewer Is BetterNeural Magic DeepSparse 1.6Model: ResNet-50, Sparse INT8 - Scenario: Synchronous Single-Streamba0.27930.55860.83791.11721.3965SE +/- 0.0046, N = 31.24041.2413
OpenBenchmarking.orgms/batch, Fewer Is BetterNeural Magic DeepSparse 1.6Model: ResNet-50, Sparse INT8 - Scenario: Synchronous Single-Streamba246810Min: 1.24 / Avg: 1.24 / Max: 1.25

OpenBenchmarking.orgitems/sec, More Is BetterNeural Magic DeepSparse 1.6Model: ResNet-50, Sparse INT8 - Scenario: Synchronous Single-Streamba2004006008001000SE +/- 3.00, N = 3804.75804.18
OpenBenchmarking.orgitems/sec, More Is BetterNeural Magic DeepSparse 1.6Model: ResNet-50, Sparse INT8 - Scenario: Synchronous Single-Streamba140280420560700Min: 798.24 / Avg: 804.18 / Max: 807.92

OpenBenchmarking.orgms/batch, Fewer Is BetterNeural Magic DeepSparse 1.6Model: ResNet-50, Sparse INT8 - Scenario: Asynchronous Multi-Streamab1.26362.52723.79085.05446.318SE +/- 0.0055, N = 35.59555.6159
OpenBenchmarking.orgms/batch, Fewer Is BetterNeural Magic DeepSparse 1.6Model: ResNet-50, Sparse INT8 - Scenario: Asynchronous Multi-Streamab246810Min: 5.59 / Avg: 5.6 / Max: 5.61

OpenBenchmarking.orgitems/sec, More Is BetterNeural Magic DeepSparse 1.6Model: ResNet-50, Sparse INT8 - Scenario: Asynchronous Multi-Streamab4K8K12K16K20KSE +/- 16.76, N = 317108.4617047.64
OpenBenchmarking.orgitems/sec, More Is BetterNeural Magic DeepSparse 1.6Model: ResNet-50, Sparse INT8 - Scenario: Asynchronous Multi-Streamab3K6K9K12K15KMin: 17075.12 / Avg: 17108.46 / Max: 17128.07

OpenBenchmarking.orgms/batch, Fewer Is BetterNeural Magic DeepSparse 1.6Model: CV Classification, ResNet-50 ImageNet - Scenario: Asynchronous Multi-Streamab1224364860SE +/- 0.07, N = 354.4154.49
OpenBenchmarking.orgms/batch, Fewer Is BetterNeural Magic DeepSparse 1.6Model: CV Classification, ResNet-50 ImageNet - Scenario: Asynchronous Multi-Streamab1122334455Min: 54.3 / Avg: 54.41 / Max: 54.55

OpenBenchmarking.orgitems/sec, More Is BetterNeural Magic DeepSparse 1.6Model: CV Classification, ResNet-50 ImageNet - Scenario: Asynchronous Multi-Streamab400800120016002000SE +/- 2.24, N = 31761.401759.07
OpenBenchmarking.orgitems/sec, More Is BetterNeural Magic DeepSparse 1.6Model: CV Classification, ResNet-50 ImageNet - Scenario: Asynchronous Multi-Streamab30060090012001500Min: 1757.01 / Avg: 1761.4 / Max: 1764.36

OpenBenchmarking.orgms/batch, Fewer Is BetterNeural Magic DeepSparse 1.6Model: CV Detection, YOLOv5s COCO - Scenario: Synchronous Single-Streamba1.06172.12343.18514.24685.3085SE +/- 0.0110, N = 34.71804.7188
OpenBenchmarking.orgms/batch, Fewer Is BetterNeural Magic DeepSparse 1.6Model: CV Detection, YOLOv5s COCO - Scenario: Synchronous Single-Streamba246810Min: 4.7 / Avg: 4.72 / Max: 4.74

OpenBenchmarking.orgitems/sec, More Is BetterNeural Magic DeepSparse 1.6Model: CV Detection, YOLOv5s COCO - Scenario: Synchronous Single-Streamba50100150200250SE +/- 0.50, N = 3211.77211.74
OpenBenchmarking.orgitems/sec, More Is BetterNeural Magic DeepSparse 1.6Model: CV Detection, YOLOv5s COCO - Scenario: Synchronous Single-Streamba4080120160200Min: 210.77 / Avg: 211.74 / Max: 212.39

OpenBenchmarking.orgms/batch, Fewer Is BetterNeural Magic DeepSparse 1.6Model: CV Detection, YOLOv5s COCO, Sparse INT8 - Scenario: Synchronous Single-Streamba1.06032.12063.18094.24125.3015SE +/- 0.0079, N = 34.71174.7126
OpenBenchmarking.orgms/batch, Fewer Is BetterNeural Magic DeepSparse 1.6Model: CV Detection, YOLOv5s COCO, Sparse INT8 - Scenario: Synchronous Single-Streamba246810Min: 4.7 / Avg: 4.71 / Max: 4.72

OpenBenchmarking.orgitems/sec, More Is BetterNeural Magic DeepSparse 1.6Model: CV Detection, YOLOv5s COCO, Sparse INT8 - Scenario: Synchronous Single-Streamba50100150200250SE +/- 0.35, N = 3212.13212.10
OpenBenchmarking.orgitems/sec, More Is BetterNeural Magic DeepSparse 1.6Model: CV Detection, YOLOv5s COCO, Sparse INT8 - Scenario: Synchronous Single-Streamba4080120160200Min: 211.6 / Avg: 212.1 / Max: 212.78

OpenBenchmarking.orgms/batch, Fewer Is BetterNeural Magic DeepSparse 1.6Model: CV Classification, ResNet-50 ImageNet - Scenario: Synchronous Single-Streamba1.08052.1613.24154.3225.4025SE +/- 0.0103, N = 34.77754.8022
OpenBenchmarking.orgms/batch, Fewer Is BetterNeural Magic DeepSparse 1.6Model: CV Classification, ResNet-50 ImageNet - Scenario: Synchronous Single-Streamba246810Min: 4.79 / Avg: 4.8 / Max: 4.82

OpenBenchmarking.orgitems/sec, More Is BetterNeural Magic DeepSparse 1.6Model: CV Classification, ResNet-50 ImageNet - Scenario: Synchronous Single-Streamba50100150200250SE +/- 0.44, N = 3209.20208.12
OpenBenchmarking.orgitems/sec, More Is BetterNeural Magic DeepSparse 1.6Model: CV Classification, ResNet-50 ImageNet - Scenario: Synchronous Single-Streamba4080120160200Min: 207.25 / Avg: 208.12 / Max: 208.7

OpenBenchmarking.orgms/batch, Fewer Is BetterNeural Magic DeepSparse 1.6Model: ResNet-50, Baseline - Scenario: Synchronous Single-Streamab1.08652.1733.25954.3465.4325SE +/- 0.0118, N = 34.76374.8290
OpenBenchmarking.orgms/batch, Fewer Is BetterNeural Magic DeepSparse 1.6Model: ResNet-50, Baseline - Scenario: Synchronous Single-Streamab246810Min: 4.74 / Avg: 4.76 / Max: 4.78

OpenBenchmarking.orgitems/sec, More Is BetterNeural Magic DeepSparse 1.6Model: ResNet-50, Baseline - Scenario: Synchronous Single-Streamab50100150200250SE +/- 0.52, N = 3209.80206.97
OpenBenchmarking.orgitems/sec, More Is BetterNeural Magic DeepSparse 1.6Model: ResNet-50, Baseline - Scenario: Synchronous Single-Streamab4080120160200Min: 209.13 / Avg: 209.8 / Max: 210.82

SVT-AV1

This is a benchmark of the SVT-AV1 open-source video encoder/decoder. SVT-AV1 was originally developed by Intel as part of their Open Visual Cloud / Scalable Video Technology (SVT). Development of SVT-AV1 has since moved to the Alliance for Open Media as part of upstream AV1 development. SVT-AV1 is a CPU-based multi-threaded video encoder for the AV1 video format with a sample YUV video file. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgFrames Per Second, More Is BetterSVT-AV1 1.8Encoder Mode: Preset 13 - Input: Bosphorus 4Kba4080120160200SE +/- 1.61, N = 15184.35176.671. (CXX) g++ options: -march=native -mno-avx -mavx2 -mavx512f -mavx512bw -mavx512dq
OpenBenchmarking.orgFrames Per Second, More Is BetterSVT-AV1 1.8Encoder Mode: Preset 13 - Input: Bosphorus 4Kba306090120150Min: 164.52 / Avg: 176.67 / Max: 184.741. (CXX) g++ options: -march=native -mno-avx -mavx2 -mavx512f -mavx512bw -mavx512dq

Xmrig

Xmrig is an open-source cross-platform CPU/GPU miner for RandomX, KawPow, CryptoNight and AstroBWT. This test profile is setup to measure the Xmrig CPU mining performance. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgH/s, More Is BetterXmrig 6.21Variant: GhostRider - Hash Count: 1Mab7K14K21K28K35KSE +/- 24.02, N = 331859.731728.91. (CXX) g++ options: -fexceptions -fno-rtti -maes -O3 -Ofast -static-libgcc -static-libstdc++ -rdynamic -lssl -lcrypto -luv -lpthread -lrt -ldl -lhwloc
OpenBenchmarking.orgH/s, More Is BetterXmrig 6.21Variant: GhostRider - Hash Count: 1Mab6K12K18K24K30KMin: 31825.8 / Avg: 31859.67 / Max: 31906.11. (CXX) g++ options: -fexceptions -fno-rtti -maes -O3 -Ofast -static-libgcc -static-libstdc++ -rdynamic -lssl -lcrypto -luv -lpthread -lrt -ldl -lhwloc

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: Quality 75, Compression Effort 7ab0.18680.37360.56040.74720.934SE +/- 0.00, N = 30.830.821. (CXX) g++ options: -msse4.2 -fno-rtti -O3 -ldl
OpenBenchmarking.orgMP/s, More Is BetterWebP2 Image Encode 20220823Encode Settings: Quality 75, Compression Effort 7ab246810Min: 0.82 / Avg: 0.83 / Max: 0.831. (CXX) g++ options: -msse4.2 -fno-rtti -O3 -ldl

Java SciMark

This test runs the Java version of SciMark 2, which is a benchmark for scientific and numerical computing developed by programmers at the National Institute of Standards and Technology. This benchmark is made up of Fast Foruier Transform, Jacobi Successive Over-relaxation, Monte Carlo, Sparse Matrix Multiply, and dense LU matrix factorization benchmarks. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgMflops, More Is BetterJava SciMark 2.2Computational Test: Compositeba9001800270036004500SE +/- 6.24, N = 33996.763984.62
OpenBenchmarking.orgMflops, More Is BetterJava SciMark 2.2Computational Test: Compositeba7001400210028003500Min: 3973.95 / Avg: 3984.62 / Max: 3995.57

SVT-AV1

This is a benchmark of the SVT-AV1 open-source video encoder/decoder. SVT-AV1 was originally developed by Intel as part of their Open Visual Cloud / Scalable Video Technology (SVT). Development of SVT-AV1 has since moved to the Alliance for Open Media as part of upstream AV1 development. SVT-AV1 is a CPU-based multi-threaded video encoder for the AV1 video format with a sample YUV video file. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgFrames Per Second, More Is BetterSVT-AV1 1.8Encoder Mode: Preset 4 - Input: Bosphorus 4Kab246810SE +/- 0.041, N = 38.2488.2081. (CXX) g++ options: -march=native -mno-avx -mavx2 -mavx512f -mavx512bw -mavx512dq
OpenBenchmarking.orgFrames Per Second, More Is BetterSVT-AV1 1.8Encoder Mode: Preset 4 - Input: Bosphorus 4Kab3691215Min: 8.17 / Avg: 8.25 / Max: 8.321. (CXX) g++ options: -march=native -mno-avx -mavx2 -mavx512f -mavx512bw -mavx512dq

OpenBenchmarking.orgFrames Per Second, More Is BetterSVT-AV1 1.8Encoder Mode: Preset 4 - Input: Bosphorus 1080pab510152025SE +/- 0.13, N = 321.4221.311. (CXX) g++ options: -march=native -mno-avx -mavx2 -mavx512f -mavx512bw -mavx512dq
OpenBenchmarking.orgFrames Per Second, More Is BetterSVT-AV1 1.8Encoder Mode: Preset 4 - Input: Bosphorus 1080pab510152025Min: 21.2 / Avg: 21.42 / Max: 21.661. (CXX) g++ options: -march=native -mno-avx -mavx2 -mavx512f -mavx512bw -mavx512dq

OpenBenchmarking.orgFrames Per Second, More Is BetterSVT-AV1 1.8Encoder Mode: Preset 8 - Input: Bosphorus 4Kba20406080100SE +/- 0.17, N = 386.8486.431. (CXX) g++ options: -march=native -mno-avx -mavx2 -mavx512f -mavx512bw -mavx512dq
OpenBenchmarking.orgFrames Per Second, More Is BetterSVT-AV1 1.8Encoder Mode: Preset 8 - Input: Bosphorus 4Kba1632486480Min: 86.1 / Avg: 86.43 / Max: 86.631. (CXX) g++ options: -march=native -mno-avx -mavx2 -mavx512f -mavx512bw -mavx512dq

Xmrig

Xmrig is an open-source cross-platform CPU/GPU miner for RandomX, KawPow, CryptoNight and AstroBWT. This test profile is setup to measure the Xmrig CPU mining performance. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgH/s, More Is BetterXmrig 6.21Variant: CryptoNight-Heavy - Hash Count: 1Mba30K60K90K120K150KSE +/- 33.09, N = 3123777.7123041.61. (CXX) g++ options: -fexceptions -fno-rtti -maes -O3 -Ofast -static-libgcc -static-libstdc++ -rdynamic -lssl -lcrypto -luv -lpthread -lrt -ldl -lhwloc
OpenBenchmarking.orgH/s, More Is BetterXmrig 6.21Variant: CryptoNight-Heavy - Hash Count: 1Mba20K40K60K80K100KMin: 123001.2 / Avg: 123041.6 / Max: 123107.21. (CXX) g++ options: -fexceptions -fno-rtti -maes -O3 -Ofast -static-libgcc -static-libstdc++ -rdynamic -lssl -lcrypto -luv -lpthread -lrt -ldl -lhwloc

OpenBenchmarking.orgH/s, More Is BetterXmrig 6.21Variant: CryptoNight-Femto UPX2 - Hash Count: 1Mab30K60K90K120K150KSE +/- 220.87, N = 3123199.0122070.31. (CXX) g++ options: -fexceptions -fno-rtti -maes -O3 -Ofast -static-libgcc -static-libstdc++ -rdynamic -lssl -lcrypto -luv -lpthread -lrt -ldl -lhwloc
OpenBenchmarking.orgH/s, More Is BetterXmrig 6.21Variant: CryptoNight-Femto UPX2 - Hash Count: 1Mab20K40K60K80K100KMin: 122955.9 / Avg: 123199.03 / Max: 1236401. (CXX) g++ options: -fexceptions -fno-rtti -maes -O3 -Ofast -static-libgcc -static-libstdc++ -rdynamic -lssl -lcrypto -luv -lpthread -lrt -ldl -lhwloc

OpenBenchmarking.orgH/s, More Is BetterXmrig 6.21Variant: Monero - Hash Count: 1Mab30K60K90K120K150KSE +/- 404.54, N = 3123352.8122971.01. (CXX) g++ options: -fexceptions -fno-rtti -maes -O3 -Ofast -static-libgcc -static-libstdc++ -rdynamic -lssl -lcrypto -luv -lpthread -lrt -ldl -lhwloc
OpenBenchmarking.orgH/s, More Is BetterXmrig 6.21Variant: Monero - Hash Count: 1Mab20K40K60K80K100KMin: 122819.9 / Avg: 123352.83 / Max: 124146.51. (CXX) g++ options: -fexceptions -fno-rtti -maes -O3 -Ofast -static-libgcc -static-libstdc++ -rdynamic -lssl -lcrypto -luv -lpthread -lrt -ldl -lhwloc

OpenBenchmarking.orgH/s, More Is BetterXmrig 6.21Variant: KawPow - Hash Count: 1Mab30K60K90K120K150KSE +/- 87.00, N = 3123558.6123411.11. (CXX) g++ options: -fexceptions -fno-rtti -maes -O3 -Ofast -static-libgcc -static-libstdc++ -rdynamic -lssl -lcrypto -luv -lpthread -lrt -ldl -lhwloc
OpenBenchmarking.orgH/s, More Is BetterXmrig 6.21Variant: KawPow - Hash Count: 1Mab20K40K60K80K100KMin: 123456.8 / Avg: 123558.6 / Max: 123731.71. (CXX) g++ options: -fexceptions -fno-rtti -maes -O3 -Ofast -static-libgcc -static-libstdc++ -rdynamic -lssl -lcrypto -luv -lpthread -lrt -ldl -lhwloc

OpenBenchmarking.orgH/s, More Is BetterXmrig 6.21Variant: Wownero - Hash Count: 1Mba30K60K90K120K150KSE +/- 621.69, N = 3131613.6131141.91. (CXX) g++ options: -fexceptions -fno-rtti -maes -O3 -Ofast -static-libgcc -static-libstdc++ -rdynamic -lssl -lcrypto -luv -lpthread -lrt -ldl -lhwloc
OpenBenchmarking.orgH/s, More Is BetterXmrig 6.21Variant: Wownero - Hash Count: 1Mba20K40K60K80K100KMin: 130327.1 / Avg: 131141.93 / Max: 132362.71. (CXX) g++ options: -fexceptions -fno-rtti -maes -O3 -Ofast -static-libgcc -static-libstdc++ -rdynamic -lssl -lcrypto -luv -lpthread -lrt -ldl -lhwloc

SVT-AV1

This is a benchmark of the SVT-AV1 open-source video encoder/decoder. SVT-AV1 was originally developed by Intel as part of their Open Visual Cloud / Scalable Video Technology (SVT). Development of SVT-AV1 has since moved to the Alliance for Open Media as part of upstream AV1 development. SVT-AV1 is a CPU-based multi-threaded video encoder for the AV1 video format with a sample YUV video file. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgFrames Per Second, More Is BetterSVT-AV1 1.8Encoder Mode: Preset 12 - Input: Bosphorus 4Kba4080120160200SE +/- 1.43, N = 3186.61178.911. (CXX) g++ options: -march=native -mno-avx -mavx2 -mavx512f -mavx512bw -mavx512dq
OpenBenchmarking.orgFrames Per Second, More Is BetterSVT-AV1 1.8Encoder Mode: Preset 12 - Input: Bosphorus 4Kba306090120150Min: 177.42 / Avg: 178.91 / Max: 181.771. (CXX) g++ options: -march=native -mno-avx -mavx2 -mavx512f -mavx512bw -mavx512dq

OpenBenchmarking.orgFrames Per Second, More Is BetterSVT-AV1 1.8Encoder Mode: Preset 8 - Input: Bosphorus 1080pab4080120160200SE +/- 1.87, N = 3165.10162.561. (CXX) g++ options: -march=native -mno-avx -mavx2 -mavx512f -mavx512bw -mavx512dq
OpenBenchmarking.orgFrames Per Second, More Is BetterSVT-AV1 1.8Encoder Mode: Preset 8 - Input: Bosphorus 1080pab306090120150Min: 161.77 / Avg: 165.1 / Max: 168.241. (CXX) g++ options: -march=native -mno-avx -mavx2 -mavx512f -mavx512bw -mavx512dq

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: Quality 100, Compression Effort 5ab246810SE +/- 0.04, N = 36.516.281. (CXX) g++ options: -msse4.2 -fno-rtti -O3 -ldl
OpenBenchmarking.orgMP/s, More Is BetterWebP2 Image Encode 20220823Encode Settings: Quality 100, Compression Effort 5ab3691215Min: 6.46 / Avg: 6.51 / Max: 6.591. (CXX) g++ options: -msse4.2 -fno-rtti -O3 -ldl

OpenBenchmarking.orgMP/s, More Is BetterWebP2 Image Encode 20220823Encode Settings: Defaultba3691215SE +/- 0.08, N = 39.639.481. (CXX) g++ options: -msse4.2 -fno-rtti -O3 -ldl
OpenBenchmarking.orgMP/s, More Is BetterWebP2 Image Encode 20220823Encode Settings: Defaultba3691215Min: 9.32 / Avg: 9.48 / Max: 9.571. (CXX) g++ options: -msse4.2 -fno-rtti -O3 -ldl

SVT-AV1

This is a benchmark of the SVT-AV1 open-source video encoder/decoder. SVT-AV1 was originally developed by Intel as part of their Open Visual Cloud / Scalable Video Technology (SVT). Development of SVT-AV1 has since moved to the Alliance for Open Media as part of upstream AV1 development. SVT-AV1 is a CPU-based multi-threaded video encoder for the AV1 video format with a sample YUV video file. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgFrames Per Second, More Is BetterSVT-AV1 1.8Encoder Mode: Preset 12 - Input: Bosphorus 1080pab120240360480600SE +/- 1.39, N = 3571.88569.961. (CXX) g++ options: -march=native -mno-avx -mavx2 -mavx512f -mavx512bw -mavx512dq
OpenBenchmarking.orgFrames Per Second, More Is BetterSVT-AV1 1.8Encoder Mode: Preset 12 - Input: Bosphorus 1080pab100200300400500Min: 569.28 / Avg: 571.88 / Max: 574.021. (CXX) g++ options: -march=native -mno-avx -mavx2 -mavx512f -mavx512bw -mavx512dq

OpenBenchmarking.orgFrames Per Second, More Is BetterSVT-AV1 1.8Encoder Mode: Preset 13 - Input: Bosphorus 1080pba140280420560700SE +/- 8.75, N = 3639.09635.811. (CXX) g++ options: -march=native -mno-avx -mavx2 -mavx512f -mavx512bw -mavx512dq
OpenBenchmarking.orgFrames Per Second, More Is BetterSVT-AV1 1.8Encoder Mode: Preset 13 - Input: Bosphorus 1080pba110220330440550Min: 620.74 / Avg: 635.81 / Max: 651.061. (CXX) g++ options: -march=native -mno-avx -mavx2 -mavx512f -mavx512bw -mavx512dq

Java SciMark

This test runs the Java version of SciMark 2, which is a benchmark for scientific and numerical computing developed by programmers at the National Institute of Standards and Technology. This benchmark is made up of Fast Foruier Transform, Jacobi Successive Over-relaxation, Monte Carlo, Sparse Matrix Multiply, and dense LU matrix factorization benchmarks. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgMflops, More Is BetterJava SciMark 2.2Computational Test: Jacobi Successive Over-Relaxationab400800120016002000SE +/- 0.16, N = 31703.421703.25
OpenBenchmarking.orgMflops, More Is BetterJava SciMark 2.2Computational Test: Jacobi Successive Over-Relaxationab30060090012001500Min: 1703.26 / Avg: 1703.42 / Max: 1703.73

OpenBenchmarking.orgMflops, More Is BetterJava SciMark 2.2Computational Test: Dense LU Matrix Factorizationba3K6K9K12K15KSE +/- 31.70, N = 313434.0913358.53
OpenBenchmarking.orgMflops, More Is BetterJava SciMark 2.2Computational Test: Dense LU Matrix Factorizationba2K4K6K8K10KMin: 13308.38 / Avg: 13358.53 / Max: 13417.19

OpenBenchmarking.orgMflops, More Is BetterJava SciMark 2.2Computational Test: Sparse Matrix Multiplyab6001200180024003000SE +/- 3.16, N = 32809.012792.09
OpenBenchmarking.orgMflops, More Is BetterJava SciMark 2.2Computational Test: Sparse Matrix Multiplyab5001000150020002500Min: 2804.52 / Avg: 2809.01 / Max: 2815.12

OpenBenchmarking.orgMflops, More Is BetterJava SciMark 2.2Computational Test: Fast Fourier Transformba90180270360450SE +/- 0.36, N = 3421.91420.74
OpenBenchmarking.orgMflops, More Is BetterJava SciMark 2.2Computational Test: Fast Fourier Transformba80160240320400Min: 420.05 / Avg: 420.74 / Max: 421.29

OpenBenchmarking.orgMflops, More Is BetterJava SciMark 2.2Computational Test: Monte Carloba400800120016002000SE +/- 0.75, N = 31632.451631.42
OpenBenchmarking.orgMflops, More Is BetterJava SciMark 2.2Computational Test: Monte Carloba30060090012001500Min: 1629.97 / Avg: 1631.42 / Max: 1632.45

160 Results Shown

LeelaChessZero:
  BLAS
  Eigen
PyTorch:
  CPU - 256 - Efficientnet_v2_l
  CPU - 16 - Efficientnet_v2_l
  CPU - 32 - Efficientnet_v2_l
Apache Spark TPC-H:
  50 - Q22
  50 - Q21
  50 - Q20
  50 - Q19
  50 - Q18
  50 - Q17
  50 - Q16
  50 - Q15
  50 - Q14
  50 - Q13
  50 - Q12
  50 - Q11
  50 - Q10
  50 - Q09
  50 - Q08
  50 - Q07
  50 - Q06
  50 - Q05
  50 - Q04
  50 - Q03
  50 - Q02
  50 - Q01
  50 - Geometric Mean Of All Queries
  10 - Q22
  10 - Q21
  10 - Q20
  10 - Q19
  10 - Q18
  10 - Q17
  10 - Q16
  10 - Q15
  10 - Q14
  10 - Q13
  10 - Q12
  10 - Q11
  10 - Q10
  10 - Q09
  10 - Q08
  10 - Q07
  10 - Q06
  10 - Q05
  10 - Q04
  10 - Q03
  10 - Q02
  10 - Q01
  10 - Geometric Mean Of All Queries
PyTorch:
  CPU - 32 - ResNet-152
  CPU - 16 - ResNet-152
  CPU - 256 - ResNet-152
WebP2 Image Encode
PyTorch
OpenSSL:
  SHA512
  SHA256
PyTorch:
  CPU - 1 - Efficientnet_v2_l
  CPU - 1 - ResNet-152
  CPU - 256 - ResNet-50
  CPU - 32 - ResNet-50
  CPU - 16 - ResNet-50
Neural Magic DeepSparse:
  BERT-Large, NLP Question Answering - Synchronous Single-Stream:
    ms/batch
    items/sec
  BERT-Large, NLP Question Answering - Asynchronous Multi-Stream:
    ms/batch
    items/sec
Apache Spark TPC-H:
  1 - Q22
  1 - Q21
  1 - Q20
  1 - Q19
  1 - Q18
  1 - Q17
  1 - Q16
  1 - Q15
  1 - Q14
  1 - Q13
  1 - Q12
  1 - Q11
  1 - Q10
  1 - Q09
  1 - Q08
  1 - Q07
  1 - Q06
  1 - Q05
  1 - Q04
  1 - Q03
  1 - Q02
  1 - Q01
  1 - Geometric Mean Of All Queries
OpenSSL:
  RSA4096:
    verify/s
    sign/s
WebP2 Image Encode
Neural Magic DeepSparse:
  NLP Text Classification, BERT base uncased SST2, Sparse INT8 - Synchronous Single-Stream:
    ms/batch
    items/sec
  NLP Document Classification, oBERT base uncased on IMDB - Asynchronous Multi-Stream:
    ms/batch
    items/sec
  BERT-Large, NLP Question Answering, Sparse INT8 - Asynchronous Multi-Stream:
    ms/batch
    items/sec
  NLP Token Classification, BERT base uncased conll2003 - Asynchronous Multi-Stream:
    ms/batch
    items/sec
  NLP Text Classification, BERT base uncased SST2, Sparse INT8 - Asynchronous Multi-Stream:
    ms/batch
    items/sec
  NLP Token Classification, BERT base uncased conll2003 - Synchronous Single-Stream:
    ms/batch
    items/sec
  BERT-Large, NLP Question Answering, Sparse INT8 - Synchronous Single-Stream:
    ms/batch
    items/sec
  NLP Document Classification, oBERT base uncased on IMDB - Synchronous Single-Stream:
    ms/batch
    items/sec
  CV Segmentation, 90% Pruned YOLACT Pruned - Asynchronous Multi-Stream:
    ms/batch
    items/sec
  NLP Text Classification, DistilBERT mnli - Asynchronous Multi-Stream:
    ms/batch
    items/sec
  CV Segmentation, 90% Pruned YOLACT Pruned - Synchronous Single-Stream:
    ms/batch
    items/sec
  NLP Text Classification, DistilBERT mnli - Synchronous Single-Stream:
    ms/batch
    items/sec
  CV Detection, YOLOv5s COCO - Asynchronous Multi-Stream:
    ms/batch
    items/sec
  CV Detection, YOLOv5s COCO, Sparse INT8 - Asynchronous Multi-Stream:
    ms/batch
    items/sec
  ResNet-50, Baseline - Asynchronous Multi-Stream:
    ms/batch
    items/sec
  ResNet-50, Sparse INT8 - Synchronous Single-Stream:
    ms/batch
    items/sec
  ResNet-50, Sparse INT8 - Asynchronous Multi-Stream:
    ms/batch
    items/sec
  CV Classification, ResNet-50 ImageNet - Asynchronous Multi-Stream:
    ms/batch
    items/sec
  CV Detection, YOLOv5s COCO - Synchronous Single-Stream:
    ms/batch
    items/sec
  CV Detection, YOLOv5s COCO, Sparse INT8 - Synchronous Single-Stream:
    ms/batch
    items/sec
  CV Classification, ResNet-50 ImageNet - Synchronous Single-Stream:
    ms/batch
    items/sec
  ResNet-50, Baseline - Synchronous Single-Stream:
    ms/batch
    items/sec
SVT-AV1
Xmrig
WebP2 Image Encode
Java SciMark
SVT-AV1:
  Preset 4 - Bosphorus 4K
  Preset 4 - Bosphorus 1080p
  Preset 8 - Bosphorus 4K
Xmrig:
  CryptoNight-Heavy - 1M
  CryptoNight-Femto UPX2 - 1M
  Monero - 1M
  KawPow - 1M
  Wownero - 1M
SVT-AV1:
  Preset 12 - Bosphorus 4K
  Preset 8 - Bosphorus 1080p
WebP2 Image Encode:
  Quality 100, Compression Effort 5
  Default
SVT-AV1:
  Preset 12 - Bosphorus 1080p
  Preset 13 - Bosphorus 1080p
Java SciMark:
  Jacobi Successive Over-Relaxation
  Dense LU Matrix Factorization
  Sparse Matrix Multiply
  Fast Fourier Transform
  Monte Carlo