X3D Zen 4

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Ryzen 9 7900X3D
March 03 2023
  14 Hours, 36 Minutes
Ryzen 9 7900X
March 04 2023
  15 Hours, 29 Minutes
Ryzen 9 79500X3D
March 04 2023
  15 Hours, 2 Minutes
Ryzen 9 7950X
March 05 2023
  14 Hours, 35 Minutes
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X3D Zen 4OpenBenchmarking.orgPhoronix Test SuiteAMD Ryzen 9 7900X3D 12-Core @ 4.40GHz (12 Cores / 24 Threads)AMD Ryzen 9 7900X 12-Core @ 4.70GHz (12 Cores / 24 Threads)AMD Ryzen 9 7950X3D 16-Core @ 4.20GHz (16 Cores / 32 Threads)AMD Ryzen 9 7950X 16-Core @ 4.50GHz (16 Cores / 32 Threads)ASUS ROG CROSSHAIR X670E HERO (9922 BIOS)AMD Device 14d832GBWestern Digital WD_BLACK SN850X 1000GB + 2000GBAMD Radeon RX 7900 XTX 24GB (2304/1249MHz)AMD Device ab30ASUS MG28UIntel I225-V + Intel Wi-Fi 6 AX210/AX211/AX411Ubuntu 23.046.2.2-060202-generic (x86_64)GNOME Shell 43.2X Server 1.21.1.6 + Wayland4.6 Mesa 23.1.0-devel (git-efcb639 2023-02-13 lunar-oibaf-ppa) (LLVM 15.0.7 DRM 3.49)GCC 12.2.0ext43840x2160ProcessorsMotherboardChipsetMemoryDiskGraphicsAudioMonitorNetworkOSKernelDesktopDisplay ServerOpenGLCompilerFile-SystemScreen ResolutionX3D Zen 4 BenchmarksSystem Logs- Transparent Huge Pages: madvise- --build=x86_64-linux-gnu --disable-vtable-verify --disable-werror --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-multiarch --enable-multilib --enable-nls --enable-objc-gc=auto --enable-offload-defaulted --enable-offload-targets=nvptx-none=/build/gcc-12-AKimc9/gcc-12-12.2.0/debian/tmp-nvptx/usr,amdgcn-amdhsa=/build/gcc-12-AKimc9/gcc-12-12.2.0/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-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: 0xa601203- Python 3.11.1- itlb_multihit: Not affected + l1tf: Not affected + mds: Not affected + meltdown: Not affected + mmio_stale_data: Not affected + retbleed: Not affected + spec_store_bypass: Mitigation of SSB disabled via prctl + spectre_v1: Mitigation of usercopy/swapgs barriers and __user pointer sanitization + spectre_v2: Mitigation of Retpolines IBPB: conditional IBRS_FW STIBP: always-on RSB filling PBRSB-eIBRS: Not affected + srbds: Not affected + tsx_async_abort: Not affected

Ryzen 9 7900X3DRyzen 9 7900XRyzen 9 79500X3DRyzen 9 7950XResult OverviewPhoronix Test Suite100%118%135%153%CloverLeafPennantACES DGEMMEmbreeoneDNNASKAPXmrigKTX-Software toktxOpenVINOGPAWGROMACSTensorFlowOpenFOAMXcompact3d Incompact3dClickHouseONNX RuntimeLULESHsrsRANZstd CompressionNCNNLeelaChessZeroPyHPC Benchmarks

X3D Zen 4openfoam: drivaerFastback, Medium Mesh Size - Execution Timeopenfoam: drivaerFastback, Medium Mesh Size - Mesh Timetensorflow: CPU - 256 - ResNet-50onnx: yolov4 - CPU - Standardonnx: yolov4 - CPU - Standardonnx: super-resolution-10 - CPU - Standardonnx: super-resolution-10 - CPU - Standardonnx: ArcFace ResNet-100 - CPU - Standardonnx: ArcFace ResNet-100 - CPU - Standardonnx: ResNet50 v1-12-int8 - CPU - Standardonnx: ResNet50 v1-12-int8 - CPU - Standardlczero: BLASlczero: Eigenonnx: CaffeNet 12-int8 - CPU - Standardonnx: CaffeNet 12-int8 - CPU - Standardonnx: Faster R-CNN R-50-FPN-int8 - CPU - Standardonnx: Faster R-CNN R-50-FPN-int8 - CPU - Standardtensorflow: CPU - 256 - GoogLeNetcompress-zstd: 19 - Decompression Speedcompress-zstd: 19 - Compression Speedcompress-zstd: 19, Long Mode - Decompression Speedcompress-zstd: 19, Long Mode - Compression Speedclickhouse: 100M Rows Hits Dataset, Third Runclickhouse: 100M Rows Hits Dataset, Second Runclickhouse: 100M Rows Hits Dataset, First Run / Cold Cacheonnx: GPT-2 - CPU - Standardonnx: GPT-2 - CPU - Standardtensorflow: CPU - 64 - ResNet-50toktx: UASTC 4 + Zstd Compression 19gpaw: Carbon Nanotubecompress-zstd: 8 - Decompression Speedcompress-zstd: 8 - Compression Speedonnx: fcn-resnet101-11 - CPU - Parallelonnx: fcn-resnet101-11 - CPU - Parallelonnx: yolov4 - CPU - Parallelonnx: yolov4 - CPU - Parallelonnx: CaffeNet 12-int8 - CPU - Parallelonnx: CaffeNet 12-int8 - CPU - Parallelonnx: bertsquad-12 - CPU - Parallelonnx: bertsquad-12 - CPU - Parallelncnn: CPU - FastestDetncnn: CPU - vision_transformerncnn: CPU - regnety_400mncnn: CPU - squeezenet_ssdncnn: CPU - yolov4-tinyncnn: CPU - resnet50ncnn: CPU - alexnetncnn: CPU - resnet18ncnn: CPU - vgg16ncnn: CPU - googlenetncnn: CPU - blazefacencnn: CPU - efficientnet-b0ncnn: CPU - mnasnetncnn: CPU - shufflenet-v2ncnn: CPU-v3-v3 - mobilenet-v3ncnn: CPU-v2-v2 - mobilenet-v2ncnn: CPU - mobilenetonnx: fcn-resnet101-11 - CPU - Standardonnx: fcn-resnet101-11 - CPU - Standardonnx: GPT-2 - CPU - Parallelonnx: GPT-2 - CPU - Parallelonnx: bertsquad-12 - CPU - Standardonnx: bertsquad-12 - CPU - Standardonnx: ArcFace ResNet-100 - CPU - Parallelonnx: ArcFace ResNet-100 - CPU - Parallelonnx: Faster R-CNN R-50-FPN-int8 - CPU - Parallelonnx: Faster R-CNN R-50-FPN-int8 - CPU - Parallelonnx: ResNet50 v1-12-int8 - CPU - Parallelonnx: ResNet50 v1-12-int8 - CPU - Parallelonnx: super-resolution-10 - CPU - Parallelonnx: super-resolution-10 - CPU - Paralleltensorflow: CPU - 32 - ResNet-50askap: tConvolve MT - Degriddingaskap: tConvolve MT - Griddingonednn: Recurrent Neural Network Training - bf16bf16bf16 - CPUonednn: Recurrent Neural Network Inference - bf16bf16bf16 - CPUtensorflow: CPU - 256 - AlexNetgromacs: MPI CPU - water_GMX50_bareincompact3d: input.i3d 193 Cells Per Directionxmrig: Monero - 1Mopenvino: Person Detection FP16 - CPUopenvino: Person Detection FP16 - CPUopenvino: Person Detection FP32 - CPUopenvino: Person Detection FP32 - CPUcompress-zstd: 3, Long Mode - Decompression Speedcompress-zstd: 3, Long Mode - Compression Speedcompress-zstd: 3 - Decompression Speedcompress-zstd: 3 - Compression Speedcompress-zstd: 12 - Decompression Speedcompress-zstd: 12 - Compression Speedopenvino: Face Detection FP16 - CPUopenvino: Face Detection FP16 - CPUopenvino: Face Detection FP16-INT8 - CPUopenvino: Face Detection FP16-INT8 - CPUcompress-zstd: 8, Long Mode - Decompression Speedcompress-zstd: 8, Long Mode - Compression Speedopenvino: Machine Translation EN To DE FP16 - CPUopenvino: Machine Translation EN To DE FP16 - CPUopenvino: Person Vehicle Bike Detection FP16 - CPUopenvino: Person Vehicle Bike Detection FP16 - CPUopenvino: Vehicle Detection FP16-INT8 - CPUopenvino: Vehicle Detection FP16-INT8 - CPUopenvino: Age Gender Recognition Retail 0013 FP16 - CPUopenvino: Age Gender Recognition Retail 0013 FP16 - CPUopenvino: Vehicle Detection FP16 - CPUopenvino: Vehicle Detection FP16 - CPUopenvino: Age Gender Recognition Retail 0013 FP16-INT8 - CPUopenvino: Age Gender Recognition Retail 0013 FP16-INT8 - CPUopenvino: Weld Porosity Detection FP16-INT8 - CPUopenvino: Weld Porosity Detection FP16-INT8 - CPUopenvino: Weld Porosity Detection FP16 - CPUopenvino: Weld Porosity Detection FP16 - CPUxmrig: Wownero - 1Mopenfoam: drivaerFastback, Small Mesh Size - Execution Timeopenfoam: drivaerFastback, Small Mesh Size - Mesh Timepyhpc: CPU - Numpy - 4194304 - Isoneutral Mixingtensorflow: CPU - 64 - GoogLeNetonednn: IP Shapes 1D - bf16bf16bf16 - CPUtensorflow: CPU - 16 - ResNet-50pyhpc: CPU - Numpy - 4194304 - Equation of Statecloverleaf: Lagrangian-Eulerian Hydrodynamicssrsran: 4G PHY_DL_Test 100 PRB MIMO 64-QAMsrsran: 4G PHY_DL_Test 100 PRB MIMO 64-QAMpennant: sedovbigembree: Pathtracer - Asian Dragon Objaskap: tConvolve MPI - Griddingaskap: tConvolve MPI - Degriddingsrsran: 4G PHY_DL_Test 100 PRB SISO 256-QAMsrsran: 4G PHY_DL_Test 100 PRB SISO 256-QAMembree: Pathtracer ISPC - Asian Dragon Objtensorflow: CPU - 32 - GoogLeNetonednn: Matrix Multiply Batch Shapes Transformer - bf16bf16bf16 - CPUmt-dgemm: Sustained Floating-Point Ratesrsran: 4G PHY_DL_Test 100 PRB MIMO 256-QAMsrsran: 4G PHY_DL_Test 100 PRB MIMO 256-QAMtensorflow: CPU - 64 - AlexNetembree: Pathtracer - Crownembree: Pathtracer - Asian Dragonpennant: leblancbigonednn: Deconvolution Batch shapes_1d - bf16bf16bf16 - CPUembree: Pathtracer ISPC - Crownembree: Pathtracer ISPC - Asian Dragonsrsran: OFDM_Testtensorflow: CPU - 16 - GoogLeNettensorflow: CPU - 32 - AlexNetincompact3d: input.i3d 129 Cells Per Directionaskap: Hogbom Clean OpenMPonednn: Convolution Batch Shapes Auto - bf16bf16bf16 - CPUtensorflow: CPU - 16 - AlexNettoktx: Zstd Compression 19srsran: 5G PHY_DL_NR Test 52 PRB SISO 64-QAMsrsran: 5G PHY_DL_NR Test 52 PRB SISO 64-QAMsrsran: 4G PHY_DL_Test 100 PRB SISO 64-QAMsrsran: 4G PHY_DL_Test 100 PRB SISO 64-QAMtoktx: UASTC 3 + Zstd Compression 19onednn: IP Shapes 3D - bf16bf16bf16 - CPUlulesh: askap: tConvolve OpenMP - Degriddingaskap: tConvolve OpenMP - Griddingtoktx: UASTC 3onednn: Deconvolution Batch shapes_3d - bf16bf16bf16 - CPUpyhpc: CPU - JAX - 4194304 - Isoneutral MixingRyzen 9 7900X3DRyzen 9 7900XRyzen 9 79500X3DRyzen 9 7950X1948.056193.3558938.89102.271110.078327.51702138.32725.563839.73682.36463424.169188217670.8655051155.1414.509368.9207118.962082.125.21876.314.3308.81303.48269.005.10690195.76039.06169.165143.1502352.91026.5664.5931.50536125.4677.970251.24481802.97977.567112.89294.3692.6511.0611.5714.7312.474.607.0825.949.031.494.573.253.733.143.579.33347.9732.873776.35362157.29253.137218.820535.142728.455520.717748.26452.97822335.70510.094799.054839.012906.782100.991560.86803.714328.372.27861.962960313564.71065.825.601064.335.612217.41319.62162.43710.72453.8298.3589.3910.15304.8619.642365.3940.955.65107.765.041188.174.771257.380.3930316.757.48801.870.6717663.846.121959.525.991000.4714966.1138.7360526.2090671.081123.261.0751038.110.72631.28235.3614.930.9376623.832412051.39923.93215.8585.926.9603126.270.3034648.215552250.3665.2278.3024.225526.552519.310425.1817227.045931.4349237333333124.65223.0312.6903210545.8611.38144158.9711.528136.8209.9250.6619.710.0371.161658953.046110078.066052.166.3742.029032161.5558199.3449840.36101.171910.110335.85153173.78423.944842.37882.33461430.959187917721.014088998.86016.881460.1065123.872101.823.41997.413.0290.14285.41258.645.79435172.80940.20157.108150.8682393.0857.4633.0951.57963116.2658.601151.20427830.06972.137413.86564.2284.5710.0511.7814.2412.384.987.7725.748.821.384.313.173.463.133.508.84571.2861.750536.83177146.33850.690319.727131.993631.258220.201749.49732.67309374.0118.89505112.41540.002755.492002.691434.06731.376353.602.27068.218612713863.01000.885.971012.485.902249.41393.721844014.32452.0248.8546.2010.95279.4821.442410.4808.553.54112.024.741265.144.411358.900.3533984.409.00666.350.6019661.305.512176.115.501089.1615870.6171.6184625.0164071.057125.620.97949938.90.71449.63240.6627.136.8809823.815811693.210092.1264.6669.426.4941127.670.2648268.248120254.9677.8294.4924.678826.507925.146124.7101327.639230.8877237000000128.74232.3014.6115010440.1831.81291162.6611.637145.3211.6251.1622.79.6981.517498484.56615756.775024.895.9441.798301863.9535178.1076943.88101.97409.996046.29145161.23027.308137.39452.06799486.612194517870.9381491084.90714.448670.1553137.772030.525.21872.415.0321.76316.84279.875.39416185.38444.20126.296126.8992391.61053.7522.6921.91347105.9299.440181.05436947.63567.547814.80884.6882.0311.9611.7214.2811.864.286.6024.348.521.634.603.403.863.313.768.87282.6443.539416.07438164.53249.535620.190729.770033.592720.140049.66052.59883384.7168.02960124.53044.272995.192293.311209.12623.394418.972.69558.773192415627.41085.087.321094.437.272254.01338.32203.63959.62452.8292.4589.4513.53304.0226.262422.11004.258.99135.504.821658.154.681706.680.3940658.967.971003.480.6723679.436.112616.086.011330.5319562.9125.9854223.9068451.074145.290.72951043.190.73129.18243.8638.327.0352431.00921249510858.8258.5660.134.1642149.390.22977311.258406256.8686.0339.8032.072734.703516.860823.9588636.237939.7144245966667147.01258.7712.5392537548.2501.08640176.2211.460144.2211.5252.0616.38.7471.083738987.939111369.66780.795.1261.507152126.1028190.9367344.87100.747110.086256.14984165.00722.568244.79412.06309485.241191517730.8169941224.0014.265670.0910140.762104.423.31990.012.5276.94275.45250.505.89782169.50244.58119.500138.0142379.1837.4509.3251.96381100.49489.954911.08333922.33761.610716.23444.4675.7611.4812.1414.2112.174.867.4624.618.581.544.403.233.623.153.628.70448.7642.228366.82261146.49747.001921.275527.303036.625619.327451.74242.43239411.0077.17184139.42544.392833.492173.951130.44578.911439.542.60766.213994313188.91040.727.651057.427.532223.81413.92170.14227.62439.9253.6554.4214.38281.5928.372390.4845.757.85138.144.781670.934.341843.30.3544741.9710.19784.250.6126015.995.532892.635.541442.5320609.4161.6749222.7938081.057143.880.66436043.080.72747.00236.9617.834.8457729.815311211.210788.8261.8665.831.7783147.080.21280110.983997250.7667.0351.0732.534333.632424.358773.6074836.554937.2215236600000146.99264.3314.6268368448.4592.10831176.7211.220142.9209.5247.4609.08.4051.522328479.87766156.826099.224.8851.40849OpenBenchmarking.org

OpenFOAM

OpenFOAM is the leading free, open-source software for computational fluid dynamics (CFD). This test profile currently uses the drivaerFastback test case for analyzing automotive aerodynamics or alternatively the older motorBike input. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgSeconds, Fewer Is BetterOpenFOAM 10Input: drivaerFastback, Medium Mesh Size - Execution TimeRyzen 9 7900X3DRyzen 9 7900XRyzen 9 79500X3DRyzen 9 7950X50010001500200025001948.062161.561863.952126.101. (CXX) g++ options: -std=c++14 -m64 -O3 -ftemplate-depth-100 -fPIC -fuse-ld=bfd -Xlinker --add-needed --no-as-needed -lfoamToVTK -ldynamicMesh -llagrangian -lgenericPatchFields -lfileFormats -lOpenFOAM -ldl -lm

OpenBenchmarking.orgSeconds, Fewer Is BetterOpenFOAM 10Input: drivaerFastback, Medium Mesh Size - Mesh TimeRyzen 9 7900X3DRyzen 9 7900XRyzen 9 79500X3DRyzen 9 7950X4080120160200193.36199.34178.11190.941. (CXX) g++ options: -std=c++14 -m64 -O3 -ftemplate-depth-100 -fPIC -fuse-ld=bfd -Xlinker --add-needed --no-as-needed -lfoamToVTK -ldynamicMesh -llagrangian -lgenericPatchFields -lfileFormats -lOpenFOAM -ldl -lm

TensorFlow

This is a benchmark of the TensorFlow deep learning framework using the TensorFlow reference benchmarks (tensorflow/benchmarks with tf_cnn_benchmarks.py). Note with the Phoronix Test Suite there is also pts/tensorflow-lite for benchmarking the TensorFlow Lite binaries too. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgimages/sec, More Is BetterTensorFlow 2.12-rc0Device: CPU - Batch Size: 256 - Model: ResNet-50Ryzen 9 7900X3DRyzen 9 7900XRyzen 9 79500X3DRyzen 9 7950X1020304050SE +/- 0.01, N = 3SE +/- 0.01, N = 3SE +/- 0.01, N = 3SE +/- 0.00, N = 338.8940.3643.8844.87

ONNX Runtime

ONNX Runtime is developed by Microsoft and partners as a open-source, cross-platform, high performance machine learning inferencing and training accelerator. This test profile runs the ONNX Runtime with various models available from the ONNX Model Zoo. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgInference Time Cost (ms), Fewer Is BetterONNX Runtime 1.14Model: yolov4 - Device: CPU - Executor: StandardRyzen 9 7900X3DRyzen 9 7900XRyzen 9 79500X3DRyzen 9 7950X20406080100SE +/- 4.87, N = 15SE +/- 4.06, N = 15SE +/- 3.62, N = 15SE +/- 3.19, N = 15102.27101.17101.97100.751. (CXX) g++ options: -ffunction-sections -fdata-sections -march=native -mtune=native -O3 -flto=auto -fno-fat-lto-objects -ldl -lrt

OpenBenchmarking.orgInferences Per Second, More Is BetterONNX Runtime 1.14Model: yolov4 - Device: CPU - Executor: StandardRyzen 9 7900X3DRyzen 9 7900XRyzen 9 79500X3DRyzen 9 7950X3691215SE +/- 0.45158, N = 15SE +/- 0.40412, N = 15SE +/- 0.38311, N = 15SE +/- 0.36261, N = 1510.0783210.110339.9960410.086251. (CXX) g++ options: -ffunction-sections -fdata-sections -march=native -mtune=native -O3 -flto=auto -fno-fat-lto-objects -ldl -lrt

OpenBenchmarking.orgInference Time Cost (ms), Fewer Is BetterONNX Runtime 1.14Model: super-resolution-10 - Device: CPU - Executor: StandardRyzen 9 7900X3DRyzen 9 7900XRyzen 9 79500X3DRyzen 9 7950X246810SE +/- 0.40239, N = 15SE +/- 0.22770, N = 15SE +/- 0.18428, N = 15SE +/- 0.19969, N = 137.517025.851536.291456.149841. (CXX) g++ options: -ffunction-sections -fdata-sections -march=native -mtune=native -O3 -flto=auto -fno-fat-lto-objects -ldl -lrt

OpenBenchmarking.orgInferences Per Second, More Is BetterONNX Runtime 1.14Model: super-resolution-10 - Device: CPU - Executor: StandardRyzen 9 7900X3DRyzen 9 7900XRyzen 9 79500X3DRyzen 9 7950X4080120160200SE +/- 7.10, N = 15SE +/- 5.34, N = 15SE +/- 5.64, N = 15SE +/- 6.30, N = 13138.33173.78161.23165.011. (CXX) g++ options: -ffunction-sections -fdata-sections -march=native -mtune=native -O3 -flto=auto -fno-fat-lto-objects -ldl -lrt

OpenBenchmarking.orgInference Time Cost (ms), Fewer Is BetterONNX Runtime 1.14Model: ArcFace ResNet-100 - Device: CPU - Executor: StandardRyzen 9 7900X3DRyzen 9 7900XRyzen 9 79500X3DRyzen 9 7950X612182430SE +/- 1.05, N = 12SE +/- 0.86, N = 15SE +/- 1.02, N = 15SE +/- 0.66, N = 1525.5623.9427.3122.571. (CXX) g++ options: -ffunction-sections -fdata-sections -march=native -mtune=native -O3 -flto=auto -fno-fat-lto-objects -ldl -lrt

OpenBenchmarking.orgInferences Per Second, More Is BetterONNX Runtime 1.14Model: ArcFace ResNet-100 - Device: CPU - Executor: StandardRyzen 9 7900X3DRyzen 9 7900XRyzen 9 79500X3DRyzen 9 7950X1020304050SE +/- 1.38, N = 12SE +/- 1.23, N = 15SE +/- 1.50, N = 15SE +/- 1.19, N = 1539.7442.3837.3944.791. (CXX) g++ options: -ffunction-sections -fdata-sections -march=native -mtune=native -O3 -flto=auto -fno-fat-lto-objects -ldl -lrt

OpenBenchmarking.orgInference Time Cost (ms), Fewer Is BetterONNX Runtime 1.14Model: ResNet50 v1-12-int8 - Device: CPU - Executor: StandardRyzen 9 7900X3DRyzen 9 7900XRyzen 9 79500X3DRyzen 9 7950X0.5321.0641.5962.1282.66SE +/- 0.03587, N = 15SE +/- 0.05616, N = 12SE +/- 0.04809, N = 15SE +/- 0.02087, N = 152.364632.334612.067992.063091. (CXX) g++ options: -ffunction-sections -fdata-sections -march=native -mtune=native -O3 -flto=auto -fno-fat-lto-objects -ldl -lrt

OpenBenchmarking.orgInferences Per Second, More Is BetterONNX Runtime 1.14Model: ResNet50 v1-12-int8 - Device: CPU - Executor: StandardRyzen 9 7900X3DRyzen 9 7900XRyzen 9 79500X3DRyzen 9 7950X110220330440550SE +/- 6.30, N = 15SE +/- 10.29, N = 12SE +/- 9.53, N = 15SE +/- 4.65, N = 15424.17430.96486.61485.241. (CXX) g++ options: -ffunction-sections -fdata-sections -march=native -mtune=native -O3 -flto=auto -fno-fat-lto-objects -ldl -lrt

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 0.28Backend: BLASRyzen 9 7900X3DRyzen 9 7900XRyzen 9 79500X3DRyzen 9 7950X400800120016002000SE +/- 23.20, N = 4SE +/- 14.80, N = 3SE +/- 13.05, N = 3SE +/- 14.71, N = 318821879194519151. (CXX) g++ options: -flto -pthread

OpenBenchmarking.orgNodes Per Second, More Is BetterLeelaChessZero 0.28Backend: EigenRyzen 9 7900X3DRyzen 9 7900XRyzen 9 79500X3DRyzen 9 7950X400800120016002000SE +/- 19.01, N = 4SE +/- 19.78, N = 3SE +/- 13.42, N = 3SE +/- 4.00, N = 317671772178717731. (CXX) g++ options: -flto -pthread

ONNX Runtime

ONNX Runtime is developed by Microsoft and partners as a open-source, cross-platform, high performance machine learning inferencing and training accelerator. This test profile runs the ONNX Runtime with various models available from the ONNX Model Zoo. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgInference Time Cost (ms), Fewer Is BetterONNX Runtime 1.14Model: CaffeNet 12-int8 - Device: CPU - Executor: StandardRyzen 9 7900X3DRyzen 9 7900XRyzen 9 79500X3DRyzen 9 7950X0.22820.45640.68460.91281.141SE +/- 0.005430, N = 3SE +/- 0.029891, N = 15SE +/- 0.033238, N = 15SE +/- 0.007823, N = 60.8655051.0140880.9381490.8169941. (CXX) g++ options: -ffunction-sections -fdata-sections -march=native -mtune=native -O3 -flto=auto -fno-fat-lto-objects -ldl -lrt

OpenBenchmarking.orgInferences Per Second, More Is BetterONNX Runtime 1.14Model: CaffeNet 12-int8 - Device: CPU - Executor: StandardRyzen 9 7900X3DRyzen 9 7900XRyzen 9 79500X3DRyzen 9 7950X30060090012001500SE +/- 7.21, N = 3SE +/- 31.87, N = 15SE +/- 39.20, N = 15SE +/- 11.41, N = 61155.14998.861084.911224.001. (CXX) g++ options: -ffunction-sections -fdata-sections -march=native -mtune=native -O3 -flto=auto -fno-fat-lto-objects -ldl -lrt

OpenBenchmarking.orgInference Time Cost (ms), Fewer Is BetterONNX Runtime 1.14Model: Faster R-CNN R-50-FPN-int8 - Device: CPU - Executor: StandardRyzen 9 7900X3DRyzen 9 7900XRyzen 9 79500X3DRyzen 9 7950X48121620SE +/- 0.08, N = 3SE +/- 0.55, N = 15SE +/- 0.48, N = 15SE +/- 0.02, N = 314.5116.8814.4514.271. (CXX) g++ options: -ffunction-sections -fdata-sections -march=native -mtune=native -O3 -flto=auto -fno-fat-lto-objects -ldl -lrt

OpenBenchmarking.orgInferences Per Second, More Is BetterONNX Runtime 1.14Model: Faster R-CNN R-50-FPN-int8 - Device: CPU - Executor: StandardRyzen 9 7900X3DRyzen 9 7900XRyzen 9 79500X3DRyzen 9 7950X1632486480SE +/- 0.38, N = 3SE +/- 1.94, N = 15SE +/- 2.04, N = 15SE +/- 0.09, N = 368.9260.1170.1670.091. (CXX) g++ options: -ffunction-sections -fdata-sections -march=native -mtune=native -O3 -flto=auto -fno-fat-lto-objects -ldl -lrt

TensorFlow

This is a benchmark of the TensorFlow deep learning framework using the TensorFlow reference benchmarks (tensorflow/benchmarks with tf_cnn_benchmarks.py). Note with the Phoronix Test Suite there is also pts/tensorflow-lite for benchmarking the TensorFlow Lite binaries too. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgimages/sec, More Is BetterTensorFlow 2.12-rc0Device: CPU - Batch Size: 256 - Model: GoogLeNetRyzen 9 7900X3DRyzen 9 7900XRyzen 9 79500X3DRyzen 9 7950X306090120150SE +/- 0.04, N = 3SE +/- 0.02, N = 3SE +/- 0.03, N = 3SE +/- 0.03, N = 3118.96123.87137.77140.76

Zstd Compression

This test measures the time needed to compress/decompress a sample file (silesia.tar) using Zstd (Zstandard) compression with options for different compression levels / settings. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgMB/s, More Is BetterZstd Compression 1.5.4Compression Level: 19 - Decompression SpeedRyzen 9 7900X3DRyzen 9 7900XRyzen 9 79500X3DRyzen 9 7950X5001000150020002500SE +/- 14.47, N = 15SE +/- 31.89, N = 3SE +/- 25.89, N = 15SE +/- 4.22, N = 32082.12101.82030.52104.41. (CC) gcc options: -O3 -pthread -lz -llzma -llz4

OpenBenchmarking.orgMB/s, More Is BetterZstd Compression 1.5.4Compression Level: 19 - Compression SpeedRyzen 9 7900X3DRyzen 9 7900XRyzen 9 79500X3DRyzen 9 7950X612182430SE +/- 0.31, N = 15SE +/- 0.03, N = 3SE +/- 0.37, N = 15SE +/- 0.09, N = 325.223.425.223.31. (CC) gcc options: -O3 -pthread -lz -llzma -llz4

OpenBenchmarking.orgMB/s, More Is BetterZstd Compression 1.5.4Compression Level: 19, Long Mode - Decompression SpeedRyzen 9 7900X3DRyzen 9 7900XRyzen 9 79500X3DRyzen 9 7950X400800120016002000SE +/- 29.67, N = 15SE +/- 8.37, N = 15SE +/- 16.22, N = 3SE +/- 6.34, N = 31876.31997.41872.41990.01. (CC) gcc options: -O3 -pthread -lz -llzma -llz4

OpenBenchmarking.orgMB/s, More Is BetterZstd Compression 1.5.4Compression Level: 19, Long Mode - Compression SpeedRyzen 9 7900X3DRyzen 9 7900XRyzen 9 79500X3DRyzen 9 7950X48121620SE +/- 0.15, N = 15SE +/- 0.12, N = 15SE +/- 0.03, N = 3SE +/- 0.03, N = 314.313.015.012.51. (CC) gcc options: -O3 -pthread -lz -llzma -llz4

ClickHouse

ClickHouse is an open-source, high performance OLAP data management system. This test profile uses ClickHouse's standard benchmark recommendations per https://clickhouse.com/docs/en/operations/performance-test/ / https://github.com/ClickHouse/ClickBench/tree/main/clickhouse with the 100 million rows web analytics dataset. The reported value is the query processing time using the geometric mean of all separate queries performed as an aggregate. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgQueries Per Minute, Geo Mean, More Is BetterClickHouse 22.12.3.5100M Rows Hits Dataset, Third RunRyzen 9 7900X3DRyzen 9 7900XRyzen 9 79500X3DRyzen 9 7950X70140210280350SE +/- 1.13, N = 3SE +/- 3.74, N = 3SE +/- 3.76, N = 3SE +/- 0.25, N = 3308.81290.14321.76276.94MIN: 14.79 / MAX: 12000MIN: 16.06 / MAX: 12000MIN: 15.82 / MAX: 10000MIN: 15.4 / MAX: 10000

OpenBenchmarking.orgQueries Per Minute, Geo Mean, More Is BetterClickHouse 22.12.3.5100M Rows Hits Dataset, Second RunRyzen 9 7900X3DRyzen 9 7900XRyzen 9 79500X3DRyzen 9 7950X70140210280350SE +/- 0.93, N = 3SE +/- 0.26, N = 3SE +/- 2.16, N = 3SE +/- 3.10, N = 3303.48285.41316.84275.45MIN: 14.85 / MAX: 10000MIN: 16.08 / MAX: 12000MIN: 16.12 / MAX: 10000MIN: 16.28 / MAX: 12000

OpenBenchmarking.orgQueries Per Minute, Geo Mean, More Is BetterClickHouse 22.12.3.5100M Rows Hits Dataset, First Run / Cold CacheRyzen 9 7900X3DRyzen 9 7900XRyzen 9 79500X3DRyzen 9 7950X60120180240300SE +/- 1.41, N = 3SE +/- 1.44, N = 3SE +/- 1.59, N = 3SE +/- 0.81, N = 3269.00258.64279.87250.50MIN: 14.44 / MAX: 8571.43MIN: 15.82 / MAX: 10000MIN: 13.15 / MAX: 7500MIN: 12.61 / MAX: 10000

ONNX Runtime

ONNX Runtime is developed by Microsoft and partners as a open-source, cross-platform, high performance machine learning inferencing and training accelerator. This test profile runs the ONNX Runtime with various models available from the ONNX Model Zoo. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgInference Time Cost (ms), Fewer Is BetterONNX Runtime 1.14Model: GPT-2 - Device: CPU - Executor: StandardRyzen 9 7900X3DRyzen 9 7900XRyzen 9 79500X3DRyzen 9 7950X1.3272.6543.9815.3086.635SE +/- 0.03513, N = 3SE +/- 0.06489, N = 15SE +/- 0.07238, N = 3SE +/- 0.01353, N = 35.106905.794355.394165.897821. (CXX) g++ options: -ffunction-sections -fdata-sections -march=native -mtune=native -O3 -flto=auto -fno-fat-lto-objects -ldl -lrt

OpenBenchmarking.orgInferences Per Second, More Is BetterONNX Runtime 1.14Model: GPT-2 - Device: CPU - Executor: StandardRyzen 9 7900X3DRyzen 9 7900XRyzen 9 79500X3DRyzen 9 7950X4080120160200SE +/- 1.34, N = 3SE +/- 1.80, N = 15SE +/- 2.46, N = 3SE +/- 0.39, N = 3195.76172.81185.38169.501. (CXX) g++ options: -ffunction-sections -fdata-sections -march=native -mtune=native -O3 -flto=auto -fno-fat-lto-objects -ldl -lrt

TensorFlow

This is a benchmark of the TensorFlow deep learning framework using the TensorFlow reference benchmarks (tensorflow/benchmarks with tf_cnn_benchmarks.py). Note with the Phoronix Test Suite there is also pts/tensorflow-lite for benchmarking the TensorFlow Lite binaries too. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgimages/sec, More Is BetterTensorFlow 2.12-rc0Device: CPU - Batch Size: 64 - Model: ResNet-50Ryzen 9 7900X3DRyzen 9 7900XRyzen 9 79500X3DRyzen 9 7950X1020304050SE +/- 0.02, N = 3SE +/- 0.01, N = 3SE +/- 0.04, N = 3SE +/- 0.02, N = 339.0640.2044.2044.58

KTX-Software toktx

This is a benchmark of The Khronos Group's KTX-Software library and tools. KTX-Software provides "toktx" for converting/creating in the KTX container format for image textures. This benchmark times how long it takes to convert to KTX 2.0 format with various settings using a reference PNG sample input. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgSeconds, Fewer Is BetterKTX-Software toktx 4.0Settings: UASTC 4 + Zstd Compression 19Ryzen 9 7900X3DRyzen 9 7900XRyzen 9 79500X3DRyzen 9 7950X4080120160200SE +/- 0.05, N = 3SE +/- 0.13, N = 3SE +/- 0.03, N = 3SE +/- 0.21, N = 3169.17157.11126.30119.50

GPAW

GPAW is a density-functional theory (DFT) Python code based on the projector-augmented wave (PAW) method and the atomic simulation environment (ASE). Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgSeconds, Fewer Is BetterGPAW 22.1Input: Carbon NanotubeRyzen 9 7900X3DRyzen 9 7900XRyzen 9 79500X3DRyzen 9 7950X306090120150SE +/- 0.15, N = 3SE +/- 0.21, N = 3SE +/- 0.16, N = 3SE +/- 0.12, N = 3143.15150.87126.90138.011. (CC) gcc options: -shared -fwrapv -O2 -lxc -lblas -lmpi

Zstd Compression

This test measures the time needed to compress/decompress a sample file (silesia.tar) using Zstd (Zstandard) compression with options for different compression levels / settings. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgMB/s, More Is BetterZstd Compression 1.5.4Compression Level: 8 - Decompression SpeedRyzen 9 7900X3DRyzen 9 7900XRyzen 9 79500X3DRyzen 9 7950X5001000150020002500SE +/- 4.93, N = 3SE +/- 6.76, N = 3SE +/- 15.85, N = 15SE +/- 7.71, N = 32352.92393.02391.62379.11. (CC) gcc options: -O3 -pthread -lz -llzma -llz4

OpenBenchmarking.orgMB/s, More Is BetterZstd Compression 1.5.4Compression Level: 8 - Compression SpeedRyzen 9 7900X3DRyzen 9 7900XRyzen 9 79500X3DRyzen 9 7950X2004006008001000SE +/- 7.21, N = 3SE +/- 1.87, N = 3SE +/- 9.05, N = 15SE +/- 3.61, N = 31026.5857.41053.7837.41. (CC) gcc options: -O3 -pthread -lz -llzma -llz4

ONNX Runtime

ONNX Runtime is developed by Microsoft and partners as a open-source, cross-platform, high performance machine learning inferencing and training accelerator. This test profile runs the ONNX Runtime with various models available from the ONNX Model Zoo. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgInference Time Cost (ms), Fewer Is BetterONNX Runtime 1.14Model: fcn-resnet101-11 - Device: CPU - Executor: ParallelRyzen 9 7900X3DRyzen 9 7900XRyzen 9 79500X3DRyzen 9 7950X140280420560700SE +/- 7.18, N = 5SE +/- 3.35, N = 3SE +/- 4.59, N = 3SE +/- 5.36, N = 3664.59633.10522.69509.331. (CXX) g++ options: -ffunction-sections -fdata-sections -march=native -mtune=native -O3 -flto=auto -fno-fat-lto-objects -ldl -lrt

OpenBenchmarking.orgInferences Per Second, More Is BetterONNX Runtime 1.14Model: fcn-resnet101-11 - Device: CPU - Executor: ParallelRyzen 9 7900X3DRyzen 9 7900XRyzen 9 79500X3DRyzen 9 7950X0.44190.88381.32571.76762.2095SE +/- 0.01582, N = 5SE +/- 0.00841, N = 3SE +/- 0.01691, N = 3SE +/- 0.02061, N = 31.505361.579631.913471.963811. (CXX) g++ options: -ffunction-sections -fdata-sections -march=native -mtune=native -O3 -flto=auto -fno-fat-lto-objects -ldl -lrt

OpenBenchmarking.orgInference Time Cost (ms), Fewer Is BetterONNX Runtime 1.14Model: yolov4 - Device: CPU - Executor: ParallelRyzen 9 7900X3DRyzen 9 7900XRyzen 9 79500X3DRyzen 9 7950X306090120150SE +/- 0.38, N = 3SE +/- 0.42, N = 3SE +/- 0.20, N = 3SE +/- 1.07, N = 5125.47116.27105.93100.491. (CXX) g++ options: -ffunction-sections -fdata-sections -march=native -mtune=native -O3 -flto=auto -fno-fat-lto-objects -ldl -lrt

OpenBenchmarking.orgInferences Per Second, More Is BetterONNX Runtime 1.14Model: yolov4 - Device: CPU - Executor: ParallelRyzen 9 7900X3DRyzen 9 7900XRyzen 9 79500X3DRyzen 9 7950X3691215SE +/- 0.02410, N = 3SE +/- 0.03144, N = 3SE +/- 0.01779, N = 3SE +/- 0.10261, N = 57.970258.601159.440189.954911. (CXX) g++ options: -ffunction-sections -fdata-sections -march=native -mtune=native -O3 -flto=auto -fno-fat-lto-objects -ldl -lrt

OpenBenchmarking.orgInference Time Cost (ms), Fewer Is BetterONNX Runtime 1.14Model: CaffeNet 12-int8 - Device: CPU - Executor: ParallelRyzen 9 7900X3DRyzen 9 7900XRyzen 9 79500X3DRyzen 9 7950X0.28010.56020.84031.12041.4005SE +/- 0.01782, N = 3SE +/- 0.01294, N = 5SE +/- 0.00846, N = 3SE +/- 0.00816, N = 31.244811.204271.054361.083331. (CXX) g++ options: -ffunction-sections -fdata-sections -march=native -mtune=native -O3 -flto=auto -fno-fat-lto-objects -ldl -lrt

OpenBenchmarking.orgInferences Per Second, More Is BetterONNX Runtime 1.14Model: CaffeNet 12-int8 - Device: CPU - Executor: ParallelRyzen 9 7900X3DRyzen 9 7900XRyzen 9 79500X3DRyzen 9 7950X2004006008001000SE +/- 11.49, N = 3SE +/- 9.08, N = 5SE +/- 7.64, N = 3SE +/- 6.96, N = 3802.98830.07947.64922.341. (CXX) g++ options: -ffunction-sections -fdata-sections -march=native -mtune=native -O3 -flto=auto -fno-fat-lto-objects -ldl -lrt

OpenBenchmarking.orgInference Time Cost (ms), Fewer Is BetterONNX Runtime 1.14Model: bertsquad-12 - Device: CPU - Executor: ParallelRyzen 9 7900X3DRyzen 9 7900XRyzen 9 79500X3DRyzen 9 7950X20406080100SE +/- 0.50, N = 3SE +/- 0.81, N = 3SE +/- 0.70, N = 4SE +/- 0.67, N = 377.5772.1467.5561.611. (CXX) g++ options: -ffunction-sections -fdata-sections -march=native -mtune=native -O3 -flto=auto -fno-fat-lto-objects -ldl -lrt

OpenBenchmarking.orgInferences Per Second, More Is BetterONNX Runtime 1.14Model: bertsquad-12 - Device: CPU - Executor: ParallelRyzen 9 7900X3DRyzen 9 7900XRyzen 9 79500X3DRyzen 9 7950X48121620SE +/- 0.08, N = 3SE +/- 0.15, N = 3SE +/- 0.15, N = 4SE +/- 0.18, N = 312.8913.8714.8116.231. (CXX) g++ options: -ffunction-sections -fdata-sections -march=native -mtune=native -O3 -flto=auto -fno-fat-lto-objects -ldl -lrt

NCNN

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

OpenBenchmarking.orgms, Fewer Is BetterNCNN 20220729Target: CPU - Model: FastestDetRyzen 9 7900X3DRyzen 9 7900XRyzen 9 79500X3DRyzen 9 7950X1.0532.1063.1594.2125.265SE +/- 0.07, N = 3SE +/- 0.19, N = 3SE +/- 0.02, N = 3SE +/- 0.03, N = 74.364.224.684.46MIN: 4.18 / MAX: 4.8MIN: 3.94 / MAX: 4.84MIN: 4.55 / MAX: 6.08MIN: 4.27 / MAX: 5.741. (CXX) g++ options: -O3 -rdynamic -lgomp -lpthread

OpenBenchmarking.orgms, Fewer Is BetterNCNN 20220729Target: CPU - Model: vision_transformerRyzen 9 7900X3DRyzen 9 7900XRyzen 9 79500X3DRyzen 9 7950X20406080100SE +/- 0.54, N = 3SE +/- 0.26, N = 3SE +/- 1.49, N = 3SE +/- 0.63, N = 792.6584.5782.0375.76MIN: 91.31 / MAX: 100.98MIN: 83.77 / MAX: 112.37MIN: 80.21 / MAX: 86.13MIN: 74.12 / MAX: 90.631. (CXX) g++ options: -O3 -rdynamic -lgomp -lpthread

OpenBenchmarking.orgms, Fewer Is BetterNCNN 20220729Target: CPU - Model: regnety_400mRyzen 9 7900X3DRyzen 9 7900XRyzen 9 79500X3DRyzen 9 7950X3691215SE +/- 0.02, N = 3SE +/- 0.12, N = 3SE +/- 0.02, N = 3SE +/- 0.09, N = 711.0610.0511.9611.48MIN: 10.51 / MAX: 18MIN: 9.63 / MAX: 43.59MIN: 11.54 / MAX: 15.93MIN: 10.72 / MAX: 48.41. (CXX) g++ options: -O3 -rdynamic -lgomp -lpthread

OpenBenchmarking.orgms, Fewer Is BetterNCNN 20220729Target: CPU - Model: squeezenet_ssdRyzen 9 7900X3DRyzen 9 7900XRyzen 9 79500X3DRyzen 9 7950X3691215SE +/- 0.26, N = 3SE +/- 0.14, N = 3SE +/- 0.06, N = 3SE +/- 0.08, N = 711.5711.7811.7212.14MIN: 10.88 / MAX: 89.31MIN: 11.23 / MAX: 63.22MIN: 11.48 / MAX: 18.6MIN: 11.7 / MAX: 20.561. (CXX) g++ options: -O3 -rdynamic -lgomp -lpthread

OpenBenchmarking.orgms, Fewer Is BetterNCNN 20220729Target: CPU - Model: yolov4-tinyRyzen 9 7900X3DRyzen 9 7900XRyzen 9 79500X3DRyzen 9 7950X48121620SE +/- 0.47, N = 3SE +/- 0.14, N = 3SE +/- 0.06, N = 3SE +/- 0.06, N = 714.7314.2414.2814.21MIN: 13.78 / MAX: 20.88MIN: 13.88 / MAX: 55.6MIN: 13.99 / MAX: 17.85MIN: 13.76 / MAX: 41.481. (CXX) g++ options: -O3 -rdynamic -lgomp -lpthread

OpenBenchmarking.orgms, Fewer Is BetterNCNN 20220729Target: CPU - Model: resnet50Ryzen 9 7900X3DRyzen 9 7900XRyzen 9 79500X3DRyzen 9 7950X3691215SE +/- 0.18, N = 3SE +/- 0.19, N = 3SE +/- 0.27, N = 3SE +/- 0.12, N = 712.4712.3811.8612.17MIN: 11.8 / MAX: 20.06MIN: 11.55 / MAX: 20.74MIN: 11.44 / MAX: 44.27MIN: 11.51 / MAX: 20.611. (CXX) g++ options: -O3 -rdynamic -lgomp -lpthread

OpenBenchmarking.orgms, Fewer Is BetterNCNN 20220729Target: CPU - Model: alexnetRyzen 9 7900X3DRyzen 9 7900XRyzen 9 79500X3DRyzen 9 7950X1.12052.2413.36154.4825.6025SE +/- 0.05, N = 3SE +/- 0.06, N = 3SE +/- 0.03, N = 3SE +/- 0.08, N = 74.604.984.284.86MIN: 4.43 / MAX: 11.35MIN: 4.73 / MAX: 10.59MIN: 4.13 / MAX: 10.29MIN: 4.63 / MAX: 9.891. (CXX) g++ options: -O3 -rdynamic -lgomp -lpthread

OpenBenchmarking.orgms, Fewer Is BetterNCNN 20220729Target: CPU - Model: resnet18Ryzen 9 7900X3DRyzen 9 7900XRyzen 9 79500X3DRyzen 9 7950X246810SE +/- 0.31, N = 3SE +/- 0.25, N = 3SE +/- 0.01, N = 3SE +/- 0.10, N = 77.087.776.607.46MIN: 6.25 / MAX: 13.9MIN: 7.02 / MAX: 14.55MIN: 6.42 / MAX: 12.76MIN: 7.15 / MAX: 14.271. (CXX) g++ options: -O3 -rdynamic -lgomp -lpthread

OpenBenchmarking.orgms, Fewer Is BetterNCNN 20220729Target: CPU - Model: vgg16Ryzen 9 7900X3DRyzen 9 7900XRyzen 9 79500X3DRyzen 9 7950X612182430SE +/- 0.43, N = 3SE +/- 0.35, N = 3SE +/- 0.45, N = 3SE +/- 0.40, N = 725.9425.7424.3424.61MIN: 24.38 / MAX: 80.6MIN: 24.62 / MAX: 110.19MIN: 23.49 / MAX: 49.31MIN: 23.44 / MAX: 36.141. (CXX) g++ options: -O3 -rdynamic -lgomp -lpthread

OpenBenchmarking.orgms, Fewer Is BetterNCNN 20220729Target: CPU - Model: googlenetRyzen 9 7900X3DRyzen 9 7900XRyzen 9 79500X3DRyzen 9 7950X3691215SE +/- 0.35, N = 3SE +/- 0.23, N = 3SE +/- 0.00, N = 3SE +/- 0.15, N = 79.038.828.528.58MIN: 7.88 / MAX: 43.33MIN: 7.98 / MAX: 72.14MIN: 8.28 / MAX: 14.26MIN: 8.16 / MAX: 15.241. (CXX) g++ options: -O3 -rdynamic -lgomp -lpthread

OpenBenchmarking.orgms, Fewer Is BetterNCNN 20220729Target: CPU - Model: blazefaceRyzen 9 7900X3DRyzen 9 7900XRyzen 9 79500X3DRyzen 9 7950X0.36680.73361.10041.46721.834SE +/- 0.02, N = 3SE +/- 0.01, N = 3SE +/- 0.00, N = 3SE +/- 0.01, N = 71.491.381.631.54MIN: 1.4 / MAX: 8.23MIN: 1.31 / MAX: 7.52MIN: 1.57 / MAX: 4.47MIN: 1.46 / MAX: 8.061. (CXX) g++ options: -O3 -rdynamic -lgomp -lpthread

OpenBenchmarking.orgms, Fewer Is BetterNCNN 20220729Target: CPU - Model: efficientnet-b0Ryzen 9 7900X3DRyzen 9 7900XRyzen 9 79500X3DRyzen 9 7950X1.0352.073.1054.145.175SE +/- 0.08, N = 3SE +/- 0.09, N = 3SE +/- 0.01, N = 3SE +/- 0.02, N = 74.574.314.604.40MIN: 4.29 / MAX: 38.08MIN: 4.09 / MAX: 69.92MIN: 4.49 / MAX: 8.48MIN: 4.27 / MAX: 12.061. (CXX) g++ options: -O3 -rdynamic -lgomp -lpthread

OpenBenchmarking.orgms, Fewer Is BetterNCNN 20220729Target: CPU - Model: mnasnetRyzen 9 7900X3DRyzen 9 7900XRyzen 9 79500X3DRyzen 9 7950X0.7651.532.2953.063.825SE +/- 0.02, N = 3SE +/- 0.08, N = 3SE +/- 0.01, N = 3SE +/- 0.02, N = 73.253.173.403.23MIN: 3.13 / MAX: 9.66MIN: 3 / MAX: 45.73MIN: 3.28 / MAX: 7.36MIN: 3.12 / MAX: 10.321. (CXX) g++ options: -O3 -rdynamic -lgomp -lpthread

OpenBenchmarking.orgms, Fewer Is BetterNCNN 20220729Target: CPU - Model: shufflenet-v2Ryzen 9 7900X3DRyzen 9 7900XRyzen 9 79500X3DRyzen 9 7950X0.86851.7372.60553.4744.3425SE +/- 0.02, N = 3SE +/- 0.03, N = 3SE +/- 0.01, N = 3SE +/- 0.02, N = 73.733.463.863.62MIN: 3.55 / MAX: 9.54MIN: 3.36 / MAX: 9.94MIN: 3.71 / MAX: 9.56MIN: 3.44 / MAX: 10.541. (CXX) g++ options: -O3 -rdynamic -lgomp -lpthread

OpenBenchmarking.orgms, Fewer Is BetterNCNN 20220729Target: CPU-v3-v3 - Model: mobilenet-v3Ryzen 9 7900X3DRyzen 9 7900XRyzen 9 79500X3DRyzen 9 7950X0.74481.48962.23442.97923.724SE +/- 0.01, N = 3SE +/- 0.07, N = 3SE +/- 0.01, N = 3SE +/- 0.01, N = 73.143.133.313.15MIN: 3.07 / MAX: 7.15MIN: 2.81 / MAX: 65.6MIN: 3.21 / MAX: 7.38MIN: 3.05 / MAX: 9.871. (CXX) g++ options: -O3 -rdynamic -lgomp -lpthread

OpenBenchmarking.orgms, Fewer Is BetterNCNN 20220729Target: CPU-v2-v2 - Model: mobilenet-v2Ryzen 9 7900X3DRyzen 9 7900XRyzen 9 79500X3DRyzen 9 7950X0.8461.6922.5383.3844.23SE +/- 0.01, N = 3SE +/- 0.04, N = 3SE +/- 0.01, N = 3SE +/- 0.02, N = 73.573.503.763.62MIN: 3.49 / MAX: 7.6MIN: 3.31 / MAX: 10.67MIN: 3.66 / MAX: 7.74MIN: 3.49 / MAX: 11.581. (CXX) g++ options: -O3 -rdynamic -lgomp -lpthread

OpenBenchmarking.orgms, Fewer Is BetterNCNN 20220729Target: CPU - Model: mobilenetRyzen 9 7900X3DRyzen 9 7900XRyzen 9 79500X3DRyzen 9 7950X3691215SE +/- 0.06, N = 3SE +/- 0.10, N = 3SE +/- 0.02, N = 3SE +/- 0.08, N = 79.338.848.878.70MIN: 9.06 / MAX: 16.18MIN: 8.3 / MAX: 71.01MIN: 8.73 / MAX: 12.08MIN: 8.36 / MAX: 15.031. (CXX) g++ options: -O3 -rdynamic -lgomp -lpthread

ONNX Runtime

ONNX Runtime is developed by Microsoft and partners as a open-source, cross-platform, high performance machine learning inferencing and training accelerator. This test profile runs the ONNX Runtime with various models available from the ONNX Model Zoo. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgInference Time Cost (ms), Fewer Is BetterONNX Runtime 1.14Model: fcn-resnet101-11 - Device: CPU - Executor: StandardRyzen 9 7900X3DRyzen 9 7900XRyzen 9 79500X3DRyzen 9 7950X120240360480600SE +/- 0.19, N = 3SE +/- 3.02, N = 3SE +/- 4.02, N = 3SE +/- 1.13, N = 3347.97571.29282.64448.761. (CXX) g++ options: -ffunction-sections -fdata-sections -march=native -mtune=native -O3 -flto=auto -fno-fat-lto-objects -ldl -lrt

OpenBenchmarking.orgInferences Per Second, More Is BetterONNX Runtime 1.14Model: fcn-resnet101-11 - Device: CPU - Executor: StandardRyzen 9 7900X3DRyzen 9 7900XRyzen 9 79500X3DRyzen 9 7950X0.79641.59282.38923.18563.982SE +/- 0.00156, N = 3SE +/- 0.00921, N = 3SE +/- 0.04984, N = 3SE +/- 0.00558, N = 32.873771.750533.539412.228361. (CXX) g++ options: -ffunction-sections -fdata-sections -march=native -mtune=native -O3 -flto=auto -fno-fat-lto-objects -ldl -lrt

OpenBenchmarking.orgInference Time Cost (ms), Fewer Is BetterONNX Runtime 1.14Model: GPT-2 - Device: CPU - Executor: ParallelRyzen 9 7900X3DRyzen 9 7900XRyzen 9 79500X3DRyzen 9 7950X246810SE +/- 0.02269, N = 3SE +/- 0.07342, N = 3SE +/- 0.02467, N = 3SE +/- 0.00930, N = 36.353626.831776.074386.822611. (CXX) g++ options: -ffunction-sections -fdata-sections -march=native -mtune=native -O3 -flto=auto -fno-fat-lto-objects -ldl -lrt

OpenBenchmarking.orgInferences Per Second, More Is BetterONNX Runtime 1.14Model: GPT-2 - Device: CPU - Executor: ParallelRyzen 9 7900X3DRyzen 9 7900XRyzen 9 79500X3DRyzen 9 7950X4080120160200SE +/- 0.56, N = 3SE +/- 1.56, N = 3SE +/- 0.66, N = 3SE +/- 0.20, N = 3157.29146.34164.53146.501. (CXX) g++ options: -ffunction-sections -fdata-sections -march=native -mtune=native -O3 -flto=auto -fno-fat-lto-objects -ldl -lrt

OpenBenchmarking.orgInference Time Cost (ms), Fewer Is BetterONNX Runtime 1.14Model: bertsquad-12 - Device: CPU - Executor: StandardRyzen 9 7900X3DRyzen 9 7900XRyzen 9 79500X3DRyzen 9 7950X1224364860SE +/- 0.34, N = 3SE +/- 0.07, N = 3SE +/- 0.47, N = 3SE +/- 0.16, N = 353.1450.6949.5447.001. (CXX) g++ options: -ffunction-sections -fdata-sections -march=native -mtune=native -O3 -flto=auto -fno-fat-lto-objects -ldl -lrt

OpenBenchmarking.orgInferences Per Second, More Is BetterONNX Runtime 1.14Model: bertsquad-12 - Device: CPU - Executor: StandardRyzen 9 7900X3DRyzen 9 7900XRyzen 9 79500X3DRyzen 9 7950X510152025SE +/- 0.12, N = 3SE +/- 0.03, N = 3SE +/- 0.19, N = 3SE +/- 0.07, N = 318.8219.7320.1921.281. (CXX) g++ options: -ffunction-sections -fdata-sections -march=native -mtune=native -O3 -flto=auto -fno-fat-lto-objects -ldl -lrt

OpenBenchmarking.orgInference Time Cost (ms), Fewer Is BetterONNX Runtime 1.14Model: ArcFace ResNet-100 - Device: CPU - Executor: ParallelRyzen 9 7900X3DRyzen 9 7900XRyzen 9 79500X3DRyzen 9 7950X816243240SE +/- 0.13, N = 3SE +/- 0.21, N = 3SE +/- 0.19, N = 3SE +/- 0.08, N = 335.1431.9929.7727.301. (CXX) g++ options: -ffunction-sections -fdata-sections -march=native -mtune=native -O3 -flto=auto -fno-fat-lto-objects -ldl -lrt

OpenBenchmarking.orgInferences Per Second, More Is BetterONNX Runtime 1.14Model: ArcFace ResNet-100 - Device: CPU - Executor: ParallelRyzen 9 7900X3DRyzen 9 7900XRyzen 9 79500X3DRyzen 9 7950X816243240SE +/- 0.11, N = 3SE +/- 0.21, N = 3SE +/- 0.21, N = 3SE +/- 0.11, N = 328.4631.2633.5936.631. (CXX) g++ options: -ffunction-sections -fdata-sections -march=native -mtune=native -O3 -flto=auto -fno-fat-lto-objects -ldl -lrt

OpenBenchmarking.orgInference Time Cost (ms), Fewer Is BetterONNX Runtime 1.14Model: Faster R-CNN R-50-FPN-int8 - Device: CPU - Executor: ParallelRyzen 9 7900X3DRyzen 9 7900XRyzen 9 79500X3DRyzen 9 7950X510152025SE +/- 0.04, N = 3SE +/- 0.02, N = 3SE +/- 0.23, N = 3SE +/- 0.16, N = 320.7220.2020.1419.331. (CXX) g++ options: -ffunction-sections -fdata-sections -march=native -mtune=native -O3 -flto=auto -fno-fat-lto-objects -ldl -lrt

OpenBenchmarking.orgInferences Per Second, More Is BetterONNX Runtime 1.14Model: Faster R-CNN R-50-FPN-int8 - Device: CPU - Executor: ParallelRyzen 9 7900X3DRyzen 9 7900XRyzen 9 79500X3DRyzen 9 7950X1224364860SE +/- 0.10, N = 3SE +/- 0.05, N = 3SE +/- 0.55, N = 3SE +/- 0.42, N = 348.2649.5049.6651.741. (CXX) g++ options: -ffunction-sections -fdata-sections -march=native -mtune=native -O3 -flto=auto -fno-fat-lto-objects -ldl -lrt

OpenBenchmarking.orgInference Time Cost (ms), Fewer Is BetterONNX Runtime 1.14Model: ResNet50 v1-12-int8 - Device: CPU - Executor: ParallelRyzen 9 7900X3DRyzen 9 7900XRyzen 9 79500X3DRyzen 9 7950X0.67011.34022.01032.68043.3505SE +/- 0.01374, N = 3SE +/- 0.01009, N = 3SE +/- 0.01408, N = 3SE +/- 0.00583, N = 32.978222.673092.598832.432391. (CXX) g++ options: -ffunction-sections -fdata-sections -march=native -mtune=native -O3 -flto=auto -fno-fat-lto-objects -ldl -lrt

OpenBenchmarking.orgInferences Per Second, More Is BetterONNX Runtime 1.14Model: ResNet50 v1-12-int8 - Device: CPU - Executor: ParallelRyzen 9 7900X3DRyzen 9 7900XRyzen 9 79500X3DRyzen 9 7950X90180270360450SE +/- 1.54, N = 3SE +/- 1.41, N = 3SE +/- 2.07, N = 3SE +/- 0.99, N = 3335.71374.01384.72411.011. (CXX) g++ options: -ffunction-sections -fdata-sections -march=native -mtune=native -O3 -flto=auto -fno-fat-lto-objects -ldl -lrt

OpenBenchmarking.orgInference Time Cost (ms), Fewer Is BetterONNX Runtime 1.14Model: super-resolution-10 - Device: CPU - Executor: ParallelRyzen 9 7900X3DRyzen 9 7900XRyzen 9 79500X3DRyzen 9 7950X3691215SE +/- 0.00988, N = 3SE +/- 0.01908, N = 3SE +/- 0.01572, N = 3SE +/- 0.02538, N = 310.094708.895058.029607.171841. (CXX) g++ options: -ffunction-sections -fdata-sections -march=native -mtune=native -O3 -flto=auto -fno-fat-lto-objects -ldl -lrt

OpenBenchmarking.orgInferences Per Second, More Is BetterONNX Runtime 1.14Model: super-resolution-10 - Device: CPU - Executor: ParallelRyzen 9 7900X3DRyzen 9 7900XRyzen 9 79500X3DRyzen 9 7950X306090120150SE +/- 0.10, N = 3SE +/- 0.24, N = 3SE +/- 0.24, N = 3SE +/- 0.49, N = 399.05112.42124.53139.431. (CXX) g++ options: -ffunction-sections -fdata-sections -march=native -mtune=native -O3 -flto=auto -fno-fat-lto-objects -ldl -lrt

TensorFlow

This is a benchmark of the TensorFlow deep learning framework using the TensorFlow reference benchmarks (tensorflow/benchmarks with tf_cnn_benchmarks.py). Note with the Phoronix Test Suite there is also pts/tensorflow-lite for benchmarking the TensorFlow Lite binaries too. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgimages/sec, More Is BetterTensorFlow 2.12-rc0Device: CPU - Batch Size: 32 - Model: ResNet-50Ryzen 9 7900X3DRyzen 9 7900XRyzen 9 79500X3DRyzen 9 7950X1020304050SE +/- 0.06, N = 3SE +/- 0.01, N = 3SE +/- 0.06, N = 3SE +/- 0.03, N = 339.0140.0044.2744.39

ASKAP

ASKAP is a set of benchmarks from the Australian SKA Pathfinder. The principal ASKAP benchmarks are the Hogbom Clean Benchmark (tHogbomClean) and Convolutional Resamping Benchmark (tConvolve) as well as some previous ASKAP benchmarks being included as well for OpenCL and CUDA execution of tConvolve. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgMillion Grid Points Per Second, More Is BetterASKAP 1.0Test: tConvolve MT - DegriddingRyzen 9 7900X3DRyzen 9 7900XRyzen 9 79500X3DRyzen 9 7950X6001200180024003000SE +/- 24.29, N = 3SE +/- 39.07, N = 3SE +/- 7.84, N = 3SE +/- 6.59, N = 32906.782755.492995.192833.491. (CXX) g++ options: -O3 -fstrict-aliasing -fopenmp

OpenBenchmarking.orgMillion Grid Points Per Second, More Is BetterASKAP 1.0Test: tConvolve MT - GriddingRyzen 9 7900X3DRyzen 9 7900XRyzen 9 79500X3DRyzen 9 7950X5001000150020002500SE +/- 11.10, N = 3SE +/- 11.79, N = 3SE +/- 8.06, N = 3SE +/- 8.23, N = 32100.992002.692293.312173.951. (CXX) g++ options: -O3 -fstrict-aliasing -fopenmp

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 3.0Harness: Recurrent Neural Network Training - Data Type: bf16bf16bf16 - Engine: CPURyzen 9 7900X3DRyzen 9 7900XRyzen 9 79500X3DRyzen 9 7950X30060090012001500SE +/- 1.50, N = 3SE +/- 1.79, N = 3SE +/- 2.36, N = 3SE +/- 1.31, N = 31560.861434.061209.121130.44MIN: 1554.07MIN: 1423.92MIN: 1195.27MIN: 1121.321. (CXX) g++ options: -O3 -march=native -fopenmp -msse4.1 -fPIC -pie -ldl -lpthread

OpenBenchmarking.orgms, Fewer Is BetteroneDNN 3.0Harness: Recurrent Neural Network Inference - Data Type: bf16bf16bf16 - Engine: CPURyzen 9 7900X3DRyzen 9 7900XRyzen 9 79500X3DRyzen 9 7950X2004006008001000SE +/- 2.26, N = 3SE +/- 1.56, N = 3SE +/- 1.70, N = 3SE +/- 4.41, N = 3803.71731.38623.39578.91MIN: 796.39MIN: 721.81MIN: 614.18MIN: 566.671. (CXX) g++ options: -O3 -march=native -fopenmp -msse4.1 -fPIC -pie -ldl -lpthread

TensorFlow

This is a benchmark of the TensorFlow deep learning framework using the TensorFlow reference benchmarks (tensorflow/benchmarks with tf_cnn_benchmarks.py). Note with the Phoronix Test Suite there is also pts/tensorflow-lite for benchmarking the TensorFlow Lite binaries too. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgimages/sec, More Is BetterTensorFlow 2.12-rc0Device: CPU - Batch Size: 256 - Model: AlexNetRyzen 9 7900X3DRyzen 9 7900XRyzen 9 79500X3DRyzen 9 7950X100200300400500SE +/- 0.33, N = 3SE +/- 0.11, N = 3SE +/- 0.24, N = 3SE +/- 0.19, N = 3328.37353.60418.97439.54

GROMACS

The GROMACS (GROningen MAchine for Chemical Simulations) molecular dynamics package testing with the water_GMX50 data. This test profile allows selecting between CPU and GPU-based GROMACS builds. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgNs Per Day, More Is BetterGROMACS 2023Implementation: MPI CPU - Input: water_GMX50_bareRyzen 9 7900X3DRyzen 9 7900XRyzen 9 79500X3DRyzen 9 7950X0.60641.21281.81922.42563.032SE +/- 0.002, N = 3SE +/- 0.004, N = 3SE +/- 0.002, N = 3SE +/- 0.004, N = 32.2782.2702.6952.6071. (CXX) g++ options: -O3

Xcompact3d Incompact3d

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

OpenBenchmarking.orgSeconds, Fewer Is BetterXcompact3d Incompact3d 2021-03-11Input: input.i3d 193 Cells Per DirectionRyzen 9 7900X3DRyzen 9 7900XRyzen 9 79500X3DRyzen 9 7950X1530456075SE +/- 0.70, N = 4SE +/- 0.82, N = 3SE +/- 0.66, N = 4SE +/- 0.31, N = 361.9668.2258.7766.211. (F9X) gfortran options: -cpp -O2 -funroll-loops -floop-optimize -fcray-pointer -fbacktrace -lmpi_usempif08 -lmpi_mpifh -lmpi -lopen-rte -lopen-pal -lhwloc -levent_core -levent_pthreads -lm -lz

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 Xmlrig CPU mining performance. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgH/s, More Is BetterXmrig 6.18.1Variant: Monero - Hash Count: 1MRyzen 9 7900X3DRyzen 9 7900XRyzen 9 79500X3DRyzen 9 7950X3K6K9K12K15KSE +/- 76.91, N = 3SE +/- 111.27, N = 3SE +/- 69.71, N = 3SE +/- 39.19, N = 313564.713863.015627.413188.91. (CXX) g++ options: -fexceptions -fno-rtti -maes -O3 -Ofast -static-libgcc -static-libstdc++ -rdynamic -lssl -lcrypto -luv -lpthread -lrt -ldl -lhwloc

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.orgms, Fewer Is BetterOpenVINO 2022.3Model: Person Detection FP16 - Device: CPURyzen 9 7900X3DRyzen 9 7900XRyzen 9 79500X3DRyzen 9 7950X2004006008001000SE +/- 3.14, N = 3SE +/- 7.16, N = 3SE +/- 2.36, N = 3SE +/- 1.82, N = 31065.821000.881085.081040.72MIN: 618.47 / MAX: 1180.09MIN: 603.97 / MAX: 1146.51MIN: 997.16 / MAX: 1282.69MIN: 623.58 / MAX: 1238.551. (CXX) g++ options: -fPIC -fsigned-char -ffunction-sections -fdata-sections -O3 -fno-strict-overflow -fwrapv -shared

OpenBenchmarking.orgFPS, More Is BetterOpenVINO 2022.3Model: Person Detection FP16 - Device: CPURyzen 9 7900X3DRyzen 9 7900XRyzen 9 79500X3DRyzen 9 7950X246810SE +/- 0.02, N = 3SE +/- 0.05, N = 3SE +/- 0.01, N = 3SE +/- 0.01, N = 35.605.977.327.651. (CXX) g++ options: -fPIC -fsigned-char -ffunction-sections -fdata-sections -O3 -fno-strict-overflow -fwrapv -shared

OpenBenchmarking.orgms, Fewer Is BetterOpenVINO 2022.3Model: Person Detection FP32 - Device: CPURyzen 9 7900X3DRyzen 9 7900XRyzen 9 79500X3DRyzen 9 7950X2004006008001000SE +/- 2.18, N = 3SE +/- 3.50, N = 3SE +/- 6.09, N = 3SE +/- 8.14, N = 31064.331012.481094.431057.42MIN: 940.91 / MAX: 1184.64MIN: 584.86 / MAX: 1150.29MIN: 672.11 / MAX: 1267.85MIN: 582.42 / MAX: 1238.031. (CXX) g++ options: -fPIC -fsigned-char -ffunction-sections -fdata-sections -O3 -fno-strict-overflow -fwrapv -shared

OpenBenchmarking.orgFPS, More Is BetterOpenVINO 2022.3Model: Person Detection FP32 - Device: CPURyzen 9 7900X3DRyzen 9 7900XRyzen 9 79500X3DRyzen 9 7950X246810SE +/- 0.02, N = 3SE +/- 0.02, N = 3SE +/- 0.04, N = 3SE +/- 0.06, N = 35.615.907.277.531. (CXX) g++ options: -fPIC -fsigned-char -ffunction-sections -fdata-sections -O3 -fno-strict-overflow -fwrapv -shared

Zstd Compression

This test measures the time needed to compress/decompress a sample file (silesia.tar) using Zstd (Zstandard) compression with options for different compression levels / settings. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgMB/s, More Is BetterZstd Compression 1.5.4Compression Level: 3, Long Mode - Decompression SpeedRyzen 9 7900X3DRyzen 9 7900XRyzen 9 79500X3DRyzen 9 7950X5001000150020002500SE +/- 5.96, N = 3SE +/- 3.63, N = 3SE +/- 3.72, N = 3SE +/- 4.39, N = 32217.42249.42254.02223.81. (CC) gcc options: -O3 -pthread -lz -llzma -llz4

OpenBenchmarking.orgMB/s, More Is BetterZstd Compression 1.5.4Compression Level: 3, Long Mode - Compression SpeedRyzen 9 7900X3DRyzen 9 7900XRyzen 9 79500X3DRyzen 9 7950X30060090012001500SE +/- 7.40, N = 3SE +/- 1.62, N = 3SE +/- 1.80, N = 3SE +/- 3.37, N = 31319.61393.71338.31413.91. (CC) gcc options: -O3 -pthread -lz -llzma -llz4

OpenBenchmarking.orgMB/s, More Is BetterZstd Compression 1.5.4Compression Level: 3 - Decompression SpeedRyzen 9 7900X3DRyzen 9 7900XRyzen 9 79500X3DRyzen 9 7950X5001000150020002500SE +/- 7.53, N = 3SE +/- 5.24, N = 3SE +/- 6.56, N = 3SE +/- 3.32, N = 32162.42184.02203.62170.11. (CC) gcc options: -O3 -pthread -lz -llzma -llz4

OpenBenchmarking.orgMB/s, More Is BetterZstd Compression 1.5.4Compression Level: 3 - Compression SpeedRyzen 9 7900X3DRyzen 9 7900XRyzen 9 79500X3DRyzen 9 7950X9001800270036004500SE +/- 10.85, N = 3SE +/- 10.25, N = 3SE +/- 2.07, N = 3SE +/- 22.63, N = 33710.74014.33959.64227.61. (CC) gcc options: -O3 -pthread -lz -llzma -llz4

OpenBenchmarking.orgMB/s, More Is BetterZstd Compression 1.5.4Compression Level: 12 - Decompression SpeedRyzen 9 7900X3DRyzen 9 7900XRyzen 9 79500X3DRyzen 9 7950X5001000150020002500SE +/- 2.91, N = 3SE +/- 16.52, N = 3SE +/- 9.67, N = 3SE +/- 6.83, N = 32453.82452.02452.82439.91. (CC) gcc options: -O3 -pthread -lz -llzma -llz4

OpenBenchmarking.orgMB/s, More Is BetterZstd Compression 1.5.4Compression Level: 12 - Compression SpeedRyzen 9 7900X3DRyzen 9 7900XRyzen 9 79500X3DRyzen 9 7950X60120180240300SE +/- 2.69, N = 3SE +/- 0.55, N = 3SE +/- 1.20, N = 3SE +/- 1.42, N = 3298.3248.8292.4253.61. (CC) gcc options: -O3 -pthread -lz -llzma -llz4

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.orgms, Fewer Is BetterOpenVINO 2022.3Model: Face Detection FP16 - Device: CPURyzen 9 7900X3DRyzen 9 7900XRyzen 9 79500X3DRyzen 9 7950X130260390520650SE +/- 0.29, N = 3SE +/- 0.69, N = 3SE +/- 0.95, N = 3SE +/- 0.39, N = 3589.39546.20589.45554.42MIN: 309.39 / MAX: 685.91MIN: 275.75 / MAX: 574.42MIN: 407.34 / MAX: 615.98MIN: 280.02 / MAX: 579.261. (CXX) g++ options: -fPIC -fsigned-char -ffunction-sections -fdata-sections -O3 -fno-strict-overflow -fwrapv -shared

OpenBenchmarking.orgFPS, More Is BetterOpenVINO 2022.3Model: Face Detection FP16 - Device: CPURyzen 9 7900X3DRyzen 9 7900XRyzen 9 79500X3DRyzen 9 7950X48121620SE +/- 0.00, N = 3SE +/- 0.02, N = 3SE +/- 0.03, N = 3SE +/- 0.02, N = 310.1510.9513.5314.381. (CXX) g++ options: -fPIC -fsigned-char -ffunction-sections -fdata-sections -O3 -fno-strict-overflow -fwrapv -shared

OpenBenchmarking.orgms, Fewer Is BetterOpenVINO 2022.3Model: Face Detection FP16-INT8 - Device: CPURyzen 9 7900X3DRyzen 9 7900XRyzen 9 79500X3DRyzen 9 7950X70140210280350SE +/- 0.08, N = 3SE +/- 0.86, N = 3SE +/- 1.12, N = 3SE +/- 0.86, N = 3304.86279.48304.02281.59MIN: 160.61 / MAX: 318.49MIN: 148.87 / MAX: 292.1MIN: 154.56 / MAX: 315.21MIN: 146.44 / MAX: 293.541. (CXX) g++ options: -fPIC -fsigned-char -ffunction-sections -fdata-sections -O3 -fno-strict-overflow -fwrapv -shared

OpenBenchmarking.orgFPS, More Is BetterOpenVINO 2022.3Model: Face Detection FP16-INT8 - Device: CPURyzen 9 7900X3DRyzen 9 7900XRyzen 9 79500X3DRyzen 9 7950X714212835SE +/- 0.01, N = 3SE +/- 0.07, N = 3SE +/- 0.09, N = 3SE +/- 0.09, N = 319.6421.4426.2628.371. (CXX) g++ options: -fPIC -fsigned-char -ffunction-sections -fdata-sections -O3 -fno-strict-overflow -fwrapv -shared

Zstd Compression

This test measures the time needed to compress/decompress a sample file (silesia.tar) using Zstd (Zstandard) compression with options for different compression levels / settings. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgMB/s, More Is BetterZstd Compression 1.5.4Compression Level: 8, Long Mode - Decompression SpeedRyzen 9 7900X3DRyzen 9 7900XRyzen 9 79500X3DRyzen 9 7950X5001000150020002500SE +/- 4.07, N = 3SE +/- 0.74, N = 3SE +/- 12.98, N = 3SE +/- 0.47, N = 32365.32410.42422.12390.41. (CC) gcc options: -O3 -pthread -lz -llzma -llz4

OpenBenchmarking.orgMB/s, More Is BetterZstd Compression 1.5.4Compression Level: 8, Long Mode - Compression SpeedRyzen 9 7900X3DRyzen 9 7900XRyzen 9 79500X3DRyzen 9 7950X2004006008001000SE +/- 4.92, N = 3SE +/- 0.92, N = 3SE +/- 1.52, N = 3SE +/- 0.72, N = 3940.9808.51004.2845.71. (CC) gcc options: -O3 -pthread -lz -llzma -llz4

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.orgms, Fewer Is BetterOpenVINO 2022.3Model: Machine Translation EN To DE FP16 - Device: CPURyzen 9 7900X3DRyzen 9 7900XRyzen 9 79500X3DRyzen 9 7950X1326395265SE +/- 0.23, N = 3SE +/- 0.10, N = 3SE +/- 0.23, N = 3SE +/- 0.22, N = 355.6553.5458.9957.85MIN: 26.86 / MAX: 87.31MIN: 31.21 / MAX: 70.2MIN: 30.71 / MAX: 70.41MIN: 27.45 / MAX: 68.11. (CXX) g++ options: -fPIC -fsigned-char -ffunction-sections -fdata-sections -O3 -fno-strict-overflow -fwrapv -shared

OpenBenchmarking.orgFPS, More Is BetterOpenVINO 2022.3Model: Machine Translation EN To DE FP16 - Device: CPURyzen 9 7900X3DRyzen 9 7900XRyzen 9 79500X3DRyzen 9 7950X306090120150SE +/- 0.45, N = 3SE +/- 0.21, N = 3SE +/- 0.53, N = 3SE +/- 0.55, N = 3107.76112.02135.50138.141. (CXX) g++ options: -fPIC -fsigned-char -ffunction-sections -fdata-sections -O3 -fno-strict-overflow -fwrapv -shared

OpenBenchmarking.orgms, Fewer Is BetterOpenVINO 2022.3Model: Person Vehicle Bike Detection FP16 - Device: CPURyzen 9 7900X3DRyzen 9 7900XRyzen 9 79500X3DRyzen 9 7950X1.1342.2683.4024.5365.67SE +/- 0.03, N = 3SE +/- 0.04, N = 3SE +/- 0.01, N = 3SE +/- 0.03, N = 35.044.744.824.78MIN: 3.53 / MAX: 13.4MIN: 3.18 / MAX: 12.15MIN: 3.33 / MAX: 13.06MIN: 3.45 / MAX: 12.821. (CXX) g++ options: -fPIC -fsigned-char -ffunction-sections -fdata-sections -O3 -fno-strict-overflow -fwrapv -shared

OpenBenchmarking.orgFPS, More Is BetterOpenVINO 2022.3Model: Person Vehicle Bike Detection FP16 - Device: CPURyzen 9 7900X3DRyzen 9 7900XRyzen 9 79500X3DRyzen 9 7950X400800120016002000SE +/- 6.32, N = 3SE +/- 11.19, N = 3SE +/- 1.97, N = 3SE +/- 9.91, N = 31188.171265.141658.151670.931. (CXX) g++ options: -fPIC -fsigned-char -ffunction-sections -fdata-sections -O3 -fno-strict-overflow -fwrapv -shared

OpenBenchmarking.orgms, Fewer Is BetterOpenVINO 2022.3Model: Vehicle Detection FP16-INT8 - Device: CPURyzen 9 7900X3DRyzen 9 7900XRyzen 9 79500X3DRyzen 9 7950X1.07332.14663.21994.29325.3665SE +/- 0.00, N = 3SE +/- 0.02, N = 3SE +/- 0.01, N = 3SE +/- 0.01, N = 34.774.414.684.34MIN: 2.89 / MAX: 23.9MIN: 2.6 / MAX: 12.74MIN: 2.79 / MAX: 16.02MIN: 2.71 / MAX: 12.091. (CXX) g++ options: -fPIC -fsigned-char -ffunction-sections -fdata-sections -O3 -fno-strict-overflow -fwrapv -shared

OpenBenchmarking.orgFPS, More Is BetterOpenVINO 2022.3Model: Vehicle Detection FP16-INT8 - Device: CPURyzen 9 7900X3DRyzen 9 7900XRyzen 9 79500X3DRyzen 9 7950X400800120016002000SE +/- 0.73, N = 3SE +/- 6.32, N = 3SE +/- 3.94, N = 3SE +/- 2.59, N = 31257.381358.901706.681843.301. (CXX) g++ options: -fPIC -fsigned-char -ffunction-sections -fdata-sections -O3 -fno-strict-overflow -fwrapv -shared

OpenBenchmarking.orgms, Fewer Is BetterOpenVINO 2022.3Model: Age Gender Recognition Retail 0013 FP16 - Device: CPURyzen 9 7900X3DRyzen 9 7900XRyzen 9 79500X3DRyzen 9 7950X0.08780.17560.26340.35120.439SE +/- 0.00, N = 3SE +/- 0.00, N = 3SE +/- 0.00, N = 3SE +/- 0.00, N = 30.390.350.390.35MIN: 0.24 / MAX: 61.73MIN: 0.21 / MAX: 8.31MIN: 0.22 / MAX: 8.71MIN: 0.21 / MAX: 7.041. (CXX) g++ options: -fPIC -fsigned-char -ffunction-sections -fdata-sections -O3 -fno-strict-overflow -fwrapv -shared

OpenBenchmarking.orgFPS, More Is BetterOpenVINO 2022.3Model: Age Gender Recognition Retail 0013 FP16 - Device: CPURyzen 9 7900X3DRyzen 9 7900XRyzen 9 79500X3DRyzen 9 7950X10K20K30K40K50KSE +/- 15.66, N = 3SE +/- 51.92, N = 3SE +/- 72.52, N = 3SE +/- 86.54, N = 330316.7533984.4040658.9644741.971. (CXX) g++ options: -fPIC -fsigned-char -ffunction-sections -fdata-sections -O3 -fno-strict-overflow -fwrapv -shared

OpenBenchmarking.orgms, Fewer Is BetterOpenVINO 2022.3Model: Vehicle Detection FP16 - Device: CPURyzen 9 7900X3DRyzen 9 7900XRyzen 9 79500X3DRyzen 9 7950X3691215SE +/- 0.02, N = 3SE +/- 0.12, N = 3SE +/- 0.02, N = 3SE +/- 0.04, N = 37.489.007.9710.19MIN: 4.3 / MAX: 42.8MIN: 4.65 / MAX: 19.47MIN: 4.7 / MAX: 18.6MIN: 4.41 / MAX: 24.51. (CXX) g++ options: -fPIC -fsigned-char -ffunction-sections -fdata-sections -O3 -fno-strict-overflow -fwrapv -shared

OpenBenchmarking.orgFPS, More Is BetterOpenVINO 2022.3Model: Vehicle Detection FP16 - Device: CPURyzen 9 7900X3DRyzen 9 7900XRyzen 9 79500X3DRyzen 9 7950X2004006008001000SE +/- 2.18, N = 3SE +/- 9.18, N = 3SE +/- 3.11, N = 3SE +/- 3.17, N = 3801.87666.351003.48784.251. (CXX) g++ options: -fPIC -fsigned-char -ffunction-sections -fdata-sections -O3 -fno-strict-overflow -fwrapv -shared

OpenBenchmarking.orgms, Fewer Is BetterOpenVINO 2022.3Model: Age Gender Recognition Retail 0013 FP16-INT8 - Device: CPURyzen 9 7900X3DRyzen 9 7900XRyzen 9 79500X3DRyzen 9 7950X0.15080.30160.45240.60320.754SE +/- 0.00, N = 3SE +/- 0.00, N = 3SE +/- 0.00, N = 3SE +/- 0.00, N = 30.670.600.670.61MIN: 0.37 / MAX: 45.37MIN: 0.33 / MAX: 7.83MIN: 0.35 / MAX: 9.57MIN: 0.34 / MAX: 7.641. (CXX) g++ options: -fPIC -fsigned-char -ffunction-sections -fdata-sections -O3 -fno-strict-overflow -fwrapv -shared

OpenBenchmarking.orgFPS, More Is BetterOpenVINO 2022.3Model: Age Gender Recognition Retail 0013 FP16-INT8 - Device: CPURyzen 9 7900X3DRyzen 9 7900XRyzen 9 79500X3DRyzen 9 7950X6K12K18K24K30KSE +/- 3.40, N = 3SE +/- 119.95, N = 3SE +/- 77.85, N = 3SE +/- 29.30, N = 317663.8419661.3023679.4326015.991. (CXX) g++ options: -fPIC -fsigned-char -ffunction-sections -fdata-sections -O3 -fno-strict-overflow -fwrapv -shared

OpenBenchmarking.orgms, Fewer Is BetterOpenVINO 2022.3Model: Weld Porosity Detection FP16-INT8 - Device: CPURyzen 9 7900X3DRyzen 9 7900XRyzen 9 79500X3DRyzen 9 7950X246810SE +/- 0.00, N = 3SE +/- 0.03, N = 3SE +/- 0.01, N = 3SE +/- 0.00, N = 36.125.516.115.53MIN: 3.22 / MAX: 17.67MIN: 2.96 / MAX: 12.69MIN: 3.19 / MAX: 13.31MIN: 2.99 / MAX: 13.651. (CXX) g++ options: -fPIC -fsigned-char -ffunction-sections -fdata-sections -O3 -fno-strict-overflow -fwrapv -shared

OpenBenchmarking.orgFPS, More Is BetterOpenVINO 2022.3Model: Weld Porosity Detection FP16-INT8 - Device: CPURyzen 9 7900X3DRyzen 9 7900XRyzen 9 79500X3DRyzen 9 7950X6001200180024003000SE +/- 0.41, N = 3SE +/- 13.39, N = 3SE +/- 2.92, N = 3SE +/- 2.33, N = 31959.522176.112616.082892.631. (CXX) g++ options: -fPIC -fsigned-char -ffunction-sections -fdata-sections -O3 -fno-strict-overflow -fwrapv -shared

OpenBenchmarking.orgms, Fewer Is BetterOpenVINO 2022.3Model: Weld Porosity Detection FP16 - Device: CPURyzen 9 7900X3DRyzen 9 7900XRyzen 9 79500X3DRyzen 9 7950X246810SE +/- 0.00, N = 3SE +/- 0.00, N = 3SE +/- 0.00, N = 3SE +/- 0.01, N = 35.995.506.015.54MIN: 3.12 / MAX: 18.55MIN: 2.79 / MAX: 16.27MIN: 3.17 / MAX: 13.52MIN: 2.85 / MAX: 12.561. (CXX) g++ options: -fPIC -fsigned-char -ffunction-sections -fdata-sections -O3 -fno-strict-overflow -fwrapv -shared

OpenBenchmarking.orgFPS, More Is BetterOpenVINO 2022.3Model: Weld Porosity Detection FP16 - Device: CPURyzen 9 7900X3DRyzen 9 7900XRyzen 9 79500X3DRyzen 9 7950X30060090012001500SE +/- 0.24, N = 3SE +/- 0.21, N = 3SE +/- 0.83, N = 3SE +/- 1.85, N = 31000.471089.161330.531442.531. (CXX) g++ options: -fPIC -fsigned-char -ffunction-sections -fdata-sections -O3 -fno-strict-overflow -fwrapv -shared

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 Xmlrig CPU mining performance. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgH/s, More Is BetterXmrig 6.18.1Variant: Wownero - Hash Count: 1MRyzen 9 7900X3DRyzen 9 7900XRyzen 9 79500X3DRyzen 9 7950X4K8K12K16K20KSE +/- 23.48, N = 3SE +/- 13.65, N = 3SE +/- 21.89, N = 3SE +/- 28.90, N = 314966.115870.619562.920609.41. (CXX) g++ options: -fexceptions -fno-rtti -maes -O3 -Ofast -static-libgcc -static-libstdc++ -rdynamic -lssl -lcrypto -luv -lpthread -lrt -ldl -lhwloc

OpenFOAM

OpenFOAM is the leading free, open-source software for computational fluid dynamics (CFD). This test profile currently uses the drivaerFastback test case for analyzing automotive aerodynamics or alternatively the older motorBike input. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgSeconds, Fewer Is BetterOpenFOAM 10Input: drivaerFastback, Small Mesh Size - Execution TimeRyzen 9 7900X3DRyzen 9 7900XRyzen 9 79500X3DRyzen 9 7950X4080120160200138.74171.62125.99161.671. (CXX) g++ options: -std=c++14 -m64 -O3 -ftemplate-depth-100 -fPIC -fuse-ld=bfd -Xlinker --add-needed --no-as-needed -lfoamToVTK -ldynamicMesh -llagrangian -lgenericPatchFields -lfileFormats -lOpenFOAM -ldl -lm

OpenBenchmarking.orgSeconds, Fewer Is BetterOpenFOAM 10Input: drivaerFastback, Small Mesh Size - Mesh TimeRyzen 9 7900X3DRyzen 9 7900XRyzen 9 79500X3DRyzen 9 7950X61218243026.2125.0223.9122.791. (CXX) g++ options: -std=c++14 -m64 -O3 -ftemplate-depth-100 -fPIC -fuse-ld=bfd -Xlinker --add-needed --no-as-needed -lfoamToVTK -ldynamicMesh -llagrangian -lgenericPatchFields -lfileFormats -lOpenFOAM -ldl -lm

PyHPC Benchmarks

PyHPC-Benchmarks is a suite of Python high performance computing benchmarks for execution on CPUs and GPUs using various popular Python HPC libraries. The PyHPC CPU-based benchmarks focus on sequential CPU performance. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgSeconds, Fewer Is BetterPyHPC Benchmarks 3.0Device: CPU - Backend: Numpy - Project Size: 4194304 - Benchmark: Isoneutral MixingRyzen 9 7900X3DRyzen 9 7900XRyzen 9 79500X3DRyzen 9 7950X0.24320.48640.72960.97281.216SE +/- 0.002, N = 3SE +/- 0.001, N = 3SE +/- 0.008, N = 3SE +/- 0.001, N = 31.0811.0571.0741.057

TensorFlow

This is a benchmark of the TensorFlow deep learning framework using the TensorFlow reference benchmarks (tensorflow/benchmarks with tf_cnn_benchmarks.py). Note with the Phoronix Test Suite there is also pts/tensorflow-lite for benchmarking the TensorFlow Lite binaries too. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgimages/sec, More Is BetterTensorFlow 2.12-rc0Device: CPU - Batch Size: 64 - Model: GoogLeNetRyzen 9 7900X3DRyzen 9 7900XRyzen 9 79500X3DRyzen 9 7950X306090120150SE +/- 0.03, N = 3SE +/- 0.06, N = 3SE +/- 0.14, N = 3SE +/- 0.10, N = 3123.26125.62145.29143.88

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 3.0Harness: IP Shapes 1D - Data Type: bf16bf16bf16 - Engine: CPURyzen 9 7900X3DRyzen 9 7900XRyzen 9 79500X3DRyzen 9 7950X0.24190.48380.72570.96761.2095SE +/- 0.002405, N = 4SE +/- 0.004105, N = 4SE +/- 0.010030, N = 15SE +/- 0.006372, N = 151.0751000.9794990.7295100.664360MIN: 1.03MIN: 0.91MIN: 0.63MIN: 0.591. (CXX) g++ options: -O3 -march=native -fopenmp -msse4.1 -fPIC -pie -ldl -lpthread

TensorFlow

This is a benchmark of the TensorFlow deep learning framework using the TensorFlow reference benchmarks (tensorflow/benchmarks with tf_cnn_benchmarks.py). Note with the Phoronix Test Suite there is also pts/tensorflow-lite for benchmarking the TensorFlow Lite binaries too. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgimages/sec, More Is BetterTensorFlow 2.12-rc0Device: CPU - Batch Size: 16 - Model: ResNet-50Ryzen 9 7900X3DRyzen 9 7900XRyzen 9 79500X3DRyzen 9 7950X1020304050SE +/- 0.04, N = 3SE +/- 0.00, N = 3SE +/- 0.08, N = 3SE +/- 0.02, N = 338.1138.9043.1943.08

PyHPC Benchmarks

PyHPC-Benchmarks is a suite of Python high performance computing benchmarks for execution on CPUs and GPUs using various popular Python HPC libraries. The PyHPC CPU-based benchmarks focus on sequential CPU performance. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgSeconds, Fewer Is BetterPyHPC Benchmarks 3.0Device: CPU - Backend: Numpy - Project Size: 4194304 - Benchmark: Equation of StateRyzen 9 7900X3DRyzen 9 7900XRyzen 9 79500X3DRyzen 9 7950X0.16450.3290.49350.6580.8225SE +/- 0.011, N = 12SE +/- 0.001, N = 3SE +/- 0.000, N = 3SE +/- 0.001, N = 30.7260.7140.7310.727

CloverLeaf

CloverLeaf is a Lagrangian-Eulerian hydrodynamics benchmark. This test profile currently makes use of CloverLeaf's OpenMP version and benchmarked with the clover_bm.in input file (Problem 5). Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgSeconds, Fewer Is BetterCloverLeafLagrangian-Eulerian HydrodynamicsRyzen 9 7900X3DRyzen 9 7900XRyzen 9 79500X3DRyzen 9 7950X1122334455SE +/- 0.07, N = 3SE +/- 0.50, N = 3SE +/- 0.10, N = 3SE +/- 0.12, N = 331.2849.6329.1847.001. (F9X) gfortran options: -O3 -march=native -funroll-loops -fopenmp

srsRAN

srsRAN is an open-source LTE/5G software radio suite created by Software Radio Systems (SRS). The srsRAN radio suite was formerly known as srsLTE and can be used for building your own software-defined radio (SDR) 4G/5G mobile network. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgUE Mb/s, More Is BettersrsRAN 22.04.1Test: 4G PHY_DL_Test 100 PRB MIMO 64-QAMRyzen 9 7900X3DRyzen 9 7900XRyzen 9 79500X3DRyzen 9 7950X50100150200250SE +/- 2.56, N = 11SE +/- 0.87, N = 3SE +/- 0.33, N = 3SE +/- 0.72, N = 3235.3240.6243.8236.91. (CXX) g++ options: -std=c++14 -fno-strict-aliasing -march=native -mfpmath=sse -mavx2 -fvisibility=hidden -O3 -fno-trapping-math -fno-math-errno -mavx512f -mavx512cd -mavx512bw -mavx512dq -ldl -lpthread -lm

OpenBenchmarking.orgeNb Mb/s, More Is BettersrsRAN 22.04.1Test: 4G PHY_DL_Test 100 PRB MIMO 64-QAMRyzen 9 7900X3DRyzen 9 7900XRyzen 9 79500X3DRyzen 9 7950X140280420560700SE +/- 4.54, N = 11SE +/- 1.85, N = 3SE +/- 1.67, N = 3SE +/- 0.43, N = 3614.9627.1638.3617.81. (CXX) g++ options: -std=c++14 -fno-strict-aliasing -march=native -mfpmath=sse -mavx2 -fvisibility=hidden -O3 -fno-trapping-math -fno-math-errno -mavx512f -mavx512cd -mavx512bw -mavx512dq -ldl -lpthread -lm

Pennant

Pennant is an application focused on hydrodynamics on general unstructured meshes in 2D. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgHydro Cycle Time - Seconds, Fewer Is BetterPennant 1.0.1Test: sedovbigRyzen 9 7900X3DRyzen 9 7900XRyzen 9 79500X3DRyzen 9 7950X816243240SE +/- 0.29, N = 3SE +/- 0.14, N = 3SE +/- 0.11, N = 3SE +/- 0.02, N = 330.9436.8827.0434.851. (CXX) g++ options: -fopenmp -lmpi_cxx -lmpi

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 4.0Binary: Pathtracer - Model: Asian Dragon ObjRyzen 9 7900X3DRyzen 9 7900XRyzen 9 79500X3DRyzen 9 7950X714212835SE +/- 0.00, N = 3SE +/- 0.02, N = 3SE +/- 0.03, N = 3SE +/- 0.04, N = 323.8323.8231.0129.82MIN: 23.72 / MAX: 24.15MIN: 23.68 / MAX: 24.06MIN: 30.82 / MAX: 31.62MIN: 29.53 / MAX: 30.29

ASKAP

ASKAP is a set of benchmarks from the Australian SKA Pathfinder. The principal ASKAP benchmarks are the Hogbom Clean Benchmark (tHogbomClean) and Convolutional Resamping Benchmark (tConvolve) as well as some previous ASKAP benchmarks being included as well for OpenCL and CUDA execution of tConvolve. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgMpix/sec, More Is BetterASKAP 1.0Test: tConvolve MPI - GriddingRyzen 9 7900X3DRyzen 9 7900XRyzen 9 79500X3DRyzen 9 7950X3K6K9K12K15KSE +/- 124.23, N = 3SE +/- 116.93, N = 3SE +/- 0.00, N = 3SE +/- 111.37, N = 612051.311693.212495.011211.21. (CXX) g++ options: -O3 -fstrict-aliasing -fopenmp

OpenBenchmarking.orgMpix/sec, More Is BetterASKAP 1.0Test: tConvolve MPI - DegriddingRyzen 9 7900X3DRyzen 9 7900XRyzen 9 79500X3DRyzen 9 7950X2K4K6K8K10KSE +/- 84.09, N = 3SE +/- 0.00, N = 3SE +/- 74.40, N = 3SE +/- 106.21, N = 69923.9310092.1010858.8010788.801. (CXX) g++ options: -O3 -fstrict-aliasing -fopenmp

srsRAN

srsRAN is an open-source LTE/5G software radio suite created by Software Radio Systems (SRS). The srsRAN radio suite was formerly known as srsLTE and can be used for building your own software-defined radio (SDR) 4G/5G mobile network. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgUE Mb/s, More Is BettersrsRAN 22.04.1Test: 4G PHY_DL_Test 100 PRB SISO 256-QAMRyzen 9 7900X3DRyzen 9 7900XRyzen 9 79500X3DRyzen 9 7950X60120180240300SE +/- 0.42, N = 15SE +/- 0.59, N = 4SE +/- 1.65, N = 4SE +/- 0.18, N = 4215.8264.6258.5261.81. (CXX) g++ options: -std=c++14 -fno-strict-aliasing -march=native -mfpmath=sse -mavx2 -fvisibility=hidden -O3 -fno-trapping-math -fno-math-errno -mavx512f -mavx512cd -mavx512bw -mavx512dq -ldl -lpthread -lm

OpenBenchmarking.orgeNb Mb/s, More Is BettersrsRAN 22.04.1Test: 4G PHY_DL_Test 100 PRB SISO 256-QAMRyzen 9 7900X3DRyzen 9 7900XRyzen 9 79500X3DRyzen 9 7950X140280420560700SE +/- 3.59, N = 15SE +/- 2.31, N = 4SE +/- 3.65, N = 4SE +/- 2.30, N = 4585.9669.4660.1665.81. (CXX) g++ options: -std=c++14 -fno-strict-aliasing -march=native -mfpmath=sse -mavx2 -fvisibility=hidden -O3 -fno-trapping-math -fno-math-errno -mavx512f -mavx512cd -mavx512bw -mavx512dq -ldl -lpthread -lm

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 4.0Binary: Pathtracer ISPC - Model: Asian Dragon ObjRyzen 9 7900X3DRyzen 9 7900XRyzen 9 79500X3DRyzen 9 7950X816243240SE +/- 0.01, N = 3SE +/- 0.04, N = 3SE +/- 0.07, N = 3SE +/- 0.01, N = 326.9626.4934.1631.78MIN: 26.76 / MAX: 27.4MIN: 26.24 / MAX: 27.06MIN: 33.76 / MAX: 35.23MIN: 31.44 / MAX: 32.76

TensorFlow

This is a benchmark of the TensorFlow deep learning framework using the TensorFlow reference benchmarks (tensorflow/benchmarks with tf_cnn_benchmarks.py). Note with the Phoronix Test Suite there is also pts/tensorflow-lite for benchmarking the TensorFlow Lite binaries too. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgimages/sec, More Is BetterTensorFlow 2.12-rc0Device: CPU - Batch Size: 32 - Model: GoogLeNetRyzen 9 7900X3DRyzen 9 7900XRyzen 9 79500X3DRyzen 9 7950X306090120150SE +/- 0.03, N = 3SE +/- 0.13, N = 3SE +/- 0.15, N = 3SE +/- 0.17, N = 3126.27127.67149.39147.08

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 3.0Harness: Matrix Multiply Batch Shapes Transformer - Data Type: bf16bf16bf16 - Engine: CPURyzen 9 7900X3DRyzen 9 7900XRyzen 9 79500X3DRyzen 9 7950X0.06830.13660.20490.27320.3415SE +/- 0.004459, N = 15SE +/- 0.000581, N = 4SE +/- 0.000569, N = 4SE +/- 0.000189, N = 40.3034640.2648260.2297730.212801MIN: 0.29MIN: 0.25MIN: 0.22MIN: 0.21. (CXX) g++ options: -O3 -march=native -fopenmp -msse4.1 -fPIC -pie -ldl -lpthread

ACES DGEMM

This is a multi-threaded DGEMM benchmark. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgGFLOP/s, More Is BetterACES DGEMM 1.0Sustained Floating-Point RateRyzen 9 7900X3DRyzen 9 7900XRyzen 9 79500X3DRyzen 9 7950X3691215SE +/- 0.008361, N = 3SE +/- 0.062303, N = 3SE +/- 0.160508, N = 3SE +/- 0.134859, N = 38.2155528.24812011.25840610.9839971. (CC) gcc options: -O3 -march=native -fopenmp

srsRAN

srsRAN is an open-source LTE/5G software radio suite created by Software Radio Systems (SRS). The srsRAN radio suite was formerly known as srsLTE and can be used for building your own software-defined radio (SDR) 4G/5G mobile network. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgUE Mb/s, More Is BettersrsRAN 22.04.1Test: 4G PHY_DL_Test 100 PRB MIMO 256-QAMRyzen 9 7900X3DRyzen 9 7900XRyzen 9 79500X3DRyzen 9 7950X60120180240300SE +/- 2.06, N = 3SE +/- 1.39, N = 3SE +/- 0.67, N = 3SE +/- 0.25, N = 3250.3254.9256.8250.71. (CXX) g++ options: -std=c++14 -fno-strict-aliasing -march=native -mfpmath=sse -mavx2 -fvisibility=hidden -O3 -fno-trapping-math -fno-math-errno -mavx512f -mavx512cd -mavx512bw -mavx512dq -ldl -lpthread -lm

OpenBenchmarking.orgeNb Mb/s, More Is BettersrsRAN 22.04.1Test: 4G PHY_DL_Test 100 PRB MIMO 256-QAMRyzen 9 7900X3DRyzen 9 7900XRyzen 9 79500X3DRyzen 9 7950X150300450600750SE +/- 7.85, N = 3SE +/- 1.63, N = 3SE +/- 1.62, N = 3SE +/- 0.74, N = 3665.2677.8686.0667.01. (CXX) g++ options: -std=c++14 -fno-strict-aliasing -march=native -mfpmath=sse -mavx2 -fvisibility=hidden -O3 -fno-trapping-math -fno-math-errno -mavx512f -mavx512cd -mavx512bw -mavx512dq -ldl -lpthread -lm

TensorFlow

This is a benchmark of the TensorFlow deep learning framework using the TensorFlow reference benchmarks (tensorflow/benchmarks with tf_cnn_benchmarks.py). Note with the Phoronix Test Suite there is also pts/tensorflow-lite for benchmarking the TensorFlow Lite binaries too. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgimages/sec, More Is BetterTensorFlow 2.12-rc0Device: CPU - Batch Size: 64 - Model: AlexNetRyzen 9 7900X3DRyzen 9 7900XRyzen 9 79500X3DRyzen 9 7950X80160240320400SE +/- 0.09, N = 3SE +/- 0.30, N = 3SE +/- 0.40, N = 3SE +/- 0.64, N = 3278.30294.49339.80351.07

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 4.0Binary: Pathtracer - Model: CrownRyzen 9 7900X3DRyzen 9 7900XRyzen 9 79500X3DRyzen 9 7950X816243240SE +/- 0.03, N = 3SE +/- 0.03, N = 3SE +/- 0.16, N = 3SE +/- 0.05, N = 324.2324.6832.0732.53MIN: 23.99 / MAX: 24.64MIN: 24.44 / MAX: 25.19MIN: 31.5 / MAX: 32.66MIN: 32.17 / MAX: 33.24

OpenBenchmarking.orgFrames Per Second, More Is BetterEmbree 4.0Binary: Pathtracer - Model: Asian DragonRyzen 9 7900X3DRyzen 9 7900XRyzen 9 79500X3DRyzen 9 7950X816243240SE +/- 0.01, N = 3SE +/- 0.04, N = 3SE +/- 0.05, N = 3SE +/- 0.03, N = 326.5526.5134.7033.63MIN: 26.42 / MAX: 26.93MIN: 26.37 / MAX: 26.79MIN: 34.46 / MAX: 35.13MIN: 33.39 / MAX: 34.01

Pennant

Pennant is an application focused on hydrodynamics on general unstructured meshes in 2D. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgHydro Cycle Time - Seconds, Fewer Is BetterPennant 1.0.1Test: leblancbigRyzen 9 7900X3DRyzen 9 7900XRyzen 9 79500X3DRyzen 9 7950X612182430SE +/- 0.03, N = 3SE +/- 0.01, N = 3SE +/- 0.03, N = 3SE +/- 0.02, N = 319.3125.1516.8624.361. (CXX) g++ options: -fopenmp -lmpi_cxx -lmpi

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 3.0Harness: Deconvolution Batch shapes_1d - Data Type: bf16bf16bf16 - Engine: CPURyzen 9 7900X3DRyzen 9 7900XRyzen 9 79500X3DRyzen 9 7950X1.16592.33183.49774.66365.8295SE +/- 0.01434, N = 3SE +/- 0.04268, N = 3SE +/- 0.03845, N = 3SE +/- 0.02903, N = 35.181724.710133.958863.60748MIN: 4.98MIN: 4.54MIN: 3.72MIN: 3.431. (CXX) g++ options: -O3 -march=native -fopenmp -msse4.1 -fPIC -pie -ldl -lpthread

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 4.0Binary: Pathtracer ISPC - Model: CrownRyzen 9 7900X3DRyzen 9 7900XRyzen 9 79500X3DRyzen 9 7950X816243240SE +/- 0.04, N = 3SE +/- 0.10, N = 3SE +/- 0.10, N = 3SE +/- 0.12, N = 327.0527.6436.2436.55MIN: 26.79 / MAX: 27.57MIN: 27.15 / MAX: 28.38MIN: 35.78 / MAX: 36.89MIN: 35.98 / MAX: 37.5

OpenBenchmarking.orgFrames Per Second, More Is BetterEmbree 4.0Binary: Pathtracer ISPC - Model: Asian DragonRyzen 9 7900X3DRyzen 9 7900XRyzen 9 79500X3DRyzen 9 7950X918273645SE +/- 0.02, N = 3SE +/- 0.01, N = 3SE +/- 0.04, N = 4SE +/- 0.01, N = 331.4330.8939.7137.22MIN: 31.23 / MAX: 32MIN: 30.69 / MAX: 31.38MIN: 39.34 / MAX: 40.55MIN: 36.85 / MAX: 38.38

srsRAN

srsRAN is an open-source LTE/5G software radio suite created by Software Radio Systems (SRS). The srsRAN radio suite was formerly known as srsLTE and can be used for building your own software-defined radio (SDR) 4G/5G mobile network. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgSamples / Second, More Is BettersrsRAN 22.04.1Test: OFDM_TestRyzen 9 7900X3DRyzen 9 7900XRyzen 9 79500X3DRyzen 9 7950X50M100M150M200M250MSE +/- 1519137.18, N = 3SE +/- 1266227.99, N = 3SE +/- 1072898.46, N = 3SE +/- 1178982.61, N = 32373333332370000002459666672366000001. (CXX) g++ options: -std=c++14 -fno-strict-aliasing -march=native -mfpmath=sse -mavx2 -fvisibility=hidden -O3 -fno-trapping-math -fno-math-errno -mavx512f -mavx512cd -mavx512bw -mavx512dq -ldl -lpthread -lm

TensorFlow

This is a benchmark of the TensorFlow deep learning framework using the TensorFlow reference benchmarks (tensorflow/benchmarks with tf_cnn_benchmarks.py). Note with the Phoronix Test Suite there is also pts/tensorflow-lite for benchmarking the TensorFlow Lite binaries too. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgimages/sec, More Is BetterTensorFlow 2.12-rc0Device: CPU - Batch Size: 16 - Model: GoogLeNetRyzen 9 7900X3DRyzen 9 7900XRyzen 9 79500X3DRyzen 9 7950X306090120150SE +/- 0.02, N = 4SE +/- 0.09, N = 4SE +/- 0.07, N = 4SE +/- 0.14, N = 4124.65128.74147.01146.99

OpenBenchmarking.orgimages/sec, More Is BetterTensorFlow 2.12-rc0Device: CPU - Batch Size: 32 - Model: AlexNetRyzen 9 7900X3DRyzen 9 7900XRyzen 9 79500X3DRyzen 9 7950X60120180240300SE +/- 0.10, N = 3SE +/- 0.05, N = 4SE +/- 0.06, N = 4SE +/- 0.14, N = 4223.03232.30258.77264.33

Xcompact3d Incompact3d

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

OpenBenchmarking.orgSeconds, Fewer Is BetterXcompact3d Incompact3d 2021-03-11Input: input.i3d 129 Cells Per DirectionRyzen 9 7900X3DRyzen 9 7900XRyzen 9 79500X3DRyzen 9 7950X48121620SE +/- 0.05, N = 4SE +/- 0.05, N = 4SE +/- 0.02, N = 4SE +/- 0.04, N = 412.6914.6112.5414.631. (F9X) gfortran options: -cpp -O2 -funroll-loops -floop-optimize -fcray-pointer -fbacktrace -lmpi_usempif08 -lmpi_mpifh -lmpi -lopen-rte -lopen-pal -lhwloc -levent_core -levent_pthreads -lm -lz

ASKAP

ASKAP is a set of benchmarks from the Australian SKA Pathfinder. The principal ASKAP benchmarks are the Hogbom Clean Benchmark (tHogbomClean) and Convolutional Resamping Benchmark (tConvolve) as well as some previous ASKAP benchmarks being included as well for OpenCL and CUDA execution of tConvolve. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgIterations Per Second, More Is BetterASKAP 1.0Test: Hogbom Clean OpenMPRyzen 9 7900X3DRyzen 9 7900XRyzen 9 79500X3DRyzen 9 7950X120240360480600SE +/- 1.12, N = 5SE +/- 2.17, N = 5SE +/- 0.74, N = 5SE +/- 1.79, N = 5545.86440.18548.25448.461. (CXX) g++ options: -O3 -fstrict-aliasing -fopenmp

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 3.0Harness: Convolution Batch Shapes Auto - Data Type: bf16bf16bf16 - Engine: CPURyzen 9 7900X3DRyzen 9 7900XRyzen 9 79500X3DRyzen 9 7950X0.47440.94881.42321.89762.372SE +/- 0.00176, N = 7SE +/- 0.00247, N = 7SE +/- 0.00908, N = 7SE +/- 0.37855, N = 151.381441.812911.086402.10831MIN: 1.34MIN: 1.74MIN: 1.01MIN: 1.631. (CXX) g++ options: -O3 -march=native -fopenmp -msse4.1 -fPIC -pie -ldl -lpthread

TensorFlow

This is a benchmark of the TensorFlow deep learning framework using the TensorFlow reference benchmarks (tensorflow/benchmarks with tf_cnn_benchmarks.py). Note with the Phoronix Test Suite there is also pts/tensorflow-lite for benchmarking the TensorFlow Lite binaries too. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgimages/sec, More Is BetterTensorFlow 2.12-rc0Device: CPU - Batch Size: 16 - Model: AlexNetRyzen 9 7900X3DRyzen 9 7900XRyzen 9 79500X3DRyzen 9 7950X4080120160200SE +/- 0.07, N = 4SE +/- 0.22, N = 4SE +/- 0.18, N = 5SE +/- 0.11, N = 5158.97162.66176.22176.72

KTX-Software toktx

This is a benchmark of The Khronos Group's KTX-Software library and tools. KTX-Software provides "toktx" for converting/creating in the KTX container format for image textures. This benchmark times how long it takes to convert to KTX 2.0 format with various settings using a reference PNG sample input. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgSeconds, Fewer Is BetterKTX-Software toktx 4.0Settings: Zstd Compression 19Ryzen 9 7900X3DRyzen 9 7900XRyzen 9 79500X3DRyzen 9 7950X3691215SE +/- 0.03, N = 4SE +/- 0.07, N = 4SE +/- 0.06, N = 5SE +/- 0.05, N = 511.5311.6411.4611.22

srsRAN

srsRAN is an open-source LTE/5G software radio suite created by Software Radio Systems (SRS). The srsRAN radio suite was formerly known as srsLTE and can be used for building your own software-defined radio (SDR) 4G/5G mobile network. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgUE Mb/s, More Is BettersrsRAN 22.04.1Test: 5G PHY_DL_NR Test 52 PRB SISO 64-QAMRyzen 9 7900X3DRyzen 9 7900XRyzen 9 79500X3DRyzen 9 7950X306090120150SE +/- 4.42, N = 5SE +/- 0.21, N = 5SE +/- 0.93, N = 5SE +/- 0.23, N = 5136.8145.3144.2142.91. (CXX) g++ options: -std=c++14 -fno-strict-aliasing -march=native -mfpmath=sse -mavx2 -fvisibility=hidden -O3 -fno-trapping-math -fno-math-errno -mavx512f -mavx512cd -mavx512bw -mavx512dq -ldl -lpthread -lm

OpenBenchmarking.orgeNb Mb/s, More Is BettersrsRAN 22.04.1Test: 5G PHY_DL_NR Test 52 PRB SISO 64-QAMRyzen 9 7900X3DRyzen 9 7900XRyzen 9 79500X3DRyzen 9 7950X50100150200250SE +/- 1.58, N = 5SE +/- 0.81, N = 5SE +/- 1.38, N = 5SE +/- 0.56, N = 5209.9211.6211.5209.51. (CXX) g++ options: -std=c++14 -fno-strict-aliasing -march=native -mfpmath=sse -mavx2 -fvisibility=hidden -O3 -fno-trapping-math -fno-math-errno -mavx512f -mavx512cd -mavx512bw -mavx512dq -ldl -lpthread -lm

OpenBenchmarking.orgUE Mb/s, More Is BettersrsRAN 22.04.1Test: 4G PHY_DL_Test 100 PRB SISO 64-QAMRyzen 9 7900X3DRyzen 9 7900XRyzen 9 79500X3DRyzen 9 7950X60120180240300SE +/- 0.45, N = 5SE +/- 0.34, N = 5SE +/- 0.83, N = 5SE +/- 0.90, N = 5250.6251.1252.0247.41. (CXX) g++ options: -std=c++14 -fno-strict-aliasing -march=native -mfpmath=sse -mavx2 -fvisibility=hidden -O3 -fno-trapping-math -fno-math-errno -mavx512f -mavx512cd -mavx512bw -mavx512dq -ldl -lpthread -lm

OpenBenchmarking.orgeNb Mb/s, More Is BettersrsRAN 22.04.1Test: 4G PHY_DL_Test 100 PRB SISO 64-QAMRyzen 9 7900X3DRyzen 9 7900XRyzen 9 79500X3DRyzen 9 7950X130260390520650SE +/- 1.40, N = 5SE +/- 1.26, N = 5SE +/- 4.56, N = 5SE +/- 6.18, N = 5619.7622.7616.3609.01. (CXX) g++ options: -std=c++14 -fno-strict-aliasing -march=native -mfpmath=sse -mavx2 -fvisibility=hidden -O3 -fno-trapping-math -fno-math-errno -mavx512f -mavx512cd -mavx512bw -mavx512dq -ldl -lpthread -lm

KTX-Software toktx

This is a benchmark of The Khronos Group's KTX-Software library and tools. KTX-Software provides "toktx" for converting/creating in the KTX container format for image textures. This benchmark times how long it takes to convert to KTX 2.0 format with various settings using a reference PNG sample input. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgSeconds, Fewer Is BetterKTX-Software toktx 4.0Settings: UASTC 3 + Zstd Compression 19Ryzen 9 7900X3DRyzen 9 7900XRyzen 9 79500X3DRyzen 9 7950X3691215SE +/- 0.014, N = 5SE +/- 0.013, N = 5SE +/- 0.012, N = 5SE +/- 0.005, N = 510.0379.6988.7478.405

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 3.0Harness: IP Shapes 3D - Data Type: bf16bf16bf16 - Engine: CPURyzen 9 7900X3DRyzen 9 7900XRyzen 9 79500X3DRyzen 9 7950X0.34250.6851.02751.371.7125SE +/- 0.00690, N = 5SE +/- 0.01359, N = 5SE +/- 0.00875, N = 5SE +/- 0.00933, N = 51.161651.517491.083731.52232MIN: 1.08MIN: 1.4MIN: 0.97MIN: 1.41. (CXX) g++ options: -O3 -march=native -fopenmp -msse4.1 -fPIC -pie -ldl -lpthread

LULESH

LULESH is the Livermore Unstructured Lagrangian Explicit Shock Hydrodynamics. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgz/s, More Is BetterLULESH 2.0.3Ryzen 9 7900X3DRyzen 9 7900XRyzen 9 79500X3DRyzen 9 7950X2K4K6K8K10KSE +/- 19.85, N = 7SE +/- 18.50, N = 6SE +/- 15.81, N = 7SE +/- 22.43, N = 68953.058484.578987.948479.881. (CXX) g++ options: -O3 -fopenmp -lm -lmpi_cxx -lmpi

ASKAP

ASKAP is a set of benchmarks from the Australian SKA Pathfinder. The principal ASKAP benchmarks are the Hogbom Clean Benchmark (tHogbomClean) and Convolutional Resamping Benchmark (tConvolve) as well as some previous ASKAP benchmarks being included as well for OpenCL and CUDA execution of tConvolve. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgMillion Grid Points Per Second, More Is BetterASKAP 1.0Test: tConvolve OpenMP - DegriddingRyzen 9 7900X3DRyzen 9 7900XRyzen 9 79500X3DRyzen 9 7950X2K4K6K8K10KSE +/- 76.62, N = 7SE +/- 107.63, N = 6SE +/- 97.44, N = 7SE +/- 35.18, N = 410078.065756.7711369.606156.821. (CXX) g++ options: -O3 -fstrict-aliasing -fopenmp

OpenBenchmarking.orgMillion Grid Points Per Second, More Is BetterASKAP 1.0Test: tConvolve OpenMP - GriddingRyzen 9 7900X3DRyzen 9 7900XRyzen 9 79500X3DRyzen 9 7950X15003000450060007500SE +/- 30.03, N = 7SE +/- 34.63, N = 6SE +/- 61.20, N = 7SE +/- 46.08, N = 66052.165024.896780.796099.221. (CXX) g++ options: -O3 -fstrict-aliasing -fopenmp

KTX-Software toktx

This is a benchmark of The Khronos Group's KTX-Software library and tools. KTX-Software provides "toktx" for converting/creating in the KTX container format for image textures. This benchmark times how long it takes to convert to KTX 2.0 format with various settings using a reference PNG sample input. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgSeconds, Fewer Is BetterKTX-Software toktx 4.0Settings: UASTC 3Ryzen 9 7900X3DRyzen 9 7900XRyzen 9 79500X3DRyzen 9 7950X246810SE +/- 0.004, N = 6SE +/- 0.006, N = 7SE +/- 0.019, N = 7SE +/- 0.003, N = 76.3745.9445.1264.885

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 3.0Harness: Deconvolution Batch shapes_3d - Data Type: bf16bf16bf16 - Engine: CPURyzen 9 7900X3DRyzen 9 7900XRyzen 9 79500X3DRyzen 9 7950X0.45650.9131.36951.8262.2825SE +/- 0.00266, N = 9SE +/- 0.00295, N = 9SE +/- 0.00172, N = 9SE +/- 0.00250, N = 92.029031.798301.507151.40849MIN: 1.97MIN: 1.7MIN: 1.46MIN: 1.341. (CXX) g++ options: -O3 -march=native -fopenmp -msse4.1 -fPIC -pie -ldl -lpthread

KTX-Software toktx

This is a benchmark of The Khronos Group's KTX-Software library and tools. KTX-Software provides "toktx" for converting/creating in the KTX container format for image textures. This benchmark times how long it takes to convert to KTX 2.0 format with various settings using a reference PNG sample input. Learn more via the OpenBenchmarking.org test page.

Settings: Zstd Compression 9

Ryzen 9 7900X3D: The test run did not produce a result.

Ryzen 9 7900X: The test run did not produce a result.

Ryzen 9 79500X3D: The test run did not produce a result.

Ryzen 9 7950X: The test run did not produce a result.

Open Porous Media Git

This is a test of Open Porous Media, a set of open-source tools concerning simulation of flow and transport of fluids in porous media. This test profile builds OPM and its dependencies from upstream Git. Learn more via the OpenBenchmarking.org test page.

OPM Benchmark: Drogon - Threads: 16

Ryzen 9 7900X3D: The test run did not produce a result. E: There are not enough slots available in the system to satisfy the 16

Ryzen 9 7900X: The test run did not produce a result. E: There are not enough slots available in the system to satisfy the 16

Ryzen 9 79500X3D: The test run did not produce a result. E: mpirun was unable to launch the specified application as it could not access

Ryzen 9 7950X: The test run did not produce a result. E: mpirun was unable to launch the specified application as it could not access

OPM Benchmark: Flow MPI Norne - Threads: 16

Ryzen 9 7900X3D: The test run did not produce a result. E: There are not enough slots available in the system to satisfy the 16

Ryzen 9 7900X: The test run did not produce a result. E: There are not enough slots available in the system to satisfy the 16

Ryzen 9 79500X3D: The test run did not produce a result. E: mpirun was unable to launch the specified application as it could not access

Ryzen 9 7950X: The test run did not produce a result. E: mpirun was unable to launch the specified application as it could not access

OPM Benchmark: PUNQ-S3 - Threads: 16

Ryzen 9 7900X3D: The test run did not produce a result. E: There are not enough slots available in the system to satisfy the 16

Ryzen 9 7900X: The test run did not produce a result. E: There are not enough slots available in the system to satisfy the 16

Ryzen 9 79500X3D: The test run did not produce a result. E: mpirun was unable to launch the specified application as it could not access

Ryzen 9 7950X: The test run did not produce a result. E: mpirun was unable to launch the specified application as it could not access

OPM Benchmark: Flow MPI Norne-4C MSW - Threads: 16

Ryzen 9 7900X3D: The test run did not produce a result. E: There are not enough slots available in the system to satisfy the 16

Ryzen 9 7900X: The test run did not produce a result. E: There are not enough slots available in the system to satisfy the 16

Ryzen 9 79500X3D: The test run did not produce a result. E: mpirun was unable to launch the specified application as it could not access

Ryzen 9 7950X: The test run did not produce a result. E: mpirun was unable to launch the specified application as it could not access

OPM Benchmark: Flow MPI Extra - Threads: 16

Ryzen 9 7900X3D: The test run did not produce a result. E: There are not enough slots available in the system to satisfy the 16

Ryzen 9 7900X: The test run did not produce a result. E: There are not enough slots available in the system to satisfy the 16

Ryzen 9 79500X3D: The test run did not produce a result. E: mpirun was unable to launch the specified application as it could not access

Ryzen 9 7950X: The test run did not produce a result. E: mpirun was unable to launch the specified application as it could not access

OPM Benchmark: SPE10 Model 1 - Threads: 16

Ryzen 9 7900X3D: The test run did not produce a result. E: There are not enough slots available in the system to satisfy the 16

Ryzen 9 7900X: The test run did not produce a result. E: There are not enough slots available in the system to satisfy the 16

Ryzen 9 79500X3D: The test run did not produce a result. E: mpirun was unable to launch the specified application as it could not access

Ryzen 9 7950X: The test run did not produce a result. E: mpirun was unable to launch the specified application as it could not access

OPM Benchmark: Smeaheia - Threads: 16

Ryzen 9 7900X3D: The test run did not produce a result. E: There are not enough slots available in the system to satisfy the 16

Ryzen 9 7900X: The test run did not produce a result. E: There are not enough slots available in the system to satisfy the 16

Ryzen 9 79500X3D: The test run did not produce a result. E: mpirun was unable to launch the specified application as it could not access

Ryzen 9 7950X: The test run did not produce a result. E: mpirun was unable to launch the specified application as it could not access

OPM Benchmark: SPE10 Model 2 - Threads: 16

Ryzen 9 7900X3D: The test run did not produce a result. E: There are not enough slots available in the system to satisfy the 16

Ryzen 9 7900X: The test run did not produce a result. E: There are not enough slots available in the system to satisfy the 16

Ryzen 9 79500X3D: The test run did not produce a result. E: mpirun was unable to launch the specified application as it could not access

Ryzen 9 7950X: The test run did not produce a result. E: mpirun was unable to launch the specified application as it could not access

OPM Benchmark: Upscale-Relperm - Threads: 16

Ryzen 9 7900X3D: The test run did not produce a result. E: There are not enough slots available in the system to satisfy the 16

Ryzen 9 7900X: The test run did not produce a result. E: There are not enough slots available in the system to satisfy the 16

Ryzen 9 79500X3D: The test run did not produce a result. E: mpirun was unable to launch the specified application as it could not access

Ryzen 9 7950X: The test run did not produce a result. E: mpirun was unable to launch the specified application as it could not access

PyHPC Benchmarks

PyHPC-Benchmarks is a suite of Python high performance computing benchmarks for execution on CPUs and GPUs using various popular Python HPC libraries. The PyHPC CPU-based benchmarks focus on sequential CPU performance. Learn more via the OpenBenchmarking.org test page.

Device: CPU - Backend: Aesara - Project Size: 4194304 - Benchmark: Equation of State

Ryzen 9 7900X3D: The test run did not produce a result.

Ryzen 9 7900X: The test run did not produce a result.

Ryzen 9 79500X3D: The test run did not produce a result.

Ryzen 9 7950X: The test run did not produce a result.

Device: CPU - Backend: Aesara - Project Size: 4194304 - Benchmark: Isoneutral Mixing

Ryzen 9 7900X3D: The test run did not produce a result.

Ryzen 9 7900X: The test run did not produce a result.

Ryzen 9 79500X3D: The test run did not produce a result.

Ryzen 9 7950X: The test run did not produce a result.

Device: CPU - Backend: PyTorch - Project Size: 4194304 - Benchmark: Equation of State

Ryzen 9 7900X3D: The test run did not produce a result.

Ryzen 9 7900X: The test run did not produce a result.

Ryzen 9 79500X3D: The test run did not produce a result.

Ryzen 9 7950X: The test run did not produce a result.

Device: CPU - Backend: PyTorch - Project Size: 4194304 - Benchmark: Isoneutral Mixing

Ryzen 9 7900X3D: The test run did not produce a result.

Ryzen 9 7900X: The test run did not produce a result.

Ryzen 9 79500X3D: The test run did not produce a result.

Ryzen 9 7950X: The test run did not produce a result.

Device: CPU - Backend: JAX - Project Size: 4194304 - Benchmark: Equation of State

Ryzen 9 7900X3D: The test run did not produce a result.

Ryzen 9 7900X: The test run did not produce a result.

Ryzen 9 79500X3D: The test run did not produce a result.

Ryzen 9 7950X: The test run did not produce a result.

Device: CPU - Backend: TensorFlow - Project Size: 4194304 - Benchmark: Equation of State

Ryzen 9 7900X3D: The test run did not produce a result.

Ryzen 9 7900X: The test run did not produce a result.

Ryzen 9 79500X3D: The test run did not produce a result.

Ryzen 9 7950X: The test run did not produce a result.

Device: CPU - Backend: TensorFlow - Project Size: 4194304 - Benchmark: Isoneutral Mixing

Ryzen 9 7900X3D: The test run did not produce a result.

Ryzen 9 7900X: The test run did not produce a result.

Ryzen 9 79500X3D: The test run did not produce a result.

Ryzen 9 7950X: The test run did not produce a result.

Device: CPU - Backend: Numba - Project Size: 4194304 - Benchmark: Equation of State

Ryzen 9 7900X3D: The test run did not produce a result.

Ryzen 9 7900X: The test run did not produce a result.

Ryzen 9 79500X3D: The test run did not produce a result.

Ryzen 9 7950X: The test run did not produce a result.

Device: CPU - Backend: Numba - Project Size: 4194304 - Benchmark: Isoneutral Mixing

Ryzen 9 7900X3D: The test run did not produce a result.

Ryzen 9 7900X: The test run did not produce a result.

Ryzen 9 79500X3D: The test run did not produce a result.

Ryzen 9 7950X: The test run did not produce a result.

Device: CPU - Backend: JAX - Project Size: 4194304 - Benchmark: Isoneutral Mixing

Ryzen 9 7900X3D: The test run did not produce a result.

Ryzen 9 7900X: The test run did not produce a result.

Ryzen 9 79500X3D: The test run did not produce a result.

Ryzen 9 7950X: The test run did not produce a result.

161 Results Shown

OpenFOAM:
  drivaerFastback, Medium Mesh Size - Execution Time
  drivaerFastback, Medium Mesh Size - Mesh Time
TensorFlow
ONNX Runtime:
  yolov4 - CPU - Standard:
    Inference Time Cost (ms)
    Inferences Per Second
  super-resolution-10 - CPU - Standard:
    Inference Time Cost (ms)
    Inferences Per Second
  ArcFace ResNet-100 - CPU - Standard:
    Inference Time Cost (ms)
    Inferences Per Second
  ResNet50 v1-12-int8 - CPU - Standard:
    Inference Time Cost (ms)
    Inferences Per Second
LeelaChessZero:
  BLAS
  Eigen
ONNX Runtime:
  CaffeNet 12-int8 - CPU - Standard:
    Inference Time Cost (ms)
    Inferences Per Second
  Faster R-CNN R-50-FPN-int8 - CPU - Standard:
    Inference Time Cost (ms)
    Inferences Per Second
TensorFlow
Zstd Compression:
  19 - Decompression Speed
  19 - Compression Speed
  19, Long Mode - Decompression Speed
  19, Long Mode - Compression Speed
ClickHouse:
  100M Rows Hits Dataset, Third Run
  100M Rows Hits Dataset, Second Run
  100M Rows Hits Dataset, First Run / Cold Cache
ONNX Runtime:
  GPT-2 - CPU - Standard:
    Inference Time Cost (ms)
    Inferences Per Second
TensorFlow
KTX-Software toktx
GPAW
Zstd Compression:
  8 - Decompression Speed
  8 - Compression Speed
ONNX Runtime:
  fcn-resnet101-11 - CPU - Parallel:
    Inference Time Cost (ms)
    Inferences Per Second
  yolov4 - CPU - Parallel:
    Inference Time Cost (ms)
    Inferences Per Second
  CaffeNet 12-int8 - CPU - Parallel:
    Inference Time Cost (ms)
    Inferences Per Second
  bertsquad-12 - CPU - Parallel:
    Inference Time Cost (ms)
    Inferences Per Second
NCNN:
  CPU - FastestDet
  CPU - vision_transformer
  CPU - regnety_400m
  CPU - squeezenet_ssd
  CPU - yolov4-tiny
  CPU - resnet50
  CPU - alexnet
  CPU - resnet18
  CPU - vgg16
  CPU - googlenet
  CPU - blazeface
  CPU - efficientnet-b0
  CPU - mnasnet
  CPU - shufflenet-v2
  CPU-v3-v3 - mobilenet-v3
  CPU-v2-v2 - mobilenet-v2
  CPU - mobilenet
ONNX Runtime:
  fcn-resnet101-11 - CPU - Standard:
    Inference Time Cost (ms)
    Inferences Per Second
  GPT-2 - CPU - Parallel:
    Inference Time Cost (ms)
    Inferences Per Second
  bertsquad-12 - CPU - Standard:
    Inference Time Cost (ms)
    Inferences Per Second
  ArcFace ResNet-100 - CPU - Parallel:
    Inference Time Cost (ms)
    Inferences Per Second
  Faster R-CNN R-50-FPN-int8 - CPU - Parallel:
    Inference Time Cost (ms)
    Inferences Per Second
  ResNet50 v1-12-int8 - CPU - Parallel:
    Inference Time Cost (ms)
    Inferences Per Second
  super-resolution-10 - CPU - Parallel:
    Inference Time Cost (ms)
    Inferences Per Second
TensorFlow
ASKAP:
  tConvolve MT - Degridding
  tConvolve MT - Gridding
oneDNN:
  Recurrent Neural Network Training - bf16bf16bf16 - CPU
  Recurrent Neural Network Inference - bf16bf16bf16 - CPU
TensorFlow
GROMACS
Xcompact3d Incompact3d
Xmrig
OpenVINO:
  Person Detection FP16 - CPU:
    ms
    FPS
  Person Detection FP32 - CPU:
    ms
    FPS
Zstd Compression:
  3, Long Mode - Decompression Speed
  3, Long Mode - Compression Speed
  3 - Decompression Speed
  3 - Compression Speed
  12 - Decompression Speed
  12 - Compression Speed
OpenVINO:
  Face Detection FP16 - CPU:
    ms
    FPS
  Face Detection FP16-INT8 - CPU:
    ms
    FPS
Zstd Compression:
  8, Long Mode - Decompression Speed
  8, Long Mode - Compression Speed
OpenVINO:
  Machine Translation EN To DE FP16 - CPU:
    ms
    FPS
  Person Vehicle Bike Detection FP16 - CPU:
    ms
    FPS
  Vehicle Detection FP16-INT8 - CPU:
    ms
    FPS
  Age Gender Recognition Retail 0013 FP16 - CPU:
    ms
    FPS
  Vehicle Detection FP16 - CPU:
    ms
    FPS
  Age Gender Recognition Retail 0013 FP16-INT8 - CPU:
    ms
    FPS
  Weld Porosity Detection FP16-INT8 - CPU:
    ms
    FPS
  Weld Porosity Detection FP16 - CPU:
    ms
    FPS
Xmrig
OpenFOAM:
  drivaerFastback, Small Mesh Size - Execution Time
  drivaerFastback, Small Mesh Size - Mesh Time
PyHPC Benchmarks
TensorFlow
oneDNN
TensorFlow
PyHPC Benchmarks
CloverLeaf
srsRAN:
  4G PHY_DL_Test 100 PRB MIMO 64-QAM:
    UE Mb/s
    eNb Mb/s
Pennant
Embree
ASKAP:
  tConvolve MPI - Gridding
  tConvolve MPI - Degridding
srsRAN:
  4G PHY_DL_Test 100 PRB SISO 256-QAM:
    UE Mb/s
    eNb Mb/s
Embree
TensorFlow
oneDNN
ACES DGEMM
srsRAN:
  4G PHY_DL_Test 100 PRB MIMO 256-QAM:
    UE Mb/s
    eNb Mb/s
TensorFlow
Embree:
  Pathtracer - Crown
  Pathtracer - Asian Dragon
Pennant
oneDNN
Embree:
  Pathtracer ISPC - Crown
  Pathtracer ISPC - Asian Dragon
srsRAN
TensorFlow:
  CPU - 16 - GoogLeNet
  CPU - 32 - AlexNet
Xcompact3d Incompact3d
ASKAP
oneDNN
TensorFlow
KTX-Software toktx
srsRAN:
  5G PHY_DL_NR Test 52 PRB SISO 64-QAM:
    UE Mb/s
    eNb Mb/s
  4G PHY_DL_Test 100 PRB SISO 64-QAM:
    UE Mb/s
    eNb Mb/s
KTX-Software toktx
oneDNN
LULESH
ASKAP:
  tConvolve OpenMP - Degridding
  tConvolve OpenMP - Gridding
KTX-Software toktx
oneDNN