7773x

tests for a future article.

Compare your own system(s) to this result file with the Phoronix Test Suite by running the command: phoronix-test-suite benchmark 2305086-NE-7773X808085
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  Test
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a
May 02 2023
  3 Hours, 1 Minute
b
May 02 2023
  4 Hours, 10 Minutes
5 a
May 04 2023
  4 Hours, 53 Minutes
5 b
May 04 2023
  59 Minutes
5 2p a
May 04 2023
  4 Hours, 1 Minute
5 2p b
May 04 2023
  5 Hours, 22 Minutes
7373x
May 08 2023
  3 Hours, 34 Minutes
2 x AMD EPYC 7373X 16-Core
May 08 2023
  4 Hours, 5 Minutes
7373X 2P
May 08 2023
  3 Hours, 57 Minutes
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7773x ProcessorMotherboardChipsetMemoryDiskGraphicsMonitorNetworkOSKernelDesktopDisplay ServerVulkanCompilerFile-SystemScreen Resolutionab5 a5 b5 2p a5 2p b7373x2 x AMD EPYC 7373X 16-Core7373X 2PAMD EPYC 7773X 64-Core @ 2.20GHz (64 Cores / 128 Threads)AMD DAYTONA_X (RYM1009B BIOS)AMD Starship/Matisse256GB3841GB Micron_9300_MTFDHAL3T8TDPASPEEDVE2282 x Mellanox MT27710Ubuntu 22.045.15.0-47-generic (x86_64)GNOME Shell 42.4X Server 1.21.1.31.2.204GCC 11.2.0ext41920x1080AMD EPYC 7573X 32-Core @ 2.80GHz (32 Cores / 64 Threads)2 x AMD EPYC 7573X 32-Core @ 2.80GHz (64 Cores / 128 Threads)512GBAMD EPYC 7373X 16-Core @ 3.05GHz (16 Cores / 32 Threads)256GB2 x AMD EPYC 7373X 16-Core @ 3.05GHz (32 Cores / 64 Threads)512GBOpenBenchmarking.orgKernel Details- Transparent Huge Pages: madviseCompiler Details- --build=x86_64-linux-gnu --disable-vtable-verify --disable-werror --enable-bootstrap --enable-cet --enable-checking=release --enable-clocale=gnu --enable-default-pie --enable-gnu-unique-object --enable-languages=c,ada,c++,go,brig,d,fortran,objc,obj-c++,m2 --enable-libphobos-checking=release --enable-libstdcxx-debug --enable-libstdcxx-time=yes --enable-link-serialization=2 --enable-multiarch --enable-multilib --enable-nls --enable-objc-gc=auto --enable-offload-targets=nvptx-none=/build/gcc-11-gBFGDP/gcc-11-11.2.0/debian/tmp-nvptx/usr,amdgcn-amdhsa=/build/gcc-11-gBFGDP/gcc-11-11.2.0/debian/tmp-gcn/usr --enable-plugin --enable-shared --enable-threads=posix --host=x86_64-linux-gnu --program-prefix=x86_64-linux-gnu- --target=x86_64-linux-gnu --with-abi=m64 --with-arch-32=i686 --with-build-config=bootstrap-lto-lean --with-default-libstdcxx-abi=new --with-gcc-major-version-only --with-multilib-list=m32,m64,mx32 --with-target-system-zlib=auto --with-tune=generic --without-cuda-driver -v Processor Details- Scaling Governor: acpi-cpufreq performance (Boost: Enabled) - CPU Microcode: 0xa001229Python Details- Python 3.10.6Security Details- 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 and seccomp + 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 + srbds: Not affected + tsx_async_abort: Not affected

ab5 a5 b5 2p a5 2p b7373x2 x AMD EPYC 7373X 16-Core7373X 2PResult OverviewPhoronix Test Suite100%174%248%322%396%ACES DGEMMOpenFOAMSPECFEM3DEmbreeJohn The RipperTimed LLVM CompilationOpenVKLTimed FFmpeg CompilationSVT-AV1VVenCFFmpegQuantLib

7773x ncnn: CPU - googlenetncnn: CPU - mobilenetncnn: CPU - resnet50ncnn: CPU - efficientnet-b0ncnn: CPU-v2-v2 - mobilenet-v2ncnn: CPU - resnet18ncnn: CPU - regnety_400mncnn: CPU - FastestDetlczero: Eigenncnn: CPU-v3-v3 - mobilenet-v3ncnn: CPU - shufflenet-v2ncnn: CPU - alexnetopenfoam: drivaerFastback, Medium Mesh Size - Mesh Timelczero: BLASopenvino: Person Vehicle Bike Detection FP16 - CPUlulesh: openvino: Vehicle Detection FP16 - CPUmt-dgemm: Sustained Floating-Point Ratespecfem3d: Mount St. Helensopenvino: Vehicle Detection FP16-INT8 - CPUjohn-the-ripper: bcryptjohn-the-ripper: Blowfishjohn-the-ripper: WPA PSKblender: Classroom - CPU-Onlyopenvino: Weld Porosity Detection FP16-INT8 - CPUspecfem3d: Layered Halfspaceblender: Barbershop - CPU-Onlyaskap: tConvolve MPI - Degriddingopenvino: Face Detection FP16-INT8 - CPUspecfem3d: Homogeneous Halfspacecompress-7zip: Decompression Ratingblender: Pabellon Barcelona - CPU-Onlyopenvino: Weld Porosity Detection FP16 - CPUblender: BMW27 - CPU-Onlyjohn-the-ripper: MD5opencv: Coreembree: Pathtracer - Crownblender: Fishy Cat - CPU-Onlyembree: Pathtracer ISPC - Crownpennant: leblancbigspecfem3d: Water-layered Halfspaceopenvino: Person Detection FP32 - CPUopenvino: Machine Translation EN To DE FP16 - CPUopenvino: Person Detection FP16 - CPUopenvino: Face Detection FP16 - CPUaskap: tConvolve MPI - Griddingembree: Pathtracer ISPC - Asian Dragon Objopencv: Object Detectionspecfem3d: Tomographic Modelembree: Pathtracer - Asian Dragonembree: Pathtracer ISPC - Asian Dragonpennant: sedovbigembree: Pathtracer - Asian Dragon Objncnn: CPU - squeezenet_ssdonednn: Convolution Batch Shapes Auto - f32 - CPUbuild-llvm: Ninjagromacs: MPI CPU - water_GMX50_bareincompact3d: input.i3d 129 Cells Per Directioncloverleaf: Lagrangian-Eulerian Hydrodynamicsopenvino: Age Gender Recognition Retail 0013 FP16 - CPUcompress-7zip: Compression Ratingncnn: CPU - yolov4-tinyopenvino: Age Gender Recognition Retail 0013 FP16-INT8 - CPUopenfoam: drivaerFastback, Small Mesh Size - Execution Timeincompact3d: input.i3d 193 Cells Per Directiononednn: Deconvolution Batch shapes_1d - f32 - CPUpetsc: Streamsjohn-the-ripper: HMAC-SHA512onednn: IP Shapes 1D - f32 - CPUopenvkl: vklBenchmark ISPCopencv: DNN - Deep Neural Networkonednn: IP Shapes 3D - f32 - CPUonednn: Deconvolution Batch shapes_3d - f32 - CPUopencv: Graph APIopenfoam: drivaerFastback, Medium Mesh Size - Execution Timencnn: CPU - mnasnetncnn: CPU - blazefaceaskap: Hogbom Clean OpenMPonednn: Recurrent Neural Network Inference - f32 - CPUbuild-llvm: Unix Makefilesbuild-ffmpeg: Time To Compileaskap: tConvolve OpenMP - Griddingaskap: tConvolve MT - Griddingopenvino: Age Gender Recognition Retail 0013 FP16-INT8 - CPUopenvino: Age Gender Recognition Retail 0013 FP16 - CPUncnn: CPU - vgg16openvino: Person Detection FP32 - CPUopenvino: Person Detection FP16 - CPUopencv: Stitchingopenvino: Face Detection FP16 - CPUopenvino: Weld Porosity Detection FP16 - CPUopenvino: Machine Translation EN To DE FP16 - CPUaskap: tConvolve MT - Degriddingsvt-av1: Preset 8 - Bosphorus 4Ksvt-av1: Preset 12 - Bosphorus 4Konednn: Recurrent Neural Network Training - f32 - CPUopenvino: Weld Porosity Detection FP16-INT8 - CPUopenvino: Face Detection FP16-INT8 - CPUaskap: tConvolve OpenMP - Degriddingopenvino: Vehicle Detection FP16 - CPUopenvino: Vehicle Detection FP16-INT8 - CPUsvt-av1: Preset 13 - Bosphorus 4Kopenvino: Person Vehicle Bike Detection FP16 - CPUvvenc: Bosphorus 1080p - Fastersvt-av1: Preset 12 - Bosphorus 1080pclickhouse: 100M Rows Hits Dataset, First Run / Cold Cachevvenc: Bosphorus 4K - Fasterffmpeg: libx265 - Liveffmpeg: libx265 - Livesvt-av1: Preset 4 - Bosphorus 4Kclickhouse: 100M Rows Hits Dataset, Second Runclickhouse: 100M Rows Hits Dataset, Third Runsvt-av1: Preset 8 - Bosphorus 1080popenfoam: drivaerFastback, Small Mesh Size - Mesh Timecompress-zstd: 8, Long Mode - Compression Speedcompress-zstd: 8 - Compression Speedcompress-zstd: 3, Long Mode - Compression Speedvvenc: Bosphorus 1080p - Fastsvt-av1: Preset 13 - Bosphorus 1080pvvenc: Bosphorus 4K - Fastncnn: CPU - vision_transformercompress-zstd: 12 - Compression Speedcompress-zstd: 19, Long Mode - Decompression Speedcompress-zstd: 8 - Decompression Speedcompress-zstd: 19 - Decompression Speedcompress-zstd: 19 - Compression Speedcompress-zstd: 3, Long Mode - Decompression Speedcompress-zstd: 8, Long Mode - Decompression Speedcompress-zstd: 19, Long Mode - Compression Speedcompress-zstd: 3 - Decompression Speedcompress-zstd: 12 - Decompression Speedsvt-av1: Preset 4 - Bosphorus 1080pquantlib: draco: Church Facadeffmpeg: libx265 - Video On Demandffmpeg: libx265 - Video On Demandcompress-zstd: 3 - Compression Speeddraco: Lionffmpeg: libx265 - Platformffmpeg: libx265 - Platformespeak: Text-To-Speech Synthesisffmpeg: libx265 - Uploadffmpeg: libx265 - Uploadz3: 1.smt2z3: 2.smt2ab5 a5 b5 2p a5 2p b7373x2 x AMD EPYC 7373X 16-Core7373X 2P25.34858329.38349611.678414616862308646020138872.4530.518912661260.8317.20934908288.7627.61553400069.107734.7763.371128.08154095064.511713.86220230078.475173.844670.5238165.7077.29040.45056813679600047040.481652246.95716.92873.442222.837195.92430.006604.84211.367105.7847.744.863109.98424.72995716.552552.2416.28610.2952746.55793173.4743.67486743.73173.2321.59116.9319.0917.8419.5815.4411.310.8953.5219.08514210.2915.67.13120.3933755541888.222257.1371205.1129.0456911.753321461889.05912768736020295772.022674.2930.115899704259.8732799.527.0316.81708024641121388.731198.4527.655430007706134.6163.36475.10407827.4675402738.04138.848.0512.1636827.564.64093191013.53017939473.8289.5636119.320.827622164.4497.2994.4380412111.3435737.8239692823.9238091.4640.24442817.21184736.9214556185.75041351650001.26107469397561.246183.12487235810363.735911.718.12806.452749.622248.48117.04220481.25493.351.621.7424.0439273911.972011602608.3426.68230.278308.3367.548214.9331183.6323.921175.0119018.326.5416.93198.13516.9330.114601.984428.5111.364106.9847.2067748894.826439.07437.35109.71125.596085744.5988.5752.616.374549.8346.128133.39270.81190.813901276.817.61300.81434.29.31277.31445.910.2342692.45833172.53393950643.902819488543.90172.5695669428.15721.62116.8091581414.1113.714.89.036.468.1226.349.2512386.197.735.48117.437814191252.0520920.487841.4917.874518.862199071244.866019260325130848113.311767.1349.136149469408.7920991.717.9224.987445867244220136.58822.1942.5236210006834343.949252.6840.24087.97402245.709427135.4792.615.488.2324990.139.19412773919.08966485748.522844.911814.0011143.958914.851.14656230.3785.0225.0675640112.0925209.6227191819.9827340.9650.74590419.63050084.4956531992.6068960590001.37996340399970.625932.76234206970428.65926.083.82869.565679.645290.53920.37817750.46599.681.161.2621.082886.122881.041840321935.619.45172.539611.0565.337220.8131182.6118.1886.4119018.31912.84199.6912.7731.837629.3437.2011.961110.4945.714.743457.81456.30107.38222.337396792.11067.8854.216.846571.0846.406126.26289.11229.11438.81304.218.21361.51460.19.541326.51478.110.762756.95718161.5446.892856.6476046.70162.1927.82622.95110.01117.604518.640319.355553092601526034513107248.73867645425.089622797360500043.978740.119944.33457433539.223619.63009634248.507445.105444.1884231.09150.69975294924000339427.71276297.22320.6470.856226.733196.06331.795622.73212.02110.2945.794.76108.36422.70639917.253560.5656.3910.8282820.422.93110.1493.2977.7780.8135.1227.738.94100.6540.45828621.2633.2718.699.38414582842523.5742030.0381632.8131.3445159.6094538682504.3611850211857925941358.553501.6925.221006745213.641983.334.8314.49141946945399671.641594.1422.59684500081.450827.9673.33014.29473123.93606599710.64175.4810.5415.8649980.164.409111.22476781376.806773.96127.65636968.692237.170.674336138.7178.2852.4865429415.6739455.8640373938.133.00107910.624130210.5221790020002.678014520.9118061.85167205.4639238.4914.65436.6811212.84219.40315.45512102.57738.591.3733.552946.972975.152013.5220.06182.112506.762.836169.1121390.3618.26914.241664119.5812.76169.65812.6624.492540.729445.189.57492.5254.584.784463.68461.53107.122.563946702.81024808.514.812525.1545.548144.31283.61222.91437.51315.6181332.31454.79.571306.71482.710.412760.95682168.45694118644.972783.7473444.31170.94271146327.86822.38112.819760537112.43115.68120.2760.7938.6751.8128.3553.25781628.8837.8928.5599.9326879912524.0542551.8981623.8331.7608769.594769352498.7411754211777125845758.573504.1525.472190291213.4641983.334.9114.41593115844074071.731592.7122.51668300023644581.091327.973.26024.41801223.26803264110.64176.7610.6315.7651199.164.04418855311.79752558576.628773.77797.79332568.702235.810.669349138.5658.2222.4838690815.5138800.3439684445.8940352.4832.97431610.762441610.368574130.1789732600002.88451452871330.9172261.89859419702203.6511849.4624.56434.7831305.96221.78915.34412678.97176.411.331.432.812952.762948.392874922020.2120.07180.9111068.869.536176.1071385.3318.25912.4215662.119.6912.79172.57312.6624.268565.057440.569.906107.2947.074.842467.46448.03104.16923.335275702.21013.4741.515.044546.0345.768145.49282.81227.11441.11312181336.51445.19.51309.51498.910.4952850.85729173.05225728343.772775.9481843.64173.5600295828.13722.10114.26177556211.7612.2313.256.974.927.0517.67.3517144.55.864.76149.003721955598.410188.248400.078.02433637.795953129652.03315733165170803212.97964.1991.272692415768.94116629.7151.264616343128235252.02454.978.75195900023.58995.9621.385114.5090978.6002645433.1652.663.174.741543520.104535.50584661924.907323.568423.8794723.358712.711.93416391.7922.9856.8646898318.2614994.7615587918.2316278.2578.74933425.21746066.82625596800001.874462130.6097463.77803596.969164.522.4729.927906.609433.97129.97913312.88783.70.971.0620.472496.522493.981684.8617.58151.7310352.649.204152.1941760.4916.58821.361479219.9912.26147.35413.3631.274487.076351.0111.224114.6344.063.993386.60384.9692.98426.386727727913.5865.415.801506.5175.719140.06305.11312.91523.91389.619.214131541.710.11281.11557.210.0232854.15406162.3346.662661456346.671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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: googlenet5 2p b5 2p a7373X 2P2 x AMD EPYC 7373X 16-Coreb5 a7373x306090120150112.4393.2945.4127.6319.0914.1111.76MIN: 29.99 / MAX: 148.59MIN: 52.46 / MAX: 137.19MIN: 28.42 / MAX: 186.92MIN: 23.37 / MAX: 37.04MIN: 18.77 / MAX: 25.761. (CXX) g++ options: -O3 -rdynamic -lgomp -lpthread

OpenBenchmarking.orgms, Fewer Is BetterNCNN 20220729Target: CPU - Model: mobilenet5 2p b7373X 2P5 2p a2 x AMD EPYC 7373X 16-Coreb5 a7373x306090120150115.6879.8277.7767.1517.8413.7012.23MIN: 64.45 / MAX: 159.93MIN: 65.63 / MAX: 95.23MIN: 67.11 / MAX: 156MIN: 21.26 / MAX: 78.89MIN: 17.55 / MAX: 25.781. (CXX) g++ options: -O3 -rdynamic -lgomp -lpthread

OpenBenchmarking.orgms, Fewer Is BetterNCNN 20220729Target: CPU - Model: resnet505 2p b5 2p a7373X 2P2 x AMD EPYC 7373X 16-Coreb5 a7373x306090120150120.2780.8130.7125.3819.5814.8013.25MIN: 42.99 / MAX: 192.41MIN: 62.51 / MAX: 112.38MIN: 27.2 / MAX: 36.97MIN: 22.8 / MAX: 34.84MIN: 19.15 / MAX: 44.791. (CXX) g++ options: -O3 -rdynamic -lgomp -lpthread

OpenBenchmarking.orgms, Fewer Is BetterNCNN 20220729Target: CPU - Model: efficientnet-b05 2p b7373X 2P2 x AMD EPYC 7373X 16-Core5 2p ab5 a7373x142842567060.7946.6946.6735.1215.449.036.97MIN: 47.67 / MAX: 141.85MIN: 36.92 / MAX: 81.01MIN: 36.84 / MAX: 52.67MIN: 33.83 / MAX: 41.96MIN: 13.63 / MAX: 18.67MIN: 8.93 / MAX: 11.07MIN: 6.9 / MAX: 7.41. (CXX) g++ options: -O3 -rdynamic -lgomp -lpthread

OpenBenchmarking.orgms, Fewer Is BetterNCNN 20220729Target: CPU-v2-v2 - Model: mobilenet-v25 2p b7373X 2P2 x AMD EPYC 7373X 16-Core5 2p ab5 a7373x91827364538.6733.1628.8527.7011.306.464.92MIN: 28.02 / MAX: 119.64MIN: 24.4 / MAX: 44MIN: 18.28 / MAX: 40.64MIN: 23.18 / MAX: 43.54MIN: 9.74 / MAX: 14.96MIN: 6.35 / MAX: 8.73MIN: 4.84 / MAX: 5.411. (CXX) g++ options: -O3 -rdynamic -lgomp -lpthread

OpenBenchmarking.orgms, Fewer Is BetterNCNN 20220729Target: CPU - Model: resnet185 2p b5 2p a7373X 2P2 x AMD EPYC 7373X 16-Coreb5 a7373x122436486051.8038.9415.1413.6210.898.127.05MIN: 16.09 / MAX: 93.56MIN: 16.05 / MAX: 124.98MIN: 13.62 / MAX: 18.75MIN: 13.43 / MAX: 16.6MIN: 10.68 / MAX: 11.74MIN: 8.01 / MAX: 10.04MIN: 6.95 / MAX: 7.651. (CXX) g++ options: -O3 -rdynamic -lgomp -lpthread

OpenBenchmarking.orgms, Fewer Is BetterNCNN 20220729Target: CPU - Model: regnety_400m5 2p b5 2p a2 x AMD EPYC 7373X 16-Core7373X 2Pb5 a7373x306090120150128.35100.6586.2284.8853.5226.3417.60MIN: 111.43 / MAX: 240.27MIN: 97.81 / MAX: 136.12MIN: 82.8 / MAX: 122.51MIN: 80.66 / MAX: 90.33MIN: 50.93 / MAX: 71.06MIN: 25.99 / MAX: 28.26MIN: 17.32 / MAX: 18.741. (CXX) g++ options: -O3 -rdynamic -lgomp -lpthread

OpenBenchmarking.orgms, Fewer Is BetterNCNN 20220729Target: CPU - Model: FastestDet5 2p b5 2p a7373X 2P2 x AMD EPYC 7373X 16-Coreb5 a7373x122436486053.2540.4539.4821.3619.089.257.35MIN: 30.07 / MAX: 66.77MIN: 27.4 / MAX: 462.07MIN: 21.82 / MAX: 52.04MIN: 19.71 / MAX: 29.28MIN: 13.65 / MAX: 21.7MIN: 9.12 / MAX: 9.81MIN: 7.23 / MAX: 7.881. (CXX) g++ options: -O3 -rdynamic -lgomp -lpthread

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: Eigen5 a7373X 2P2 x AMD EPYC 7373X 16-Core7373xb5 2p b5 2p a2K4K6K8K10K12381357145017145142781682861. (CXX) g++ options: -flto -pthread

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-v3-v3 - Model: mobilenet-v37373X 2P5 2p b2 x AMD EPYC 7373X 16-Core5 2p ab5 a7373x71421283529.5228.8824.1921.2610.296.194.50MIN: 25.64 / MAX: 34.13MIN: 23.66 / MAX: 168.43MIN: 19.28 / MAX: 34.5MIN: 20.79 / MAX: 28.25MIN: 9.51 / MAX: 11.93MIN: 6.05 / MAX: 6.93MIN: 4.43 / MAX: 5.261. (CXX) g++ options: -O3 -rdynamic -lgomp -lpthread

OpenBenchmarking.orgms, Fewer Is BetterNCNN 20220729Target: CPU - Model: shufflenet-v25 2p b5 2p a2 x AMD EPYC 7373X 16-Core7373X 2Pb5 a7373x91827364537.8933.2731.8831.6515.607.735.86MIN: 34.63 / MAX: 113.32MIN: 29.37 / MAX: 96.69MIN: 27.33 / MAX: 35.67MIN: 28.59 / MAX: 37.25MIN: 12.95 / MAX: 19.73MIN: 7.58 / MAX: 9.71MIN: 5.76 / MAX: 6.621. (CXX) g++ options: -O3 -rdynamic -lgomp -lpthread

OpenBenchmarking.orgms, Fewer Is BetterNCNN 20220729Target: CPU - Model: alexnet5 2p b5 2p a7373X 2P2 x AMD EPYC 7373X 16-Coreb5 a7373x71421283528.5518.6010.299.787.135.484.76MIN: 12.6 / MAX: 62.18MIN: 17.59 / MAX: 34.64MIN: 9.46 / MAX: 14.07MIN: 9.12 / MAX: 10.95MIN: 6.97 / MAX: 7.76MIN: 5.36 / MAX: 6.34MIN: 4.68 / MAX: 5.711. (CXX) g++ options: -O3 -rdynamic -lgomp -lpthread

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 - Mesh Time7373xb5 b5 a7373X 2P2 x AMD EPYC 7373X 16-Core5 2p b5 2p aa306090120150149.00120.39117.60117.44116.27114.4599.9399.3825.351. (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

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: BLAS5 a2 x AMD EPYC 7373X 16-Core7373X 2P7373xb5 2p b5 2p a2K4K6K8K10K14191676170919555554799182841. (CXX) g++ options: -flto -pthread

OpenVINO

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

OpenBenchmarking.orgFPS, More Is BetterOpenVINO 2022.3Model: Person Vehicle Bike Detection FP16 - Device: CPU7373x2 x AMD EPYC 7373X 16-Core5 ab5 2p a5 2p b5001000150020002500598.401181.751252.051888.202523.572524.051. (CXX) g++ options: -isystem -fsigned-char -ffunction-sections -fdata-sections -msse4.1 -msse4.2 -O3 -fno-strict-overflow -fwrapv -fPIC -fvisibility=hidden -Os -std=c++11 -MD -MT -MF

LULESH

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

OpenBenchmarking.orgz/s, More Is BetterLULESH 2.0.37373x5 ab2 x AMD EPYC 7373X 16-Core7373X 2P5 2p a5 2p b9K18K27K36K45K10188.2520920.4922257.1427032.9027107.1442030.0442551.901. (CXX) g++ options: -O3 -fopenmp -lm -lmpi_cxx -lmpi

OpenVINO

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

OpenBenchmarking.orgFPS, More Is BetterOpenVINO 2022.3Model: Vehicle Detection FP16 - Device: CPU7373x2 x AMD EPYC 7373X 16-Core5 ab5 2p b5 2p a400800120016002000400.07786.17841.491205.111623.831632.811. (CXX) g++ options: -isystem -fsigned-char -ffunction-sections -fdata-sections -msse4.1 -msse4.2 -O3 -fno-strict-overflow -fwrapv -fPIC -fvisibility=hidden -Os -std=c++11 -MD -MT -MF

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 Rate7373x2 x AMD EPYC 7373X 16-Core7373X 2P5 a5 bba5 2p a5 2p b714212835SE +/- 0.247911, N = 158.02433614.48164714.70415317.87450018.64030029.04569029.38349631.34451531.7608761. (CC) gcc options: -O3 -march=native -fopenmp

SPECFEM3D

simulates acoustic (fluid), elastic (solid), coupled acoustic/elastic, poroelastic or seismic wave propagation in any type of conforming mesh of hexahedra. This test profile currently relies on CPU-based execution for SPECFEM3D and using a variety of their built-in examples/models for benchmarking. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgSeconds, Fewer Is BetterSPECFEM3D 4.0Model: Mount St. Helens7373x5 b5 a2 x AMD EPYC 7373X 16-Core7373X 2Pba5 2p a5 2p b918273645SE +/- 0.038048290, N = 337.79595312919.35555309218.86219907018.40662976917.82039039511.75332146011.6784146169.6094538689.5947693501. (F9X) gfortran options: -O2 -fopenmp -std=f2003 -fimplicit-none -fmax-errors=10 -pedantic -pedantic-errors -O3 -finline-functions -lmpi_usempif08 -lmpi_mpifh -lmpi -lopen-rte -lopen-pal -lhwloc -levent_core -levent_pthreads -lm -lz

OpenVINO

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

OpenBenchmarking.orgFPS, More Is BetterOpenVINO 2022.3Model: Vehicle Detection FP16-INT8 - Device: CPU7373x5 a2 x AMD EPYC 7373X 16-Coreb5 2p b5 2p a5001000150020002500652.031244.861274.041889.052498.742504.361. (CXX) g++ options: -isystem -fsigned-char -ffunction-sections -fdata-sections -msse4.1 -msse4.2 -O3 -fno-strict-overflow -fwrapv -fPIC -fvisibility=hidden -Os -std=c++11 -MD -MT -MF

John The Ripper

This is a benchmark of John The Ripper, which is a password cracker. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgReal C/S, More Is BetterJohn The Ripper 2023.03.14Test: bcrypt7373x5 b5 a2 x AMD EPYC 7373X 16-Core7373X 2Pab5 2p b5 2p a30K60K90K120K150KSE +/- 99.80, N = 3315736015260192623606255186230912761175421185021. (CC) gcc options: -m64 -lssl -lcrypto -fopenmp -lgmp -lm -lrt -lz -ldl -lcrypt -lbz2

OpenBenchmarking.orgReal C/S, More Is BetterJohn The Ripper 2023.03.14Test: Blowfish7373x5 a5 b2 x AMD EPYC 7373X 16-Core7373X 2Pab5 2p b5 2p a30K60K90K120K150KSE +/- 185.66, N = 3316516032560345622446230286460873601177711185791. (CC) gcc options: -m64 -lssl -lcrypto -fopenmp -lgmp -lm -lrt -lz -ldl -lcrypt -lbz2

OpenBenchmarking.orgReal C/S, More Is BetterJohn The Ripper 2023.03.14Test: WPA PSK7373x5 a5 b2 x AMD EPYC 7373X 16-Core7373X 2Pab5 2p b5 2p a60K120K180K240K300KSE +/- 297.59, N = 3708031308481310721362601391272013882029572584572594131. (CC) gcc options: -m64 -lssl -lcrypto -fopenmp -lgmp -lm -lrt -lz -ldl -lcrypt -lbz2

Blender

Blender is an open-source 3D creation and modeling software project. This test is of Blender's Cycles performance with various sample files. GPU computing via NVIDIA OptiX and NVIDIA CUDA is currently supported as well as HIP for AMD Radeon GPUs and Intel oneAPI for Intel Graphics. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgSeconds, Fewer Is BetterBlender 3.5Blend File: Classroom - Compute: CPU-Only7373x5 a2 x AMD EPYC 7373X 16-Core7373X 2Pab5 2p b5 2p a50100150200250SE +/- 0.17, N = 3212.97113.31108.30108.0672.4572.0258.5758.55

OpenVINO

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

OpenBenchmarking.orgFPS, More Is BetterOpenVINO 2022.3Model: Weld Porosity Detection FP16-INT8 - Device: CPU7373x5 a2 x AMD EPYC 7373X 16-Coreb5 2p a5 2p b8001600240032004000964.191767.131914.222674.293501.693504.151. (CXX) g++ options: -isystem -fsigned-char -ffunction-sections -fdata-sections -msse4.1 -msse4.2 -O3 -fno-strict-overflow -fwrapv -fPIC -fvisibility=hidden -Os -std=c++11 -MD -MT -MF

SPECFEM3D

simulates acoustic (fluid), elastic (solid), coupled acoustic/elastic, poroelastic or seismic wave propagation in any type of conforming mesh of hexahedra. This test profile currently relies on CPU-based execution for SPECFEM3D and using a variety of their built-in examples/models for benchmarking. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgSeconds, Fewer Is BetterSPECFEM3D 4.0Model: Layered Halfspace7373x7373X 2P5 a5 b2 x AMD EPYC 7373X 16-Coreab5 2p b5 2p a20406080100SE +/- 0.29, N = 391.2749.8349.1448.7448.7230.5230.1225.4725.221. (F9X) gfortran options: -O2 -fopenmp -std=f2003 -fimplicit-none -fmax-errors=10 -pedantic -pedantic-errors -O3 -finline-functions -lmpi_usempif08 -lmpi_mpifh -lmpi -lopen-rte -lopen-pal -lhwloc -levent_core -levent_pthreads -lm -lz

Blender

Blender is an open-source 3D creation and modeling software project. This test is of Blender's Cycles performance with various sample files. GPU computing via NVIDIA OptiX and NVIDIA CUDA is currently supported as well as HIP for AMD Radeon GPUs and Intel oneAPI for Intel Graphics. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgSeconds, Fewer Is BetterBlender 3.5Blend File: Barbershop - Compute: CPU-Only7373x5 a7373X 2P2 x AMD EPYC 7373X 16-Coreab5 2p a5 2p b170340510680850SE +/- 0.09, N = 3768.94408.79396.80393.87260.83259.87213.60213.46

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 - Degridding7373x5 a7373X 2P2 x AMD EPYC 7373X 16-Coreb5 2p a5 2p b9K18K27K36K45K11662.020991.721420.121866.332799.541983.341983.31. (CXX) g++ options: -O3 -fstrict-aliasing -fopenmp

OpenVINO

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

OpenBenchmarking.orgFPS, More Is BetterOpenVINO 2022.3Model: Face Detection FP16-INT8 - Device: CPU7373x5 a2 x AMD EPYC 7373X 16-Coreb5 2p a5 2p b8162432409.7117.9219.3127.0334.8334.911. (CXX) g++ options: -isystem -fsigned-char -ffunction-sections -fdata-sections -msse4.1 -msse4.2 -O3 -fno-strict-overflow -fwrapv -fPIC -fvisibility=hidden -Os -std=c++11 -MD -MT -MF

SPECFEM3D

simulates acoustic (fluid), elastic (solid), coupled acoustic/elastic, poroelastic or seismic wave propagation in any type of conforming mesh of hexahedra. This test profile currently relies on CPU-based execution for SPECFEM3D and using a variety of their built-in examples/models for benchmarking. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgSeconds, Fewer Is BetterSPECFEM3D 4.0Model: Homogeneous Halfspace7373x5 b5 a7373X 2P2 x AMD EPYC 7373X 16-Coreab5 2p a5 2p b1224364860SE +/- 0.20, N = 351.2625.0924.9923.9023.2717.2116.8214.4914.421. (F9X) gfortran options: -O2 -fopenmp -std=f2003 -fimplicit-none -fmax-errors=10 -pedantic -pedantic-errors -O3 -finline-functions -lmpi_usempif08 -lmpi_mpifh -lmpi -lopen-rte -lopen-pal -lhwloc -levent_core -levent_pthreads -lm -lz

7-Zip Compression

This is a test of 7-Zip compression/decompression with its integrated benchmark feature. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgMIPS, More Is Better7-Zip Compression 22.01Test: Decompression Rating7373x2 x AMD EPYC 7373X 16-Core7373X 2P5 ab5 2p b5 2p a100K200K300K400K500K1282352326232361362442204112134407404539961. (CXX) g++ options: -lpthread -ldl -O2 -fPIC

Blender

Blender is an open-source 3D creation and modeling software project. This test is of Blender's Cycles performance with various sample files. GPU computing via NVIDIA OptiX and NVIDIA CUDA is currently supported as well as HIP for AMD Radeon GPUs and Intel oneAPI for Intel Graphics. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgSeconds, Fewer Is BetterBlender 3.5Blend File: Pabellon Barcelona - Compute: CPU-Only7373x5 a2 x AMD EPYC 7373X 16-Core7373X 2Pab5 2p b5 2p a60120180240300SE +/- 0.10, N = 3252.02136.58127.96127.5088.7688.7371.7371.64

OpenVINO

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

OpenBenchmarking.orgFPS, More Is BetterOpenVINO 2022.3Model: Weld Porosity Detection FP16 - Device: CPU7373x5 a2 x AMD EPYC 7373X 16-Coreb5 2p b5 2p a30060090012001500454.90822.19892.671198.451592.711594.141. (CXX) g++ options: -isystem -fsigned-char -ffunction-sections -fdata-sections -msse4.1 -msse4.2 -O3 -fno-strict-overflow -fwrapv -fPIC -fvisibility=hidden -Os -std=c++11 -MD -MT -MF

Blender

Blender is an open-source 3D creation and modeling software project. This test is of Blender's Cycles performance with various sample files. GPU computing via NVIDIA OptiX and NVIDIA CUDA is currently supported as well as HIP for AMD Radeon GPUs and Intel oneAPI for Intel Graphics. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgSeconds, Fewer Is BetterBlender 3.5Blend File: BMW27 - Compute: CPU-Only7373x5 a2 x AMD EPYC 7373X 16-Core7373X 2Pab5 2p a5 2p b20406080100SE +/- 0.03, N = 378.7542.5240.6140.4727.6127.6022.5922.51

John The Ripper

This is a benchmark of John The Ripper, which is a password cracker. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgReal C/S, More Is BetterJohn The Ripper 2023.03.14Test: MD57373x5 b5 a2 x AMD EPYC 7373X 16-Core7373X 2Pab5 2p b5 2p a1.5M3M4.5M6M7.5MSE +/- 1000.00, N = 31959000360500036210003735000373900055340005543000668300068450001. (CC) gcc options: -m64 -lssl -lcrypto -fopenmp -lgmp -lm -lrt -lz -ldl -lcrypt -lbz2

OpenCV

This is a benchmark of the OpenCV (Computer Vision) library's built-in performance tests. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgms, Fewer Is BetterOpenCV 4.7Test: Core5 2p b7373X 2P2 x AMD EPYC 7373X 16-Coreb5 a50K100K150K200K250K236445987388562177061683431. (CXX) g++ options: -fPIC -fsigned-char -pthread -fomit-frame-pointer -ffunction-sections -fdata-sections -msse -msse2 -msse3 -fvisibility=hidden -O3 -shared

Embree

OpenBenchmarking.orgFrames Per Second, More Is BetterEmbree 4.0.1Binary: Pathtracer - Model: Crown7373x5 a5 b7373X 2P2 x AMD EPYC 7373X 16-Corea5 2p b5 2p a20406080100SE +/- 0.05, N = 323.5943.9543.9844.2244.8869.1181.0981.45MIN: 23.47 / MAX: 23.76MIN: 43.49 / MAX: 44.42MIN: 43.29 / MAX: 44.67MIN: 43.54 / MAX: 44.81MIN: 44.32 / MAX: 45.69MIN: 68.18 / MAX: 71.75MIN: 80.03 / MAX: 82.56MIN: 80.49 / MAX: 83.06

Blender

Blender is an open-source 3D creation and modeling software project. This test is of Blender's Cycles performance with various sample files. GPU computing via NVIDIA OptiX and NVIDIA CUDA is currently supported as well as HIP for AMD Radeon GPUs and Intel oneAPI for Intel Graphics. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgSeconds, Fewer Is BetterBlender 3.5Blend File: Fishy Cat - Compute: CPU-Only7373x5 a7373X 2P2 x AMD EPYC 7373X 16-Coreab5 2p a5 2p b20406080100SE +/- 0.04, N = 395.9652.6849.4449.2734.7734.6127.9627.90

Embree

OpenBenchmarking.orgFrames Per Second, More Is BetterEmbree 4.0.1Binary: Pathtracer ISPC - Model: Crown7373x7373X 2P5 b5 a2 x AMD EPYC 7373X 16-Coreba5 2p b5 2p a1632486480SE +/- 0.11, N = 321.3940.0040.1240.2440.3663.3663.3773.2673.33MIN: 21.25 / MAX: 21.62MIN: 39.56 / MAX: 40.59MIN: 39.64 / MAX: 40.56MIN: 39.64 / MAX: 40.95MIN: 39.78 / MAX: 41.03MIN: 62.44 / MAX: 66.52MIN: 62.18 / MAX: 66.58MIN: 72.13 / MAX: 74.82MIN: 71.99 / MAX: 75.06

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: leblancbig7373x5 a2 x AMD EPYC 7373X 16-Core7373X 2Pb5 2p b5 2p a4812162014.5090907.9740227.4653737.4197395.1040784.4180124.2947311. (CXX) g++ options: -fopenmp -lmpi_cxx -lmpi

SPECFEM3D

simulates acoustic (fluid), elastic (solid), coupled acoustic/elastic, poroelastic or seismic wave propagation in any type of conforming mesh of hexahedra. This test profile currently relies on CPU-based execution for SPECFEM3D and using a variety of their built-in examples/models for benchmarking. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgSeconds, Fewer Is BetterSPECFEM3D 4.0Model: Water-layered Halfspace7373x5 a5 b7373X 2P2 x AMD EPYC 7373X 16-Coreab5 2p a5 2p b20406080100SE +/- 0.13, N = 378.6045.7144.3343.8643.7828.0827.4723.9423.271. (F9X) gfortran options: -O2 -fopenmp -std=f2003 -fimplicit-none -fmax-errors=10 -pedantic -pedantic-errors -O3 -finline-functions -lmpi_usempif08 -lmpi_mpifh -lmpi -lopen-rte -lopen-pal -lhwloc -levent_core -levent_pthreads -lm -lz

OpenVINO

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

OpenBenchmarking.orgFPS, More Is BetterOpenVINO 2022.3Model: Person Detection FP32 - Device: CPU7373x5 a2 x AMD EPYC 7373X 16-Coreb5 2p a5 2p b36912153.165.476.108.0410.6410.641. (CXX) g++ options: -isystem -fsigned-char -ffunction-sections -fdata-sections -msse4.1 -msse4.2 -O3 -fno-strict-overflow -fwrapv -fPIC -fvisibility=hidden -Os -std=c++11 -MD -MT -MF

OpenBenchmarking.orgFPS, More Is BetterOpenVINO 2022.3Model: Machine Translation EN To DE FP16 - Device: CPU7373x5 a2 x AMD EPYC 7373X 16-Coreb5 2p a5 2p b408012016020052.6692.6198.39138.84175.48176.761. (CXX) g++ options: -isystem -fsigned-char -ffunction-sections -fdata-sections -msse4.1 -msse4.2 -O3 -fno-strict-overflow -fwrapv -fPIC -fvisibility=hidden -Os -std=c++11 -MD -MT -MF

OpenBenchmarking.orgFPS, More Is BetterOpenVINO 2022.3Model: Person Detection FP16 - Device: CPU7373x5 a2 x AMD EPYC 7373X 16-Coreb5 2p a5 2p b36912153.175.486.178.0510.5410.631. (CXX) g++ options: -isystem -fsigned-char -ffunction-sections -fdata-sections -msse4.1 -msse4.2 -O3 -fno-strict-overflow -fwrapv -fPIC -fvisibility=hidden -Os -std=c++11 -MD -MT -MF

OpenBenchmarking.orgFPS, More Is BetterOpenVINO 2022.3Model: Face Detection FP16 - Device: CPU7373x5 a2 x AMD EPYC 7373X 16-Coreb5 2p b5 2p a481216204.748.238.8612.1615.7615.861. (CXX) g++ options: -isystem -fsigned-char -ffunction-sections -fdata-sections -msse4.1 -msse4.2 -O3 -fno-strict-overflow -fwrapv -fPIC -fvisibility=hidden -Os -std=c++11 -MD -MT -MF

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 - Gridding7373x5 a2 x AMD EPYC 7373X 16-Core7373X 2Pb5 2p a5 2p b11K22K33K44K55K15435.024990.129155.129155.136827.549980.151199.11. (CXX) g++ options: -O3 -fstrict-aliasing -fopenmp

Embree

OpenBenchmarking.orgFrames Per Second, More Is BetterEmbree 4.0.1Binary: Pathtracer ISPC - Model: Asian Dragon Obj7373x7373X 2P2 x AMD EPYC 7373X 16-Core5 a5 b5 2p b5 2p aab1428425670SE +/- 0.03, N = 320.1034.8635.2439.1939.2264.0464.4164.5164.64MIN: 20.01 / MAX: 21.52MIN: 34.63 / MAX: 35.47MIN: 35.01 / MAX: 35.91MIN: 38.97 / MAX: 39.59MIN: 39 / MAX: 39.63MIN: 63.29 / MAX: 64.92MIN: 63.78 / MAX: 65.49MIN: 63.96 / MAX: 66.18MIN: 64.13 / MAX: 65.46

OpenCV

This is a benchmark of the OpenCV (Computer Vision) library's built-in performance tests. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgms, Fewer Is BetterOpenCV 4.7Test: Object Detection5 2p b7373X 2Pb2 x AMD EPYC 7373X 16-Core5 a20K40K60K80K100K88553321873191031850277391. (CXX) g++ options: -fPIC -fsigned-char -pthread -fomit-frame-pointer -ffunction-sections -fdata-sections -msse -msse2 -msse3 -fvisibility=hidden -O3 -shared

SPECFEM3D

simulates acoustic (fluid), elastic (solid), coupled acoustic/elastic, poroelastic or seismic wave propagation in any type of conforming mesh of hexahedra. This test profile currently relies on CPU-based execution for SPECFEM3D and using a variety of their built-in examples/models for benchmarking. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgSeconds, Fewer Is BetterSPECFEM3D 4.0Model: Tomographic Model7373x5 b5 a7373X 2P2 x AMD EPYC 7373X 16-Coreab5 2p b5 2p a816243240SE +/- 0.15, N = 335.5119.6319.0918.3318.0313.8613.5311.8011.221. (F9X) gfortran options: -O2 -fopenmp -std=f2003 -fimplicit-none -fmax-errors=10 -pedantic -pedantic-errors -O3 -finline-functions -lmpi_usempif08 -lmpi_mpifh -lmpi -lopen-rte -lopen-pal -lhwloc -levent_core -levent_pthreads -lm -lz

Embree

OpenBenchmarking.orgFrames Per Second, More Is BetterEmbree 4.0.1Binary: Pathtracer - Model: Asian Dragon7373x7373X 2P2 x AMD EPYC 7373X 16-Core5 b5 a5 2p b5 2p aa20406080100SE +/- 0.14, N = 324.9142.7442.8348.5148.5276.6376.8178.48MIN: 24.47 / MAX: 26.52MIN: 42.44 / MAX: 44.03MIN: 42.56 / MAX: 43.84MIN: 48.29 / MAX: 48.79MIN: 48.32 / MAX: 48.91MIN: 75.97 / MAX: 78.17MIN: 76.07 / MAX: 77.73MIN: 77.64 / MAX: 80.46

OpenBenchmarking.orgFrames Per Second, More Is BetterEmbree 4.0.1Binary: Pathtracer ISPC - Model: Asian Dragon7373x7373X 2P2 x AMD EPYC 7373X 16-Core5 a5 b5 2p bba5 2p a1632486480SE +/- 0.01, N = 323.5740.1840.5144.9145.1173.7873.8373.8473.96MIN: 23.24 / MAX: 24.98MIN: 39.87 / MAX: 41.09MIN: 40.25 / MAX: 41.33MIN: 44.68 / MAX: 45.26MIN: 44.88 / MAX: 45.48MIN: 72.91 / MAX: 74.82MIN: 73.34 / MAX: 74.66MIN: 73.31 / MAX: 75.9MIN: 73.12 / MAX: 75.27

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: sedovbig7373x5 a7373X 2P2 x AMD EPYC 7373X 16-Coreb5 2p b5 2p a61218243023.87947014.00111013.31026013.2864809.5636107.7933257.6563691. (CXX) g++ options: -fopenmp -lmpi_cxx -lmpi

Embree

OpenBenchmarking.orgFrames Per Second, More Is BetterEmbree 4.0.1Binary: Pathtracer - Model: Asian Dragon Obj7373x7373X 2P2 x AMD EPYC 7373X 16-Core5 a5 b5 2p a5 2p ba1632486480SE +/- 0.08, N = 323.3638.4338.7843.9644.1968.6968.7070.52MIN: 22.36 / MAX: 24.19MIN: 38.17 / MAX: 39.69MIN: 38.54 / MAX: 39.74MIN: 43.73 / MAX: 44.3MIN: 43.94 / MAX: 44.51MIN: 68.03 / MAX: 70.15MIN: 67.96 / MAX: 69.64MIN: 69.67 / MAX: 71.94

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: squeezenet_ssd5 2p a5 2p b7373X 2P2 x AMD EPYC 7373X 16-Coreb5 a7373x91827364537.1735.8123.8922.5819.3214.8512.71MIN: 30.62 / MAX: 51.54MIN: 29.14 / MAX: 58.45MIN: 22.35 / MAX: 46.47MIN: 21.5 / MAX: 36.98MIN: 18.86 / MAX: 22.39MIN: 14.49 / MAX: 25.32MIN: 12.37 / MAX: 13.221. (CXX) g++ options: -O3 -rdynamic -lgomp -lpthread

oneDNN

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

OpenBenchmarking.orgms, Fewer Is BetteroneDNN 3.1Harness: Convolution Batch Shapes Auto - Data Type: f32 - Engine: CPU7373x5 a7373X 2P2 x AMD EPYC 7373X 16-Coreb5 2p a5 2p b0.43520.87041.30561.74082.1761.9341601.1465601.0434801.0345600.8276220.6743360.669349MIN: 1.89MIN: 1.09MIN: 0.98MIN: 0.98MIN: 0.78MIN: 0.62MIN: 0.61. (CXX) g++ options: -O3 -march=native -fopenmp -msse4.1 -fPIC -pie -ldl -lpthread

Timed LLVM Compilation

This test times how long it takes to compile/build the LLVM compiler stack. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgSeconds, Fewer Is BetterTimed LLVM Compilation 16.0Build System: Ninja7373x5 b5 a7373X 2P2 x AMD EPYC 7373X 16-Coreab5 2p a5 2p b80160240320400SE +/- 0.08, N = 3391.79231.09230.38212.52211.49165.71164.45138.72138.57

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_bare7373x5 a7373X 2P2 x AMD EPYC 7373X 16-Coreab5 2p b5 2p a246810SE +/- 0.026, N = 32.9855.0225.1935.2487.2907.2998.2228.2851. (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 129 Cells Per Direction7373x5 a7373X 2Pb2 x AMD EPYC 7373X 16-Core5 2p a5 2p b2468106.864689835.067564014.753952984.438041213.932473902.486542942.483869081. (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

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 Hydrodynamics2 x AMD EPYC 7373X 16-Core7373X 2P7373x5 2p a5 2p b5 ab71421283530.6728.5918.2615.6715.5112.0911.341. (F9X) gfortran options: -O3 -march=native -funroll-loops -fopenmp

OpenVINO

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

OpenBenchmarking.orgFPS, More Is BetterOpenVINO 2022.3Model: Age Gender Recognition Retail 0013 FP16 - Device: CPU7373x5 a2 x AMD EPYC 7373X 16-Coreb5 2p b5 2p a8K16K24K32K40K14994.7625209.6229028.2535737.8238800.3439455.861. (CXX) g++ options: -isystem -fsigned-char -ffunction-sections -fdata-sections -msse4.1 -msse4.2 -O3 -fno-strict-overflow -fwrapv -fPIC -fvisibility=hidden -Os -std=c++11 -MD -MT -MF

7-Zip Compression

This is a test of 7-Zip compression/decompression with its integrated benchmark feature. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgMIPS, More Is Better7-Zip Compression 22.01Test: Compression Rating7373x2 x AMD EPYC 7373X 16-Core7373X 2P5 a5 2p bb5 2p a90K180K270K360K450K1558792418032438622719183968443969284037391. (CXX) g++ options: -lpthread -ldl -O2 -fPIC

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: yolov4-tiny5 2p b5 2p a7373X 2P2 x AMD EPYC 7373X 16-Coreb5 a7373x102030405045.8938.1033.7431.9823.9219.9818.23MIN: 34.08 / MAX: 64.66MIN: 29.08 / MAX: 101.85MIN: 28.02 / MAX: 43.18MIN: 26.72 / MAX: 48.39MIN: 23.17 / MAX: 30.48MIN: 19.53 / MAX: 23.19MIN: 17.97 / MAX: 23.771. (CXX) g++ options: -O3 -rdynamic -lgomp -lpthread

OpenVINO

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

OpenBenchmarking.orgFPS, More Is BetterOpenVINO 2022.3Model: Age Gender Recognition Retail 0013 FP16-INT8 - Device: CPU7373x5 a2 x AMD EPYC 7373X 16-Coreb5 2p b9K18K27K36K45K16278.2527340.9631155.5938091.4640352.481. (CXX) g++ options: -isystem -fsigned-char -ffunction-sections -fdata-sections -msse4.1 -msse4.2 -O3 -fno-strict-overflow -fwrapv -fPIC -fvisibility=hidden -Os -std=c++11 -MD -MT -MF

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 Time7373x2 x AMD EPYC 7373X 16-Core7373X 2P5 a5 bab5 2p a5 2p b2040608010078.7576.0974.5950.7550.7040.4540.2433.0032.971. (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

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 Direction7373x5 ab2 x AMD EPYC 7373X 16-Core7373X 2P5 2p b5 2p a61218243025.2219.6317.2113.8013.7210.7610.621. (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

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 3.1Harness: Deconvolution Batch shapes_1d - Data Type: f32 - Engine: CPU5 2p a5 2p bb7373x7373X 2P2 x AMD EPYC 7373X 16-Core5 a369121510.5221010.368506.921456.826255.879515.787984.49565MIN: 8.88MIN: 8.54MIN: 6.32MIN: 5.9MIN: 4.97MIN: 4.87MIN: 3.91. (CXX) g++ options: -O3 -march=native -fopenmp -msse4.1 -fPIC -pie -ldl -lpthread

PETSc

PETSc, the Portable, Extensible Toolkit for Scientific Computation, is for the scalable (parallel) solution of scientific applications modeled by partial differential equations. This test profile runs the PETSc "make streams" benchmark and records the throughput rate when all available cores are utilized for the MPI Streams build. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgMB/s, More Is BetterPETSc 3.19Test: Streams5 ab5 2p b16K32K48K64K80K31992.6156185.7574130.181. (CC) gcc options: -fPIC -O3 -O2 -lpthread -ludev -lpciaccess -lm

John The Ripper

This is a benchmark of John The Ripper, which is a password cracker. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgReal C/S, More Is BetterJohn The Ripper 2023.03.14Test: HMAC-SHA5127373x2 x AMD EPYC 7373X 16-Core7373X 2P5 2p b5 2p a5 b5 aba30M60M90M120M150MSE +/- 266743.32, N = 3596800006721300068530000732600007900200094924000960590001351650001367960001. (CC) gcc options: -m64 -lssl -lcrypto -fopenmp -lgmp -lm -lrt -lz -ldl -lcrypt -lbz2

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 3.1Harness: IP Shapes 1D - Data Type: f32 - Engine: CPU5 2p b5 2p a7373X 2P2 x AMD EPYC 7373X 16-Core7373x5 ab0.6491.2981.9472.5963.2452.884512.678012.174962.058181.874461.379961.26107MIN: 1.79MIN: 1.89MIN: 1.61MIN: 1.58MIN: 1.72MIN: 1.25MIN: 1.061. (CXX) g++ options: -O3 -march=native -fopenmp -msse4.1 -fPIC -pie -ldl -lpthread

OpenVKL

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

OpenBenchmarking.orgItems / Sec, More Is BetterOpenVKL 1.3.1Benchmark: vklBenchmark ISPC7373x7373X 2P2 x AMD EPYC 7373X 16-Core5 b5 a5 2p a5 2p bba100200300400500SE +/- 0.33, N = 3213306309339340452452469470MIN: 29 / MAX: 1843MIN: 54 / MAX: 1694MIN: 54 / MAX: 1845MIN: 54 / MAX: 2307MIN: 55 / MAX: 2309MIN: 98 / MAX: 1875MIN: 99 / MAX: 2013MIN: 84 / MAX: 2565MIN: 84 / MAX: 2616

OpenCV

This is a benchmark of the OpenCV (Computer Vision) library's built-in performance tests. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgms, Fewer Is BetterOpenCV 4.7Test: DNN - Deep Neural Network5 2p b7373X 2P2 x AMD EPYC 7373X 16-Core5 ab20K40K60K80K100K87133823606565739997397561. (CXX) g++ options: -fPIC -fsigned-char -pthread -fomit-frame-pointer -ffunction-sections -fdata-sections -msse -msse2 -msse3 -fvisibility=hidden -O3 -shared

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 3.1Harness: IP Shapes 3D - Data Type: f32 - Engine: CPUb7373X 2P5 2p b5 2p a2 x AMD EPYC 7373X 16-Core5 a7373x0.28040.56080.84121.12161.4021.2461800.9481430.9172260.9118060.7508530.6259300.609746MIN: 1.13MIN: 0.62MIN: 0.77MIN: 0.78MIN: 0.57MIN: 0.57MIN: 0.571. (CXX) g++ options: -O3 -march=native -fopenmp -msse4.1 -fPIC -pie -ldl -lpthread

OpenBenchmarking.orgms, Fewer Is BetteroneDNN 3.1Harness: Deconvolution Batch shapes_3d - Data Type: f32 - Engine: CPU7373xb5 a7373X 2P2 x AMD EPYC 7373X 16-Core5 2p b5 2p a0.85011.70022.55033.40044.25053.778033.124872.762342.733572.700571.898591.85167MIN: 3.69MIN: 2.06MIN: 2.59MIN: 2.6MIN: 2.52MIN: 1.58MIN: 1.611. (CXX) g++ options: -O3 -march=native -fopenmp -msse4.1 -fPIC -pie -ldl -lpthread

OpenCV

This is a benchmark of the OpenCV (Computer Vision) library's built-in performance tests. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgms, Fewer Is BetterOpenCV 4.7Test: Graph API5 2p b7373X 2P2 x AMD EPYC 7373X 16-Coreb5 a90K180K270K360K450K4197023637452630672358102069701. (CXX) g++ options: -fPIC -fsigned-char -pthread -fomit-frame-pointer -ffunction-sections -fdata-sections -msse -msse2 -msse3 -fvisibility=hidden -O3 -shared

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 Time7373x5 a5 bb2 x AMD EPYC 7373X 16-Core7373X 2P5 2p a5 2p ba130260390520650596.97428.66427.71363.74334.90332.03205.46203.6540.481. (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

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: mnasnet5 2p b7373X 2P5 2p a2 x AMD EPYC 7373X 16-Coreb5 a7373x112233445549.4638.9838.4937.6211.716.084.52MIN: 36.42 / MAX: 176.46MIN: 32.96 / MAX: 44.92MIN: 25.51 / MAX: 75.24MIN: 29.31 / MAX: 44.7MIN: 9.43 / MAX: 20.81MIN: 6.01 / MAX: 6.541. (CXX) g++ options: -O3 -rdynamic -lgomp -lpthread

OpenBenchmarking.orgms, Fewer Is BetterNCNN 20220729Target: CPU - Model: blazeface5 2p b7373X 2P2 x AMD EPYC 7373X 16-Core5 2p ab5 a7373x61218243024.5618.7518.4014.658.123.822.40MIN: 20.64 / MAX: 91.2MIN: 15.74 / MAX: 22.59MIN: 16.72 / MAX: 22.27MIN: 11.34 / MAX: 73.36MIN: 6.94 / MAX: 11.1MIN: 3.45 / MAX: 79.741. (CXX) g++ options: -O3 -rdynamic -lgomp -lpthread

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 OpenMP5 2p b5 2p a2 x AMD EPYC 7373X 16-Core7373X 2P7373xb5 a2004006008001000434.78436.68458.72458.72729.93806.45869.571. (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 3.1Harness: Recurrent Neural Network Inference - Data Type: f32 - Engine: CPU7373X 2P5 2p b5 2p a2 x AMD EPYC 7373X 16-Core7373xb5 a300600900120015001349.921305.961212.841177.81906.61749.62679.65MIN: 1150.78MIN: 1060.61MIN: 1070.52MIN: 1030.68MIN: 898.73MIN: 731.75MIN: 664.641. (CXX) g++ options: -O3 -march=native -fopenmp -msse4.1 -fPIC -pie -ldl -lpthread

Timed LLVM Compilation

This test times how long it takes to compile/build the LLVM compiler stack. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgSeconds, Fewer Is BetterTimed LLVM Compilation 16.0Build System: Unix Makefiles7373x5 b5 a2 x AMD EPYC 7373X 16-Core7373X 2Pba5 2p b5 2p a90180270360450SE +/- 0.96, N = 3433.97297.22290.54277.06271.83248.48246.96221.79219.40

Timed FFmpeg Compilation

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

OpenBenchmarking.orgSeconds, Fewer Is BetterTimed FFmpeg Compilation 6.0Time To Compile7373x5 b5 a7373X 2P2 x AMD EPYC 7373X 16-Coreba5 2p a5 2p b714212835SE +/- 0.03, N = 329.9820.6420.3819.7019.5617.0416.9315.4615.34

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 - Gridding2 x AMD EPYC 7373X 16-Core5 2p a7373X 2P5 2p b7373x5 ab4K8K12K16K20K11576.312102.512102.512678.913312.817750.420481.21. (CXX) g++ options: -O3 -fstrict-aliasing -fopenmp

OpenBenchmarking.orgMillion Grid Points Per Second, More Is BetterASKAP 1.0Test: tConvolve MT - Griddingb5 a5 2p b5 2p a7373x7373X 2P2 x AMD EPYC 7373X 16-Core2K4K6K8K10K5493.356599.687176.417738.598783.709605.639627.341. (CXX) g++ options: -O3 -fstrict-aliasing -fopenmp

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: Age Gender Recognition Retail 0013 FP16-INT8 - Device: CPUb5 2p b5 a2 x AMD EPYC 7373X 16-Core7373x0.36450.7291.09351.4581.82251.621.331.161.010.97MIN: 0.69 / MAX: 13.34MIN: 0.64 / MAX: 26.34MIN: 0.66 / MAX: 12.23MIN: 0.6 / MAX: 20.54MIN: 0.58 / MAX: 12.031. (CXX) g++ options: -isystem -fsigned-char -ffunction-sections -fdata-sections -msse4.1 -msse4.2 -O3 -fno-strict-overflow -fwrapv -fPIC -fvisibility=hidden -Os -std=c++11 -MD -MT -MF

OpenBenchmarking.orgms, Fewer Is BetterOpenVINO 2022.3Model: Age Gender Recognition Retail 0013 FP16 - Device: CPUb5 2p b5 2p a5 a2 x AMD EPYC 7373X 16-Core7373x0.39150.7831.17451.5661.95751.741.401.371.261.091.06MIN: 0.84 / MAX: 14.57MIN: 0.68 / MAX: 42.1MIN: 0.67 / MAX: 28.86MIN: 0.69 / MAX: 12.96MIN: 0.64 / MAX: 18.03MIN: 0.62 / MAX: 11.461. (CXX) g++ options: -isystem -fsigned-char -ffunction-sections -fdata-sections -msse4.1 -msse4.2 -O3 -fno-strict-overflow -fwrapv -fPIC -fvisibility=hidden -Os -std=c++11 -MD -MT -MF

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: vgg165 2p a5 2p b2 x AMD EPYC 7373X 16-Core7373X 2Pb5 a7373x81624324033.5532.8132.7729.8224.0421.0820.47MIN: 28.65 / MAX: 42.53MIN: 30.06 / MAX: 44.76MIN: 29.33 / MAX: 38.66MIN: 27.79 / MAX: 34.74MIN: 23.49 / MAX: 30.66MIN: 20.78 / MAX: 24.35MIN: 20.22 / MAX: 21.341. (CXX) g++ options: -O3 -rdynamic -lgomp -lpthread

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 FP32 - Device: CPUb5 2p b5 2p a5 a2 x AMD EPYC 7373X 16-Core7373x80016002400320040003927.002952.762946.972886.122595.652496.52MIN: 3402.58 / MAX: 4474.47MIN: 2193.59 / MAX: 3652.32MIN: 2004.15 / MAX: 3534.38MIN: 1694.68 / MAX: 3104.67MIN: 2193.47 / MAX: 2987.27MIN: 1381.65 / MAX: 2622.641. (CXX) g++ options: -isystem -fsigned-char -ffunction-sections -fdata-sections -msse4.1 -msse4.2 -O3 -fno-strict-overflow -fwrapv -fPIC -fvisibility=hidden -Os -std=c++11 -MD -MT -MF

OpenBenchmarking.orgms, Fewer Is BetterOpenVINO 2022.3Model: Person Detection FP16 - Device: CPUb5 2p a5 2p b5 a2 x AMD EPYC 7373X 16-Core7373x80016002400320040003911.972975.152948.392881.042547.352493.98MIN: 3337.4 / MAX: 4451.63MIN: 2241.37 / MAX: 3616.82MIN: 1547.54 / MAX: 3537.3MIN: 1536.21 / MAX: 3142.35MIN: 1516.1 / MAX: 2961.68MIN: 2275.06 / MAX: 2587.161. (CXX) g++ options: -isystem -fsigned-char -ffunction-sections -fdata-sections -msse4.1 -msse4.2 -O3 -fno-strict-overflow -fwrapv -fPIC -fvisibility=hidden -Os -std=c++11 -MD -MT -MF

OpenCV

This is a benchmark of the OpenCV (Computer Vision) library's built-in performance tests. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgms, Fewer Is BetterOpenCV 4.7Test: Stitching5 2p b2 x AMD EPYC 7373X 16-Core7373X 2Pb5 a60K120K180K240K300K2874922329772281232011601840321. (CXX) g++ options: -fPIC -fsigned-char -pthread -fomit-frame-pointer -ffunction-sections -fdata-sections -msse -msse2 -msse3 -fvisibility=hidden -O3 -shared

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: CPUb5 2p b5 2p a5 a2 x AMD EPYC 7373X 16-Core7373x60012001800240030002608.342020.212013.521935.601782.061684.86MIN: 2421.38 / MAX: 2754.89MIN: 1823.96 / MAX: 3111.51MIN: 1890.96 / MAX: 2802.82MIN: 1852.05 / MAX: 1974.19MIN: 1650.91 / MAX: 2051.03MIN: 1636.65 / MAX: 1721.461. (CXX) g++ options: -isystem -fsigned-char -ffunction-sections -fdata-sections -msse4.1 -msse4.2 -O3 -fno-strict-overflow -fwrapv -fPIC -fvisibility=hidden -Os -std=c++11 -MD -MT -MF

OpenBenchmarking.orgms, Fewer Is BetterOpenVINO 2022.3Model: Weld Porosity Detection FP16 - Device: CPUb5 2p b5 2p a5 a2 x AMD EPYC 7373X 16-Core7373x61218243026.6820.0720.0619.4517.9117.58MIN: 15.32 / MAX: 46.54MIN: 13.26 / MAX: 75.83MIN: 11.41 / MAX: 47.48MIN: 11.98 / MAX: 28.4MIN: 9.87 / MAX: 67.23MIN: 15.76 / MAX: 27.271. (CXX) g++ options: -isystem -fsigned-char -ffunction-sections -fdata-sections -msse4.1 -msse4.2 -O3 -fno-strict-overflow -fwrapv -fPIC -fvisibility=hidden -Os -std=c++11 -MD -MT -MF

OpenBenchmarking.orgms, Fewer Is BetterOpenVINO 2022.3Model: Machine Translation EN To DE FP16 - Device: CPUb5 2p a5 2p b5 a2 x AMD EPYC 7373X 16-Core7373x50100150200250230.27182.10180.91172.53162.50151.73MIN: 166.99 / MAX: 311.89MIN: 117.14 / MAX: 548.18MIN: 124.49 / MAX: 288.01MIN: 81.35 / MAX: 207.95MIN: 133.61 / MAX: 274.15MIN: 131.11 / MAX: 163.851. (CXX) g++ options: -isystem -fsigned-char -ffunction-sections -fdata-sections -msse4.1 -msse4.2 -O3 -fno-strict-overflow -fwrapv -fPIC -fvisibility=hidden -Os -std=c++11 -MD -MT -MF

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 - Degriddingb5 a7373x5 2p b2 x AMD EPYC 7373X 16-Core7373X 2P5 2p a3K6K9K12K15K8308.339611.0510352.6011068.8011891.4012025.7012506.701. (CXX) g++ options: -O3 -fstrict-aliasing -fopenmp

SVT-AV1

OpenBenchmarking.orgFrames Per Second, More Is BetterSVT-AV1 1.5Encoder Mode: Preset 8 - Input: Bosphorus 4K7373x2 x AMD EPYC 7373X 16-Core7373X 2P5 2p a5 ab5 2p b5 ba1632486480SE +/- 0.56, N = 1249.2058.3658.7062.8465.3467.5569.5470.8673.441. (CXX) g++ options: -march=native -mno-avx -mavx2 -mavx512f -mavx512bw -mavx512dq

OpenBenchmarking.orgFrames Per Second, More Is BetterSVT-AV1 1.5Encoder Mode: Preset 12 - Input: Bosphorus 4K7373x7373X 2P2 x AMD EPYC 7373X 16-Core5 2p a5 2p bb5 aa5 b50100150200250SE +/- 0.73, N = 3152.19162.78163.33169.11176.11214.93220.81222.84226.731. (CXX) g++ options: -march=native -mno-avx -mavx2 -mavx512f -mavx512bw -mavx512dq

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 3.1Harness: Recurrent Neural Network Training - Data Type: f32 - Engine: CPU7373x5 2p a5 2p b2 x AMD EPYC 7373X 16-Core7373X 2Pb5 a4008001200160020001760.491390.361385.331377.391370.611183.631182.61MIN: 1746.27MIN: 1287.43MIN: 1314.76MIN: 1316MIN: 1312.47MIN: 1162.73MIN: 1161.831. (CXX) g++ options: -O3 -march=native -fopenmp -msse4.1 -fPIC -pie -ldl -lpthread

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: Weld Porosity Detection FP16-INT8 - Device: CPUb5 2p a5 2p b5 a2 x AMD EPYC 7373X 16-Core7373x61218243023.9218.2618.2518.1016.7016.58MIN: 15.02 / MAX: 35.74MIN: 10.53 / MAX: 60.19MIN: 8.84 / MAX: 40.73MIN: 9.23 / MAX: 28.11MIN: 9.01 / MAX: 41.25MIN: 12.62 / MAX: 25.961. (CXX) g++ options: -isystem -fsigned-char -ffunction-sections -fdata-sections -msse4.1 -msse4.2 -O3 -fno-strict-overflow -fwrapv -fPIC -fvisibility=hidden -Os -std=c++11 -MD -MT -MF

OpenBenchmarking.orgms, Fewer Is BetterOpenVINO 2022.3Model: Face Detection FP16-INT8 - Device: CPUb5 2p a5 2p b5 a2 x AMD EPYC 7373X 16-Core7373x300600900120015001175.01914.24912.42886.41826.77821.36MIN: 982.69 / MAX: 1202.21MIN: 797.83 / MAX: 966.84MIN: 878.63 / MAX: 988.74MIN: 851.09 / MAX: 900.44MIN: 796.91 / MAX: 888.72MIN: 798.88 / MAX: 834.551. (CXX) g++ options: -isystem -fsigned-char -ffunction-sections -fdata-sections -msse4.1 -msse4.2 -O3 -fno-strict-overflow -fwrapv -fPIC -fvisibility=hidden -Os -std=c++11 -MD -MT -MF

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 - Degridding2 x AMD EPYC 7373X 16-Core7373X 2P7373x5 2p b5 2p ab5 a4K8K12K16K20K13312.813312.814792.015662.116641.019018.319018.31. (CXX) g++ options: -O3 -fstrict-aliasing -fopenmp

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: Vehicle Detection FP16 - Device: CPUb2 x AMD EPYC 7373X 16-Core7373x5 2p b5 2p a5 a61218243026.5420.3319.9919.6919.5819.00MIN: 14.19 / MAX: 63.19MIN: 14.4 / MAX: 46.38MIN: 12.45 / MAX: 25.77MIN: 11.03 / MAX: 75.83MIN: 11.25 / MAX: 73.87MIN: 13.62 / MAX: 32.751. (CXX) g++ options: -isystem -fsigned-char -ffunction-sections -fdata-sections -msse4.1 -msse4.2 -O3 -fno-strict-overflow -fwrapv -fPIC -fvisibility=hidden -Os -std=c++11 -MD -MT -MF

OpenBenchmarking.orgms, Fewer Is BetterOpenVINO 2022.3Model: Vehicle Detection FP16-INT8 - Device: CPUb5 a5 2p b5 2p a2 x AMD EPYC 7373X 16-Core7373x4812162016.9312.8412.7912.7612.5412.26MIN: 10.73 / MAX: 31.24MIN: 6.96 / MAX: 23.28MIN: 7.68 / MAX: 43.18MIN: 7.65 / MAX: 43.58MIN: 9.03 / MAX: 28.23MIN: 7.79 / MAX: 21.631. (CXX) g++ options: -isystem -fsigned-char -ffunction-sections -fdata-sections -msse4.1 -msse4.2 -O3 -fno-strict-overflow -fwrapv -fPIC -fvisibility=hidden -Os -std=c++11 -MD -MT -MF

SVT-AV1

OpenBenchmarking.orgFrames Per Second, More Is BetterSVT-AV1 1.5Encoder Mode: Preset 13 - Input: Bosphorus 4K7373x7373X 2P2 x AMD EPYC 7373X 16-Core5 2p a5 2p ba5 bb5 a4080120160200SE +/- 0.70, N = 3147.35159.26166.54169.66172.57195.92196.06198.14199.691. (CXX) g++ options: -march=native -mno-avx -mavx2 -mavx512f -mavx512bw -mavx512dq

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 Vehicle Bike Detection FP16 - Device: CPUb2 x AMD EPYC 7373X 16-Core7373x5 a5 2p b5 2p a4812162016.9313.5213.3612.7712.6612.66MIN: 13.88 / MAX: 33.11MIN: 10.48 / MAX: 44.97MIN: 8.79 / MAX: 23.44MIN: 7.39 / MAX: 23.62MIN: 8.38 / MAX: 48.88MIN: 7.58 / MAX: 53.451. (CXX) g++ options: -isystem -fsigned-char -ffunction-sections -fdata-sections -msse4.1 -msse4.2 -O3 -fno-strict-overflow -fwrapv -fPIC -fvisibility=hidden -Os -std=c++11 -MD -MT -MF

VVenC

VVenC is the Fraunhofer Versatile Video Encoder as a fast/efficient H.266/VVC encoder. The vvenc encoder makes use of SIMD Everywhere (SIMDe). The vvenc software is published under the Clear BSD License. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgFrames Per Second, More Is BetterVVenC 1.8Video Input: Bosphorus 1080p - Video Preset: Faster7373X 2P5 2p b2 x AMD EPYC 7373X 16-Core5 2p aab7373x5 b5 a714212835SE +/- 0.03, N = 324.2224.2724.3124.4930.0130.1131.2731.8031.841. (CXX) g++ options: -O3 -flto=auto -fno-fat-lto-objects

SVT-AV1

OpenBenchmarking.orgFrames Per Second, More Is BetterSVT-AV1 1.5Encoder Mode: Preset 12 - Input: Bosphorus 1080p7373x7373X 2P2 x AMD EPYC 7373X 16-Core5 2p a5 2p bba5 b5 a140280420560700SE +/- 2.97, N = 3487.08522.16525.64540.73565.06601.98604.84622.73629.301. (CXX) g++ options: -march=native -mno-avx -mavx2 -mavx512f -mavx512bw -mavx512dq

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, First Run / Cold Cache7373x2 x AMD EPYC 7373X 16-Core7373X 2Pb5 a5 2p b5 2p a100200300400500351.01420.29420.94428.51437.20440.56445.18MIN: 13.78 / MAX: 6666.67MIN: 24.7 / MAX: 5454.55MIN: 24.79 / MAX: 3750MIN: 34.8 / MAX: 5454.55MIN: 24.3 / MAX: 6000MIN: 40.98 / MAX: 4000MIN: 41.18 / MAX: 3157.89

VVenC

VVenC is the Fraunhofer Versatile Video Encoder as a fast/efficient H.266/VVC encoder. The vvenc encoder makes use of SIMD Everywhere (SIMDe). The vvenc software is published under the Clear BSD License. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgFrames Per Second, More Is BetterVVenC 1.8Video Input: Bosphorus 4K - Video Preset: Faster5 2p a5 2p b7373X 2P2 x AMD EPYC 7373X 16-Core7373xba5 a5 b3691215SE +/- 0.022, N = 39.5749.90610.08310.12711.22411.36411.36711.96112.0201. (CXX) g++ options: -O3 -flto=auto -fno-fat-lto-objects

FFmpeg

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

OpenBenchmarking.orgFPS, More Is BetterFFmpeg 6.0Encoder: libx265 - Scenario: Live5 2p a7373X 2Pab5 2p b5 b5 a2 x AMD EPYC 7373X 16-Core7373x306090120150SE +/- 0.29, N = 392.5299.82105.78106.98107.29110.29110.49111.07114.631. (CXX) g++ options: -O3 -rdynamic -lpthread -lrt -ldl -lnuma

OpenBenchmarking.orgSeconds, Fewer Is BetterFFmpeg 6.0Encoder: libx265 - Scenario: Live5 2p a7373X 2Pab5 2p b5 b5 a2 x AMD EPYC 7373X 16-Core7373x1224364860SE +/- 0.13, N = 354.5850.5947.7447.2147.0745.7945.7145.4744.061. (CXX) g++ options: -O3 -rdynamic -lpthread -lrt -ldl -lnuma

SVT-AV1

OpenBenchmarking.orgFrames Per Second, More Is BetterSVT-AV1 1.5Encoder Mode: Preset 4 - Input: Bosphorus 4K7373x2 x AMD EPYC 7373X 16-Core7373X 2P5 a5 b5 2p ab5 2p ba1.09422.18843.28264.37685.471SE +/- 0.021, N = 33.9934.6444.6764.7434.7604.7844.8264.8424.8631. (CXX) g++ options: -march=native -mno-avx -mavx2 -mavx512f -mavx512bw -mavx512dq

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, Second Run7373x7373X 2P2 x AMD EPYC 7373X 16-Coreb5 a5 2p a5 2p b100200300400500386.60433.56438.36439.07457.81463.68467.46MIN: 13.7 / MAX: 6666.67MIN: 24.58 / MAX: 4285.71MIN: 25.08 / MAX: 4285.71MIN: 35.82 / MAX: 6000MIN: 24.13 / MAX: 5454.55MIN: 41.64 / MAX: 4615.38MIN: 40.6 / MAX: 4615.38

OpenBenchmarking.orgQueries Per Minute, Geo Mean, More Is BetterClickHouse 22.12.3.5100M Rows Hits Dataset, Third Run7373x2 x AMD EPYC 7373X 16-Core7373X 2Pb5 2p b5 a5 2p a100200300400500384.96429.56436.29437.35448.03456.30461.53MIN: 13.8 / MAX: 6666.67MIN: 25.01 / MAX: 4615.38MIN: 24.91 / MAX: 3750MIN: 35.59 / MAX: 5454.55MIN: 41.38 / MAX: 2608.7MIN: 24.65 / MAX: 5454.55MIN: 41.49 / MAX: 3000

SVT-AV1

OpenBenchmarking.orgFrames Per Second, More Is BetterSVT-AV1 1.5Encoder Mode: Preset 8 - Input: Bosphorus 1080p7373x2 x AMD EPYC 7373X 16-Core7373X 2P5 2p b5 2p a5 a5 bba20406080100SE +/- 1.23, N = 592.98100.59101.82104.17107.10107.38108.36109.71109.981. (CXX) g++ options: -march=native -mno-avx -mavx2 -mavx512f -mavx512bw -mavx512dq

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 - Mesh Time7373xba7373X 2P2 x AMD EPYC 7373X 16-Core5 2p b5 b5 2p a5 a61218243026.3925.6024.7324.6724.2723.3422.7122.5622.341. (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

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 - Compression Speed7373X 2P2 x AMD EPYC 7373X 16-Core5 2p b5 2p a7373xb5 a2004006008001000671.6680.9702.2702.8727.0744.5792.11. (CC) gcc options: -O3 -pthread -lz -llzma -llz4

OpenBenchmarking.orgMB/s, More Is BetterZstd Compression 1.5.4Compression Level: 8 - Compression Speed7373xb7373X 2P5 2p b2 x AMD EPYC 7373X 16-Core5 2p a5 a2004006008001000913.5988.5992.41013.41022.31024.01067.81. (CC) gcc options: -O3 -pthread -lz -llzma -llz4

OpenBenchmarking.orgMB/s, More Is BetterZstd Compression 1.5.4Compression Level: 3, Long Mode - Compression Speed5 2p bb5 2p a7373X 2P5 a2 x AMD EPYC 7373X 16-Core7373x2004006008001000741.5752.6808.5813.6854.2854.9865.41. (CC) gcc options: -O3 -pthread -lz -llzma -llz4

VVenC

VVenC is the Fraunhofer Versatile Video Encoder as a fast/efficient H.266/VVC encoder. The vvenc encoder makes use of SIMD Everywhere (SIMDe). The vvenc software is published under the Clear BSD License. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgFrames Per Second, More Is BetterVVenC 1.8Video Input: Bosphorus 1080p - Video Preset: Fast2 x AMD EPYC 7373X 16-Core5 2p a7373X 2P5 2p b7373xba5 a5 b48121620SE +/- 0.10, N = 314.7914.8114.9415.0415.8016.3716.5516.8517.251. (CXX) g++ options: -O3 -flto=auto -fno-fat-lto-objects

SVT-AV1

OpenBenchmarking.orgFrames Per Second, More Is BetterSVT-AV1 1.5Encoder Mode: Preset 13 - Input: Bosphorus 1080p7373X 2P7373x2 x AMD EPYC 7373X 16-Core5 2p a5 2p bba5 b5 a120240360480600SE +/- 5.77, N = 3490.99506.52510.79525.15546.03549.83552.24560.57571.081. (CXX) g++ options: -march=native -mno-avx -mavx2 -mavx512f -mavx512bw -mavx512dq

VVenC

VVenC is the Fraunhofer Versatile Video Encoder as a fast/efficient H.266/VVC encoder. The vvenc encoder makes use of SIMD Everywhere (SIMDe). The vvenc software is published under the Clear BSD License. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgFrames Per Second, More Is BetterVVenC 1.8Video Input: Bosphorus 4K - Video Preset: Fast5 2p a7373x5 2p b7373X 2P2 x AMD EPYC 7373X 16-Coreba5 b5 a246810SE +/- 0.010, N = 35.5485.7195.7685.7745.8776.1286.2866.3906.4061. (CXX) g++ options: -O3 -flto=auto -fno-fat-lto-objects

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: vision_transformer5 2p b2 x AMD EPYC 7373X 16-Core7373X 2P5 2p a7373xb5 a306090120150145.49145.33144.55144.31140.06133.39126.26MIN: 141.27 / MAX: 245.34MIN: 142.5 / MAX: 157.84MIN: 140.93 / MAX: 165.57MIN: 140.5 / MAX: 157.63MIN: 137.05 / MAX: 145.39MIN: 129.7 / MAX: 252.77MIN: 125.42 / MAX: 132.031. (CXX) g++ options: -O3 -rdynamic -lgomp -lpthread

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: 12 - Compression Speedb5 2p b5 2p a2 x AMD EPYC 7373X 16-Core5 a7373X 2P7373x70140210280350270.8282.8283.6288.9289.1295.0305.11. (CC) gcc options: -O3 -pthread -lz -llzma -llz4

OpenBenchmarking.orgMB/s, More Is BetterZstd Compression 1.5.4Compression Level: 19, Long Mode - Decompression Speedb5 2p a5 2p b5 a2 x AMD EPYC 7373X 16-Core7373X 2P7373x300600900120015001190.81222.91227.11229.11289.91292.11312.91. (CC) gcc options: -O3 -pthread -lz -llzma -llz4

OpenBenchmarking.orgMB/s, More Is BetterZstd Compression 1.5.4Compression Level: 8 - Decompression Speedb5 2p a5 a5 2p b7373X 2P2 x AMD EPYC 7373X 16-Core7373x300600900120015001390.01437.51438.81441.11518.11523.61523.91. (CC) gcc options: -O3 -pthread -lz -llzma -llz4

OpenBenchmarking.orgMB/s, More Is BetterZstd Compression 1.5.4Compression Level: 19 - Decompression Speedb5 a5 2p b5 2p a2 x AMD EPYC 7373X 16-Core7373x7373X 2P300600900120015001276.81304.21312.01315.61375.81389.61394.31. (CC) gcc options: -O3 -pthread -lz -llzma -llz4

OpenBenchmarking.orgMB/s, More Is BetterZstd Compression 1.5.4Compression Level: 19 - Compression Speedb5 2p a5 2p b5 a2 x AMD EPYC 7373X 16-Core7373X 2P7373x51015202517.618.018.018.218.618.919.21. (CC) gcc options: -O3 -pthread -lz -llzma -llz4

OpenBenchmarking.orgMB/s, More Is BetterZstd Compression 1.5.4Compression Level: 3, Long Mode - Decompression Speedb5 2p a5 2p b5 a7373x7373X 2P2 x AMD EPYC 7373X 16-Core300600900120015001300.81332.31336.51361.51413.01414.11415.41. (CC) gcc options: -O3 -pthread -lz -llzma -llz4

OpenBenchmarking.orgMB/s, More Is BetterZstd Compression 1.5.4Compression Level: 8, Long Mode - Decompression Speedb5 2p b5 2p a5 a7373X 2P7373x2 x AMD EPYC 7373X 16-Core300600900120015001434.21445.11454.71460.11538.41541.71559.81. (CC) gcc options: -O3 -pthread -lz -llzma -llz4

OpenBenchmarking.orgMB/s, More Is BetterZstd Compression 1.5.4Compression Level: 19, Long Mode - Compression Speedb5 2p b5 a5 2p a7373x2 x AMD EPYC 7373X 16-Core7373X 2P36912159.309.509.549.5710.1010.1010.101. (CC) gcc options: -O3 -pthread -lz -llzma -llz4

OpenBenchmarking.orgMB/s, More Is BetterZstd Compression 1.5.4Compression Level: 3 - Decompression Speedb7373x5 2p a5 2p b5 a7373X 2P2 x AMD EPYC 7373X 16-Core300600900120015001277.31281.11306.71309.51326.51362.41384.11. (CC) gcc options: -O3 -pthread -lz -llzma -llz4

OpenBenchmarking.orgMB/s, More Is BetterZstd Compression 1.5.4Compression Level: 12 - Decompression Speedb5 a5 2p a5 2p b7373X 2P7373x2 x AMD EPYC 7373X 16-Core300600900120015001445.91478.11482.71498.91552.01557.21563.01. (CC) gcc options: -O3 -pthread -lz -llzma -llz4

SVT-AV1

OpenBenchmarking.orgFrames Per Second, More Is BetterSVT-AV1 1.5Encoder Mode: Preset 4 - Input: Bosphorus 1080p7373x2 x AMD EPYC 7373X 16-Coreba5 2p a7373X 2P5 2p b5 a5 b3691215SE +/- 0.02, N = 310.0210.2010.2310.3010.4110.4310.5010.7610.831. (CXX) g++ options: -march=native -mno-avx -mavx2 -mavx512f -mavx512bw -mavx512dq

QuantLib

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

OpenBenchmarking.orgMFLOPS, More Is BetterQuantLib 1.30ba5 a5 2p a5 b5 2p b7373x2 x AMD EPYC 7373X 16-Core7373X 2P6001200180024003000SE +/- 25.52, N = 32692.42746.52756.92760.92820.42850.82854.12894.22907.31. (CXX) g++ options: -O3 -march=native -fPIE -pie

Google Draco

Draco is a library developed by Google for compressing/decompressing 3D geometric meshes and point clouds. This test profile uses some Artec3D PLY models as the sample 3D model input formats for Draco compression/decompression. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgms, Fewer Is BetterGoogle Draco 1.5.6Model: Church Facadeba5 2p b5 a5 2p a2 x AMD EPYC 7373X 16-Core7373X 2P7373x13002600390052006500SE +/- 3.21, N = 3583357935729571856825498548554061. (CXX) g++ options: -O3

FFmpeg

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

OpenBenchmarking.orgSeconds, Fewer Is BetterFFmpeg 6.0Encoder: libx265 - Scenario: Video On Demanda5 2p bb7373X 2P5 2p a2 x AMD EPYC 7373X 16-Core7373x5 a4080120160200SE +/- 0.15, N = 3173.47173.05172.53170.68168.46165.87162.33161.541. (CXX) g++ options: -O3 -rdynamic -lpthread -lrt -ldl -lnuma

OpenBenchmarking.orgFPS, More Is BetterFFmpeg 6.0Encoder: libx265 - Scenario: Video On Demanda5 2p bb7373X 2P5 2p a2 x AMD EPYC 7373X 16-Core7373x5 a1122334455SE +/- 0.04, N = 343.6743.7743.9044.3844.9745.6746.6646.891. (CXX) g++ options: -O3 -rdynamic -lpthread -lrt -ldl -lnuma

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 - Compression Speed7373x5 2p b5 2p a7373X 2Pb2 x AMD EPYC 7373X 16-Core5 a60012001800240030002661.02775.92783.72801.42819.02842.32856.61. (CC) gcc options: -O3 -pthread -lz -llzma -llz4

Google Draco

Draco is a library developed by Google for compressing/decompressing 3D geometric meshes and point clouds. This test profile uses some Artec3D PLY models as the sample 3D model input formats for Draco compression/decompression. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgms, Fewer Is BetterGoogle Draco 1.5.6Model: Lionba5 2p b5 a5 2p a2 x AMD EPYC 7373X 16-Core7373X 2P7373x10002000300040005000SE +/- 7.02, N = 3488548674818476047344642461445631. (CXX) g++ options: -O3

FFmpeg

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

OpenBenchmarking.orgFPS, More Is BetterFFmpeg 6.0Encoder: libx265 - Scenario: Platform5 2p bab5 2p a2 x AMD EPYC 7373X 16-Core7373X 2P7373x5 a1122334455SE +/- 0.02, N = 343.6443.7343.9044.3144.5645.7246.6746.701. (CXX) g++ options: -O3 -rdynamic -lpthread -lrt -ldl -lnuma

OpenBenchmarking.orgSeconds, Fewer Is BetterFFmpeg 6.0Encoder: libx265 - Scenario: Platform5 2p bab5 2p a2 x AMD EPYC 7373X 16-Core7373X 2P7373x5 a4080120160200SE +/- 0.08, N = 3173.56173.23172.57170.94169.99165.70162.30162.191. (CXX) g++ options: -O3 -rdynamic -lpthread -lrt -ldl -lnuma

eSpeak-NG Speech Engine

This test times how long it takes the eSpeak speech synthesizer to read Project Gutenberg's The Outline of Science and output to a WAV file. This test profile is now tracking the eSpeak-NG version of eSpeak. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgSeconds, Fewer Is BettereSpeak-NG Speech Engine 20200907Text-To-Speech Synthesisb5 2p b5 2p a5 a7373X 2P7373x2 x AMD EPYC 7373X 16-Core71421283528.1628.1427.8727.8326.5126.5126.471. (CC) gcc options: -O2 -std=c99

FFmpeg

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

OpenBenchmarking.orgFPS, More Is BetterFFmpeg 6.0Encoder: libx265 - Scenario: Uploadab5 2p b2 x AMD EPYC 7373X 16-Core7373X 2P5 2p a7373x5 b5 a510152025SE +/- 0.01, N = 321.5921.6222.1022.2122.3522.3822.8322.9322.951. (CXX) g++ options: -O3 -rdynamic -lpthread -lrt -ldl -lnuma

OpenBenchmarking.orgSeconds, Fewer Is BetterFFmpeg 6.0Encoder: libx265 - Scenario: Uploadab5 2p b2 x AMD EPYC 7373X 16-Core7373X 2P5 2p a7373x5 b5 a306090120150SE +/- 0.05, N = 3116.93116.81114.26113.67112.96112.82110.61110.14110.011. (CXX) g++ options: -O3 -rdynamic -lpthread -lrt -ldl -lnuma

Z3 Theorem Prover

The Z3 Theorem Prover / SMT solver is developed by Microsoft Research under the MIT license. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgSeconds, Fewer Is BetterZ3 Theorem Prover 4.12.1SMT File: 1.smt27373X 2P2 x AMD EPYC 7373X 16-Core51015202521.7221.221. (CXX) g++ options: -lpthread -std=c++17 -fvisibility=hidden -mfpmath=sse -msse -msse2 -O3 -fPIC

OpenBenchmarking.orgSeconds, Fewer Is BetterZ3 Theorem Prover 4.12.1SMT File: 2.smt27373X 2P2 x AMD EPYC 7373X 16-Core163248648070.5170.291. (CXX) g++ options: -lpthread -std=c++17 -fvisibility=hidden -mfpmath=sse -msse -msse2 -O3 -fPIC

145 Results Shown

NCNN:
  CPU - googlenet
  CPU - mobilenet
  CPU - resnet50
  CPU - efficientnet-b0
  CPU-v2-v2 - mobilenet-v2
  CPU - resnet18
  CPU - regnety_400m
  CPU - FastestDet
LeelaChessZero
NCNN:
  CPU-v3-v3 - mobilenet-v3
  CPU - shufflenet-v2
  CPU - alexnet
OpenFOAM
LeelaChessZero
OpenVINO
LULESH
OpenVINO
ACES DGEMM
SPECFEM3D
OpenVINO
John The Ripper:
  bcrypt
  Blowfish
  WPA PSK
Blender
OpenVINO
SPECFEM3D
Blender
ASKAP
OpenVINO
SPECFEM3D
7-Zip Compression
Blender
OpenVINO
Blender
John The Ripper
OpenCV
Embree
Blender
Embree
Pennant
SPECFEM3D
OpenVINO:
  Person Detection FP32 - CPU
  Machine Translation EN To DE FP16 - CPU
  Person Detection FP16 - CPU
  Face Detection FP16 - CPU
ASKAP
Embree
OpenCV
SPECFEM3D
Embree:
  Pathtracer - Asian Dragon
  Pathtracer ISPC - Asian Dragon
Pennant
Embree
NCNN
oneDNN
Timed LLVM Compilation
GROMACS
Xcompact3d Incompact3d
CloverLeaf
OpenVINO
7-Zip Compression
NCNN
OpenVINO
OpenFOAM
Xcompact3d Incompact3d
oneDNN
PETSc
John The Ripper
oneDNN
OpenVKL
OpenCV
oneDNN:
  IP Shapes 3D - f32 - CPU
  Deconvolution Batch shapes_3d - f32 - CPU
OpenCV
OpenFOAM
NCNN:
  CPU - mnasnet
  CPU - blazeface
ASKAP
oneDNN
Timed LLVM Compilation
Timed FFmpeg Compilation
ASKAP:
  tConvolve OpenMP - Gridding
  tConvolve MT - Gridding
OpenVINO:
  Age Gender Recognition Retail 0013 FP16-INT8 - CPU
  Age Gender Recognition Retail 0013 FP16 - CPU
NCNN
OpenVINO:
  Person Detection FP32 - CPU
  Person Detection FP16 - CPU
OpenCV
OpenVINO:
  Face Detection FP16 - CPU
  Weld Porosity Detection FP16 - CPU
  Machine Translation EN To DE FP16 - CPU
ASKAP
SVT-AV1:
  Preset 8 - Bosphorus 4K
  Preset 12 - Bosphorus 4K
oneDNN
OpenVINO:
  Weld Porosity Detection FP16-INT8 - CPU
  Face Detection FP16-INT8 - CPU
ASKAP
OpenVINO:
  Vehicle Detection FP16 - CPU
  Vehicle Detection FP16-INT8 - CPU
SVT-AV1
OpenVINO
VVenC
SVT-AV1
ClickHouse
VVenC
FFmpeg:
  libx265 - Live:
    FPS
    Seconds
SVT-AV1
ClickHouse:
  100M Rows Hits Dataset, Second Run
  100M Rows Hits Dataset, Third Run
SVT-AV1
OpenFOAM
Zstd Compression:
  8, Long Mode - Compression Speed
  8 - Compression Speed
  3, Long Mode - Compression Speed
VVenC
SVT-AV1
VVenC
NCNN
Zstd Compression:
  12 - Compression Speed
  19, Long Mode - Decompression Speed
  8 - Decompression Speed
  19 - Decompression Speed
  19 - Compression Speed
  3, Long Mode - Decompression Speed
  8, Long Mode - Decompression Speed
  19, Long Mode - Compression Speed
  3 - Decompression Speed
  12 - Decompression Speed
SVT-AV1
QuantLib
Google Draco
FFmpeg:
  libx265 - Video On Demand:
    Seconds
    FPS
Zstd Compression
Google Draco
FFmpeg:
  libx265 - Platform:
    FPS
    Seconds
eSpeak-NG Speech Engine
FFmpeg:
  libx265 - Upload:
    FPS
    Seconds
Z3 Theorem Prover:
  1.smt2
  2.smt2