server-cpus-june-2021

2 x AMD EPYC 7763 64-Core testing with a AMD DAYTONA_X (RYM1001D BIOS) and llvmpipe on Ubuntu 21.04 via the Phoronix Test Suite.

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Result
Identifier
Performance Per
Dollar
Date
Run
  Test
  Duration
2 x EPYC 7763
June 13 2021
  11 Hours, 11 Minutes
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2 x EPYC 7763

Processor: 2 x AMD EPYC 7763 64-Core @ 2.45GHz (128 Cores / 256 Threads), Motherboard: AMD DAYTONA_X (RYM1001D BIOS), Chipset: AMD Starship/Matisse, Memory: 504GB, Disk: 7682GB INTEL SSDPF2KX076TZ, Graphics: llvmpipe, Monitor: VE228, Network: 2 x Mellanox MT27710

OS: Ubuntu 21.04, Kernel: 5.13.0-051300rc4-generic (x86_64) 20210530, Display Server: X Server 1.20.11, OpenGL: 4.5 Mesa 21.0.1 (LLVM 11.0.1 256 bits), Vulkan: 1.0.2, Compiler: GCC 10.3.0, File-System: ext4, Screen Resolution: 1920x1080

Kernel Notes: Transparent Huge Pages: madvise
Compiler Notes: --build=x86_64-linux-gnu --disable-vtable-verify --disable-werror --enable-bootstrap --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-mutex --enable-multiarch --enable-multilib --enable-nls --enable-objc-gc=auto --enable-offload-targets=nvptx-none=/build/gcc-10-gDeRY6/gcc-10-10.3.0/debian/tmp-nvptx/usr,amdgcn-amdhsa=/build/gcc-10-gDeRY6/gcc-10-10.3.0/debian/tmp-gcn/usr,hsa --enable-plugin --enable-shared --enable-threads=posix --host=x86_64-linux-gnu --program-prefix=x86_64-linux-gnu- --target=x86_64-linux-gnu --with-abi=m64 --with-arch-32=i686 --with-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 Notes: Scaling Governor: acpi-cpufreq performance (Boost: Enabled) - CPU Microcode: 0xa001119
Python Notes: Python 3.9.5
Security Notes: itlb_multihit: Not affected + l1tf: Not affected + mds: Not affected + meltdown: 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 Full AMD retpoline IBPB: conditional IBRS_FW STIBP: always-on RSB filling + srbds: Not affected + tsx_async_abort: Not affected

server-cpus-june-2021 OpenBenchmarking.orgPhoronix Test Suite2 x AMD EPYC 7763 64-Core @ 2.45GHz (128 Cores / 256 Threads)AMD DAYTONA_X (RYM1001D BIOS)AMD Starship/Matisse504GB7682GB INTEL SSDPF2KX076TZllvmpipeVE2282 x Mellanox MT27710Ubuntu 21.045.13.0-051300rc4-generic (x86_64) 20210530X Server 1.20.114.5 Mesa 21.0.1 (LLVM 11.0.1 256 bits)1.0.2GCC 10.3.0ext41920x1080ProcessorMotherboardChipsetMemoryDiskGraphicsMonitorNetworkOSKernelDisplay ServerOpenGLVulkanCompilerFile-SystemScreen ResolutionServer-cpus-june-2021 BenchmarksSystem Logs- Transparent Huge Pages: madvise- --build=x86_64-linux-gnu --disable-vtable-verify --disable-werror --enable-bootstrap --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-mutex --enable-multiarch --enable-multilib --enable-nls --enable-objc-gc=auto --enable-offload-targets=nvptx-none=/build/gcc-10-gDeRY6/gcc-10-10.3.0/debian/tmp-nvptx/usr,amdgcn-amdhsa=/build/gcc-10-gDeRY6/gcc-10-10.3.0/debian/tmp-gcn/usr,hsa --enable-plugin --enable-shared --enable-threads=posix --host=x86_64-linux-gnu --program-prefix=x86_64-linux-gnu- --target=x86_64-linux-gnu --with-abi=m64 --with-arch-32=i686 --with-build-config=bootstrap-lto-lean --with-default-libstdcxx-abi=new --with-gcc-major-version-only --with-multilib-list=m32,m64,mx32 --with-target-system-zlib=auto --with-tune=generic --without-cuda-driver -v - Scaling Governor: acpi-cpufreq performance (Boost: Enabled) - CPU Microcode: 0xa001119 - Python 3.9.5- itlb_multihit: Not affected + l1tf: Not affected + mds: Not affected + meltdown: 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 Full AMD retpoline IBPB: conditional IBRS_FW STIBP: always-on RSB filling + srbds: Not affected + tsx_async_abort: Not affected

server-cpus-june-2021 gromacs: MPI CPU - water_GMX50_bareaskap: Hogbom Clean OpenMPaskap: tConvolve OpenMP - Degriddingaskap: tConvolve OpenMP - Griddingaskap: tConvolve MPI - Griddingaskap: tConvolve MPI - Degriddingaskap: tConvolve MT - Griddingliquid-dsp: 160 - 256 - 57liquid-dsp: 128 - 256 - 57liquid-dsp: 64 - 256 - 57cpuminer-opt: LBC, LBRY Creditscpuminer-opt: Skeincoincpuminer-opt: Garlicoincpuminer-opt: Deepcoincpuminer-opt: x25xcpuminer-opt: Magiaircrack-ng: openssl: RSA 4096-bit Performancewebp2: Quality 100, Lossless Compressionwebp2: Quality 100, Compression Effort 5webp2: Quality 95, Compression Effort 7webp2: Quality 75, Compression Effort 7tachyon: Total Timem-queens: Time To Solvebuild-wasmer: Time To Compileonednn: Matrix Multiply Batch Shapes Transformer - u8s8f32 - CPUonednn: Recurrent Neural Network Training - bf16bf16bf16 - CPUonednn: Matrix Multiply Batch Shapes Transformer - f32 - CPUonednn: Recurrent Neural Network Training - u8s8f32 - CPUonednn: Recurrent Neural Network Training - f32 - CPUonednn: Deconvolution Batch shapes_1d - u8s8f32 - CPUonednn: Deconvolution Batch shapes_3d - f32 - CPUonednn: Deconvolution Batch shapes_1d - f32 - CPUonednn: Convolution Batch Shapes Auto - f32 - CPUonednn: IP Shapes 3D - u8s8f32 - CPUonednn: IP Shapes 1D - u8s8f32 - CPUonednn: IP Shapes 3D - f32 - CPUonednn: IP Shapes 1D - f32 - CPUrays1bench: Large Sceneyafaray: Total Time For Sample Sceneprimesieve: 1e12 Prime Number Generationpovray: Trace Timec-ray: Total Time - 4K, 16 Rays Per Pixelbuild2: Time To Compilebuild-php: Time To Compilebuild-nodejs: Time To Compilebuild-mesa: Time To Compilebuild-llvm: Unix Makefilesbuild-llvm: Ninjabuild-linux-kernel: Time To Compilebuild-imagemagick: Time To Compilebuild-godot: Time To Compilebuild-gdb: Time To Compilebuild-ffmpeg: Time To Compilebuild-apache: Time To Compileavifenc: 6, Losslessebizzy: asmfish: 1024 Hash Memory, 26 Depthstockfish: Total Timecompress-7zip: Compress Speed Testcoremark: CoreMark Size 666 - Iterations Per Secondopenvkl: vklBenchmarkStructuredVolumeopenvkl: vklBenchmarkVdbVolumeopenvkl: vklBenchmarkoidn: RTLightmap.hdr.4096x4096oidn: RT.ldr_alb_nrm.3840x2160oidn: RT.hdr_alb_nrm.3840x2160mt-dgemm: Sustained Floating-Point Ratex265: Bosphorus 4Ksvt-vp9: Visual Quality Optimized - Bosphorus 1080psvt-vp9: PSNR/SSIM Optimized - Bosphorus 1080psvt-vp9: VMAF Optimized - Bosphorus 1080psvt-hevc: 10 - Bosphorus 1080psvt-hevc: 7 - Bosphorus 1080psvt-hevc: 1 - Bosphorus 1080psvt-av1: Preset 8 - Bosphorus 4Ksvt-av1: Preset 4 - Bosphorus 4Kkvazaar: Bosphorus 4K - Ultra Fastkvazaar: Bosphorus 4K - Very Fastembree: Pathtracer ISPC - Asian Dragon Objembree: Pathtracer ISPC - Asian Dragonembree: Pathtracer - Asian Dragon Objembree: Pathtracer - Asian Dragonembree: Pathtracer ISPC - Crownembree: Pathtracer - Crowndav1d: Chimera 1080p 10-bitdav1d: Summer Nature 4Kgraphics-magick: HWB Color Spacegraphics-magick: Noise-Gaussiangraphics-magick: Enhancedgraphics-magick: Sharpengraphics-magick: Rotategraphics-magick: Swirlluxcorerender: LuxCore Benchmark - CPUluxcorerender: Orange Juice - CPUluxcorerender: Danish Mood - CPUjohn-the-ripper: MD5john-the-ripper: Blowfishxmrig: Wownero - 1Mxmrig: Monero - 1Mlulesh: lammps: Rhodopsin Proteinlammps: 20k Atomsqe: AUSURF112openfoam: Motorbike 60Mopenfoam: Motorbike 30Mincompact3d: input.i3d 193 Cells Per Directionincompact3d: X3D-benchmarking input.i3dnwchem: C240 Buckyballpennant: sedovbigamg: toybrot: C++ Threadstoybrot: C++ Taskstoybrot: OpenMPtoybrot: TBBnamd: ATPase Simulation - 327,506 Atomsrodinia: OpenMP Streamclusterrodinia: OpenMP CFD Solverrodinia: OpenMP Leukocyterodinia: OpenMP LavaMDminife: Smallnpb: SP.Cnpb: SP.Bnpb: MG.Cnpb: LU.Cnpb: IS.Dnpb: FT.Cnpb: EP.Dnpb: EP.Cnpb: CG.Cnpb: BT.Ctensorflow-lite: SqueezeNetaskap: tConvolve MT - Degriddingcpuminer-opt: Myriad-Groestlcpuminer-opt: Blake-2 Shelsing: 14 digitonednn: Recurrent Neural Network Inference - bf16bf16bf16 - CPUonednn: Recurrent Neural Network Inference - u8s8f32 - CPUonednn: Recurrent Neural Network Inference - f32 - CPUonednn: Deconvolution Batch shapes_3d - u8s8f32 - CPUonednn: Convolution Batch Shapes Auto - u8s8f32 - CPUttsiod-renderer: Phong Rendering With Soft-Shadow Mappingluxcorerender: Rainbow Colors and Prism - CPUluxcorerender: DLSC - CPUincompact3d: input.i3d 129 Cells Per Directionpennant: leblancbigcloverleaf: Lagrangian-Eulerian Hydrodynamics2 x EPYC 776310.141320.6245984.045171.5147712.444990.16000.315902333333583073333331106333335157331124649286801121404336.286099.30414388.80228464.5388.7606.963227.807121.6848.98896.24441.7830.7064123334.590.4884563319.373330.400.8422583.3246126.61020.5861351.063311.570484.724041.80828554.1550.2632.4087.2605.83154.24935.23073.15016.899177.23298.25518.30611.58651.98745.66614.71920.32029.27831131422937933953122308954985613236345.093404109870381230156846031.252.572.5338.13964824.82352.07459.91460.25596.09337.8755.1762.1015.06859.0855.4358.939167.613659.528471.5382100.6551110.70061143.60592.79653582146888456923068.6521.668.781076333318323448176.056612.736927.23531.32635.084973.0290.1414.9011.0900421297.6698001837.95.236554192545866736793867432734930.224567.4896.18851.61823.65826535.1116234.76149338.71102771.23288799.044460.84120440.0410736.779537.2348175.52257264.2453389.410480.312387804077053122.8521385.481332.191464.790.7302050.848820527.53018.4014.332.722974193.34249816.12OpenBenchmarking.org

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 2021.2Implementation: MPI CPU - Input: water_GMX50_bare2 x EPYC 77633691215SE +/- 0.07, N = 310.141. (CXX) g++ options: -O3 -pthread
OpenBenchmarking.orgNs Per Day Per Watt, More Is BetterGROMACS 2021.2Implementation: MPI CPU - Input: water_GMX50_bare2 x EPYC 77630.0050.010.0150.020.0250.022
MinAvgMax2 x EPYC 776383.1450.9560.0OpenBenchmarking.orgWatts, Fewer Is BetterGROMACS 2021.2CPU Power Consumption Monitor1402804205607001. 2 x EPYC 7763: Approximate power consumption of 17436 Joules per run.

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 OpenMP2 x EPYC 776370140210280350SE +/- 3.47, N = 4320.621. (CXX) g++ options: -O3 -fstrict-aliasing -fopenmp
OpenBenchmarking.orgIterations Per Second Per Watt, More Is BetterASKAP 1.0Test: Hogbom Clean OpenMP2 x EPYC 77630.40640.81281.21921.62562.0321.806
MinAvgMax2 x EPYC 776382.3177.5357.6OpenBenchmarking.orgWatts, Fewer Is BetterASKAP 1.0CPU Power Consumption Monitor1002003004005001. 2 x EPYC 7763: Approximate power consumption of 3728 Joules per run.

OpenBenchmarking.orgMillion Grid Points Per Second, More Is BetterASKAP 1.0Test: tConvolve OpenMP - Degridding2 x EPYC 776313002600390052006500SE +/- 38.82, N = 45984.041. (CXX) g++ options: -O3 -fstrict-aliasing -fopenmp
OpenBenchmarking.orgMillion Grid Points Per Second Per Watt, More Is BetterASKAP 1.0Test: tConvolve OpenMP - Degridding2 x EPYC 776391827364537.78
MinAvgMax2 x EPYC 776382.7158.4269.0OpenBenchmarking.orgWatts, Fewer Is BetterASKAP 1.0CPU Power Consumption Monitor701402102803501. 2 x EPYC 7763: Approximate power consumption of 2455 Joules per run.

OpenBenchmarking.orgMillion Grid Points Per Second, More Is BetterASKAP 1.0Test: tConvolve OpenMP - Gridding2 x EPYC 776311002200330044005500SE +/- 51.20, N = 45171.511. (CXX) g++ options: -O3 -fstrict-aliasing -fopenmp

OpenBenchmarking.orgMpix/sec, More Is BetterASKAP 1.0Test: tConvolve MPI - Gridding2 x EPYC 776310K20K30K40K50KSE +/- 313.07, N = 347712.41. (CXX) g++ options: -O3 -fstrict-aliasing -fopenmp
OpenBenchmarking.orgMpix/sec Per Watt, More Is BetterASKAP 1.0Test: tConvolve MPI - Gridding2 x EPYC 7763306090120150123.01
MinAvgMax2 x EPYC 776382.6387.9562.8OpenBenchmarking.orgWatts, Fewer Is BetterASKAP 1.0CPU Power Consumption Monitor1402804205607001. 2 x EPYC 7763: Approximate power consumption of 20945 Joules per run.

OpenBenchmarking.orgMpix/sec, More Is BetterASKAP 1.0Test: tConvolve MPI - Degridding2 x EPYC 776310K20K30K40K50KSE +/- 423.01, N = 344990.11. (CXX) g++ options: -O3 -fstrict-aliasing -fopenmp

OpenBenchmarking.orgMillion Grid Points Per Second, More Is BetterASKAP 1.0Test: tConvolve MT - Gridding2 x EPYC 776313002600390052006500SE +/- 2.16, N = 36000.311. (CXX) g++ options: -O3 -fstrict-aliasing -fopenmp

Liquid-DSP

LiquidSDR's Liquid-DSP is a software-defined radio (SDR) digital signal processing library. This test profile runs a multi-threaded benchmark of this SDR/DSP library focused on embedded platform usage. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgsamples/s, More Is BetterLiquid-DSP 2021.01.31Threads: 160 - Buffer Length: 256 - Filter Length: 572 x EPYC 77631300M2600M3900M5200M6500MSE +/- 3371613.53, N = 359023333331. (CC) gcc options: -O3 -pthread -lm -lc -lliquid
OpenBenchmarking.orgsamples/s Per Watt, More Is BetterLiquid-DSP 2021.01.31Threads: 160 - Buffer Length: 256 - Filter Length: 572 x EPYC 77633M6M9M12M15M13016160.24
MinAvgMax2 x EPYC 776381.6453.5536.1OpenBenchmarking.orgWatts, Fewer Is BetterLiquid-DSP 2021.01.31CPU Power Consumption Monitor1402804205607001. 2 x EPYC 7763: Approximate power consumption of 10883 Joules per run.

OpenBenchmarking.orgsamples/s, More Is BetterLiquid-DSP 2021.01.31Threads: 128 - Buffer Length: 256 - Filter Length: 572 x EPYC 77631200M2400M3600M4800M6000MSE +/- 3169822.99, N = 358307333331. (CC) gcc options: -O3 -pthread -lm -lc -lliquid
OpenBenchmarking.orgsamples/s Per Watt, More Is BetterLiquid-DSP 2021.01.31Threads: 128 - Buffer Length: 256 - Filter Length: 572 x EPYC 77633M6M9M12M15M12615116.14
MinAvgMax2 x EPYC 776381.7462.2543.7OpenBenchmarking.orgWatts, Fewer Is BetterLiquid-DSP 2021.01.31CPU Power Consumption Monitor1402804205607001. 2 x EPYC 7763: Approximate power consumption of 10939 Joules per run.

OpenBenchmarking.orgsamples/s, More Is BetterLiquid-DSP 2021.01.31Threads: 64 - Buffer Length: 256 - Filter Length: 572 x EPYC 7763700M1400M2100M2800M3500MSE +/- 4437842.32, N = 331106333331. (CC) gcc options: -O3 -pthread -lm -lc -lliquid
OpenBenchmarking.orgsamples/s Per Watt, More Is BetterLiquid-DSP 2021.01.31Threads: 64 - Buffer Length: 256 - Filter Length: 572 x EPYC 77632M4M6M8M10M9297794.92
MinAvgMax2 x EPYC 776382.5334.6414.4OpenBenchmarking.orgWatts, Fewer Is BetterLiquid-DSP 2021.01.31CPU Power Consumption Monitor1102203304405501. 2 x EPYC 7763: Approximate power consumption of 8141 Joules per run.

Cpuminer-Opt

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

OpenBenchmarking.orgkH/s, More Is BetterCpuminer-Opt 3.15.5Algorithm: LBC, LBRY Credits2 x EPYC 7763110K220K330K440K550KSE +/- 6048.06, N = 35157331. (CXX) g++ options: -O2 -lcurl -lz -lpthread -lssl -lcrypto -lgmp
OpenBenchmarking.orgkH/s Per Watt, More Is BetterCpuminer-Opt 3.15.5Algorithm: LBC, LBRY Credits2 x EPYC 776370014002100280035003265.44
MinAvgMax2 x EPYC 776382.2157.9173.0OpenBenchmarking.orgWatts, Fewer Is BetterCpuminer-Opt 3.15.5CPU Power Consumption Monitor501001502002501. 2 x EPYC 7763: Approximate power consumption of 5475 Joules per run.

OpenBenchmarking.orgkH/s, More Is BetterCpuminer-Opt 3.15.5Algorithm: Skeincoin2 x EPYC 7763200K400K600K800K1000KSE +/- 17000.09, N = 1511246491. (CXX) g++ options: -O2 -lcurl -lz -lpthread -lssl -lcrypto -lgmp
OpenBenchmarking.orgkH/s Per Watt, More Is BetterCpuminer-Opt 3.15.5Algorithm: Skeincoin2 x EPYC 7763160032004800640080007272.60
MinAvgMax2 x EPYC 776381.1154.6171.0OpenBenchmarking.orgWatts, Fewer Is BetterCpuminer-Opt 3.15.5CPU Power Consumption Monitor501001502002501. 2 x EPYC 7763: Approximate power consumption of 5392 Joules per run.

OpenBenchmarking.orgkH/s, More Is BetterCpuminer-Opt 3.15.5Algorithm: Garlicoin2 x EPYC 77636K12K18K24K30KSE +/- 116.76, N = 3286801. (CXX) g++ options: -O2 -lcurl -lz -lpthread -lssl -lcrypto -lgmp
OpenBenchmarking.orgkH/s Per Watt, More Is BetterCpuminer-Opt 3.15.5Algorithm: Garlicoin2 x EPYC 7763306090120150157.59
MinAvgMax2 x EPYC 776383.1182.0369.9OpenBenchmarking.orgWatts, Fewer Is BetterCpuminer-Opt 3.15.5CPU Power Consumption Monitor1002003004005001. 2 x EPYC 7763: Approximate power consumption of 6370 Joules per run.

OpenBenchmarking.orgkH/s, More Is BetterCpuminer-Opt 3.15.5Algorithm: Deepcoin2 x EPYC 776320K40K60K80K100KSE +/- 1493.99, N = 121121401. (CXX) g++ options: -O2 -lcurl -lz -lpthread -lssl -lcrypto -lgmp
OpenBenchmarking.orgkH/s Per Watt, More Is BetterCpuminer-Opt 3.15.5Algorithm: Deepcoin2 x EPYC 7763140280420560700671.32
MinAvgMax2 x EPYC 776382.6167.0232.4OpenBenchmarking.orgWatts, Fewer Is BetterCpuminer-Opt 3.15.5CPU Power Consumption Monitor601201802403001. 2 x EPYC 7763: Approximate power consumption of 5847 Joules per run.

OpenBenchmarking.orgkH/s, More Is BetterCpuminer-Opt 3.15.5Algorithm: x25x2 x EPYC 77639001800270036004500SE +/- 51.41, N = 44336.281. (CXX) g++ options: -O2 -lcurl -lz -lpthread -lssl -lcrypto -lgmp
OpenBenchmarking.orgkH/s Per Watt, More Is BetterCpuminer-Opt 3.15.5Algorithm: x25x2 x EPYC 776351015202519.17
MinAvgMax2 x EPYC 776382.7226.2386.5OpenBenchmarking.orgWatts, Fewer Is BetterCpuminer-Opt 3.15.5CPU Power Consumption Monitor1002003004005001. 2 x EPYC 7763: Approximate power consumption of 7916 Joules per run.

OpenBenchmarking.orgkH/s, More Is BetterCpuminer-Opt 3.15.5Algorithm: Magi2 x EPYC 776313002600390052006500SE +/- 52.03, N = 136099.301. (CXX) g++ options: -O2 -lcurl -lz -lpthread -lssl -lcrypto -lgmp
OpenBenchmarking.orgkH/s Per Watt, More Is BetterCpuminer-Opt 3.15.5Algorithm: Magi2 x EPYC 776371421283528.49
MinAvgMax2 x EPYC 776382.3214.1350.9OpenBenchmarking.orgWatts, Fewer Is BetterCpuminer-Opt 3.15.5CPU Power Consumption Monitor1002003004005001. 2 x EPYC 7763: Approximate power consumption of 7445 Joules per run.

Aircrack-ng

Aircrack-ng is a tool for assessing WiFi/WLAN network security. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgk/s, More Is BetterAircrack-ng 1.5.22 x EPYC 776390K180K270K360K450KSE +/- 159.71, N = 3414388.801. (CXX) g++ options: -O3 -fvisibility=hidden -masm=intel -fcommon -rdynamic -lpthread -lz -lcrypto -lhwloc -ldl -lm -pthread
OpenBenchmarking.orgk/s Per Watt, More Is BetterAircrack-ng 1.5.22 x EPYC 77632004006008001000881.11
MinAvgMax2 x EPYC 776381.9470.3529.7OpenBenchmarking.orgWatts, Fewer Is BetterAircrack-ng 1.5.2CPU Power Consumption Monitor1302603905206501. 2 x EPYC 7763: Approximate power consumption of 15990 Joules per run.

OpenSSL

OpenSSL is an open-source toolkit that implements SSL (Secure Sockets Layer) and TLS (Transport Layer Security) protocols. This test measures the RSA 4096-bit performance of OpenSSL. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgSigns Per Second, More Is BetterOpenSSL 1.1.1RSA 4096-bit Performance2 x EPYC 77636K12K18K24K30KSE +/- 0.99, N = 328464.51. (CC) gcc options: -pthread -m64 -O3 -lssl -lcrypto -ldl
OpenBenchmarking.orgSigns Per Second Per Watt, More Is BetterOpenSSL 1.1.1RSA 4096-bit Performance2 x EPYC 7763132639526559.57
MinAvgMax2 x EPYC 776381.7477.9563.8OpenBenchmarking.orgWatts, Fewer Is BetterOpenSSL 1.1.1CPU Power Consumption Monitor1402804205607001. 2 x EPYC 7763: Approximate power consumption of 11309 Joules per run.

WebP2 Image Encode

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

OpenBenchmarking.orgSeconds, Fewer Is BetterWebP2 Image Encode 20210126Encode Settings: Quality 100, Lossless Compression2 x EPYC 776380160240320400SE +/- 0.24, N = 3388.761. (CXX) g++ options: -msse4.2 -fno-rtti -O3 -rdynamic -lpthread -ljpeg -lwebp -lwebpdemux
MinAvgMax2 x EPYC 776380.9220.7240.5OpenBenchmarking.orgWatts, Fewer Is BetterWebP2 Image Encode 20210126CPU Power Consumption Monitor601201802403001. 2 x EPYC 7763: Approximate power consumption of 86436 Joules per run.

OpenBenchmarking.orgSeconds, Fewer Is BetterWebP2 Image Encode 20210126Encode Settings: Quality 100, Compression Effort 52 x EPYC 7763246810SE +/- 0.014, N = 66.9631. (CXX) g++ options: -msse4.2 -fno-rtti -O3 -rdynamic -lpthread -ljpeg -lwebp -lwebpdemux
MinAvgMax2 x EPYC 776381.7181.7251.2OpenBenchmarking.orgWatts, Fewer Is BetterWebP2 Image Encode 20210126CPU Power Consumption Monitor601201802403001. 2 x EPYC 7763: Approximate power consumption of 2029 Joules per run.

OpenBenchmarking.orgSeconds, Fewer Is BetterWebP2 Image Encode 20210126Encode Settings: Quality 95, Compression Effort 72 x EPYC 776350100150200250SE +/- 0.85, N = 3227.811. (CXX) g++ options: -msse4.2 -fno-rtti -O3 -rdynamic -lpthread -ljpeg -lwebp -lwebpdemux
MinAvgMax2 x EPYC 776381.6217.2238.9OpenBenchmarking.orgWatts, Fewer Is BetterWebP2 Image Encode 20210126CPU Power Consumption Monitor601201802403001. 2 x EPYC 7763: Approximate power consumption of 50250 Joules per run.

OpenBenchmarking.orgSeconds, Fewer Is BetterWebP2 Image Encode 20210126Encode Settings: Quality 75, Compression Effort 72 x EPYC 7763306090120150SE +/- 0.53, N = 3121.681. (CXX) g++ options: -msse4.2 -fno-rtti -O3 -rdynamic -lpthread -ljpeg -lwebp -lwebpdemux
MinAvgMax2 x EPYC 776381.8215.8235.3OpenBenchmarking.orgWatts, Fewer Is BetterWebP2 Image Encode 20210126CPU Power Consumption Monitor601201802403001. 2 x EPYC 7763: Approximate power consumption of 27049 Joules per run.

Tachyon

This is a test of the threaded Tachyon, a parallel ray-tracing system, measuring the time to ray-trace a sample scene. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgSeconds, Fewer Is BetterTachyon 0.99b6Total Time2 x EPYC 77633691215SE +/- 0.0972, N = 158.98891. (CC) gcc options: -m64 -O3 -fomit-frame-pointer -ffast-math -ltachyon -lm -lpthread
MinAvgMax2 x EPYC 776382.4368.9558.0OpenBenchmarking.orgWatts, Fewer Is BetterTachyon 0.99b6CPU Power Consumption Monitor1402804205607001. 2 x EPYC 7763: Approximate power consumption of 4845 Joules per run.

m-queens

A solver for the N-queens problem with multi-threading support via the OpenMP library. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgSeconds, Fewer Is Betterm-queens 1.2Time To Solve2 x EPYC 7763246810SE +/- 0.011, N = 76.2441. (CXX) g++ options: -fopenmp -O2 -march=native
MinAvgMax2 x EPYC 776382.1332.0510.4OpenBenchmarking.orgWatts, Fewer Is Betterm-queens 1.2CPU Power Consumption Monitor1302603905206501. 2 x EPYC 7763: Approximate power consumption of 3367 Joules per run.

Timed Wasmer Compilation

This test times how long it takes to compile Wasmer. Wasmer is written in the Rust programming language and is a WebAssembly runtime implementation that supports WASI and EmScripten. This test profile builds Wasmer with the Cranelift and Singlepast compiler features enabled. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgSeconds, Fewer Is BetterTimed Wasmer Compilation 1.0.2Time To Compile2 x EPYC 77631020304050SE +/- 0.27, N = 341.781. (CC) gcc options: -m64 -pie -nodefaultlibs -ldl -lgcc_s -lutil -lrt -lpthread -lm -lc
MinAvgMax2 x EPYC 776382.1205.1326.9OpenBenchmarking.orgWatts, Fewer Is BetterTimed Wasmer Compilation 1.0.2CPU Power Consumption Monitor801602403204001. 2 x EPYC 7763: Approximate power consumption of 9367 Joules per run.

oneDNN

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

OpenBenchmarking.orgms, Fewer Is BetteroneDNN 2.1.2Harness: Matrix Multiply Batch Shapes Transformer - Data Type: u8s8f32 - Engine: CPU2 x EPYC 77630.15890.31780.47670.63560.7945SE +/- 0.008059, N = 40.706412MIN: 0.611. (CXX) g++ options: -O3 -march=native -std=c++11 -fopenmp -msse4.1 -fPIC -pie -lpthread -ldl
MinAvgMax2 x EPYC 776383.4283.2435.0OpenBenchmarking.orgWatts, Fewer Is BetteroneDNN 2.1.2CPU Power Consumption Monitor1102203304405501. 2 x EPYC 7763: Approximate power consumption of 4531 Joules per run.

OpenBenchmarking.orgms, Fewer Is BetteroneDNN 2.1.2Harness: Recurrent Neural Network Training - Data Type: bf16bf16bf16 - Engine: CPU2 x EPYC 77637001400210028003500SE +/- 34.08, N = 33334.59MIN: 3036.361. (CXX) g++ options: -O3 -march=native -std=c++11 -fopenmp -msse4.1 -fPIC -pie -lpthread -ldl
MinAvgMax2 x EPYC 776383.4349.2416.5OpenBenchmarking.orgWatts, Fewer Is BetteroneDNN 2.1.2CPU Power Consumption Monitor1102203304405501. 2 x EPYC 7763: Approximate power consumption of 30265 Joules per run.

OpenBenchmarking.orgms, Fewer Is BetteroneDNN 2.1.2Harness: Matrix Multiply Batch Shapes Transformer - Data Type: f32 - Engine: CPU2 x EPYC 77630.10990.21980.32970.43960.5495SE +/- 0.003185, N = 150.488456MIN: 0.421. (CXX) g++ options: -O3 -march=native -std=c++11 -fopenmp -msse4.1 -fPIC -pie -lpthread -ldl
MinAvgMax2 x EPYC 776382.7273.1395.0OpenBenchmarking.orgWatts, Fewer Is BetteroneDNN 2.1.2CPU Power Consumption Monitor1102203304405501. 2 x EPYC 7763: Approximate power consumption of 4387 Joules per run.

OpenBenchmarking.orgms, Fewer Is BetteroneDNN 2.1.2Harness: Recurrent Neural Network Training - Data Type: u8s8f32 - Engine: CPU2 x EPYC 77637001400210028003500SE +/- 22.25, N = 33319.37MIN: 3090.921. (CXX) g++ options: -O3 -march=native -std=c++11 -fopenmp -msse4.1 -fPIC -pie -lpthread -ldl
MinAvgMax2 x EPYC 776382.4349.0416.4OpenBenchmarking.orgWatts, Fewer Is BetteroneDNN 2.1.2CPU Power Consumption Monitor1102203304405501. 2 x EPYC 7763: Approximate power consumption of 30248 Joules per run.

OpenBenchmarking.orgms, Fewer Is BetteroneDNN 2.1.2Harness: Recurrent Neural Network Training - Data Type: f32 - Engine: CPU2 x EPYC 77637001400210028003500SE +/- 12.03, N = 33330.40MIN: 3097.071. (CXX) g++ options: -O3 -march=native -std=c++11 -fopenmp -msse4.1 -fPIC -pie -lpthread -ldl
MinAvgMax2 x EPYC 776382.8349.1415.4OpenBenchmarking.orgWatts, Fewer Is BetteroneDNN 2.1.2CPU Power Consumption Monitor1102203304405501. 2 x EPYC 7763: Approximate power consumption of 30257 Joules per run.

OpenBenchmarking.orgms, Fewer Is BetteroneDNN 2.1.2Harness: Deconvolution Batch shapes_1d - Data Type: u8s8f32 - Engine: CPU2 x EPYC 77630.18950.3790.56850.7580.9475SE +/- 0.006220, N = 150.842258MIN: 0.751. (CXX) g++ options: -O3 -march=native -std=c++11 -fopenmp -msse4.1 -fPIC -pie -lpthread -ldl
MinAvgMax2 x EPYC 776383.1315.1474.5OpenBenchmarking.orgWatts, Fewer Is BetteroneDNN 2.1.2CPU Power Consumption Monitor1202403604806001. 2 x EPYC 7763: Approximate power consumption of 7878 Joules per run.

OpenBenchmarking.orgms, Fewer Is BetteroneDNN 2.1.2Harness: Deconvolution Batch shapes_3d - Data Type: f32 - Engine: CPU2 x EPYC 77630.7481.4962.2442.9923.74SE +/- 0.02376, N = 93.32461MIN: 2.131. (CXX) g++ options: -O3 -march=native -std=c++11 -fopenmp -msse4.1 -fPIC -pie -lpthread -ldl
MinAvgMax2 x EPYC 776382.6203.9368.8OpenBenchmarking.orgWatts, Fewer Is BetteroneDNN 2.1.2CPU Power Consumption Monitor1002003004005001. 2 x EPYC 7763: Approximate power consumption of 1450 Joules per run.

OpenBenchmarking.orgms, Fewer Is BetteroneDNN 2.1.2Harness: Deconvolution Batch shapes_1d - Data Type: f32 - Engine: CPU2 x EPYC 7763612182430SE +/- 0.34, N = 326.61MIN: 18.331. (CXX) g++ options: -O3 -march=native -std=c++11 -fopenmp -msse4.1 -fPIC -pie -lpthread -ldl
MinAvgMax2 x EPYC 776383.0289.5408.7OpenBenchmarking.orgWatts, Fewer Is BetteroneDNN 2.1.2CPU Power Consumption Monitor1102203304405501. 2 x EPYC 7763: Approximate power consumption of 7335 Joules per run.

OpenBenchmarking.orgms, Fewer Is BetteroneDNN 2.1.2Harness: Convolution Batch Shapes Auto - Data Type: f32 - Engine: CPU2 x EPYC 77630.13190.26380.39570.52760.6595SE +/- 0.004578, N = 70.586135MIN: 0.521. (CXX) g++ options: -O3 -march=native -std=c++11 -fopenmp -msse4.1 -fPIC -pie -lpthread -ldl
MinAvgMax2 x EPYC 776382.3288.6485.6OpenBenchmarking.orgWatts, Fewer Is BetteroneDNN 2.1.2CPU Power Consumption Monitor1302603905206501. 2 x EPYC 7763: Approximate power consumption of 2886 Joules per run.

OpenBenchmarking.orgms, Fewer Is BetteroneDNN 2.1.2Harness: IP Shapes 3D - Data Type: u8s8f32 - Engine: CPU2 x EPYC 77630.23920.47840.71760.95681.196SE +/- 0.00834, N = 51.06331MIN: 0.881. (CXX) g++ options: -O3 -march=native -std=c++11 -fopenmp -msse4.1 -fPIC -pie -lpthread -ldl
MinAvgMax2 x EPYC 776383.6238.8362.7OpenBenchmarking.orgWatts, Fewer Is BetteroneDNN 2.1.2CPU Power Consumption Monitor1002003004005001. 2 x EPYC 7763: Approximate power consumption of 3200 Joules per run.

OpenBenchmarking.orgms, Fewer Is BetteroneDNN 2.1.2Harness: IP Shapes 1D - Data Type: u8s8f32 - Engine: CPU2 x EPYC 77630.35340.70681.06021.41361.767SE +/- 0.00915, N = 41.57048MIN: 1.291. (CXX) g++ options: -O3 -march=native -std=c++11 -fopenmp -msse4.1 -fPIC -pie -lpthread -ldl
MinAvgMax2 x EPYC 776382.8282.5383.5OpenBenchmarking.orgWatts, Fewer Is BetteroneDNN 2.1.2CPU Power Consumption Monitor1002003004005001. 2 x EPYC 7763: Approximate power consumption of 5368 Joules per run.

OpenBenchmarking.orgms, Fewer Is BetteroneDNN 2.1.2Harness: IP Shapes 3D - Data Type: f32 - Engine: CPU2 x EPYC 77631.06292.12583.18874.25165.3145SE +/- 0.02745, N = 54.72404MIN: 3.951. (CXX) g++ options: -O3 -march=native -std=c++11 -fopenmp -msse4.1 -fPIC -pie -lpthread -ldl
MinAvgMax2 x EPYC 776382.7238.3357.7OpenBenchmarking.orgWatts, Fewer Is BetteroneDNN 2.1.2CPU Power Consumption Monitor1002003004005001. 2 x EPYC 7763: Approximate power consumption of 3194 Joules per run.

OpenBenchmarking.orgms, Fewer Is BetteroneDNN 2.1.2Harness: IP Shapes 1D - Data Type: f32 - Engine: CPU2 x EPYC 77630.40690.81381.22071.62762.0345SE +/- 0.00936, N = 41.80828MIN: 1.61. (CXX) g++ options: -O3 -march=native -std=c++11 -fopenmp -msse4.1 -fPIC -pie -lpthread -ldl
MinAvgMax2 x EPYC 776382.0303.1495.0OpenBenchmarking.orgWatts, Fewer Is BetteroneDNN 2.1.2CPU Power Consumption Monitor1302603905206501. 2 x EPYC 7763: Approximate power consumption of 5834 Joules per run.

rays1bench

This is a test of rays1bench, a simple path-tracer / ray-tracing that supports SSE and AVX instructions, multi-threading, and other features. This test profile is measuring the performance of the "large scene" in rays1bench. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgmrays/s, More Is Betterrays1bench 2020-01-09Large Scene2 x EPYC 7763120240360480600SE +/- 0.90, N = 9554.15
OpenBenchmarking.orgmrays/s Per Watt, More Is Betterrays1bench 2020-01-09Large Scene2 x EPYC 77630.68331.36662.04992.73323.41653.037
MinAvgMax2 x EPYC 776381.8182.4493.1OpenBenchmarking.orgWatts, Fewer Is Betterrays1bench 2020-01-09CPU Power Consumption Monitor1302603905206501. 2 x EPYC 7763: Approximate power consumption of 1338 Joules per run.

YafaRay

YafaRay is an open-source physically based montecarlo ray-tracing engine. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgSeconds, Fewer Is BetterYafaRay 3.4.1Total Time For Sample Scene2 x EPYC 77631122334455SE +/- 0.39, N = 1550.261. (CXX) g++ options: -std=c++11 -O3 -ffast-math -rdynamic -ldl -lImath -lIlmImf -lIex -lHalf -lz -lIlmThread -lxml2 -lfreetype -lpthread
MinAvgMax2 x EPYC 776381.4333.7418.7OpenBenchmarking.orgWatts, Fewer Is BetterYafaRay 3.4.1CPU Power Consumption Monitor1102203304405501. 2 x EPYC 7763: Approximate power consumption of 18018 Joules per run.

Primesieve

Primesieve generates prime numbers using a highly optimized sieve of Eratosthenes implementation. Primesieve benchmarks the CPU's L1/L2 cache performance. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgSeconds, Fewer Is BetterPrimesieve 7.41e12 Prime Number Generation2 x EPYC 77630.54181.08361.62542.16722.709SE +/- 0.005, N = 102.4081. (CXX) g++ options: -O3 -lpthread
MinAvgMax2 x EPYC 776381.3240.7553.9OpenBenchmarking.orgWatts, Fewer Is BetterPrimesieve 7.4CPU Power Consumption Monitor1402804205607001. 2 x EPYC 7763: Approximate power consumption of 1541 Joules per run.

POV-Ray

This is a test of POV-Ray, the Persistence of Vision Raytracer. POV-Ray is used to create 3D graphics using ray-tracing. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgSeconds, Fewer Is BetterPOV-Ray 3.7.0.7Trace Time2 x EPYC 7763246810SE +/- 0.038, N = 57.2601. (CXX) g++ options: -pipe -O3 -ffast-math -march=native -pthread -lSDL -lSM -lICE -lX11 -lIlmImf -lIlmImf-2_5 -lImath-2_5 -lHalf-2_5 -lIex-2_5 -lIexMath-2_5 -lIlmThread-2_5 -lIlmThread -ltiff -ljpeg -lpng -lz -lrt -lm -lboost_thread -lboost_system
MinAvgMax2 x EPYC 776382.0259.5546.6OpenBenchmarking.orgWatts, Fewer Is BetterPOV-Ray 3.7.0.7CPU Power Consumption Monitor1402804205607001. 2 x EPYC 7763: Approximate power consumption of 3530 Joules per run.

C-Ray

This is a test of C-Ray, a simple raytracer designed to test the floating-point CPU performance. This test is multi-threaded (16 threads per core), will shoot 8 rays per pixel for anti-aliasing, and will generate a 1600 x 1200 image. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgSeconds, Fewer Is BetterC-Ray 1.1Total Time - 4K, 16 Rays Per Pixel2 x EPYC 77631.3122.6243.9365.2486.56SE +/- 0.037, N = 75.8311. (CC) gcc options: -lm -lpthread -O3
MinAvgMax2 x EPYC 776381.5340.8559.8OpenBenchmarking.orgWatts, Fewer Is BetterC-Ray 1.1CPU Power Consumption Monitor1402804205607001. 2 x EPYC 7763: Approximate power consumption of 3505 Joules per run.

Build2

This test profile measures the time to bootstrap/install the build2 C++ build toolchain from source. Build2 is a cross-platform build toolchain for C/C++ code and features Cargo-like features. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgSeconds, Fewer Is BetterBuild2 0.13Time To Compile2 x EPYC 77631224364860SE +/- 0.09, N = 354.25
MinAvgMax2 x EPYC 776383.6235.8571.8OpenBenchmarking.orgWatts, Fewer Is BetterBuild2 0.13CPU Power Consumption Monitor1402804205607001. 2 x EPYC 7763: Approximate power consumption of 13755 Joules per run.

Timed PHP Compilation

This test times how long it takes to build PHP 7. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgSeconds, Fewer Is BetterTimed PHP Compilation 7.4.2Time To Compile2 x EPYC 7763816243240SE +/- 0.13, N = 335.23
MinAvgMax2 x EPYC 776382.6184.8564.1OpenBenchmarking.orgWatts, Fewer Is BetterTimed PHP Compilation 7.4.2CPU Power Consumption Monitor1402804205607001. 2 x EPYC 7763: Approximate power consumption of 8193 Joules per run.

Timed Node.js Compilation

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

OpenBenchmarking.orgSeconds, Fewer Is BetterTimed Node.js Compilation 15.11Time To Compile2 x EPYC 77631632486480SE +/- 0.30, N = 373.15
MinAvgMax2 x EPYC 776381.5346.7572.6OpenBenchmarking.orgWatts, Fewer Is BetterTimed Node.js Compilation 15.11CPU Power Consumption Monitor1402804205607001. 2 x EPYC 7763: Approximate power consumption of 27387 Joules per run.

Timed Mesa Compilation

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

OpenBenchmarking.orgSeconds, Fewer Is BetterTimed Mesa Compilation 21.0Time To Compile2 x EPYC 776348121620SE +/- 0.03, N = 316.90
MinAvgMax2 x EPYC 776382.2215.5573.4OpenBenchmarking.orgWatts, Fewer Is BetterTimed Mesa Compilation 21.0CPU Power Consumption Monitor1402804205607001. 2 x EPYC 7763: Approximate power consumption of 4812 Joules per run.

Timed LLVM Compilation

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

OpenBenchmarking.orgSeconds, Fewer Is BetterTimed LLVM Compilation 12.0Build System: Unix Makefiles2 x EPYC 77634080120160200SE +/- 0.57, N = 3177.23
MinAvgMax2 x EPYC 776383.4295.2571.6OpenBenchmarking.orgWatts, Fewer Is BetterTimed LLVM Compilation 12.0CPU Power Consumption Monitor1402804205607001. 2 x EPYC 7763: Approximate power consumption of 57855 Joules per run.

OpenBenchmarking.orgSeconds, Fewer Is BetterTimed LLVM Compilation 12.0Build System: Ninja2 x EPYC 776320406080100SE +/- 0.49, N = 398.26
MinAvgMax2 x EPYC 776382.0356.3572.4OpenBenchmarking.orgWatts, Fewer Is BetterTimed LLVM Compilation 12.0CPU Power Consumption Monitor1402804205607001. 2 x EPYC 7763: Approximate power consumption of 41211 Joules per run.

Timed Linux Kernel Compilation

This test times how long it takes to build the Linux kernel in a default configuration (defconfig) for the architecture being tested. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgSeconds, Fewer Is BetterTimed Linux Kernel Compilation 5.10.20Time To Compile2 x EPYC 7763510152025SE +/- 0.14, N = 1218.31
MinAvgMax2 x EPYC 776382.5262.4574.9OpenBenchmarking.orgWatts, Fewer Is BetterTimed Linux Kernel Compilation 5.10.20CPU Power Consumption Monitor1402804205607001. 2 x EPYC 7763: Approximate power consumption of 6889 Joules per run.

Timed ImageMagick Compilation

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

OpenBenchmarking.orgSeconds, Fewer Is BetterTimed ImageMagick Compilation 6.9.0Time To Compile2 x EPYC 77633691215SE +/- 0.04, N = 411.59
MinAvgMax2 x EPYC 776382.5187.9534.1OpenBenchmarking.orgWatts, Fewer Is BetterTimed ImageMagick Compilation 6.9.0CPU Power Consumption Monitor1402804205607001. 2 x EPYC 7763: Approximate power consumption of 3758 Joules per run.

Timed Godot Game Engine Compilation

This test times how long it takes to compile the Godot Game Engine. Godot is a popular, open-source, cross-platform 2D/3D game engine and is built using the SCons build system and targeting the X11 platform. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgSeconds, Fewer Is BetterTimed Godot Game Engine Compilation 3.2.3Time To Compile2 x EPYC 77631224364860SE +/- 0.41, N = 351.99
MinAvgMax2 x EPYC 776381.8246.4561.2OpenBenchmarking.orgWatts, Fewer Is BetterTimed Godot Game Engine Compilation 3.2.3CPU Power Consumption Monitor1402804205607001. 2 x EPYC 7763: Approximate power consumption of 14124 Joules per run.

Timed GDB GNU Debugger Compilation

This test times how long it takes to build the GNU Debugger (GDB) in a default configuration. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgSeconds, Fewer Is BetterTimed GDB GNU Debugger Compilation 10.2Time To Compile2 x EPYC 77631020304050SE +/- 0.29, N = 345.67
MinAvgMax2 x EPYC 776381.9192.7573.1OpenBenchmarking.orgWatts, Fewer Is BetterTimed GDB GNU Debugger Compilation 10.2CPU Power Consumption Monitor1402804205607001. 2 x EPYC 7763: Approximate power consumption of 9570 Joules per run.

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 4.4Time To Compile2 x EPYC 776348121620SE +/- 0.04, N = 414.72
MinAvgMax2 x EPYC 776381.6230.8572.7OpenBenchmarking.orgWatts, Fewer Is BetterTimed FFmpeg Compilation 4.4CPU Power Consumption Monitor1402804205607001. 2 x EPYC 7763: Approximate power consumption of 4904 Joules per run.

Timed Apache Compilation

This test times how long it takes to build the Apache HTTPD web server. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgSeconds, Fewer Is BetterTimed Apache Compilation 2.4.41Time To Compile2 x EPYC 7763510152025SE +/- 0.01, N = 320.32
MinAvgMax2 x EPYC 776382.6158.5201.0OpenBenchmarking.orgWatts, Fewer Is BetterTimed Apache Compilation 2.4.41CPU Power Consumption Monitor501001502002501. 2 x EPYC 7763: Approximate power consumption of 4914 Joules per run.

libavif avifenc

This is a test of the AOMedia libavif library testing the encoding of a JPEG image to AV1 Image Format (AVIF). Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgSeconds, Fewer Is Betterlibavif avifenc 0.9.0Encoder Speed: 6, Lossless2 x EPYC 7763714212835SE +/- 0.01, N = 329.281. (CXX) g++ options: -O3 -fPIC -lm
MinAvgMax2 x EPYC 776382.6203.1301.0OpenBenchmarking.orgWatts, Fewer Is Betterlibavif avifenc 0.9.0CPU Power Consumption Monitor801602403204001. 2 x EPYC 7763: Approximate power consumption of 6702 Joules per run.

ebizzy

This is a test of ebizzy, a program to generate workloads resembling web server workloads. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgRecords/s, More Is Betterebizzy 0.32 x EPYC 7763700K1400K2100K2800K3500KSE +/- 33675.96, N = 531131421. (CC) gcc options: -pthread -lpthread -O3 -march=native
OpenBenchmarking.orgRecords/s Per Watt, More Is Betterebizzy 0.32 x EPYC 7763160032004800640080007371.59
MinAvgMax2 x EPYC 776382.1422.3493.4OpenBenchmarking.orgWatts, Fewer Is Betterebizzy 0.3CPU Power Consumption Monitor1302603905206501. 2 x EPYC 7763: Approximate power consumption of 10136 Joules per run.

asmFish

This is a test of asmFish, an advanced chess benchmark written in Assembly. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgNodes/second, More Is BetterasmFish 2018-07-231024 Hash Memory, 26 Depth2 x EPYC 776360M120M180M240M300MSE +/- 2669339.16, N = 7293793395
OpenBenchmarking.orgNodes/second Per Watt, More Is BetterasmFish 2018-07-231024 Hash Memory, 26 Depth2 x EPYC 7763120K240K360K480K600K543167.01
MinAvgMax2 x EPYC 776382.4540.9570.8OpenBenchmarking.orgWatts, Fewer Is BetterasmFish 2018-07-23CPU Power Consumption Monitor1402804205607001. 2 x EPYC 7763: Approximate power consumption of 63748 Joules per run.

Stockfish

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

OpenBenchmarking.orgNodes Per Second, More Is BetterStockfish 13Total Time2 x EPYC 776370M140M210M280M350MSE +/- 623832.94, N = 33122308951. (CXX) g++ options: -lgcov -m64 -lpthread -fno-exceptions -std=c++17 -fprofile-use -fno-peel-loops -fno-tracer -pedantic -O3 -msse -msse3 -mpopcnt -mavx2 -msse4.1 -mssse3 -msse2 -mbmi2 -flto -flto=jobserver
OpenBenchmarking.orgNodes Per Second Per Watt, More Is BetterStockfish 13Total Time2 x EPYC 7763150K300K450K600K750K690302.48
MinAvgMax2 x EPYC 776381.9452.3570.8OpenBenchmarking.orgWatts, Fewer Is BetterStockfish 13CPU Power Consumption Monitor1402804205607001. 2 x EPYC 7763: Approximate power consumption of 11609 Joules per run.

7-Zip Compression

This is a test of 7-Zip using p7zip with its integrated benchmark feature or upstream 7-Zip for the Windows x64 build. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgMIPS, More Is Better7-Zip Compression 16.02Compress Speed Test2 x EPYC 7763110K220K330K440K550KSE +/- 3107.07, N = 154985611. (CXX) g++ options: -pipe -lpthread
OpenBenchmarking.orgMIPS Per Watt, More Is Better7-Zip Compression 16.02Compress Speed Test2 x EPYC 7763300600900120015001494.89
OpenBenchmarking.orgWatts, Fewer Is Better7-Zip Compression 16.02CPU Power Consumption Monitor2 x EPYC 7763100200300400500Min: 81.45 / Avg: 333.51 / Max: 572.671. 2 x EPYC 7763: Approximate power consumption of 28104 Joules per run.

Coremark

This is a test of EEMBC CoreMark processor benchmark. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgIterations/Sec, More Is BetterCoremark 1.0CoreMark Size 666 - Iterations Per Second2 x EPYC 7763700K1400K2100K2800K3500KSE +/- 43082.17, N = 33236345.091. (CC) gcc options: -O2 -lrt" -lrt
OpenBenchmarking.orgIterations/Sec Per Watt, More Is BetterCoremark 1.0CoreMark Size 666 - Iterations Per Second2 x EPYC 77632K4K6K8K10K9537.4
MinAvgMax2 x EPYC 776382.6339.3461.2OpenBenchmarking.orgWatts, Fewer Is BetterCoremark 1.0CPU Power Consumption Monitor1202403604806001. 2 x EPYC 7763: Approximate power consumption of 7918 Joules per run.

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 0.9Benchmark: vklBenchmarkStructuredVolume2 x EPYC 776320M40M60M80M100MSE +/- 857112.13, N = 3109870381MIN: 940807 / MAX: 1183908672
OpenBenchmarking.orgItems / Sec Per Watt, More Is BetterOpenVKL 0.9Benchmark: vklBenchmarkStructuredVolume2 x EPYC 7763140K280K420K560K700K631842.95
MinAvgMax2 x EPYC 776382.6173.9301.1OpenBenchmarking.orgWatts, Fewer Is BetterOpenVKL 0.9CPU Power Consumption Monitor801602403204001. 2 x EPYC 7763: Approximate power consumption of 10665 Joules per run.

OpenBenchmarking.orgItems / Sec, More Is BetterOpenVKL 0.9Benchmark: vklBenchmarkVdbVolume2 x EPYC 77635M10M15M20M25MSE +/- 140542.44, N = 323015684MIN: 826242 / MAX: 134439120
OpenBenchmarking.orgItems / Sec Per Watt, More Is BetterOpenVKL 0.9Benchmark: vklBenchmarkVdbVolume2 x EPYC 776330K60K90K120K150K138628.42
MinAvgMax2 x EPYC 776383.2166.0291.3OpenBenchmarking.orgWatts, Fewer Is BetterOpenVKL 0.9CPU Power Consumption Monitor701402102803501. 2 x EPYC 7763: Approximate power consumption of 12396 Joules per run.

OpenBenchmarking.orgItems / Sec, More Is BetterOpenVKL 0.9Benchmark: vklBenchmark2 x EPYC 7763130260390520650SE +/- 6.72, N = 4603MIN: 1 / MAX: 1751
OpenBenchmarking.orgItems / Sec Per Watt, More Is BetterOpenVKL 0.9Benchmark: vklBenchmark2 x EPYC 77630.57741.15481.73222.30962.8872.566
OpenBenchmarking.orgWatts, Fewer Is BetterOpenVKL 0.9CPU Power Consumption Monitor2 x EPYC 7763100200300400500Min: 82.64 / Avg: 234.97 / Max: 572.931. 2 x EPYC 7763: Approximate power consumption of 98686 Joules per run.

Intel Open Image Denoise

Open Image Denoise is a denoising library for ray-tracing and part of the oneAPI rendering toolkit. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgImages / Sec, More Is BetterIntel Open Image Denoise 1.4.0Run: RTLightmap.hdr.4096x40962 x EPYC 77630.28130.56260.84391.12521.4065SE +/- 0.00, N = 31.25
OpenBenchmarking.orgImages / Sec Per Watt, More Is BetterIntel Open Image Denoise 1.4.0Run: RTLightmap.hdr.4096x40962 x EPYC 77630.00090.00180.00270.00360.00450.004
MinAvgMax2 x EPYC 776382.2317.3507.0OpenBenchmarking.orgWatts, Fewer Is BetterIntel Open Image Denoise 1.4.0CPU Power Consumption Monitor1302603905206501. 2 x EPYC 7763: Approximate power consumption of 9097 Joules per run.

OpenBenchmarking.orgImages / Sec, More Is BetterIntel Open Image Denoise 1.4.0Run: RT.ldr_alb_nrm.3840x21602 x EPYC 77630.57831.15661.73492.31322.8915SE +/- 0.01, N = 42.57
OpenBenchmarking.orgImages / Sec Per Watt, More Is BetterIntel Open Image Denoise 1.4.0Run: RT.ldr_alb_nrm.3840x21602 x EPYC 77630.0020.0040.0060.0080.010.009
MinAvgMax2 x EPYC 776383.4290.9513.1OpenBenchmarking.orgWatts, Fewer Is BetterIntel Open Image Denoise 1.4.0CPU Power Consumption Monitor1302603905206501. 2 x EPYC 7763: Approximate power consumption of 4726 Joules per run.

OpenBenchmarking.orgImages / Sec, More Is BetterIntel Open Image Denoise 1.4.0Run: RT.hdr_alb_nrm.3840x21602 x EPYC 77630.56931.13861.70792.27722.8465SE +/- 0.01, N = 42.53
OpenBenchmarking.orgImages / Sec Per Watt, More Is BetterIntel Open Image Denoise 1.4.0Run: RT.hdr_alb_nrm.3840x21602 x EPYC 77630.0020.0040.0060.0080.010.009
MinAvgMax2 x EPYC 776382.3286.8511.9OpenBenchmarking.orgWatts, Fewer Is BetterIntel Open Image Denoise 1.4.0CPU Power Consumption Monitor1302603905206501. 2 x EPYC 7763: Approximate power consumption of 4588 Joules per run.

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 Rate2 x EPYC 7763918273645SE +/- 0.28, N = 1538.141. (CC) gcc options: -O3 -march=native -fopenmp
OpenBenchmarking.orgGFLOP/s Per Watt, More Is BetterACES DGEMM 1.0Sustained Floating-Point Rate2 x EPYC 77630.02520.05040.07560.10080.1260.112
MinAvgMax2 x EPYC 776382.5341.4573.1OpenBenchmarking.orgWatts, Fewer Is BetterACES DGEMM 1.0CPU Power Consumption Monitor1402804205607001. 2 x EPYC 7763: Approximate power consumption of 3460 Joules per run.

x265

This is a simple test of the x265 encoder run on the CPU with 1080p and 4K options for H.265 video encode performance with x265. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgFrames Per Second, More Is Betterx265 3.4Video Input: Bosphorus 4K2 x EPYC 7763612182430SE +/- 0.21, N = 1524.821. (CXX) g++ options: -O3 -rdynamic -lpthread -lrt -ldl -lnuma
OpenBenchmarking.orgFrames Per Second Per Watt, More Is Betterx265 3.4Video Input: Bosphorus 4K2 x EPYC 77630.02320.04640.06960.09280.1160.103
MinAvgMax2 x EPYC 776382.0240.5308.8OpenBenchmarking.orgWatts, Fewer Is Betterx265 3.4CPU Power Consumption Monitor801602403204001. 2 x EPYC 7763: Approximate power consumption of 6829 Joules per run.

SVT-VP9

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

OpenBenchmarking.orgFrames Per Second, More Is BetterSVT-VP9 0.3Tuning: Visual Quality Optimized - Input: Bosphorus 1080p2 x EPYC 776380160240320400SE +/- 0.89, N = 8352.071. (CC) gcc options: -O3 -fcommon -fPIE -fPIC -fvisibility=hidden -pie -rdynamic -lpthread -lrt -lm
OpenBenchmarking.orgFrames Per Second Per Watt, More Is BetterSVT-VP9 0.3Tuning: Visual Quality Optimized - Input: Bosphorus 1080p2 x EPYC 77630.50671.01341.52012.02682.53352.252
MinAvgMax2 x EPYC 776370.1156.3337.5OpenBenchmarking.orgWatts, Fewer Is BetterSVT-VP9 0.3CPU Power Consumption Monitor801602403204001. 2 x EPYC 7763: Approximate power consumption of 1211 Joules per run.

OpenBenchmarking.orgFrames Per Second, More Is BetterSVT-VP9 0.3Tuning: PSNR/SSIM Optimized - Input: Bosphorus 1080p2 x EPYC 7763100200300400500SE +/- 2.47, N = 9459.911. (CC) gcc options: -O3 -fcommon -fPIE -fPIC -fvisibility=hidden -pie -rdynamic -lpthread -lrt -lm
OpenBenchmarking.orgFrames Per Second Per Watt, More Is BetterSVT-VP9 0.3Tuning: PSNR/SSIM Optimized - Input: Bosphorus 1080p2 x EPYC 77630.67521.35042.02562.70083.3763.001
MinAvgMax2 x EPYC 776381.4153.2345.4OpenBenchmarking.orgWatts, Fewer Is BetterSVT-VP9 0.3CPU Power Consumption Monitor1002003004005001. 2 x EPYC 7763: Approximate power consumption of 1141 Joules per run.

OpenBenchmarking.orgFrames Per Second, More Is BetterSVT-VP9 0.3Tuning: VMAF Optimized - Input: Bosphorus 1080p2 x EPYC 7763100200300400500SE +/- 5.37, N = 15460.251. (CC) gcc options: -O3 -fcommon -fPIE -fPIC -fvisibility=hidden -pie -rdynamic -lpthread -lrt -lm
OpenBenchmarking.orgFrames Per Second Per Watt, More Is BetterSVT-VP9 0.3Tuning: VMAF Optimized - Input: Bosphorus 1080p2 x EPYC 77630.68221.36442.04662.72883.4113.032
MinAvgMax2 x EPYC 776381.6151.8343.0OpenBenchmarking.orgWatts, Fewer Is BetterSVT-VP9 0.3CPU Power Consumption Monitor801602403204001. 2 x EPYC 7763: Approximate power consumption of 1113 Joules per run.

SVT-HEVC

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

OpenBenchmarking.orgFrames Per Second, More Is BetterSVT-HEVC 1.5.0Tuning: 10 - Input: Bosphorus 1080p2 x EPYC 7763130260390520650SE +/- 3.93, N = 11596.091. (CC) gcc options: -fPIE -fPIC -O3 -O2 -pie -rdynamic -lpthread -lrt
OpenBenchmarking.orgFrames Per Second Per Watt, More Is BetterSVT-HEVC 1.5.0Tuning: 10 - Input: Bosphorus 1080p2 x EPYC 77630.96011.92022.88033.84044.80054.267
MinAvgMax2 x EPYC 776381.8139.7339.7OpenBenchmarking.orgWatts, Fewer Is BetterSVT-HEVC 1.5.0CPU Power Consumption Monitor801602403204001. 2 x EPYC 7763: Approximate power consumption of 825 Joules per run.

OpenBenchmarking.orgFrames Per Second, More Is BetterSVT-HEVC 1.5.0Tuning: 7 - Input: Bosphorus 1080p2 x EPYC 776370140210280350SE +/- 2.19, N = 10337.871. (CC) gcc options: -fPIE -fPIC -O3 -O2 -pie -rdynamic -lpthread -lrt
OpenBenchmarking.orgFrames Per Second Per Watt, More Is BetterSVT-HEVC 1.5.0Tuning: 7 - Input: Bosphorus 1080p2 x EPYC 77630.45560.91121.36681.82242.2782.025
MinAvgMax2 x EPYC 776381.4166.9377.6OpenBenchmarking.orgWatts, Fewer Is BetterSVT-HEVC 1.5.0CPU Power Consumption Monitor1002003004005001. 2 x EPYC 7763: Approximate power consumption of 1101 Joules per run.

OpenBenchmarking.orgFrames Per Second, More Is BetterSVT-HEVC 1.5.0Tuning: 1 - Input: Bosphorus 1080p2 x EPYC 77631224364860SE +/- 0.40, N = 1555.171. (CC) gcc options: -fPIE -fPIC -O3 -O2 -pie -rdynamic -lpthread -lrt
OpenBenchmarking.orgFrames Per Second Per Watt, More Is BetterSVT-HEVC 1.5.0Tuning: 1 - Input: Bosphorus 1080p2 x EPYC 77630.03510.07020.10530.14040.17550.156
MinAvgMax2 x EPYC 776382.0352.8534.8OpenBenchmarking.orgWatts, Fewer Is BetterSVT-HEVC 1.5.0CPU Power Consumption Monitor1402804205607001. 2 x EPYC 7763: Approximate power consumption of 5809 Joules per run.

SVT-AV1

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

OpenBenchmarking.orgFrames Per Second, More Is BetterSVT-AV1 0.8.7Encoder Mode: Preset 8 - Input: Bosphorus 4K2 x EPYC 77631428425670SE +/- 0.41, N = 1562.101. (CXX) g++ options: -mno-avx -mavx2 -mavx512f -mavx512bw -mavx512dq -pie
OpenBenchmarking.orgFrames Per Second Per Watt, More Is BetterSVT-AV1 0.8.7Encoder Mode: Preset 8 - Input: Bosphorus 4K2 x EPYC 77630.05540.11080.16620.22160.2770.246
MinAvgMax2 x EPYC 776382.2252.2438.4OpenBenchmarking.orgWatts, Fewer Is BetterSVT-AV1 0.8.7CPU Power Consumption Monitor1102203304405501. 2 x EPYC 7763: Approximate power consumption of 4910 Joules per run.

OpenBenchmarking.orgFrames Per Second, More Is BetterSVT-AV1 0.8.7Encoder Mode: Preset 4 - Input: Bosphorus 4K2 x EPYC 77631.14032.28063.42094.56125.7015SE +/- 0.019, N = 35.0681. (CXX) g++ options: -mno-avx -mavx2 -mavx512f -mavx512bw -mavx512dq -pie
OpenBenchmarking.orgFrames Per Second Per Watt, More Is BetterSVT-AV1 0.8.7Encoder Mode: Preset 4 - Input: Bosphorus 4K2 x EPYC 77630.00430.00860.01290.01720.02150.019
MinAvgMax2 x EPYC 776382.5261.5415.4OpenBenchmarking.orgWatts, Fewer Is BetterSVT-AV1 0.8.7CPU Power Consumption Monitor1102203304405501. 2 x EPYC 7763: Approximate power consumption of 10983 Joules per run.

Kvazaar

This is a test of Kvazaar as a CPU-based H.265 video encoder written in the C programming language and optimized in Assembly. Kvazaar is the winner of the 2016 ACM Open-Source Software Competition and developed at the Ultra Video Group, Tampere University, Finland. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgFrames Per Second, More Is BetterKvazaar 2.0Video Input: Bosphorus 4K - Video Preset: Ultra Fast2 x EPYC 77631326395265SE +/- 0.34, N = 559.081. (CC) gcc options: -pthread -ftree-vectorize -fvisibility=hidden -O2 -lpthread -lm -lrt
OpenBenchmarking.orgFrames Per Second Per Watt, More Is BetterKvazaar 2.0Video Input: Bosphorus 4K - Video Preset: Ultra Fast2 x EPYC 77630.0520.1040.1560.2080.260.231
MinAvgMax2 x EPYC 776382.5255.8341.0OpenBenchmarking.orgWatts, Fewer Is BetterKvazaar 2.0CPU Power Consumption Monitor801602403204001. 2 x EPYC 7763: Approximate power consumption of 3632 Joules per run.

OpenBenchmarking.orgFrames Per Second, More Is BetterKvazaar 2.0Video Input: Bosphorus 4K - Video Preset: Very Fast2 x EPYC 77631224364860SE +/- 0.43, N = 555.431. (CC) gcc options: -pthread -ftree-vectorize -fvisibility=hidden -O2 -lpthread -lm -lrt
OpenBenchmarking.orgFrames Per Second Per Watt, More Is BetterKvazaar 2.0Video Input: Bosphorus 4K - Video Preset: Very Fast2 x EPYC 77630.04010.08020.12030.16040.20050.178
MinAvgMax2 x EPYC 776382.7310.8465.7OpenBenchmarking.orgWatts, Fewer Is BetterKvazaar 2.0CPU Power Consumption Monitor1202403604806001. 2 x EPYC 7763: Approximate power consumption of 4537 Joules per run.

Embree

Intel Embree is a collection of high-performance ray-tracing kernels for execution on CPUs 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 3.13Binary: Pathtracer ISPC - Model: Asian Dragon Obj2 x EPYC 77631326395265SE +/- 0.40, N = 1558.94MIN: 53.57 / MAX: 65.84
OpenBenchmarking.orgFrames Per Second Per Watt, More Is BetterEmbree 3.13Binary: Pathtracer ISPC - Model: Asian Dragon Obj2 x EPYC 77630.04680.09360.14040.18720.2340.208
MinAvgMax2 x EPYC 776382.7283.5515.2OpenBenchmarking.orgWatts, Fewer Is BetterEmbree 3.13CPU Power Consumption Monitor1302603905206501. 2 x EPYC 7763: Approximate power consumption of 7541 Joules per run.

OpenBenchmarking.orgFrames Per Second, More Is BetterEmbree 3.13Binary: Pathtracer ISPC - Model: Asian Dragon2 x EPYC 77631530456075SE +/- 0.62, N = 1567.61MIN: 60.91 / MAX: 74.47
OpenBenchmarking.orgFrames Per Second Per Watt, More Is BetterEmbree 3.13Binary: Pathtracer ISPC - Model: Asian Dragon2 x EPYC 77630.04070.08140.12210.16280.20350.181
MinAvgMax2 x EPYC 776382.6374.3519.7OpenBenchmarking.orgWatts, Fewer Is BetterEmbree 3.13CPU Power Consumption Monitor1302603905206501. 2 x EPYC 7763: Approximate power consumption of 5265 Joules per run.

OpenBenchmarking.orgFrames Per Second, More Is BetterEmbree 3.13Binary: Pathtracer - Model: Asian Dragon Obj2 x EPYC 77631326395265SE +/- 0.14, N = 359.53MIN: 56.12 / MAX: 66.22
OpenBenchmarking.orgFrames Per Second Per Watt, More Is BetterEmbree 3.13Binary: Pathtracer - Model: Asian Dragon Obj2 x EPYC 77630.04880.09760.14640.19520.2440.217
MinAvgMax2 x EPYC 776382.5274.1487.3OpenBenchmarking.orgWatts, Fewer Is BetterEmbree 3.13CPU Power Consumption Monitor1302603905206501. 2 x EPYC 7763: Approximate power consumption of 7310 Joules per run.

OpenBenchmarking.orgFrames Per Second, More Is BetterEmbree 3.13Binary: Pathtracer - Model: Asian Dragon2 x EPYC 77631632486480SE +/- 0.50, N = 1571.54MIN: 64.78 / MAX: 78.4
OpenBenchmarking.orgFrames Per Second Per Watt, More Is BetterEmbree 3.13Binary: Pathtracer - Model: Asian Dragon2 x EPYC 77630.04430.08860.13290.17720.22150.197
MinAvgMax2 x EPYC 776382.8362.5503.4OpenBenchmarking.orgWatts, Fewer Is BetterEmbree 3.13CPU Power Consumption Monitor1302603905206501. 2 x EPYC 7763: Approximate power consumption of 4906 Joules per run.

OpenBenchmarking.orgFrames Per Second, More Is BetterEmbree 3.13Binary: Pathtracer ISPC - Model: Crown2 x EPYC 776320406080100SE +/- 0.10, N = 6100.66MIN: 92.79 / MAX: 113.68
OpenBenchmarking.orgFrames Per Second Per Watt, More Is BetterEmbree 3.13Binary: Pathtracer ISPC - Model: Crown2 x EPYC 77630.06080.12160.18240.24320.3040.27
MinAvgMax2 x EPYC 776382.4373.0569.7OpenBenchmarking.orgWatts, Fewer Is BetterEmbree 3.13CPU Power Consumption Monitor1402804205607001. 2 x EPYC 7763: Approximate power consumption of 4041 Joules per run.

OpenBenchmarking.orgFrames Per Second, More Is BetterEmbree 3.13Binary: Pathtracer - Model: Crown2 x EPYC 776320406080100SE +/- 0.11, N = 6110.70MIN: 99.55 / MAX: 124.02
OpenBenchmarking.orgFrames Per Second Per Watt, More Is BetterEmbree 3.13Binary: Pathtracer - Model: Crown2 x EPYC 77630.06820.13640.20460.27280.3410.303
MinAvgMax2 x EPYC 776382.6365.5571.4OpenBenchmarking.orgWatts, Fewer Is BetterEmbree 3.13CPU Power Consumption Monitor1402804205607001. 2 x EPYC 7763: Approximate power consumption of 3777 Joules per run.

dav1d

Dav1d is an open-source, speedy AV1 video decoder. This test profile times how long it takes to decode sample AV1 video content. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgFPS, More Is Betterdav1d 0.9.0Video Input: Chimera 1080p 10-bit2 x EPYC 77632004006008001000SE +/- 1.69, N = 31143.60MIN: 481.57 / MAX: 1388.521. (CC) gcc options: -pthread -lm
OpenBenchmarking.orgFPS Per Watt, More Is Betterdav1d 0.9.0Video Input: Chimera 1080p 10-bit2 x EPYC 77632468107.593
OpenBenchmarking.orgWatts, Fewer Is Betterdav1d 0.9.0CPU Power Consumption Monitor2 x EPYC 776360120180240300Min: 73.86 / Avg: 150.62 / Max: 346.931. 2 x EPYC 7763: Approximate power consumption of 62005 Joules per run.

OpenBenchmarking.orgFPS, More Is Betterdav1d 0.9.0Video Input: Summer Nature 4K2 x EPYC 7763130260390520650SE +/- 6.89, N = 3592.79MIN: 129.05 / MAX: 711.811. (CC) gcc options: -pthread -lm
OpenBenchmarking.orgFPS Per Watt, More Is Betterdav1d 0.9.0Video Input: Summer Nature 4K2 x EPYC 77630.73641.47282.20922.94563.6823.273
MinAvgMax2 x EPYC 776382.5181.1455.2OpenBenchmarking.orgWatts, Fewer Is Betterdav1d 0.9.0CPU Power Consumption Monitor1202403604806001. 2 x EPYC 7763: Approximate power consumption of 5555 Joules per run.

GraphicsMagick

This is a test of GraphicsMagick with its OpenMP implementation that performs various imaging tests on a sample 6000x4000 pixel JPEG image. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgIterations Per Minute, More Is BetterGraphicsMagick 1.3.33Operation: HWB Color Space2 x EPYC 7763140280420560700SE +/- 4.51, N = 36531. (CC) gcc options: -fopenmp -O2 -pthread -ljbig -lwebp -lwebpmux -ltiff -lfreetype -ljpeg -lXext -lSM -lICE -lX11 -llzma -lbz2 -lxml2 -lz -lm -lpthread
OpenBenchmarking.orgIterations Per Minute Per Watt, More Is BetterGraphicsMagick 1.3.33Operation: HWB Color Space2 x EPYC 77630.65091.30181.95272.60363.25452.893
MinAvgMax2 x EPYC 776382.4225.7240.1OpenBenchmarking.orgWatts, Fewer Is BetterGraphicsMagick 1.3.33CPU Power Consumption Monitor601201802403001. 2 x EPYC 7763: Approximate power consumption of 14371 Joules per run.

OpenBenchmarking.orgIterations Per Minute, More Is BetterGraphicsMagick 1.3.33Operation: Noise-Gaussian2 x EPYC 7763130260390520650SE +/- 1.53, N = 35821. (CC) gcc options: -fopenmp -O2 -pthread -ljbig -lwebp -lwebpmux -ltiff -lfreetype -ljpeg -lXext -lSM -lICE -lX11 -llzma -lbz2 -lxml2 -lz -lm -lpthread
OpenBenchmarking.orgIterations Per Minute Per Watt, More Is BetterGraphicsMagick 1.3.33Operation: Noise-Gaussian2 x EPYC 77630.49460.98921.48381.97842.4732.198
MinAvgMax2 x EPYC 776383.0264.7290.8OpenBenchmarking.orgWatts, Fewer Is BetterGraphicsMagick 1.3.33CPU Power Consumption Monitor701402102803501. 2 x EPYC 7763: Approximate power consumption of 17031 Joules per run.

OpenBenchmarking.orgIterations Per Minute, More Is BetterGraphicsMagick 1.3.33Operation: Enhanced2 x EPYC 776330060090012001500SE +/- 4.26, N = 314681. (CC) gcc options: -fopenmp -O2 -pthread -ljbig -lwebp -lwebpmux -ltiff -lfreetype -ljpeg -lXext -lSM -lICE -lX11 -llzma -lbz2 -lxml2 -lz -lm -lpthread
OpenBenchmarking.orgIterations Per Minute Per Watt, More Is BetterGraphicsMagick 1.3.33Operation: Enhanced2 x EPYC 77630.74521.49042.23562.98083.7263.312
MinAvgMax2 x EPYC 776381.6443.2476.5OpenBenchmarking.orgWatts, Fewer Is BetterGraphicsMagick 1.3.33CPU Power Consumption Monitor1202403604806001. 2 x EPYC 7763: Approximate power consumption of 28069 Joules per run.

OpenBenchmarking.orgIterations Per Minute, More Is BetterGraphicsMagick 1.3.33Operation: Sharpen2 x EPYC 77632004006008001000SE +/- 0.88, N = 38841. (CC) gcc options: -fopenmp -O2 -pthread -ljbig -lwebp -lwebpmux -ltiff -lfreetype -ljpeg -lXext -lSM -lICE -lX11 -llzma -lbz2 -lxml2 -lz -lm -lpthread
OpenBenchmarking.orgIterations Per Minute Per Watt, More Is BetterGraphicsMagick 1.3.33Operation: Sharpen2 x EPYC 77630.43560.87121.30681.74242.1781.936
MinAvgMax2 x EPYC 776382.4456.6493.4OpenBenchmarking.orgWatts, Fewer Is BetterGraphicsMagick 1.3.33CPU Power Consumption Monitor1302603905206501. 2 x EPYC 7763: Approximate power consumption of 29222 Joules per run.

OpenBenchmarking.orgIterations Per Minute, More Is BetterGraphicsMagick 1.3.33Operation: Rotate2 x EPYC 7763120240360480600SE +/- 0.88, N = 35691. (CC) gcc options: -fopenmp -O2 -pthread -ljbig -lwebp -lwebpmux -ltiff -lfreetype -ljpeg -lXext -lSM -lICE -lX11 -llzma -lbz2 -lxml2 -lz -lm -lpthread
OpenBenchmarking.orgIterations Per Minute Per Watt, More Is BetterGraphicsMagick 1.3.33Operation: Rotate2 x EPYC 77630.73491.46982.20472.93963.67453.266
MinAvgMax2 x EPYC 776382.1174.2181.2OpenBenchmarking.orgWatts, Fewer Is BetterGraphicsMagick 1.3.33CPU Power Consumption Monitor501001502002501. 2 x EPYC 7763: Approximate power consumption of 11090 Joules per run.

OpenBenchmarking.orgIterations Per Minute, More Is BetterGraphicsMagick 1.3.33Operation: Swirl2 x EPYC 77635001000150020002500SE +/- 14.11, N = 323061. (CC) gcc options: -fopenmp -O2 -pthread -ljbig -lwebp -lwebpmux -ltiff -lfreetype -ljpeg -lXext -lSM -lICE -lX11 -llzma -lbz2 -lxml2 -lz -lm -lpthread
OpenBenchmarking.orgIterations Per Minute Per Watt, More Is BetterGraphicsMagick 1.3.33Operation: Swirl2 x EPYC 77632468106.064
MinAvgMax2 x EPYC 776381.8380.3408.3OpenBenchmarking.orgWatts, Fewer Is BetterGraphicsMagick 1.3.33CPU Power Consumption Monitor1102203304405501. 2 x EPYC 7763: Approximate power consumption of 24339 Joules per run.

LuxCoreRender

LuxCoreRender is an open-source 3D physically based renderer formerly known as LuxRender. LuxCoreRender supports CPU-based rendering as well as GPU acceleration via OpenCL, NVIDIA CUDA, and NVIDIA OptiX interfaces. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgM samples/sec, More Is BetterLuxCoreRender 2.5Scene: LuxCore Benchmark - Acceleration: CPU2 x EPYC 7763246810SE +/- 0.11, N = 158.65MIN: 2.95 / MAX: 11.34
OpenBenchmarking.orgM samples/sec Per Watt, More Is BetterLuxCoreRender 2.5Scene: LuxCore Benchmark - Acceleration: CPU2 x EPYC 77630.00430.00860.01290.01720.02150.019
MinAvgMax2 x EPYC 776381.8447.0543.0OpenBenchmarking.orgWatts, Fewer Is BetterLuxCoreRender 2.5CPU Power Consumption Monitor1402804205607001. 2 x EPYC 7763: Approximate power consumption of 29739 Joules per run.

OpenBenchmarking.orgM samples/sec, More Is BetterLuxCoreRender 2.5Scene: Orange Juice - Acceleration: CPU2 x EPYC 7763510152025SE +/- 0.28, N = 1521.66MIN: 17.86 / MAX: 29.24
OpenBenchmarking.orgM samples/sec Per Watt, More Is BetterLuxCoreRender 2.5Scene: Orange Juice - Acceleration: CPU2 x EPYC 77630.00970.01940.02910.03880.04850.043
MinAvgMax2 x EPYC 776381.7508.3572.8OpenBenchmarking.orgWatts, Fewer Is BetterLuxCoreRender 2.5CPU Power Consumption Monitor1402804205607001. 2 x EPYC 7763: Approximate power consumption of 34327 Joules per run.

OpenBenchmarking.orgM samples/sec, More Is BetterLuxCoreRender 2.5Scene: Danish Mood - Acceleration: CPU2 x EPYC 7763246810SE +/- 0.13, N = 158.78MIN: 3.1 / MAX: 11.67
OpenBenchmarking.orgM samples/sec Per Watt, More Is BetterLuxCoreRender 2.5Scene: Danish Mood - Acceleration: CPU2 x EPYC 77630.00430.00860.01290.01720.02150.019
MinAvgMax2 x EPYC 776381.9465.1554.8OpenBenchmarking.orgWatts, Fewer Is BetterLuxCoreRender 2.5CPU Power Consumption Monitor1402804205607001. 2 x EPYC 7763: Approximate power consumption of 31160 Joules per run.

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 1.9.0-jumbo-1Test: MD52 x EPYC 77632M4M6M8M10MSE +/- 109447.60, N = 3107633331. (CC) gcc options: -m64 -lssl -lcrypto -fopenmp -lgmp -pthread -lm -lz -ldl -lcrypt -lbz2
OpenBenchmarking.orgReal C/S Per Watt, More Is BetterJohn The Ripper 1.9.0-jumbo-1Test: MD52 x EPYC 77635K10K15K20K25K22207.25
MinAvgMax2 x EPYC 776381.7484.7545.0OpenBenchmarking.orgWatts, Fewer Is BetterJohn The Ripper 1.9.0-jumbo-1CPU Power Consumption Monitor1402804205607001. 2 x EPYC 7763: Approximate power consumption of 31019 Joules per run.

OpenBenchmarking.orgReal C/S, More Is BetterJohn The Ripper 1.9.0-jumbo-1Test: Blowfish2 x EPYC 776340K80K120K160K200KSE +/- 2546.43, N = 31832341. (CC) gcc options: -m64 -lssl -lcrypto -fopenmp -lgmp -pthread -lm -lz -ldl -lcrypt -lbz2
OpenBenchmarking.orgReal C/S Per Watt, More Is BetterJohn The Ripper 1.9.0-jumbo-1Test: Blowfish2 x EPYC 776380160240320400379.49
MinAvgMax2 x EPYC 776381.9482.8554.4OpenBenchmarking.orgWatts, Fewer Is BetterJohn The Ripper 1.9.0-jumbo-1CPU Power Consumption Monitor1402804205607001. 2 x EPYC 7763: Approximate power consumption of 16256 Joules per run.

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 6.12.1Variant: Wownero - Hash Count: 1M2 x EPYC 776310K20K30K40K50KSE +/- 160.51, N = 348176.01. (CXX) g++ options: -fexceptions -fno-rtti -maes -O3 -Ofast -static-libgcc -static-libstdc++ -rdynamic -lssl -lcrypto -luv -lpthread -lrt -ldl -lhwloc
OpenBenchmarking.orgH/s Per Watt, More Is BetterXmrig 6.12.1Variant: Wownero - Hash Count: 1M2 x EPYC 776320406080100108.21
MinAvgMax2 x EPYC 776382.0445.2541.0OpenBenchmarking.orgWatts, Fewer Is BetterXmrig 6.12.1CPU Power Consumption Monitor1402804205607001. 2 x EPYC 7763: Approximate power consumption of 12021 Joules per run.

OpenBenchmarking.orgH/s, More Is BetterXmrig 6.12.1Variant: Monero - Hash Count: 1M2 x EPYC 776312K24K36K48K60KSE +/- 101.74, N = 356612.71. (CXX) g++ options: -fexceptions -fno-rtti -maes -O3 -Ofast -static-libgcc -static-libstdc++ -rdynamic -lssl -lcrypto -luv -lpthread -lrt -ldl -lhwloc
OpenBenchmarking.orgH/s Per Watt, More Is BetterXmrig 6.12.1Variant: Monero - Hash Count: 1M2 x EPYC 7763306090120150124.54
MinAvgMax2 x EPYC 776382.3454.6568.3OpenBenchmarking.orgWatts, Fewer Is BetterXmrig 6.12.1CPU Power Consumption Monitor1402804205607001. 2 x EPYC 7763: Approximate power consumption of 10910 Joules per run.

LULESH

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

OpenBenchmarking.orgz/s, More Is BetterLULESH 2.0.32 x EPYC 77638K16K24K32K40KSE +/- 316.92, N = 336927.241. (CXX) g++ options: -O3 -fopenmp -lm -pthread -lmpi_cxx -lmpi
OpenBenchmarking.orgz/s Per Watt, More Is BetterLULESH 2.0.32 x EPYC 776320406080100103.14
MinAvgMax2 x EPYC 776382.4358.0529.1OpenBenchmarking.orgWatts, Fewer Is BetterLULESH 2.0.3CPU Power Consumption Monitor1302603905206501. 2 x EPYC 7763: Approximate power consumption of 11099 Joules per run.

LAMMPS Molecular Dynamics Simulator

LAMMPS is a classical molecular dynamics code, and an acronym for Large-scale Atomic/Molecular Massively Parallel Simulator. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgns/day, More Is BetterLAMMPS Molecular Dynamics Simulator 29Oct2020Model: Rhodopsin Protein2 x EPYC 7763714212835SE +/- 0.38, N = 1531.331. (CXX) g++ options: -O3 -pthread -lm
OpenBenchmarking.orgns/day Per Watt, More Is BetterLAMMPS Molecular Dynamics Simulator 29Oct2020Model: Rhodopsin Protein2 x EPYC 77630.03330.06660.09990.13320.16650.148
MinAvgMax2 x EPYC 776381.8211.3443.5OpenBenchmarking.orgWatts, Fewer Is BetterLAMMPS Molecular Dynamics Simulator 29Oct2020CPU Power Consumption Monitor1202403604806001. 2 x EPYC 7763: Approximate power consumption of 1817 Joules per run.

OpenBenchmarking.orgns/day, More Is BetterLAMMPS Molecular Dynamics Simulator 29Oct2020Model: 20k Atoms2 x EPYC 7763816243240SE +/- 0.03, N = 335.081. (CXX) g++ options: -O3 -pthread -lm
OpenBenchmarking.orgns/day Per Watt, More Is BetterLAMMPS Molecular Dynamics Simulator 29Oct2020Model: 20k Atoms2 x EPYC 77630.01620.03240.04860.06480.0810.072
MinAvgMax2 x EPYC 776382.7485.8505.0OpenBenchmarking.orgWatts, Fewer Is BetterLAMMPS Molecular Dynamics Simulator 29Oct2020CPU Power Consumption Monitor1302603905206501. 2 x EPYC 7763: Approximate power consumption of 122573 Joules per run.

Quantum ESPRESSO

Quantum ESPRESSO is an integrated suite of Open-Source computer codes for electronic-structure calculations and materials modeling at the nanoscale. It is based on density-functional theory, plane waves, and pseudopotentials. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgSeconds, Fewer Is BetterQuantum ESPRESSO 6.7Input: AUSURF1122 x EPYC 77632004006008001000SE +/- 6.05, N = 3973.021. (F9X) gfortran options: -lopenblas -lFoX_dom -lFoX_sax -lFoX_wxml -lFoX_common -lFoX_utils -lFoX_fsys -lfftw3 -pthread -lmpi_usempif08 -lmpi_mpifh -lmpi -lopen-rte -lopen-pal -lhwloc -ldl -levent_core -levent_pthreads -lutil -lm -lrt -lz
OpenBenchmarking.orgWatts, Fewer Is BetterQuantum ESPRESSO 6.7CPU Power Consumption Monitor2 x EPYC 7763100200300400500Min: 82.2 / Avg: 321.72 / Max: 538.011. 2 x EPYC 7763: Approximate power consumption of 312925 Joules per run.

OpenFOAM

OpenFOAM is the leading free, open source software for computational fluid dynamics (CFD). Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgSeconds, Fewer Is BetterOpenFOAM 8Input: Motorbike 60M2 x EPYC 776320406080100SE +/- 0.25, N = 390.141. (CXX) g++ options: -std=c++11 -m64 -O3 -ftemplate-depth-100 -fPIC -fuse-ld=bfd -Xlinker --add-needed --no-as-needed -ldynamicMesh -ldecompose -lgenericPatchFields -lmetisDecomp -lscotchDecomp -llagrangian -lregionModels -lOpenFOAM -ldl -lm
MinAvgMax2 x EPYC 776381.6324.4465.3OpenBenchmarking.orgWatts, Fewer Is BetterOpenFOAM 8CPU Power Consumption Monitor1202403604806001. 2 x EPYC 7763: Approximate power consumption of 53414 Joules per run.

OpenBenchmarking.orgSeconds, Fewer Is BetterOpenFOAM 8Input: Motorbike 30M2 x EPYC 776348121620SE +/- 0.10, N = 314.901. (CXX) g++ options: -std=c++11 -m64 -O3 -ftemplate-depth-100 -fPIC -fuse-ld=bfd -Xlinker --add-needed --no-as-needed -ldynamicMesh -ldecompose -lgenericPatchFields -lmetisDecomp -lscotchDecomp -llagrangian -lregionModels -lOpenFOAM -ldl -lm
MinAvgMax2 x EPYC 776382.0316.0525.7OpenBenchmarking.orgWatts, Fewer Is BetterOpenFOAM 8CPU Power Consumption Monitor1302603905206501. 2 x EPYC 7763: Approximate power consumption of 11272 Joules per run.

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 Direction2 x EPYC 77633691215SE +/- 0.02, N = 411.091. (F9X) gfortran options: -cpp -O2 -funroll-loops -floop-optimize -fcray-pointer -fbacktrace -pthread -lmpi_usempif08 -lmpi_mpifh -lmpi -lopen-rte -lopen-pal -lhwloc -ldl -levent_core -levent_pthreads -lutil -lm -lrt -lz
MinAvgMax2 x EPYC 776383.1346.6466.9OpenBenchmarking.orgWatts, Fewer Is BetterXcompact3d Incompact3d 2021-03-11CPU Power Consumption Monitor1202403604806001. 2 x EPYC 7763: Approximate power consumption of 6586 Joules per run.

OpenBenchmarking.orgSeconds, Fewer Is BetterXcompact3d Incompact3d 2021-03-11Input: X3D-benchmarking input.i3d2 x EPYC 776360120180240300SE +/- 0.12, N = 3297.671. (F9X) gfortran options: -cpp -O2 -funroll-loops -floop-optimize -fcray-pointer -fbacktrace -pthread -lmpi_usempif08 -lmpi_mpifh -lmpi -lopen-rte -lopen-pal -lhwloc -ldl -levent_core -levent_pthreads -lutil -lm -lrt -lz
MinAvgMax2 x EPYC 776382.4455.7495.3OpenBenchmarking.orgWatts, Fewer Is BetterXcompact3d Incompact3d 2021-03-11CPU Power Consumption Monitor1302603905206501. 2 x EPYC 7763: Approximate power consumption of 138823 Joules per run.

NWChem

NWChem is an open-source high performance computational chemistry package. Per NWChem's documentation, "NWChem aims to provide its users with computational chemistry tools that are scalable both in their ability to treat large scientific computational chemistry problems efficiently, and in their use of available parallel computing resources from high-performance parallel supercomputers to conventional workstation clusters." Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgSeconds, Fewer Is BetterNWChem 7.0.2Input: C240 Buckyball2 x EPYC 77634008001200160020001837.91. (F9X) gfortran options: -lnwctask -lccsd -lmcscf -lselci -lmp2 -lmoints -lstepper -ldriver -loptim -lnwdft -lgradients -lcphf -lesp -lddscf -ldangchang -lguess -lhessian -lvib -lnwcutil -lrimp2 -lproperty -lsolvation -lnwints -lprepar -lnwmd -lnwpw -lofpw -lpaw -lpspw -lband -lnwpwlib -lcafe -lspace -lanalyze -lqhop -lpfft -ldplot -ldrdy -lvscf -lqmmm -lqmd -letrans -ltce -lbq -lmm -lcons -lperfm -ldntmc -lccca -ldimqm -lga -larmci -lpeigs -l64to32 -lopenblas -lpthread -lrt -llapack -lnwcblas -lmpi_usempif08 -lmpi_mpifh -lmpi -lopen-rte -lopen-pal -lhwloc -ldl -levent_core -levent_pthreads -lutil -lm -lz -lcomex -m64 -ffast-math -std=legacy -fdefault-integer-8 -finline-functions -O2
OpenBenchmarking.orgWatts, Fewer Is BetterNWChem 7.0.2CPU Power Consumption Monitor2 x EPYC 7763100200300400500Min: 83.05 / Avg: 453.84 / Max: 553.99

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: sedovbig2 x EPYC 77631.17822.35643.53464.71285.891SE +/- 0.035443, N = 55.2365541. (CXX) g++ options: -fopenmp -pthread -lmpi_cxx -lmpi
MinAvgMax2 x EPYC 776382.5310.2513.6OpenBenchmarking.orgWatts, Fewer Is BetterPennant 1.0.1CPU Power Consumption Monitor1302603905206501. 2 x EPYC 7763: Approximate power consumption of 3971 Joules per run.

Algebraic Multi-Grid Benchmark

AMG is a parallel algebraic multigrid solver for linear systems arising from problems on unstructured grids. The driver provided with AMG builds linear systems for various 3-dimensional problems. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgFigure Of Merit, More Is BetterAlgebraic Multi-Grid Benchmark 1.22 x EPYC 7763400M800M1200M1600M2000MSE +/- 1375840.15, N = 319254586671. (CC) gcc options: -lparcsr_ls -lparcsr_mv -lseq_mv -lIJ_mv -lkrylov -lHYPRE_utilities -lm -fopenmp -pthread -lmpi
OpenBenchmarking.orgFigure Of Merit Per Watt, More Is BetterAlgebraic Multi-Grid Benchmark 1.22 x EPYC 77631.1M2.2M3.3M4.4M5.5M5036688.65
MinAvgMax2 x EPYC 776382.6382.3488.8OpenBenchmarking.orgWatts, Fewer Is BetterAlgebraic Multi-Grid Benchmark 1.2CPU Power Consumption Monitor1302603905206501. 2 x EPYC 7763: Approximate power consumption of 17330 Joules per run.

toyBrot Fractal Generator

ToyBrot is a Mandelbrot fractal generator supporting C++ threads/tasks, OpenMP, Intel Threaded Building Blocks (TBB), and other targets. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgms, Fewer Is BettertoyBrot Fractal Generator 2020-11-18Implementation: C++ Threads2 x EPYC 77638001600240032004000SE +/- 17.86, N = 936791. (CXX) g++ options: -O3 -lpthread -lm -lgcc -lgcc_s -lc
MinAvgMax2 x EPYC 776382.9295.5562.8OpenBenchmarking.orgWatts, Fewer Is BettertoyBrot Fractal Generator 2020-11-18CPU Power Consumption Monitor1402804205607001. 2 x EPYC 7763: Approximate power consumption of 2266 Joules per run.

OpenBenchmarking.orgms, Fewer Is BettertoyBrot Fractal Generator 2020-11-18Implementation: C++ Tasks2 x EPYC 77638001600240032004000SE +/- 19.33, N = 838671. (CXX) g++ options: -O3 -lpthread -lm -lgcc -lgcc_s -lc
MinAvgMax2 x EPYC 776381.5293.2564.1OpenBenchmarking.orgWatts, Fewer Is BettertoyBrot Fractal Generator 2020-11-18CPU Power Consumption Monitor1402804205607001. 2 x EPYC 7763: Approximate power consumption of 2309 Joules per run.

OpenBenchmarking.orgms, Fewer Is BettertoyBrot Fractal Generator 2020-11-18Implementation: OpenMP2 x EPYC 77639001800270036004500SE +/- 37.08, N = 1543271. (CXX) g++ options: -O3 -lpthread -lm -lgcc -lgcc_s -lc
MinAvgMax2 x EPYC 776382.3293.6568.7OpenBenchmarking.orgWatts, Fewer Is BettertoyBrot Fractal Generator 2020-11-18CPU Power Consumption Monitor1402804205607001. 2 x EPYC 7763: Approximate power consumption of 2447 Joules per run.

OpenBenchmarking.orgms, Fewer Is BettertoyBrot Fractal Generator 2020-11-18Implementation: TBB2 x EPYC 77637001400210028003500SE +/- 28.86, N = 934931. (CXX) g++ options: -O3 -lpthread -lm -lgcc -lgcc_s -lc
MinAvgMax2 x EPYC 776381.8296.6565.7OpenBenchmarking.orgWatts, Fewer Is BettertoyBrot Fractal Generator 2020-11-18CPU Power Consumption Monitor1402804205607001. 2 x EPYC 7763: Approximate power consumption of 2241 Joules per run.

NAMD

NAMD is a parallel molecular dynamics code designed for high-performance simulation of large biomolecular systems. NAMD was developed by the Theoretical and Computational Biophysics Group in the Beckman Institute for Advanced Science and Technology at the University of Illinois at Urbana-Champaign. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgdays/ns, Fewer Is BetterNAMD 2.14ATPase Simulation - 327,506 Atoms2 x EPYC 77630.05050.1010.15150.2020.2525SE +/- 0.00164, N = 40.22456
MinAvgMax2 x EPYC 776382.0438.4560.9OpenBenchmarking.orgWatts, Fewer Is BetterNAMD 2.14CPU Power Consumption Monitor1402804205607001. 2 x EPYC 7763: Approximate power consumption of 8657 Joules per run.

Rodinia

Rodinia is a suite focused upon accelerating compute-intensive applications with accelerators. CUDA, OpenMP, and OpenCL parallel models are supported by the included applications. This profile utilizes select OpenCL, NVIDIA CUDA and OpenMP test binaries at the moment. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgSeconds, Fewer Is BetterRodinia 3.1Test: OpenMP Streamcluster2 x EPYC 7763246810SE +/- 0.116, N = 157.4891. (CXX) g++ options: -O2 -lOpenCL
MinAvgMax2 x EPYC 776381.8219.6335.5OpenBenchmarking.orgWatts, Fewer Is BetterRodinia 3.1CPU Power Consumption Monitor801602403204001. 2 x EPYC 7763: Approximate power consumption of 2519 Joules per run.

OpenBenchmarking.orgSeconds, Fewer Is BetterRodinia 3.1Test: OpenMP CFD Solver2 x EPYC 7763246810SE +/- 0.018, N = 76.1881. (CXX) g++ options: -O2 -lOpenCL
MinAvgMax2 x EPYC 776382.1241.5412.8OpenBenchmarking.orgWatts, Fewer Is BetterRodinia 3.1CPU Power Consumption Monitor1102203304405501. 2 x EPYC 7763: Approximate power consumption of 2484 Joules per run.

OpenBenchmarking.orgSeconds, Fewer Is BetterRodinia 3.1Test: OpenMP Leukocyte2 x EPYC 77631224364860SE +/- 0.40, N = 351.621. (CXX) g++ options: -O2 -lOpenCL
MinAvgMax2 x EPYC 776381.9254.2283.5OpenBenchmarking.orgWatts, Fewer Is BetterRodinia 3.1CPU Power Consumption Monitor701402102803501. 2 x EPYC 7763: Approximate power consumption of 14151 Joules per run.

OpenBenchmarking.orgSeconds, Fewer Is BetterRodinia 3.1Test: OpenMP LavaMD2 x EPYC 7763612182430SE +/- 0.13, N = 323.661. (CXX) g++ options: -O2 -lOpenCL
MinAvgMax2 x EPYC 776381.2395.2538.1OpenBenchmarking.orgWatts, Fewer Is BetterRodinia 3.1CPU Power Consumption Monitor1402804205607001. 2 x EPYC 7763: Approximate power consumption of 10801 Joules per run.

miniFE

MiniFE Finite Element is an application for unstructured implicit finite element codes. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgCG Mflops, More Is BetterminiFE 2.2Problem Size: Small2 x EPYC 77636K12K18K24K30KSE +/- 245.68, N = 426535.11. (CXX) g++ options: -O3 -fopenmp -pthread -lmpi_cxx -lmpi
OpenBenchmarking.orgCG Mflops Per Watt, More Is BetterminiFE 2.2Problem Size: Small2 x EPYC 77632040608010098.00
MinAvgMax2 x EPYC 776382.5270.8422.0OpenBenchmarking.orgWatts, Fewer Is BetterminiFE 2.2CPU Power Consumption Monitor1102203304405501. 2 x EPYC 7763: Approximate power consumption of 5077 Joules per run.

NAS Parallel Benchmarks

NPB, NAS Parallel Benchmarks, is a benchmark developed by NASA for high-end computer systems. This test profile currently uses the MPI version of NPB. This test profile offers selecting the different NPB tests/problems and varying problem sizes. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgTotal Mop/s, More Is BetterNAS Parallel Benchmarks 3.4Test / Class: SP.C2 x EPYC 776320K40K60K80K100KSE +/- 481.83, N = 4116234.761. (F9X) gfortran options: -O3 -march=native -pthread -lmpi_usempif08 -lmpi_mpifh -lmpi -lopen-rte -lopen-pal -lhwloc -ldl -levent_core -levent_pthreads -lutil -lm -lrt -lz 2. Open MPI 4.1.0
OpenBenchmarking.orgTotal Mop/s Per Watt, More Is BetterNAS Parallel Benchmarks 3.4Test / Class: SP.C2 x EPYC 776370140210280350306.24
MinAvgMax2 x EPYC 776381.8379.6503.4OpenBenchmarking.orgWatts, Fewer Is BetterNAS Parallel Benchmarks 3.4CPU Power Consumption Monitor1302603905206501. 2 x EPYC 7763: Approximate power consumption of 7591 Joules per run.

OpenBenchmarking.orgTotal Mop/s, More Is BetterNAS Parallel Benchmarks 3.4Test / Class: SP.B2 x EPYC 776330K60K90K120K150KSE +/- 1012.24, N = 7149338.711. (F9X) gfortran options: -O3 -march=native -pthread -lmpi_usempif08 -lmpi_mpifh -lmpi -lopen-rte -lopen-pal -lhwloc -ldl -levent_core -levent_pthreads -lutil -lm -lrt -lz 2. Open MPI 4.1.0
OpenBenchmarking.orgTotal Mop/s Per Watt, More Is BetterNAS Parallel Benchmarks 3.4Test / Class: SP.B2 x EPYC 7763120240360480600560.65
MinAvgMax2 x EPYC 776382.5266.4543.7OpenBenchmarking.orgWatts, Fewer Is BetterNAS Parallel Benchmarks 3.4CPU Power Consumption Monitor1402804205607001. 2 x EPYC 7763: Approximate power consumption of 2626 Joules per run.

OpenBenchmarking.orgTotal Mop/s, More Is BetterNAS Parallel Benchmarks 3.4Test / Class: MG.C2 x EPYC 776320K40K60K80K100KSE +/- 385.78, N = 7102771.231. (F9X) gfortran options: -O3 -march=native -pthread -lmpi_usempif08 -lmpi_mpifh -lmpi -lopen-rte -lopen-pal -lhwloc -ldl -levent_core -levent_pthreads -lutil -lm -lrt -lz 2. Open MPI 4.1.0
OpenBenchmarking.orgTotal Mop/s Per Watt, More Is BetterNAS Parallel Benchmarks 3.4Test / Class: MG.C2 x EPYC 7763100200300400500457.92
MinAvgMax2 x EPYC 776382.3224.4439.8OpenBenchmarking.orgWatts, Fewer Is BetterNAS Parallel Benchmarks 3.4CPU Power Consumption Monitor1202403604806001. 2 x EPYC 7763: Approximate power consumption of 2116 Joules per run.

OpenBenchmarking.orgTotal Mop/s, More Is BetterNAS Parallel Benchmarks 3.4Test / Class: LU.C2 x EPYC 776360K120K180K240K300KSE +/- 807.48, N = 5288799.041. (F9X) gfortran options: -O3 -march=native -pthread -lmpi_usempif08 -lmpi_mpifh -lmpi -lopen-rte -lopen-pal -lhwloc -ldl -levent_core -levent_pthreads -lutil -lm -lrt -lz 2. Open MPI 4.1.0
OpenBenchmarking.orgTotal Mop/s Per Watt, More Is BetterNAS Parallel Benchmarks 3.4Test / Class: LU.C2 x EPYC 77632004006008001000842.20
MinAvgMax2 x EPYC 776382.7342.9525.9OpenBenchmarking.orgWatts, Fewer Is BetterNAS Parallel Benchmarks 3.4CPU Power Consumption Monitor1302603905206501. 2 x EPYC 7763: Approximate power consumption of 5144 Joules per run.

OpenBenchmarking.orgTotal Mop/s, More Is BetterNAS Parallel Benchmarks 3.4Test / Class: IS.D2 x EPYC 776310002000300040005000SE +/- 25.73, N = 54460.841. (F9X) gfortran options: -O3 -march=native -pthread -lmpi_usempif08 -lmpi_mpifh -lmpi -lopen-rte -lopen-pal -lhwloc -ldl -levent_core -levent_pthreads -lutil -lm -lrt -lz 2. Open MPI 4.1.0
OpenBenchmarking.orgTotal Mop/s Per Watt, More Is BetterNAS Parallel Benchmarks 3.4Test / Class: IS.D2 x EPYC 77634812162014.19
MinAvgMax2 x EPYC 776382.6314.5521.1OpenBenchmarking.orgWatts, Fewer Is BetterNAS Parallel Benchmarks 3.4CPU Power Consumption Monitor1302603905206501. 2 x EPYC 7763: Approximate power consumption of 4843 Joules per run.

OpenBenchmarking.orgTotal Mop/s, More Is BetterNAS Parallel Benchmarks 3.4Test / Class: FT.C2 x EPYC 776330K60K90K120K150KSE +/- 403.59, N = 6120440.041. (F9X) gfortran options: -O3 -march=native -pthread -lmpi_usempif08 -lmpi_mpifh -lmpi -lopen-rte -lopen-pal -lhwloc -ldl -levent_core -levent_pthreads -lutil -lm -lrt -lz 2. Open MPI 4.1.0
OpenBenchmarking.orgTotal Mop/s Per Watt, More Is BetterNAS Parallel Benchmarks 3.4Test / Class: FT.C2 x EPYC 776390180270360450421.74
MinAvgMax2 x EPYC 776381.4285.6515.9OpenBenchmarking.orgWatts, Fewer Is BetterNAS Parallel Benchmarks 3.4CPU Power Consumption Monitor1302603905206501. 2 x EPYC 7763: Approximate power consumption of 3189 Joules per run.

OpenBenchmarking.orgTotal Mop/s, More Is BetterNAS Parallel Benchmarks 3.4Test / Class: EP.D2 x EPYC 77632K4K6K8K10KSE +/- 22.40, N = 410736.771. (F9X) gfortran options: -O3 -march=native -pthread -lmpi_usempif08 -lmpi_mpifh -lmpi -lopen-rte -lopen-pal -lhwloc -ldl -levent_core -levent_pthreads -lutil -lm -lrt -lz 2. Open MPI 4.1.0
OpenBenchmarking.orgTotal Mop/s Per Watt, More Is BetterNAS Parallel Benchmarks 3.4Test / Class: EP.D2 x EPYC 776361218243027.38
MinAvgMax2 x EPYC 776381.6392.2521.9OpenBenchmarking.orgWatts, Fewer Is BetterNAS Parallel Benchmarks 3.4CPU Power Consumption Monitor1302603905206501. 2 x EPYC 7763: Approximate power consumption of 7941 Joules per run.

OpenBenchmarking.orgTotal Mop/s, More Is BetterNAS Parallel Benchmarks 3.4Test / Class: EP.C2 x EPYC 77632K4K6K8K10KSE +/- 71.60, N = 159537.231. (F9X) gfortran options: -O3 -march=native -pthread -lmpi_usempif08 -lmpi_mpifh -lmpi -lopen-rte -lopen-pal -lhwloc -ldl -levent_core -levent_pthreads -lutil -lm -lrt -lz 2. Open MPI 4.1.0
OpenBenchmarking.orgTotal Mop/s Per Watt, More Is BetterNAS Parallel Benchmarks 3.4Test / Class: EP.C2 x EPYC 7763102030405044.21
MinAvgMax2 x EPYC 776381.7215.7482.5OpenBenchmarking.orgWatts, Fewer Is BetterNAS Parallel Benchmarks 3.4CPU Power Consumption Monitor1202403604806001. 2 x EPYC 7763: Approximate power consumption of 1855 Joules per run.

OpenBenchmarking.orgTotal Mop/s, More Is BetterNAS Parallel Benchmarks 3.4Test / Class: CG.C2 x EPYC 776310K20K30K40K50KSE +/- 478.32, N = 648175.521. (F9X) gfortran options: -O3 -march=native -pthread -lmpi_usempif08 -lmpi_mpifh -lmpi -lopen-rte -lopen-pal -lhwloc -ldl -levent_core -levent_pthreads -lutil -lm -lrt -lz 2. Open MPI 4.1.0
OpenBenchmarking.orgTotal Mop/s Per Watt, More Is BetterNAS Parallel Benchmarks 3.4Test / Class: CG.C2 x EPYC 77634080120160200187.33
MinAvgMax2 x EPYC 776382.0257.2474.0OpenBenchmarking.orgWatts, Fewer Is BetterNAS Parallel Benchmarks 3.4CPU Power Consumption Monitor1202403604806001. 2 x EPYC 7763: Approximate power consumption of 2786 Joules per run.

OpenBenchmarking.orgTotal Mop/s, More Is BetterNAS Parallel Benchmarks 3.4Test / Class: BT.C2 x EPYC 776360K120K180K240K300KSE +/- 222.22, N = 4257264.241. (F9X) gfortran options: -O3 -march=native -pthread -lmpi_usempif08 -lmpi_mpifh -lmpi -lopen-rte -lopen-pal -lhwloc -ldl -levent_core -levent_pthreads -lutil -lm -lrt -lz 2. Open MPI 4.1.0
OpenBenchmarking.orgTotal Mop/s Per Watt, More Is BetterNAS Parallel Benchmarks 3.4Test / Class: BT.C2 x EPYC 7763140280420560700670.35
MinAvgMax2 x EPYC 776379.7383.8541.2OpenBenchmarking.orgWatts, Fewer Is BetterNAS Parallel Benchmarks 3.4CPU Power Consumption Monitor1402804205607001. 2 x EPYC 7763: Approximate power consumption of 7388 Joules per run.

TensorFlow Lite

MinAvgMax2 x EPYC 776381.2502.8561.7OpenBenchmarking.orgWatts, Fewer Is BetterTensorFlow Lite 2020-08-23CPU Power Consumption Monitor140280420560700

ASKAP

OpenBenchmarking.orgWatts, Fewer Is BetterASKAP 1.0CPU Power Consumption Monitor2 x EPYC 776390180270360450Min: 81.41 / Avg: 239.93 / Max: 479.68

OpenBenchmarking.orgMillion Grid Points Per Second Per Watt, More Is BetterASKAP 1.0Test: tConvolve MT - Degridding2 x EPYC 7763102030405043.68

Cpuminer-Opt

MinAvgMax2 x EPYC 776382.3161.0242.7OpenBenchmarking.orgWatts, Fewer Is BetterCpuminer-Opt 3.15.5CPU Power Consumption Monitor60120180240300

OpenBenchmarking.orgkH/s Per Watt, More Is BetterCpuminer-Opt 3.15.5Algorithm: Myriad-Groestl2 x EPYC 7763300600900120015001483.20

MinAvgMax2 x EPYC 776382.5151.5168.6OpenBenchmarking.orgWatts, Fewer Is BetterCpuminer-Opt 3.15.5CPU Power Consumption Monitor50100150200250

OpenBenchmarking.orgkH/s Per Watt, More Is BetterCpuminer-Opt 3.15.5Algorithm: Blake-2 S2 x EPYC 77636K12K18K24K30K26905.34

Helsing

OpenBenchmarking.orgWatts, Fewer Is BetterHelsing 1.0-betaCPU Power Consumption Monitor2 x EPYC 776390180270360450Min: 81.86 / Avg: 375.12 / Max: 494.21

oneDNN

MinAvgMax2 x EPYC 776381.9338.2497.5OpenBenchmarking.orgWatts, Fewer Is BetteroneDNN 2.1.2CPU Power Consumption Monitor130260390520650

MinAvgMax2 x EPYC 776381.8338.8499.8OpenBenchmarking.orgWatts, Fewer Is BetteroneDNN 2.1.2CPU Power Consumption Monitor130260390520650

MinAvgMax2 x EPYC 776383.0337.8493.7OpenBenchmarking.orgWatts, Fewer Is BetteroneDNN 2.1.2CPU Power Consumption Monitor130260390520650

MinAvgMax2 x EPYC 776382.6246.0490.6OpenBenchmarking.orgWatts, Fewer Is BetteroneDNN 2.1.2CPU Power Consumption Monitor130260390520650

MinAvgMax2 x EPYC 776381.8299.2562.9OpenBenchmarking.orgWatts, Fewer Is BetteroneDNN 2.1.2CPU Power Consumption Monitor140280420560700

TTSIOD 3D Renderer

MinAvgMax2 x EPYC 776382.0289.7322.1OpenBenchmarking.orgWatts, Fewer Is BetterTTSIOD 3D Renderer 2.3bCPU Power Consumption Monitor80160240320400

OpenBenchmarking.orgFPS Per Watt, More Is BetterTTSIOD 3D Renderer 2.3bPhong Rendering With Soft-Shadow Mapping2 x EPYC 77630.40970.81941.22911.63882.04851.821

LuxCoreRender

MinAvgMax2 x EPYC 776382.5278.5414.7OpenBenchmarking.orgWatts, Fewer Is BetterLuxCoreRender 2.5CPU Power Consumption Monitor110220330440550

OpenBenchmarking.orgM samples/sec Per Watt, More Is BetterLuxCoreRender 2.5Scene: Rainbow Colors and Prism - Acceleration: CPU2 x EPYC 77630.01490.02980.04470.05960.07450.066

MinAvgMax2 x EPYC 776381.6507.1570.4OpenBenchmarking.orgWatts, Fewer Is BetterLuxCoreRender 2.5CPU Power Consumption Monitor140280420560700

OpenBenchmarking.orgM samples/sec Per Watt, More Is BetterLuxCoreRender 2.5Scene: DLSC - Acceleration: CPU2 x EPYC 77630.00630.01260.01890.02520.03150.028

Xcompact3d Incompact3d

MinAvgMax2 x EPYC 776382.4258.4471.5OpenBenchmarking.orgWatts, Fewer Is BetterXcompact3d Incompact3d 2021-03-11CPU Power Consumption Monitor120240360480600

Pennant

MinAvgMax2 x EPYC 776382.0285.2542.5OpenBenchmarking.orgWatts, Fewer Is BetterPennant 1.0.1CPU Power Consumption Monitor140280420560700

CloverLeaf

MinAvgMax2 x EPYC 776382.2330.6406.6OpenBenchmarking.orgWatts, Fewer Is BetterCloverLeafCPU Power Consumption Monitor110220330440550

TensorFlow Lite

This is a benchmark of the TensorFlow Lite implementation. The current Linux support is limited to running on CPUs. This test profile is measuring the average inference time. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgMicroseconds, Fewer Is BetterTensorFlow Lite 2020-08-23Model: SqueezeNet2 x EPYC 776311K22K33K44K55KSE +/- 1660.91, N = 1253389.4
MinAvgMax2 x EPYC 776381.2502.8561.7OpenBenchmarking.orgWatts, Fewer Is BetterTensorFlow Lite 2020-08-23CPU Power Consumption Monitor1402804205607001. 2 x EPYC 7763: Approximate power consumption of 32223 Joules per run.

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 - Degridding2 x EPYC 77632K4K6K8K10KSE +/- 390.12, N = 310480.311. (CXX) g++ options: -O3 -fstrict-aliasing -fopenmp
OpenBenchmarking.orgMillion Grid Points Per Second Per Watt, More Is BetterASKAP 1.0Test: tConvolve MT - Degridding2 x EPYC 7763102030405043.68
OpenBenchmarking.orgWatts, Fewer Is BetterASKAP 1.0CPU Power Consumption Monitor2 x EPYC 776390180270360450Min: 81.41 / Avg: 239.93 / Max: 479.681. 2 x EPYC 7763: Approximate power consumption of 108448 Joules per run.

Cpuminer-Opt

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

OpenBenchmarking.orgkH/s, More Is BetterCpuminer-Opt 3.15.5Algorithm: Myriad-Groestl2 x EPYC 776350K100K150K200K250KSE +/- 53782.51, N = 122387801. (CXX) g++ options: -O2 -lcurl -lz -lpthread -lssl -lcrypto -lgmp
OpenBenchmarking.orgkH/s Per Watt, More Is BetterCpuminer-Opt 3.15.5Algorithm: Myriad-Groestl2 x EPYC 7763300600900120015001483.20
MinAvgMax2 x EPYC 776382.3161.0242.7OpenBenchmarking.orgWatts, Fewer Is BetterCpuminer-Opt 3.15.5CPU Power Consumption Monitor601201802403001. 2 x EPYC 7763: Approximate power consumption of 5608 Joules per run.

OpenBenchmarking.orgkH/s, More Is BetterCpuminer-Opt 3.15.5Algorithm: Blake-2 S2 x EPYC 7763900K1800K2700K3600K4500KSE +/- 213346.66, N = 1540770531. (CXX) g++ options: -O2 -lcurl -lz -lpthread -lssl -lcrypto -lgmp
OpenBenchmarking.orgkH/s Per Watt, More Is BetterCpuminer-Opt 3.15.5Algorithm: Blake-2 S2 x EPYC 77636K12K18K24K30K26905.34
MinAvgMax2 x EPYC 776382.5151.5168.6OpenBenchmarking.orgWatts, Fewer Is BetterCpuminer-Opt 3.15.5CPU Power Consumption Monitor501001502002501. 2 x EPYC 7763: Approximate power consumption of 5283 Joules per run.

Helsing

Helsing is an open-source POSIX vampire number generator. This test profile measures the time it takes to generate vampire numbers between varying numbers of digits. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgSeconds, Fewer Is BetterHelsing 1.0-betaDigit Range: 14 digit2 x EPYC 7763306090120150SE +/- 9.54, N = 12122.851. (CC) gcc options: -O2 -pthread
OpenBenchmarking.orgWatts, Fewer Is BetterHelsing 1.0-betaCPU Power Consumption Monitor2 x EPYC 776390180270360450Min: 81.86 / Avg: 375.12 / Max: 494.211. 2 x EPYC 7763: Approximate power consumption of 47328 Joules per run.

oneDNN

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

OpenBenchmarking.orgms, Fewer Is BetteroneDNN 2.1.2Harness: Recurrent Neural Network Inference - Data Type: bf16bf16bf16 - Engine: CPU2 x EPYC 776330060090012001500SE +/- 26.52, N = 151385.48MIN: 1048.291. (CXX) g++ options: -O3 -march=native -std=c++11 -fopenmp -msse4.1 -fPIC -pie -lpthread -ldl
MinAvgMax2 x EPYC 776381.9338.2497.5OpenBenchmarking.orgWatts, Fewer Is BetteroneDNN 2.1.2CPU Power Consumption Monitor1302603905206501. 2 x EPYC 7763: Approximate power consumption of 27055 Joules per run.

OpenBenchmarking.orgms, Fewer Is BetteroneDNN 2.1.2Harness: Recurrent Neural Network Inference - Data Type: u8s8f32 - Engine: CPU2 x EPYC 776330060090012001500SE +/- 25.48, N = 151332.19MIN: 1053.761. (CXX) g++ options: -O3 -march=native -std=c++11 -fopenmp -msse4.1 -fPIC -pie -lpthread -ldl
MinAvgMax2 x EPYC 776381.8338.8499.8OpenBenchmarking.orgWatts, Fewer Is BetteroneDNN 2.1.2CPU Power Consumption Monitor1302603905206501. 2 x EPYC 7763: Approximate power consumption of 27084 Joules per run.

OpenBenchmarking.orgms, Fewer Is BetteroneDNN 2.1.2Harness: Recurrent Neural Network Inference - Data Type: f32 - Engine: CPU2 x EPYC 776330060090012001500SE +/- 108.05, N = 121464.79MIN: 1046.771. (CXX) g++ options: -O3 -march=native -std=c++11 -fopenmp -msse4.1 -fPIC -pie -lpthread -ldl
MinAvgMax2 x EPYC 776383.0337.8493.7OpenBenchmarking.orgWatts, Fewer Is BetteroneDNN 2.1.2CPU Power Consumption Monitor1302603905206501. 2 x EPYC 7763: Approximate power consumption of 27168 Joules per run.

OpenBenchmarking.orgms, Fewer Is BetteroneDNN 2.1.2Harness: Deconvolution Batch shapes_3d - Data Type: u8s8f32 - Engine: CPU2 x EPYC 77630.16430.32860.49290.65720.8215SE +/- 0.012353, N = 150.730205MIN: 0.521. (CXX) g++ options: -O3 -march=native -std=c++11 -fopenmp -msse4.1 -fPIC -pie -lpthread -ldl
MinAvgMax2 x EPYC 776382.6246.0490.6OpenBenchmarking.orgWatts, Fewer Is BetteroneDNN 2.1.2CPU Power Consumption Monitor1302603905206501. 2 x EPYC 7763: Approximate power consumption of 1739 Joules per run.

OpenBenchmarking.orgms, Fewer Is BetteroneDNN 2.1.2Harness: Convolution Batch Shapes Auto - Data Type: u8s8f32 - Engine: CPU2 x EPYC 77630.1910.3820.5730.7640.955SE +/- 0.037340, N = 150.848820MIN: 0.411. (CXX) g++ options: -O3 -march=native -std=c++11 -fopenmp -msse4.1 -fPIC -pie -lpthread -ldl
MinAvgMax2 x EPYC 776381.8299.2562.9OpenBenchmarking.orgWatts, Fewer Is BetteroneDNN 2.1.2CPU Power Consumption Monitor1402804205607001. 2 x EPYC 7763: Approximate power consumption of 3091 Joules per run.

TTSIOD 3D Renderer

A portable GPL 3D software renderer that supports OpenMP and Intel Threading Building Blocks with many different rendering modes. This version does not use OpenGL but is entirely CPU/software based. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgFPS, More Is BetterTTSIOD 3D Renderer 2.3bPhong Rendering With Soft-Shadow Mapping2 x EPYC 7763110220330440550SE +/- 11.48, N = 15527.531. (CXX) g++ options: -O3 -fomit-frame-pointer -ffast-math -mtune=native -flto -msse -mrecip -mfpmath=sse -msse2 -mssse3 -lSDL -fopenmp -fwhole-program -lstdc++
OpenBenchmarking.orgFPS Per Watt, More Is BetterTTSIOD 3D Renderer 2.3bPhong Rendering With Soft-Shadow Mapping2 x EPYC 77630.40970.81941.22911.63882.04851.821
MinAvgMax2 x EPYC 776382.0289.7322.1OpenBenchmarking.orgWatts, Fewer Is BetterTTSIOD 3D Renderer 2.3bCPU Power Consumption Monitor801602403204001. 2 x EPYC 7763: Approximate power consumption of 9772 Joules per run.

LuxCoreRender

LuxCoreRender is an open-source 3D physically based renderer formerly known as LuxRender. LuxCoreRender supports CPU-based rendering as well as GPU acceleration via OpenCL, NVIDIA CUDA, and NVIDIA OptiX interfaces. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgM samples/sec, More Is BetterLuxCoreRender 2.5Scene: Rainbow Colors and Prism - Acceleration: CPU2 x EPYC 7763510152025SE +/- 0.90, N = 1518.40MIN: 14.52 / MAX: 25.25
OpenBenchmarking.orgM samples/sec Per Watt, More Is BetterLuxCoreRender 2.5Scene: Rainbow Colors and Prism - Acceleration: CPU2 x EPYC 77630.01490.02980.04470.05960.07450.066
MinAvgMax2 x EPYC 776382.5278.5414.7OpenBenchmarking.orgWatts, Fewer Is BetterLuxCoreRender 2.5CPU Power Consumption Monitor1102203304405501. 2 x EPYC 7763: Approximate power consumption of 3937 Joules per run.

OpenBenchmarking.orgM samples/sec, More Is BetterLuxCoreRender 2.5Scene: DLSC - Acceleration: CPU2 x EPYC 776348121620SE +/- 0.33, N = 1514.33MIN: 11.8 / MAX: 18.81
OpenBenchmarking.orgM samples/sec Per Watt, More Is BetterLuxCoreRender 2.5Scene: DLSC - Acceleration: CPU2 x EPYC 77630.00630.01260.01890.02520.03150.028
MinAvgMax2 x EPYC 776381.6507.1570.4OpenBenchmarking.orgWatts, Fewer Is BetterLuxCoreRender 2.5CPU Power Consumption Monitor1402804205607001. 2 x EPYC 7763: Approximate power consumption of 32892 Joules per run.

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 Direction2 x EPYC 77630.61271.22541.83812.45083.0635SE +/- 0.05008949, N = 152.722974191. (F9X) gfortran options: -cpp -O2 -funroll-loops -floop-optimize -fcray-pointer -fbacktrace -pthread -lmpi_usempif08 -lmpi_mpifh -lmpi -lopen-rte -lopen-pal -lhwloc -ldl -levent_core -levent_pthreads -lutil -lm -lrt -lz
MinAvgMax2 x EPYC 776382.4258.4471.5OpenBenchmarking.orgWatts, Fewer Is BetterXcompact3d Incompact3d 2021-03-11CPU Power Consumption Monitor1202403604806001. 2 x EPYC 7763: Approximate power consumption of 2705 Joules per run.

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: leblancbig2 x EPYC 77630.75211.50422.25633.00843.7605SE +/- 0.062888, N = 153.3424981. (CXX) g++ options: -fopenmp -pthread -lmpi_cxx -lmpi
MinAvgMax2 x EPYC 776382.0285.2542.5OpenBenchmarking.orgWatts, Fewer Is BetterPennant 1.0.1CPU Power Consumption Monitor1402804205607001. 2 x EPYC 7763: Approximate power consumption of 3119 Joules per run.

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 EPYC 776348121620SE +/- 0.42, N = 1516.121. (F9X) gfortran options: -O3 -march=native -funroll-loops -fopenmp
MinAvgMax2 x EPYC 776382.2330.6406.6OpenBenchmarking.orgWatts, Fewer Is BetterCloverLeafCPU Power Consumption Monitor1102203304405501. 2 x EPYC 7763: Approximate power consumption of 6657 Joules per run.

169 Results Shown

GROMACS
ASKAP:
  Hogbom Clean OpenMP
  tConvolve OpenMP - Degridding
  tConvolve OpenMP - Gridding
  tConvolve MPI - Gridding
  tConvolve MPI - Degridding
  tConvolve MT - Gridding
Liquid-DSP:
  160 - 256 - 57
  128 - 256 - 57
  64 - 256 - 57
Cpuminer-Opt:
  LBC, LBRY Credits
  Skeincoin
  Garlicoin
  Deepcoin
  x25x
  Magi
Aircrack-ng
OpenSSL
WebP2 Image Encode:
  Quality 100, Lossless Compression
  Quality 100, Compression Effort 5
  Quality 95, Compression Effort 7
  Quality 75, Compression Effort 7
Tachyon
m-queens
Timed Wasmer Compilation
oneDNN:
  Matrix Multiply Batch Shapes Transformer - u8s8f32 - CPU
  Recurrent Neural Network Training - bf16bf16bf16 - CPU
  Matrix Multiply Batch Shapes Transformer - f32 - CPU
  Recurrent Neural Network Training - u8s8f32 - CPU
  Recurrent Neural Network Training - f32 - CPU
  Deconvolution Batch shapes_1d - u8s8f32 - CPU
  Deconvolution Batch shapes_3d - f32 - CPU
  Deconvolution Batch shapes_1d - f32 - CPU
  Convolution Batch Shapes Auto - f32 - CPU
  IP Shapes 3D - u8s8f32 - CPU
  IP Shapes 1D - u8s8f32 - CPU
  IP Shapes 3D - f32 - CPU
  IP Shapes 1D - f32 - CPU
rays1bench
YafaRay
Primesieve
POV-Ray
C-Ray
Build2
Timed PHP Compilation
Timed Node.js Compilation
Timed Mesa Compilation
Timed LLVM Compilation:
  Unix Makefiles
  Ninja
Timed Linux Kernel Compilation
Timed ImageMagick Compilation
Timed Godot Game Engine Compilation
Timed GDB GNU Debugger Compilation
Timed FFmpeg Compilation
Timed Apache Compilation
libavif avifenc
ebizzy
asmFish
Stockfish
7-Zip Compression
Coremark
OpenVKL:
  vklBenchmarkStructuredVolume
  vklBenchmarkVdbVolume
  vklBenchmark
Intel Open Image Denoise:
  RTLightmap.hdr.4096x4096
  RT.ldr_alb_nrm.3840x2160
  RT.hdr_alb_nrm.3840x2160
ACES DGEMM
x265
SVT-VP9:
  Visual Quality Optimized - Bosphorus 1080p
  PSNR/SSIM Optimized - Bosphorus 1080p
  VMAF Optimized - Bosphorus 1080p
SVT-HEVC:
  10 - Bosphorus 1080p
  7 - Bosphorus 1080p
  1 - Bosphorus 1080p
SVT-AV1:
  Preset 8 - Bosphorus 4K
  Preset 4 - Bosphorus 4K
Kvazaar:
  Bosphorus 4K - Ultra Fast
  Bosphorus 4K - Very Fast
Embree:
  Pathtracer ISPC - Asian Dragon Obj
  Pathtracer ISPC - Asian Dragon
  Pathtracer - Asian Dragon Obj
  Pathtracer - Asian Dragon
  Pathtracer ISPC - Crown
  Pathtracer - Crown
dav1d:
  Chimera 1080p 10-bit
  Summer Nature 4K
GraphicsMagick:
  HWB Color Space
  Noise-Gaussian
  Enhanced
  Sharpen
  Rotate
  Swirl
LuxCoreRender:
  LuxCore Benchmark - CPU
  Orange Juice - CPU
  Danish Mood - CPU
John The Ripper:
  MD5
  Blowfish
Xmrig:
  Wownero - 1M
  Monero - 1M
LULESH
LAMMPS Molecular Dynamics Simulator:
  Rhodopsin Protein
  20k Atoms
Quantum ESPRESSO
OpenFOAM:
  Motorbike 60M
  Motorbike 30M
Xcompact3d Incompact3d:
  input.i3d 193 Cells Per Direction
  X3D-benchmarking input.i3d
NWChem
Pennant
Algebraic Multi-Grid Benchmark
toyBrot Fractal Generator:
  C++ Threads
  C++ Tasks
  OpenMP
  TBB
NAMD
Rodinia:
  OpenMP Streamcluster
  OpenMP CFD Solver
  OpenMP Leukocyte
  OpenMP LavaMD
miniFE
NAS Parallel Benchmarks:
  SP.C
  SP.B
  MG.C
  LU.C
  IS.D
  FT.C
  EP.D
  EP.C
  CG.C
  BT.C
TensorFlow Lite:
  CPU Power Consumption Monitor:
    Watts
    Watts
  tConvolve MT - Degridding:
    Million Grid Points Per Second Per Watt
  CPU Power Consumption Monitor:
    Watts
  Myriad-Groestl:
    kH/s Per Watt
  CPU Power Consumption Monitor:
    Watts
  Blake-2 S:
    kH/s Per Watt
  CPU Power Consumption Monitor:
    Watts
    Watts
    Watts
    Watts
    Watts
    Watts
    Watts
  Phong Rendering With Soft-Shadow Mapping:
    FPS Per Watt
  CPU Power Consumption Monitor:
    Watts
  Rainbow Colors and Prism - CPU:
    M samples/sec Per Watt
  CPU Power Consumption Monitor:
    Watts
  DLSC - CPU:
    M samples/sec Per Watt
  CPU Power Consumption Monitor:
    Watts
    Watts
    Watts
TensorFlow Lite
ASKAP
Cpuminer-Opt:
  Myriad-Groestl
  Blake-2 S
Helsing
oneDNN:
  Recurrent Neural Network Inference - bf16bf16bf16 - CPU
  Recurrent Neural Network Inference - u8s8f32 - CPU
  Recurrent Neural Network Inference - f32 - CPU
  Deconvolution Batch shapes_3d - u8s8f32 - CPU
  Convolution Batch Shapes Auto - u8s8f32 - CPU
TTSIOD 3D Renderer
LuxCoreRender:
  Rainbow Colors and Prism - CPU
  DLSC - CPU
Xcompact3d Incompact3d
Pennant
CloverLeaf

2 x EPYC 7763

Processor: 2 x AMD EPYC 7763 64-Core @ 2.45GHz (128 Cores / 256 Threads), Motherboard: AMD DAYTONA_X (RYM1001D BIOS), Chipset: AMD Starship/Matisse, Memory: 504GB, Disk: 7682GB INTEL SSDPF2KX076TZ, Graphics: llvmpipe, Monitor: VE228, Network: 2 x Mellanox MT27710

OS: Ubuntu 21.04, Kernel: 5.13.0-051300rc4-generic (x86_64) 20210530, Display Server: X Server 1.20.11, OpenGL: 4.5 Mesa 21.0.1 (LLVM 11.0.1 256 bits), Vulkan: 1.0.2, Compiler: GCC 10.3.0, File-System: ext4, Screen Resolution: 1920x1080

Kernel Notes: Transparent Huge Pages: madvise
Compiler Notes: --build=x86_64-linux-gnu --disable-vtable-verify --disable-werror --enable-bootstrap --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-mutex --enable-multiarch --enable-multilib --enable-nls --enable-objc-gc=auto --enable-offload-targets=nvptx-none=/build/gcc-10-gDeRY6/gcc-10-10.3.0/debian/tmp-nvptx/usr,amdgcn-amdhsa=/build/gcc-10-gDeRY6/gcc-10-10.3.0/debian/tmp-gcn/usr,hsa --enable-plugin --enable-shared --enable-threads=posix --host=x86_64-linux-gnu --program-prefix=x86_64-linux-gnu- --target=x86_64-linux-gnu --with-abi=m64 --with-arch-32=i686 --with-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 Notes: Scaling Governor: acpi-cpufreq performance (Boost: Enabled) - CPU Microcode: 0xa001119
Python Notes: Python 3.9.5
Security Notes: itlb_multihit: Not affected + l1tf: Not affected + mds: Not affected + meltdown: 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 Full AMD retpoline IBPB: conditional IBRS_FW STIBP: always-on RSB filling + srbds: Not affected + tsx_async_abort: Not affected

Testing initiated at 13 June 2021 18:43 by user phoronix.