GCE c3d-standard-60

amazon testing on Ubuntu 22.04 via the Phoronix Test Suite.

Compare your own system(s) to this result file with the Phoronix Test Suite by running the command: phoronix-test-suite benchmark 2310065-NE-2310055NE35
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c3d-standard-60 AMD Genoa
October 03 2023
  10 Hours, 30 Minutes
t2d-standard-60 AMD Milan
October 03 2023
  13 Hours, 23 Minutes
c6g.16xlarge
October 05 2023
  9 Hours, 27 Minutes
m7a.16xlarge
October 06 2023
  9 Hours, 1 Minute
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  10 Hours, 35 Minutes

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GCE c3d-standard-60ProcessorMotherboardChipsetMemoryDiskNetworkOSKernelVulkanCompilerFile-SystemSystem Layerc3d-standard-60 AMD Genoat2d-standard-60 AMD Milanc6g.16xlargem7a.16xlargeAMD EPYC 9B14 (30 Cores / 60 Threads)Google Compute Engine c3d-standard-60Intel 440FX 82441FX PMC240GB215GB nvme_card-pdGoogle Compute Engine VirtualUbuntu 22.046.2.0-1014-gcp (x86_64)1.3.238GCC 11.4.0ext4KVMAMD EPYC 7B13 (60 Cores)Google Compute Engine t2d-standard-60215GB PersistentDiskRed Hat Virtio deviceARMv8 Neoverse-N1 (64 Cores)Amazon EC2 c6g.16xlarge (1.0 BIOS)Amazon Device 0200128GB215GB Amazon Elastic Block StoreAmazon Elastic5.19.0-1025-aws (aarch64)amazonAMD EPYC 9R14 (64 Cores)Amazon EC2 m7a.16xlarge (1.0 BIOS)Intel 440FX 82441FX PMC256GB5.19.0-1025-aws (x86_64)OpenBenchmarking.orgKernel Details- Transparent Huge Pages: madviseCompiler Details- c3d-standard-60 AMD Genoa: --build=x86_64-linux-gnu --disable-vtable-verify --disable-werror --enable-bootstrap --enable-cet --enable-checking=release --enable-clocale=gnu --enable-default-pie --enable-gnu-unique-object --enable-languages=c,ada,c++,go,brig,d,fortran,objc,obj-c++,m2 --enable-libphobos-checking=release --enable-libstdcxx-debug --enable-libstdcxx-time=yes --enable-link-serialization=2 --enable-multiarch --enable-multilib --enable-nls --enable-objc-gc=auto --enable-offload-targets=nvptx-none=/build/gcc-11-XeT9lY/gcc-11-11.4.0/debian/tmp-nvptx/usr,amdgcn-amdhsa=/build/gcc-11-XeT9lY/gcc-11-11.4.0/debian/tmp-gcn/usr --enable-plugin --enable-shared --enable-threads=posix --host=x86_64-linux-gnu --program-prefix=x86_64-linux-gnu- --target=x86_64-linux-gnu --with-abi=m64 --with-arch-32=i686 --with-build-config=bootstrap-lto-lean --with-default-libstdcxx-abi=new --with-gcc-major-version-only --with-multilib-list=m32,m64,mx32 --with-target-system-zlib=auto --with-tune=generic --without-cuda-driver -v - t2d-standard-60 AMD Milan: --build=x86_64-linux-gnu --disable-vtable-verify --disable-werror --enable-bootstrap --enable-cet --enable-checking=release --enable-clocale=gnu --enable-default-pie --enable-gnu-unique-object --enable-languages=c,ada,c++,go,brig,d,fortran,objc,obj-c++,m2 --enable-libphobos-checking=release --enable-libstdcxx-debug --enable-libstdcxx-time=yes --enable-link-serialization=2 --enable-multiarch --enable-multilib --enable-nls --enable-objc-gc=auto --enable-offload-targets=nvptx-none=/build/gcc-11-XeT9lY/gcc-11-11.4.0/debian/tmp-nvptx/usr,amdgcn-amdhsa=/build/gcc-11-XeT9lY/gcc-11-11.4.0/debian/tmp-gcn/usr --enable-plugin --enable-shared --enable-threads=posix --host=x86_64-linux-gnu --program-prefix=x86_64-linux-gnu- --target=x86_64-linux-gnu --with-abi=m64 --with-arch-32=i686 --with-build-config=bootstrap-lto-lean --with-default-libstdcxx-abi=new --with-gcc-major-version-only --with-multilib-list=m32,m64,mx32 --with-target-system-zlib=auto --with-tune=generic --without-cuda-driver -v - c6g.16xlarge: --build=aarch64-linux-gnu --disable-libquadmath --disable-libquadmath-support --disable-werror --enable-bootstrap --enable-checking=release --enable-clocale=gnu --enable-default-pie --enable-fix-cortex-a53-843419 --enable-gnu-unique-object --enable-languages=c,ada,c++,go,d,fortran,objc,obj-c++,m2 --enable-libphobos-checking=release --enable-libstdcxx-debug --enable-libstdcxx-time=yes --enable-link-serialization=2 --enable-multiarch --enable-nls --enable-objc-gc=auto --enable-plugin --enable-shared --enable-threads=posix --host=aarch64-linux-gnu --program-prefix=aarch64-linux-gnu- --target=aarch64-linux-gnu --with-build-config=bootstrap-lto-lean --with-default-libstdcxx-abi=new --with-gcc-major-version-only --with-target-system-zlib=auto -v - m7a.16xlarge: --build=x86_64-linux-gnu --disable-vtable-verify --disable-werror --enable-bootstrap --enable-cet --enable-checking=release --enable-clocale=gnu --enable-default-pie --enable-gnu-unique-object --enable-languages=c,ada,c++,go,brig,d,fortran,objc,obj-c++,m2 --enable-libphobos-checking=release --enable-libstdcxx-debug --enable-libstdcxx-time=yes --enable-link-serialization=2 --enable-multiarch --enable-multilib --enable-nls --enable-objc-gc=auto --enable-offload-targets=nvptx-none=/build/gcc-11-XeT9lY/gcc-11-11.4.0/debian/tmp-nvptx/usr,amdgcn-amdhsa=/build/gcc-11-XeT9lY/gcc-11-11.4.0/debian/tmp-gcn/usr --enable-plugin --enable-shared --enable-threads=posix --host=x86_64-linux-gnu --program-prefix=x86_64-linux-gnu- --target=x86_64-linux-gnu --with-abi=m64 --with-arch-32=i686 --with-build-config=bootstrap-lto-lean --with-default-libstdcxx-abi=new --with-gcc-major-version-only --with-multilib-list=m32,m64,mx32 --with-target-system-zlib=auto --with-tune=generic --without-cuda-driver -v Processor Details- c3d-standard-60 AMD Genoa: CPU Microcode: 0xffffffff- t2d-standard-60 AMD Milan: CPU Microcode: 0xffffffff- m7a.16xlarge: CPU Microcode: 0xa10113eJava Details- OpenJDK Runtime Environment (build 11.0.20.1+1-post-Ubuntu-0ubuntu122.04)Python Details- Python 3.10.12Security Details- c3d-standard-60 AMD Genoa: gather_data_sampling: Not affected + itlb_multihit: Not affected + l1tf: Not affected + mds: Not affected + meltdown: Not affected + mmio_stale_data: Not affected + retbleed: Not affected + spec_store_bypass: Mitigation of SSB disabled via prctl + spectre_v1: Mitigation of usercopy/swapgs barriers and __user pointer sanitization + spectre_v2: Mitigation of Retpolines IBPB: conditional IBRS_FW STIBP: always-on RSB filling PBRSB-eIBRS: Not affected + srbds: Not affected + tsx_async_abort: Not affected - t2d-standard-60 AMD Milan: gather_data_sampling: Not affected + itlb_multihit: Not affected + l1tf: Not affected + mds: Not affected + meltdown: Not affected + mmio_stale_data: Not affected + retbleed: Not affected + spec_store_bypass: Mitigation of SSB disabled via prctl + spectre_v1: Mitigation of usercopy/swapgs barriers and __user pointer sanitization + spectre_v2: Mitigation of Retpolines IBPB: conditional IBRS_FW STIBP: disabled RSB filling PBRSB-eIBRS: Not affected + srbds: Not affected + tsx_async_abort: Not affected - c6g.16xlarge: itlb_multihit: Not affected + l1tf: Not affected + mds: Not affected + meltdown: Not affected + mmio_stale_data: Not affected + retbleed: Not affected + spec_store_bypass: Mitigation of SSB disabled via prctl + spectre_v1: Mitigation of __user pointer sanitization + spectre_v2: Mitigation of CSV2 BHB + srbds: Not affected + tsx_async_abort: Not affected - m7a.16xlarge: itlb_multihit: Not affected + l1tf: Not affected + mds: Not affected + meltdown: Not affected + mmio_stale_data: Not affected + retbleed: Not affected + spec_store_bypass: Mitigation of SSB disabled via prctl + spectre_v1: Mitigation of usercopy/swapgs barriers and __user pointer sanitization + spectre_v2: Mitigation of Retpolines IBPB: conditional IBRS_FW STIBP: disabled RSB filling PBRSB-eIBRS: Not affected + srbds: Not affected + tsx_async_abort: Not affected

c3d-standard-60 AMD Genoat2d-standard-60 AMD Milanc6g.16xlargem7a.16xlargeLogarithmic Result OverviewPhoronix Test SuiteNAS Parallel BenchmarksOpenSSLnekRSGROMACSlibavif avifenclibxsmmRemhosXcompact3d Incompact3dAlgebraic Multi-Grid BenchmarkOpenVINOTimed Node.js CompilationLAMMPS Molecular Dynamics SimulatorCoremarkStockfishRodiniaApache CassandraTimed Gem5 CompilationnginxHeFFTe - Highly Efficient FFT for Exascale7-Zip CompressionLaghos

GCE c3d-standard-60openvino: Face Detection FP16-INT8 - CPUopenvino: Road Segmentation ADAS FP16-INT8 - CPUopenvino: Face Detection Retail FP16-INT8 - CPUnpb: BT.Copenvino: Age Gender Recognition Retail 0013 FP16-INT8 - CPUopenvino: Handwritten English Recognition FP16 - CPUopenvino: Road Segmentation ADAS FP16-INT8 - CPUopenvino: Handwritten English Recognition FP16-INT8 - CPUopenvino: Age Gender Recognition Retail 0013 FP16 - CPUopenvino: Person Vehicle Bike Detection FP16 - CPUopenvino: Road Segmentation ADAS FP16 - CPUnpb: FT.Ctensorflow: CPU - 64 - ResNet-50npb: MG.Cavifenc: 2openssl: ChaCha20-Poly1305openssl: RSA4096openssl: ChaCha20tensorflow: CPU - 32 - ResNet-50avifenc: 0openssl: AES-256-GCMopenvino: Weld Porosity Detection FP16 - CPUopenvino: Vehicle Detection FP16 - CPUopenvino: Weld Porosity Detection FP16-INT8 - CPUopenvino: Face Detection Retail FP16 - CPUopenvino: Face Detection FP16 - CPUtensorflow: CPU - 16 - ResNet-50openssl: AES-128-GCMbuild-linux-kernel: defconfignpb: EP.Dopenvino: Age Gender Recognition Retail 0013 FP16-INT8 - CPUopenvino: Vehicle Detection FP16-INT8 - CPUopenvino: Person Vehicle Bike Detection FP16 - CPUopenvino: Road Segmentation ADAS FP16 - CPUopenvino: Machine Translation EN To DE FP16 - CPUopenvino: Vehicle Detection FP16 - CPUopenvino: Face Detection Retail FP16-INT8 - CPUopenvino: Face Detection Retail FP16 - CPUpgbench: 100 - 1000 - Read Only - Average Latencypgbench: 100 - 1000 - Read Onlypgbench: 100 - 800 - Read Onlypgbench: 100 - 800 - Read Only - Average Latencygromacs: MPI CPU - water_GMX50_barelibxsmm: 32libxsmm: 64incompact3d: input.i3d 193 Cells Per Directionremhos: Sample Remap Exampleincompact3d: input.i3d 129 Cells Per Directionamg: openvino: Face Detection FP16 - CPUopenvino: Handwritten English Recognition FP16 - CPUopenvino: Vehicle Detection FP16-INT8 - CPUopenvino: Face Detection FP16-INT8 - CPUopenvino: Handwritten English Recognition FP16-INT8 - CPUopenvino: Age Gender Recognition Retail 0013 FP16 - CPUopenvino: Machine Translation EN To DE FP16 - CPUopenvino: Weld Porosity Detection FP16-INT8 - CPUopenssl: RSA4096openvino: Weld Porosity Detection FP16 - CPUnpb: SP.Cbuild-nodejs: Time To Compileopenssl: SHA512openradioss: Chrysler Neon 1Mcoremark: CoreMark Size 666 - Iterations Per Secondavifenc: 6rodinia: OpenMP CFD Solverlammps: 20k Atomslaghos: Sedov Blast Wave, ube_922_hex.meshavifenc: 6, Losslessbrl-cad: VGR Performance Metricbuild-linux-kernel: allmodconfigrodinia: OpenMP LavaMDcassandra: Writesopenssl: SHA256build-gem5: Time To Compileheffte: c2c - FFTW - float - 128nginx: 1000nginx: 500compress-7zip: Compression Ratingheffte: r2c - FFTW - float - 128rodinia: OpenMP Leukocyteapache-iotdb: 500 - 100 - 800 - 400apache-iotdb: 800 - 100 - 800 - 400blender: Barbershop - CPU-Onlyapache-iotdb: 800 - 100 - 500 - 400blender: Classroom - CPU-Onlycompress-7zip: Decompression Ratinglaghos: Triple Point Problemblender: BMW27 - CPU-Onlyapache-iotdb: 500 - 100 - 500 - 400apache-iotdb: 500 - 100 - 500 - 400blender: Pabellon Barcelona - CPU-Onlyblender: Fishy Cat - CPU-Onlyapache-iotdb: 500 - 100 - 800 - 400pgbench: 100 - 1000 - Read Write - Average Latencypgbench: 100 - 800 - Read Write - Average Latencyopenvino: Person Detection FP32 - CPUopenvino: Person Detection FP32 - CPUopenvino: Person Detection FP16 - CPUopenvino: Person Detection FP16 - CPUpgbench: 100 - 1000 - Read Writepgbench: 100 - 800 - Read Writeapache-iotdb: 800 - 100 - 800 - 400apache-iotdb: 800 - 100 - 500 - 400stockfish: Total Timelammps: Rhodopsin Proteinnekrs: TurboPipe Periodicnekrs: Kershawopenradioss: Rubber O-Ring Seal Installationopenradioss: Bird Strike on Windshieldopenradioss: Cell Phone Drop Testopenradioss: Bumper Beamheffte: r2c - FFTW - double - 128heffte: c2c - FFTW - double - 128rodinia: OpenMP Streamclusterrodinia: OpenMP HotSpot3Dnpb: LU.Cnpb: IS.Dnpb: CG.Cc3d-standard-60 AMD Genoat2d-standard-60 AMD Milanc6g.16xlargem7a.16xlarge340.29645.744.5396257.4854971.26964.4618.56761.1443607.041764.21576.9439647.4769.6842701.8341.538123909304773493077.617398094989362.7478.0682933280484971875.281389.698.204166.3918.3950.993430952844403783.600.42043.056.7920.77185.298.626605.122.874.391255.4489.728.019687733.3625.87157885962889833648.8131.085.8635.1939.380.5264.703650.5720079.515.9839919.71198.39414702270573337.701445843.5215523.25010.02519.776259.556.88951081964.86222864046211821313176.76788.6301180537.84187350.44271795148.57545.498347625653535988434332237226211209.00418.5933268158623.8983.91142.9083.99142.75682.12447.6810589445717.4234723940000428985833389.65147.3138.8292.8793.600557.31166.44884.16673563.132422.4019597.86568.77565.343.52122720.6144049.15370.0326.50390.7229668.12633.76225.4854846.1820.9047291.9641.989119647720337860844.618024914577020.3678.3502160259676401014.70368.3911.321285.4710.7318.2923460408261033.3994935.680.611512.5723.6466.4696.5840.674239.5211.650.498200818620037840.3995.289289.2554.224.572118116.3265.630573279204277671393.5681.009.9026.2876.720.99155.142646.5812973.014.7643228.11191.70622244804183327.881730658.4494403.2057.36826.734364.647.639629363333.35150.97418716950884997103170.930109.676155609.04162957.75278973196.94842.0103492589935068557351.583412381089.35247255222.3034.27415.0833466804112.6445.22633.58172.717140.916193.4578.96208.4773.7457935682709.46433.9611295878827.8282730620000368193583372.06123.6130.1275.68106.02960.03436.42388.53594247.771752.6216649.3722391.860.152186.8124229.14136.162.536773.312.36178.827.362.6121386.3725661.04167.94646715126487215683.267324778360270.0681291981976008.396.53181.9420.790.1158788510970102.2162213.767.330.14135.87382.471.36153.120.4648.081.02697503110432670.7672.766312.7589.525.874832820.8165.6181168610328936679996.56394.946990.100.04423.955.58735.585.502640.0119.179716.99286.201143849178631259870.7169024.4675.98325.059321.298.879409.09762.30121735542288513973224.414129.172158700.36162553.85239735202.445234046179.52210.608168.191947.861.06947.591.06477647848180770626.0412221710000175886000079.015632.357514.21218807.75915.8013343.35261.111222.993.07193219.1292100.801419.1113.071158.4381996.813146.041049.66103413.02100.15121293.8035.805216773475533996017.530830804508387.1965.4475221130805273132.482417.345.167222.1031.7269.5559254536274027.7097501.760.273666.895.0715.22315.146.6010382.222.210.347288094029230090.2747.655643.41201.811.591308613.8672.896026611843444333503.3822.534.3561.1927.600.3850.726177.9431583.810.19102392.40154.44126481506820190.792158639.2748832.6496.48031.471409.735.678788704267.96543.28627858562253861197153.800121.505224859.09233014.72330633190.60234.6614450233344699315276.234264390371.51282593218.8627.74340.114089921091.8837.12521.98188.676150.60156.41283.4056.21284.4253005312598.49355.1313541916932.7854774796667766784666759.18115.9626.1466.27124.36371.10955.93074.778210544.874085.2042007.57OpenBenchmarking.org

OpenVINO

OpenBenchmarking.orgms, Fewer Is BetterOpenVINO 2023.1Model: Face Detection FP16-INT8 - Device: CPUc3d-standard-60 AMD Genoat2d-standard-60 AMD Milanc6g.16xlargem7a.16xlarge5K10K15K20K25KSE +/- 0.21, N = 3SE +/- 0.35, N = 3SE +/- 15.60, N = 3SE +/- 0.03, N = 3340.29568.7722391.86261.11-isystem -fPIC -fvisibility=hidden -std=c++14 -MD -MT -MF -shared - MIN: 22364.17 / MAX: 22423.421. (CXX) g++ options: -fsigned-char -ffunction-sections -fdata-sections -O3 -fno-strict-overflow -fwrapv
OpenBenchmarking.orgms, Fewer Is BetterOpenVINO 2023.1Model: Face Detection FP16-INT8 - Device: CPUc3d-standard-60 AMD Genoat2d-standard-60 AMD Milanc6g.16xlargem7a.16xlarge4K8K12K16K20KMin: 339.88 / Avg: 340.29 / Max: 340.58Min: 568.2 / Avg: 568.77 / Max: 569.42Min: 22371.66 / Avg: 22391.86 / Max: 22422.55Min: 261.06 / Avg: 261.11 / Max: 261.171. (CXX) g++ options: -fsigned-char -ffunction-sections -fdata-sections -O3 -fno-strict-overflow -fwrapv

OpenBenchmarking.orgFPS, More Is BetterOpenVINO 2023.1Model: Road Segmentation ADAS FP16-INT8 - Device: CPUc3d-standard-60 AMD Genoat2d-standard-60 AMD Milanc6g.16xlargem7a.16xlarge30060090012001500SE +/- 0.79, N = 3SE +/- 0.37, N = 3SE +/- 0.00, N = 3SE +/- 0.51, N = 3645.74565.340.151222.99-pie-pie-pie1. (CXX) g++ options: -fsigned-char -ffunction-sections -fdata-sections -O3 -fno-strict-overflow -fwrapv
OpenBenchmarking.orgFPS, More Is BetterOpenVINO 2023.1Model: Road Segmentation ADAS FP16-INT8 - Device: CPUc3d-standard-60 AMD Genoat2d-standard-60 AMD Milanc6g.16xlargem7a.16xlarge2004006008001000Min: 644.52 / Avg: 645.74 / Max: 647.21Min: 564.63 / Avg: 565.34 / Max: 565.9Min: 0.15 / Avg: 0.15 / Max: 0.15Min: 1222.15 / Avg: 1222.99 / Max: 1223.921. (CXX) g++ options: -fsigned-char -ffunction-sections -fdata-sections -O3 -fno-strict-overflow -fwrapv

OpenBenchmarking.orgms, Fewer Is BetterOpenVINO 2023.1Model: Face Detection Retail FP16-INT8 - Device: CPUc3d-standard-60 AMD Genoat2d-standard-60 AMD Milanc6g.16xlargem7a.16xlarge5001000150020002500SE +/- 0.01, N = 3SE +/- 0.00, N = 3SE +/- 27.29, N = 3SE +/- 0.00, N = 34.533.522186.813.07-isystem -fPIC -fvisibility=hidden -std=c++14 -MD -MT -MF -shared - MIN: 2135.06 / MAX: 2233.341. (CXX) g++ options: -fsigned-char -ffunction-sections -fdata-sections -O3 -fno-strict-overflow -fwrapv
OpenBenchmarking.orgms, Fewer Is BetterOpenVINO 2023.1Model: Face Detection Retail FP16-INT8 - Device: CPUc3d-standard-60 AMD Genoat2d-standard-60 AMD Milanc6g.16xlargem7a.16xlarge400800120016002000Min: 4.52 / Avg: 4.53 / Max: 4.54Min: 3.52 / Avg: 3.52 / Max: 3.52Min: 2136.67 / Avg: 2186.81 / Max: 2230.56Min: 3.07 / Avg: 3.07 / Max: 3.071. (CXX) g++ options: -fsigned-char -ffunction-sections -fdata-sections -O3 -fno-strict-overflow -fwrapv

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: BT.Cc3d-standard-60 AMD Genoat2d-standard-60 AMD Milanc6g.16xlargem7a.16xlarge40K80K120K160K200KSE +/- 122.23, N = 3SE +/- 42.77, N = 3SE +/- 7.69, N = 3SE +/- 560.75, N = 396257.48122720.6124229.14193219.121. (F9X) gfortran options: -O3 -march=native -lmpi_usempif08 -lmpi_mpifh -lmpi -lopen-rte -lopen-pal -lhwloc -levent_core -levent_pthreads -lm -lz 2. Open MPI 4.1.2
OpenBenchmarking.orgTotal Mop/s, More Is BetterNAS Parallel Benchmarks 3.4Test / Class: BT.Cc3d-standard-60 AMD Genoat2d-standard-60 AMD Milanc6g.16xlargem7a.16xlarge30K60K90K120K150KMin: 96031.29 / Avg: 96257.48 / Max: 96450.87Min: 122655.41 / Avg: 122720.61 / Max: 122801.16Min: 24214.1 / Avg: 24229.14 / Max: 24239.43Min: 192102.72 / Avg: 193219.12 / Max: 193869.811. (F9X) gfortran options: -O3 -march=native -lmpi_usempif08 -lmpi_mpifh -lmpi -lopen-rte -lopen-pal -lhwloc -levent_core -levent_pthreads -lm -lz 2. Open MPI 4.1.2

OpenVINO

OpenBenchmarking.orgFPS, More Is BetterOpenVINO 2023.1Model: Age Gender Recognition Retail 0013 FP16-INT8 - Device: CPUc3d-standard-60 AMD Genoat2d-standard-60 AMD Milanc6g.16xlargem7a.16xlarge20K40K60K80K100KSE +/- 45.46, N = 3SE +/- 332.93, N = 3SE +/- 0.48, N = 3SE +/- 453.62, N = 354971.2644049.15136.1692100.80-pie-pie-pie1. (CXX) g++ options: -fsigned-char -ffunction-sections -fdata-sections -O3 -fno-strict-overflow -fwrapv
OpenBenchmarking.orgFPS, More Is BetterOpenVINO 2023.1Model: Age Gender Recognition Retail 0013 FP16-INT8 - Device: CPUc3d-standard-60 AMD Genoat2d-standard-60 AMD Milanc6g.16xlargem7a.16xlarge16K32K48K64K80KMin: 54880.77 / Avg: 54971.26 / Max: 55024.16Min: 43415.23 / Avg: 44049.15 / Max: 44542.58Min: 135.26 / Avg: 136.16 / Max: 136.9Min: 91645.52 / Avg: 92100.8 / Max: 93008.041. (CXX) g++ options: -fsigned-char -ffunction-sections -fdata-sections -O3 -fno-strict-overflow -fwrapv

OpenBenchmarking.orgFPS, More Is BetterOpenVINO 2023.1Model: Handwritten English Recognition FP16 - Device: CPUc3d-standard-60 AMD Genoat2d-standard-60 AMD Milanc6g.16xlargem7a.16xlarge30060090012001500SE +/- 0.60, N = 3SE +/- 0.96, N = 3SE +/- 0.02, N = 3SE +/- 0.70, N = 3964.46370.032.531419.11-pie-pie-pie1. (CXX) g++ options: -fsigned-char -ffunction-sections -fdata-sections -O3 -fno-strict-overflow -fwrapv
OpenBenchmarking.orgFPS, More Is BetterOpenVINO 2023.1Model: Handwritten English Recognition FP16 - Device: CPUc3d-standard-60 AMD Genoat2d-standard-60 AMD Milanc6g.16xlargem7a.16xlarge2004006008001000Min: 963.5 / Avg: 964.46 / Max: 965.57Min: 368.12 / Avg: 370.03 / Max: 371.04Min: 2.5 / Avg: 2.53 / Max: 2.55Min: 1418.14 / Avg: 1419.11 / Max: 1420.461. (CXX) g++ options: -fsigned-char -ffunction-sections -fdata-sections -O3 -fno-strict-overflow -fwrapv

OpenBenchmarking.orgms, Fewer Is BetterOpenVINO 2023.1Model: Road Segmentation ADAS FP16-INT8 - Device: CPUc3d-standard-60 AMD Genoat2d-standard-60 AMD Milanc6g.16xlargem7a.16xlarge15003000450060007500SE +/- 0.02, N = 3SE +/- 0.02, N = 3SE +/- 76.95, N = 3SE +/- 0.01, N = 318.5626.506773.3113.07-isystem -fPIC -fvisibility=hidden -std=c++14 -MD -MT -MF -shared - MIN: 6616.83 / MAX: 6859.991. (CXX) g++ options: -fsigned-char -ffunction-sections -fdata-sections -O3 -fno-strict-overflow -fwrapv
OpenBenchmarking.orgms, Fewer Is BetterOpenVINO 2023.1Model: Road Segmentation ADAS FP16-INT8 - Device: CPUc3d-standard-60 AMD Genoat2d-standard-60 AMD Milanc6g.16xlargem7a.16xlarge12002400360048006000Min: 18.52 / Avg: 18.56 / Max: 18.59Min: 26.47 / Avg: 26.5 / Max: 26.53Min: 6619.53 / Avg: 6773.31 / Max: 6855.37Min: 13.06 / Avg: 13.07 / Max: 13.081. (CXX) g++ options: -fsigned-char -ffunction-sections -fdata-sections -O3 -fno-strict-overflow -fwrapv

OpenBenchmarking.orgFPS, More Is BetterOpenVINO 2023.1Model: Handwritten English Recognition FP16-INT8 - Device: CPUc3d-standard-60 AMD Genoat2d-standard-60 AMD Milanc6g.16xlargem7a.16xlarge2004006008001000SE +/- 1.75, N = 3SE +/- 1.37, N = 3SE +/- 0.00, N = 3SE +/- 0.18, N = 3761.14390.722.361158.43-pie-pie-pie1. (CXX) g++ options: -fsigned-char -ffunction-sections -fdata-sections -O3 -fno-strict-overflow -fwrapv
OpenBenchmarking.orgFPS, More Is BetterOpenVINO 2023.1Model: Handwritten English Recognition FP16-INT8 - Device: CPUc3d-standard-60 AMD Genoat2d-standard-60 AMD Milanc6g.16xlargem7a.16xlarge2004006008001000Min: 758.9 / Avg: 761.14 / Max: 764.58Min: 387.99 / Avg: 390.72 / Max: 392.35Min: 2.36 / Avg: 2.36 / Max: 2.36Min: 1158.16 / Avg: 1158.43 / Max: 1158.761. (CXX) g++ options: -fsigned-char -ffunction-sections -fdata-sections -O3 -fno-strict-overflow -fwrapv

OpenBenchmarking.orgFPS, More Is BetterOpenVINO 2023.1Model: Age Gender Recognition Retail 0013 FP16 - Device: CPUc3d-standard-60 AMD Genoat2d-standard-60 AMD Milanc6g.16xlargem7a.16xlarge20K40K60K80K100KSE +/- 18.42, N = 3SE +/- 14.46, N = 3SE +/- 0.39, N = 3SE +/- 31.79, N = 343607.0429668.12178.8281996.81-pie-pie-pie1. (CXX) g++ options: -fsigned-char -ffunction-sections -fdata-sections -O3 -fno-strict-overflow -fwrapv
OpenBenchmarking.orgFPS, More Is BetterOpenVINO 2023.1Model: Age Gender Recognition Retail 0013 FP16 - Device: CPUc3d-standard-60 AMD Genoat2d-standard-60 AMD Milanc6g.16xlargem7a.16xlarge14K28K42K56K70KMin: 43584.18 / Avg: 43607.04 / Max: 43643.5Min: 29641.49 / Avg: 29668.12 / Max: 29691.19Min: 178.05 / Avg: 178.82 / Max: 179.26Min: 81936.96 / Avg: 81996.81 / Max: 82045.321. (CXX) g++ options: -fsigned-char -ffunction-sections -fdata-sections -O3 -fno-strict-overflow -fwrapv

OpenBenchmarking.orgFPS, More Is BetterOpenVINO 2023.1Model: Person Vehicle Bike Detection FP16 - Device: CPUc3d-standard-60 AMD Genoat2d-standard-60 AMD Milanc6g.16xlargem7a.16xlarge7001400210028003500SE +/- 4.38, N = 3SE +/- 3.66, N = 3SE +/- 0.01, N = 3SE +/- 1.10, N = 31764.21633.767.363146.04-pie-pie-pie1. (CXX) g++ options: -fsigned-char -ffunction-sections -fdata-sections -O3 -fno-strict-overflow -fwrapv
OpenBenchmarking.orgFPS, More Is BetterOpenVINO 2023.1Model: Person Vehicle Bike Detection FP16 - Device: CPUc3d-standard-60 AMD Genoat2d-standard-60 AMD Milanc6g.16xlargem7a.16xlarge5001000150020002500Min: 1756.45 / Avg: 1764.21 / Max: 1771.62Min: 627.99 / Avg: 633.76 / Max: 640.55Min: 7.34 / Avg: 7.36 / Max: 7.38Min: 3144.27 / Avg: 3146.04 / Max: 3148.061. (CXX) g++ options: -fsigned-char -ffunction-sections -fdata-sections -O3 -fno-strict-overflow -fwrapv

OpenBenchmarking.orgFPS, More Is BetterOpenVINO 2023.1Model: Road Segmentation ADAS FP16 - Device: CPUc3d-standard-60 AMD Genoat2d-standard-60 AMD Milanc6g.16xlargem7a.16xlarge2004006008001000SE +/- 1.04, N = 3SE +/- 0.93, N = 3SE +/- 0.00, N = 3SE +/- 0.11, N = 3576.94225.482.611049.66-pie-pie-pie1. (CXX) g++ options: -fsigned-char -ffunction-sections -fdata-sections -O3 -fno-strict-overflow -fwrapv
OpenBenchmarking.orgFPS, More Is BetterOpenVINO 2023.1Model: Road Segmentation ADAS FP16 - Device: CPUc3d-standard-60 AMD Genoat2d-standard-60 AMD Milanc6g.16xlargem7a.16xlarge2004006008001000Min: 575.03 / Avg: 576.94 / Max: 578.62Min: 223.89 / Avg: 225.48 / Max: 227.11Min: 2.61 / Avg: 2.61 / Max: 2.62Min: 1049.45 / Avg: 1049.66 / Max: 1049.831. (CXX) g++ options: -fsigned-char -ffunction-sections -fdata-sections -O3 -fno-strict-overflow -fwrapv

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: FT.Cc3d-standard-60 AMD Genoat2d-standard-60 AMD Milanc6g.16xlargem7a.16xlarge20K40K60K80K100KSE +/- 600.19, N = 15SE +/- 137.77, N = 3SE +/- 2.85, N = 3SE +/- 446.85, N = 339647.4754846.1821386.37103413.021. (F9X) gfortran options: -O3 -march=native -lmpi_usempif08 -lmpi_mpifh -lmpi -lopen-rte -lopen-pal -lhwloc -levent_core -levent_pthreads -lm -lz 2. Open MPI 4.1.2
OpenBenchmarking.orgTotal Mop/s, More Is BetterNAS Parallel Benchmarks 3.4Test / Class: FT.Cc3d-standard-60 AMD Genoat2d-standard-60 AMD Milanc6g.16xlargem7a.16xlarge20K40K60K80K100KMin: 38171.82 / Avg: 39647.47 / Max: 44801.35Min: 54635.02 / Avg: 54846.18 / Max: 55105.07Min: 21381 / Avg: 21386.37 / Max: 21390.73Min: 102955.06 / Avg: 103413.02 / Max: 104306.631. (F9X) gfortran options: -O3 -march=native -lmpi_usempif08 -lmpi_mpifh -lmpi -lopen-rte -lopen-pal -lhwloc -levent_core -levent_pthreads -lm -lz 2. Open MPI 4.1.2

TensorFlow

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

OpenBenchmarking.orgimages/sec, More Is BetterTensorFlow 2.12Device: CPU - Batch Size: 64 - Model: ResNet-50c3d-standard-60 AMD Genoat2d-standard-60 AMD Milanm7a.16xlarge20406080100SE +/- 0.07, N = 3SE +/- 0.03, N = 3SE +/- 0.05, N = 369.6820.90100.15
OpenBenchmarking.orgimages/sec, More Is BetterTensorFlow 2.12Device: CPU - Batch Size: 64 - Model: ResNet-50c3d-standard-60 AMD Genoat2d-standard-60 AMD Milanm7a.16xlarge20406080100Min: 69.57 / Avg: 69.68 / Max: 69.81Min: 20.85 / Avg: 20.9 / Max: 20.94Min: 100.06 / Avg: 100.15 / Max: 100.22

Device: CPU - Batch Size: 64 - Model: ResNet-50

c6g.16xlarge: The test quit with a non-zero exit status. E: ModuleNotFoundError: No module named 'absl'

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: MG.Cc3d-standard-60 AMD Genoat2d-standard-60 AMD Milanc6g.16xlargem7a.16xlarge30K60K90K120K150KSE +/- 29.69, N = 3SE +/- 145.06, N = 3SE +/- 10.99, N = 3SE +/- 526.14, N = 342701.8347291.9625661.04121293.801. (F9X) gfortran options: -O3 -march=native -lmpi_usempif08 -lmpi_mpifh -lmpi -lopen-rte -lopen-pal -lhwloc -levent_core -levent_pthreads -lm -lz 2. Open MPI 4.1.2
OpenBenchmarking.orgTotal Mop/s, More Is BetterNAS Parallel Benchmarks 3.4Test / Class: MG.Cc3d-standard-60 AMD Genoat2d-standard-60 AMD Milanc6g.16xlargem7a.16xlarge20K40K60K80K100KMin: 42650.19 / Avg: 42701.83 / Max: 42753.02Min: 47040.34 / Avg: 47291.96 / Max: 47542.83Min: 25642.24 / Avg: 25661.04 / Max: 25680.31Min: 120246.22 / Avg: 121293.8 / Max: 121903.551. (F9X) gfortran options: -O3 -march=native -lmpi_usempif08 -lmpi_mpifh -lmpi -lopen-rte -lopen-pal -lhwloc -levent_core -levent_pthreads -lm -lz 2. Open MPI 4.1.2

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 1.0Encoder Speed: 2c3d-standard-60 AMD Genoat2d-standard-60 AMD Milanc6g.16xlargem7a.16xlarge4080120160200SE +/- 0.11, N = 3SE +/- 0.03, N = 3SE +/- 0.22, N = 3SE +/- 0.22, N = 341.5441.99167.9535.811. (CXX) g++ options: -O3 -fPIC -lm
OpenBenchmarking.orgSeconds, Fewer Is Betterlibavif avifenc 1.0Encoder Speed: 2c3d-standard-60 AMD Genoat2d-standard-60 AMD Milanc6g.16xlargem7a.16xlarge306090120150Min: 41.42 / Avg: 41.54 / Max: 41.75Min: 41.94 / Avg: 41.99 / Max: 42.04Min: 167.72 / Avg: 167.95 / Max: 168.38Min: 35.56 / Avg: 35.81 / Max: 36.241. (CXX) g++ options: -O3 -fPIC -lm

OpenSSL

OpenSSL is an open-source toolkit that implements SSL (Secure Sockets Layer) and TLS (Transport Layer Security) protocols. This test profile makes use of the built-in "openssl speed" benchmarking capabilities. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgbyte/s, More Is BetterOpenSSL 3.1Algorithm: ChaCha20-Poly1305c3d-standard-60 AMD Genoat2d-standard-60 AMD Milanc6g.16xlargem7a.16xlarge50000M100000M150000M200000M250000MSE +/- 3664727.47, N = 3SE +/- 198663058.81, N = 3SE +/- 2259404.37, N = 3SE +/- 85099636.22, N = 312390930477311964772033746715126487216773475533-m64-m64-m641. (CC) gcc options: -pthread -O3 -lssl -lcrypto -ldl
OpenBenchmarking.orgbyte/s, More Is BetterOpenSSL 3.1Algorithm: ChaCha20-Poly1305c3d-standard-60 AMD Genoat2d-standard-60 AMD Milanc6g.16xlargem7a.16xlarge40000M80000M120000M160000M200000MMin: 123902548100 / Avg: 123909304773.33 / Max: 123915143030Min: 119258733230 / Avg: 119647720336.67 / Max: 119912340960Min: 46710776350 / Avg: 46715126486.67 / Max: 46718360780Min: 216656251290 / Avg: 216773475533.33 / Max: 2169389506601. (CC) gcc options: -pthread -O3 -lssl -lcrypto -ldl

OpenBenchmarking.orgverify/s, More Is BetterOpenSSL 3.1Algorithm: RSA4096c3d-standard-60 AMD Genoat2d-standard-60 AMD Milanc6g.16xlargem7a.16xlarge200K400K600K800K1000KSE +/- 50.91, N = 3SE +/- 644.45, N = 3SE +/- 6.55, N = 3SE +/- 367.82, N = 3493077.6860844.6215683.2996017.5-m64-m64-m641. (CC) gcc options: -pthread -O3 -lssl -lcrypto -ldl
OpenBenchmarking.orgverify/s, More Is BetterOpenSSL 3.1Algorithm: RSA4096c3d-standard-60 AMD Genoat2d-standard-60 AMD Milanc6g.16xlargem7a.16xlarge200K400K600K800K1000KMin: 492977.7 / Avg: 493077.6 / Max: 493144.6Min: 859670.9 / Avg: 860844.6 / Max: 861892.7Min: 215670.9 / Avg: 215683.23 / Max: 215693.2Min: 995487.9 / Avg: 996017.53 / Max: 996724.51. (CC) gcc options: -pthread -O3 -lssl -lcrypto -ldl

OpenBenchmarking.orgbyte/s, More Is BetterOpenSSL 3.1Algorithm: ChaCha20c3d-standard-60 AMD Genoat2d-standard-60 AMD Milanc6g.16xlargem7a.16xlarge70000M140000M210000M280000M350000MSE +/- 12326205.97, N = 3SE +/- 47698640.87, N = 3SE +/- 372419.81, N = 3SE +/- 280681661.27, N = 317398094989318024914577067324778360308308045083-m64-m64-m641. (CC) gcc options: -pthread -O3 -lssl -lcrypto -ldl
OpenBenchmarking.orgbyte/s, More Is BetterOpenSSL 3.1Algorithm: ChaCha20c3d-standard-60 AMD Genoat2d-standard-60 AMD Milanc6g.16xlargem7a.16xlarge50000M100000M150000M200000M250000MMin: 173956964900 / Avg: 173980949893.33 / Max: 173997876570Min: 180164591620 / Avg: 180249145770 / Max: 180329677620Min: 67324185260 / Avg: 67324778360 / Max: 67325465120Min: 307864278900 / Avg: 308308045083.33 / Max: 3088276701201. (CC) gcc options: -pthread -O3 -lssl -lcrypto -ldl

TensorFlow

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

OpenBenchmarking.orgimages/sec, More Is BetterTensorFlow 2.12Device: CPU - Batch Size: 32 - Model: ResNet-50c3d-standard-60 AMD Genoat2d-standard-60 AMD Milanm7a.16xlarge20406080100SE +/- 0.10, N = 3SE +/- 0.06, N = 3SE +/- 0.09, N = 362.7420.3687.19
OpenBenchmarking.orgimages/sec, More Is BetterTensorFlow 2.12Device: CPU - Batch Size: 32 - Model: ResNet-50c3d-standard-60 AMD Genoat2d-standard-60 AMD Milanm7a.16xlarge20406080100Min: 62.55 / Avg: 62.74 / Max: 62.84Min: 20.25 / Avg: 20.36 / Max: 20.47Min: 87.01 / Avg: 87.19 / Max: 87.29

Device: CPU - Batch Size: 32 - Model: ResNet-50

c6g.16xlarge: The test quit with a non-zero exit status. E: ModuleNotFoundError: No module named 'absl'

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 1.0Encoder Speed: 0c3d-standard-60 AMD Genoat2d-standard-60 AMD Milanc6g.16xlargem7a.16xlarge60120180240300SE +/- 0.07, N = 3SE +/- 0.08, N = 3SE +/- 0.34, N = 3SE +/- 0.10, N = 378.0778.35270.0765.451. (CXX) g++ options: -O3 -fPIC -lm
OpenBenchmarking.orgSeconds, Fewer Is Betterlibavif avifenc 1.0Encoder Speed: 0c3d-standard-60 AMD Genoat2d-standard-60 AMD Milanc6g.16xlargem7a.16xlarge50100150200250Min: 77.94 / Avg: 78.07 / Max: 78.18Min: 78.26 / Avg: 78.35 / Max: 78.51Min: 269.44 / Avg: 270.07 / Max: 270.58Min: 65.25 / Avg: 65.45 / Max: 65.581. (CXX) g++ options: -O3 -fPIC -lm

OpenSSL

OpenSSL is an open-source toolkit that implements SSL (Secure Sockets Layer) and TLS (Transport Layer Security) protocols. This test profile makes use of the built-in "openssl speed" benchmarking capabilities. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgbyte/s, More Is BetterOpenSSL 3.1Algorithm: AES-256-GCMc3d-standard-60 AMD Genoat2d-standard-60 AMD Milanc6g.16xlargem7a.16xlarge110000M220000M330000M440000M550000MSE +/- 71241287.97, N = 3SE +/- 178290221.71, N = 3SE +/- 2100313.05, N = 3SE +/- 1691817104.57, N = 3293328048497216025967640129198197600522113080527-m64-m64-m641. (CC) gcc options: -pthread -O3 -lssl -lcrypto -ldl
OpenBenchmarking.orgbyte/s, More Is BetterOpenSSL 3.1Algorithm: AES-256-GCMc3d-standard-60 AMD Genoat2d-standard-60 AMD Milanc6g.16xlargem7a.16xlarge90000M180000M270000M360000M450000MMin: 293211079750 / Avg: 293328048496.67 / Max: 293456993480Min: 215696831010 / Avg: 216025967640 / Max: 216309338390Min: 129194047620 / Avg: 129198197600 / Max: 129200835790Min: 518729446740 / Avg: 522113080526.67 / Max: 5238063617401. (CC) gcc options: -pthread -O3 -lssl -lcrypto -ldl

OpenVINO

OpenBenchmarking.orgFPS, More Is BetterOpenVINO 2023.1Model: Weld Porosity Detection FP16 - Device: CPUc3d-standard-60 AMD Genoat2d-standard-60 AMD Milanc6g.16xlargem7a.16xlarge7001400210028003500SE +/- 0.47, N = 3SE +/- 0.56, N = 3SE +/- 0.01, N = 3SE +/- 0.31, N = 31875.281014.708.393132.48-pie-pie-pie1. (CXX) g++ options: -fsigned-char -ffunction-sections -fdata-sections -O3 -fno-strict-overflow -fwrapv
OpenBenchmarking.orgFPS, More Is BetterOpenVINO 2023.1Model: Weld Porosity Detection FP16 - Device: CPUc3d-standard-60 AMD Genoat2d-standard-60 AMD Milanc6g.16xlargem7a.16xlarge5001000150020002500Min: 1874.48 / Avg: 1875.28 / Max: 1876.11Min: 1013.98 / Avg: 1014.7 / Max: 1015.81Min: 8.38 / Avg: 8.39 / Max: 8.4Min: 3131.9 / Avg: 3132.48 / Max: 3132.961. (CXX) g++ options: -fsigned-char -ffunction-sections -fdata-sections -O3 -fno-strict-overflow -fwrapv

OpenBenchmarking.orgFPS, More Is BetterOpenVINO 2023.1Model: Vehicle Detection FP16 - Device: CPUc3d-standard-60 AMD Genoat2d-standard-60 AMD Milanc6g.16xlargem7a.16xlarge5001000150020002500SE +/- 6.33, N = 3SE +/- 1.55, N = 3SE +/- 0.01, N = 3SE +/- 1.65, N = 31389.69368.396.532417.34-pie-pie-pie1. (CXX) g++ options: -fsigned-char -ffunction-sections -fdata-sections -O3 -fno-strict-overflow -fwrapv
OpenBenchmarking.orgFPS, More Is BetterOpenVINO 2023.1Model: Vehicle Detection FP16 - Device: CPUc3d-standard-60 AMD Genoat2d-standard-60 AMD Milanc6g.16xlargem7a.16xlarge400800120016002000Min: 1379.32 / Avg: 1389.69 / Max: 1401.18Min: 366.65 / Avg: 368.39 / Max: 371.49Min: 6.52 / Avg: 6.53 / Max: 6.54Min: 2414.33 / Avg: 2417.34 / Max: 2420.011. (CXX) g++ options: -fsigned-char -ffunction-sections -fdata-sections -O3 -fno-strict-overflow -fwrapv

OpenBenchmarking.orgms, Fewer Is BetterOpenVINO 2023.1Model: Weld Porosity Detection FP16-INT8 - Device: CPUc3d-standard-60 AMD Genoat2d-standard-60 AMD Milanc6g.16xlargem7a.16xlarge4080120160200SE +/- 0.01, N = 3SE +/- 0.01, N = 3SE +/- 0.24, N = 3SE +/- 0.01, N = 38.2011.32181.945.16-isystem -fPIC -fvisibility=hidden -std=c++14 -MD -MT -MF -shared - MIN: 180.71 / MAX: 184.111. (CXX) g++ options: -fsigned-char -ffunction-sections -fdata-sections -O3 -fno-strict-overflow -fwrapv
OpenBenchmarking.orgms, Fewer Is BetterOpenVINO 2023.1Model: Weld Porosity Detection FP16-INT8 - Device: CPUc3d-standard-60 AMD Genoat2d-standard-60 AMD Milanc6g.16xlargem7a.16xlarge306090120150Min: 8.19 / Avg: 8.2 / Max: 8.22Min: 11.3 / Avg: 11.32 / Max: 11.34Min: 181.46 / Avg: 181.94 / Max: 182.27Min: 5.15 / Avg: 5.16 / Max: 5.171. (CXX) g++ options: -fsigned-char -ffunction-sections -fdata-sections -O3 -fno-strict-overflow -fwrapv

OpenBenchmarking.orgFPS, More Is BetterOpenVINO 2023.1Model: Face Detection Retail FP16 - Device: CPUc3d-standard-60 AMD Genoat2d-standard-60 AMD Milanc6g.16xlargem7a.16xlarge15003000450060007500SE +/- 8.74, N = 3SE +/- 15.96, N = 3SE +/- 0.01, N = 3SE +/- 4.07, N = 34166.391285.4720.797222.10-pie-pie-pie1. (CXX) g++ options: -fsigned-char -ffunction-sections -fdata-sections -O3 -fno-strict-overflow -fwrapv
OpenBenchmarking.orgFPS, More Is BetterOpenVINO 2023.1Model: Face Detection Retail FP16 - Device: CPUc3d-standard-60 AMD Genoat2d-standard-60 AMD Milanc6g.16xlargem7a.16xlarge13002600390052006500Min: 4150.59 / Avg: 4166.39 / Max: 4180.76Min: 1254.15 / Avg: 1285.47 / Max: 1306.47Min: 20.77 / Avg: 20.79 / Max: 20.8Min: 7217.47 / Avg: 7222.1 / Max: 7230.221. (CXX) g++ options: -fsigned-char -ffunction-sections -fdata-sections -O3 -fno-strict-overflow -fwrapv

OpenBenchmarking.orgFPS, More Is BetterOpenVINO 2023.1Model: Face Detection FP16 - Device: CPUc3d-standard-60 AMD Genoat2d-standard-60 AMD Milanc6g.16xlargem7a.16xlarge714212835SE +/- 0.01, N = 3SE +/- 0.01, N = 3SE +/- 0.00, N = 3SE +/- 0.01, N = 318.3910.730.1031.72-pie-pie-pie1. (CXX) g++ options: -fsigned-char -ffunction-sections -fdata-sections -O3 -fno-strict-overflow -fwrapv
OpenBenchmarking.orgFPS, More Is BetterOpenVINO 2023.1Model: Face Detection FP16 - Device: CPUc3d-standard-60 AMD Genoat2d-standard-60 AMD Milanc6g.16xlargem7a.16xlarge714212835Min: 18.38 / Avg: 18.39 / Max: 18.4Min: 10.72 / Avg: 10.73 / Max: 10.74Min: 0.1 / Avg: 0.1 / Max: 0.1Min: 31.71 / Avg: 31.72 / Max: 31.731. (CXX) g++ options: -fsigned-char -ffunction-sections -fdata-sections -O3 -fno-strict-overflow -fwrapv

TensorFlow

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

OpenBenchmarking.orgimages/sec, More Is BetterTensorFlow 2.12Device: CPU - Batch Size: 16 - Model: ResNet-50c3d-standard-60 AMD Genoat2d-standard-60 AMD Milanm7a.16xlarge1530456075SE +/- 0.04, N = 3SE +/- 0.05, N = 3SE +/- 0.20, N = 350.9918.2969.55
OpenBenchmarking.orgimages/sec, More Is BetterTensorFlow 2.12Device: CPU - Batch Size: 16 - Model: ResNet-50c3d-standard-60 AMD Genoat2d-standard-60 AMD Milanm7a.16xlarge1326395265Min: 50.94 / Avg: 50.99 / Max: 51.07Min: 18.2 / Avg: 18.29 / Max: 18.35Min: 69.33 / Avg: 69.55 / Max: 69.95

Device: CPU - Batch Size: 16 - Model: ResNet-50

c6g.16xlarge: The test quit with a non-zero exit status. E: ModuleNotFoundError: No module named 'absl'

OpenSSL

OpenSSL is an open-source toolkit that implements SSL (Secure Sockets Layer) and TLS (Transport Layer Security) protocols. This test profile makes use of the built-in "openssl speed" benchmarking capabilities. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgbyte/s, More Is BetterOpenSSL 3.1Algorithm: AES-128-GCMc3d-standard-60 AMD Genoat2d-standard-60 AMD Milanc6g.16xlargem7a.16xlarge130000M260000M390000M520000M650000MSE +/- 342949201.09, N = 3SE +/- 376720190.05, N = 3SE +/- 5537993.15, N = 3SE +/- 1818538727.73, N = 3343095284440234604082610158788510970592545362740-m64-m64-m641. (CC) gcc options: -pthread -O3 -lssl -lcrypto -ldl
OpenBenchmarking.orgbyte/s, More Is BetterOpenSSL 3.1Algorithm: AES-128-GCMc3d-standard-60 AMD Genoat2d-standard-60 AMD Milanc6g.16xlargem7a.16xlarge100000M200000M300000M400000M500000MMin: 342460098150 / Avg: 343095284440 / Max: 343637034330Min: 233868254690 / Avg: 234604082610 / Max: 235112254400Min: 158781697500 / Avg: 158788510970 / Max: 158799480150Min: 589110555170 / Avg: 592545362740 / Max: 5952985377501. (CC) gcc options: -pthread -O3 -lssl -lcrypto -ldl

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 or alternatively an allmodconfig for building all possible kernel modules for the build. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgSeconds, Fewer Is BetterTimed Linux Kernel Compilation 6.1Build: defconfigt2d-standard-60 AMD Milanc6g.16xlargem7a.16xlarge20406080100SE +/- 0.37, N = 5SE +/- 0.82, N = 3SE +/- 0.29, N = 533.40102.2227.71
OpenBenchmarking.orgSeconds, Fewer Is BetterTimed Linux Kernel Compilation 6.1Build: defconfigt2d-standard-60 AMD Milanc6g.16xlargem7a.16xlarge20406080100Min: 32.98 / Avg: 33.4 / Max: 34.87Min: 101.39 / Avg: 102.22 / Max: 103.85Min: 27.39 / Avg: 27.71 / Max: 28.85

Build: defconfig

c3d-standard-60 AMD Genoa: The test quit with a non-zero exit status. E: linux-6.1/tools/objtool/include/objtool/elf.h:10:10: fatal error: gelf.h: No such file or directory

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: EP.Dc3d-standard-60 AMD Genoat2d-standard-60 AMD Milanc6g.16xlargem7a.16xlarge16003200480064008000SE +/- 30.67, N = 3SE +/- 51.21, N = 5SE +/- 7.28, N = 3SE +/- 8.54, N = 33783.604935.682213.767501.761. (F9X) gfortran options: -O3 -march=native -lmpi_usempif08 -lmpi_mpifh -lmpi -lopen-rte -lopen-pal -lhwloc -levent_core -levent_pthreads -lm -lz 2. Open MPI 4.1.2
OpenBenchmarking.orgTotal Mop/s, More Is BetterNAS Parallel Benchmarks 3.4Test / Class: EP.Dc3d-standard-60 AMD Genoat2d-standard-60 AMD Milanc6g.16xlargem7a.16xlarge13002600390052006500Min: 3722.29 / Avg: 3783.6 / Max: 3815.81Min: 4735 / Avg: 4935.68 / Max: 5011.74Min: 2205.13 / Avg: 2213.76 / Max: 2228.23Min: 7484.92 / Avg: 7501.76 / Max: 7512.631. (F9X) gfortran options: -O3 -march=native -lmpi_usempif08 -lmpi_mpifh -lmpi -lopen-rte -lopen-pal -lhwloc -levent_core -levent_pthreads -lm -lz 2. Open MPI 4.1.2

OpenVINO

OpenBenchmarking.orgms, Fewer Is BetterOpenVINO 2023.1Model: Age Gender Recognition Retail 0013 FP16-INT8 - Device: CPUc3d-standard-60 AMD Genoat2d-standard-60 AMD Milanc6g.16xlargem7a.16xlarge246810SE +/- 0.00, N = 3SE +/- 0.00, N = 3SE +/- 0.03, N = 3SE +/- 0.00, N = 30.400.617.330.27-isystem -fPIC -fvisibility=hidden -std=c++14 -MD -MT -MF -shared - MIN: 6.54 / MAX: 9.951. (CXX) g++ options: -fsigned-char -ffunction-sections -fdata-sections -O3 -fno-strict-overflow -fwrapv
OpenBenchmarking.orgms, Fewer Is BetterOpenVINO 2023.1Model: Age Gender Recognition Retail 0013 FP16-INT8 - Device: CPUc3d-standard-60 AMD Genoat2d-standard-60 AMD Milanc6g.16xlargem7a.16xlarge3691215Min: 0.4 / Avg: 0.4 / Max: 0.4Min: 0.6 / Avg: 0.61 / Max: 0.61Min: 7.29 / Avg: 7.33 / Max: 7.38Min: 0.27 / Avg: 0.27 / Max: 0.271. (CXX) g++ options: -fsigned-char -ffunction-sections -fdata-sections -O3 -fno-strict-overflow -fwrapv

OpenBenchmarking.orgFPS, More Is BetterOpenVINO 2023.1Model: Vehicle Detection FP16-INT8 - Device: CPUc3d-standard-60 AMD Genoat2d-standard-60 AMD Milanc6g.16xlargem7a.16xlarge8001600240032004000SE +/- 3.16, N = 3SE +/- 1.12, N = 3SE +/- 0.00, N = 15SE +/- 1.69, N = 32043.051512.570.143666.89-pie-pie-pie1. (CXX) g++ options: -fsigned-char -ffunction-sections -fdata-sections -O3 -fno-strict-overflow -fwrapv
OpenBenchmarking.orgFPS, More Is BetterOpenVINO 2023.1Model: Vehicle Detection FP16-INT8 - Device: CPUc3d-standard-60 AMD Genoat2d-standard-60 AMD Milanc6g.16xlargem7a.16xlarge6001200180024003000Min: 2037.92 / Avg: 2043.05 / Max: 2048.81Min: 1510.65 / Avg: 1512.57 / Max: 1514.53Min: 0.14 / Avg: 0.14 / Max: 0.15Min: 3663.52 / Avg: 3666.89 / Max: 3668.861. (CXX) g++ options: -fsigned-char -ffunction-sections -fdata-sections -O3 -fno-strict-overflow -fwrapv

OpenBenchmarking.orgms, Fewer Is BetterOpenVINO 2023.1Model: Person Vehicle Bike Detection FP16 - Device: CPUc3d-standard-60 AMD Genoat2d-standard-60 AMD Milanc6g.16xlargem7a.16xlarge306090120150SE +/- 0.02, N = 3SE +/- 0.14, N = 3SE +/- 0.21, N = 3SE +/- 0.00, N = 36.7923.64135.875.07-pie - MIN: 9.57 / MAX: 42.22-isystem -fPIC -fvisibility=hidden -std=c++14 -MD -MT -MF -shared - MIN: 132.35 / MAX: 148.641. (CXX) g++ options: -fsigned-char -ffunction-sections -fdata-sections -O3 -fno-strict-overflow -fwrapv
OpenBenchmarking.orgms, Fewer Is BetterOpenVINO 2023.1Model: Person Vehicle Bike Detection FP16 - Device: CPUc3d-standard-60 AMD Genoat2d-standard-60 AMD Milanc6g.16xlargem7a.16xlarge306090120150Min: 6.76 / Avg: 6.79 / Max: 6.82Min: 23.39 / Avg: 23.64 / Max: 23.86Min: 135.56 / Avg: 135.87 / Max: 136.28Min: 5.07 / Avg: 5.07 / Max: 5.081. (CXX) g++ options: -fsigned-char -ffunction-sections -fdata-sections -O3 -fno-strict-overflow -fwrapv

OpenBenchmarking.orgms, Fewer Is BetterOpenVINO 2023.1Model: Road Segmentation ADAS FP16 - Device: CPUc3d-standard-60 AMD Genoat2d-standard-60 AMD Milanc6g.16xlargem7a.16xlarge80160240320400SE +/- 0.04, N = 3SE +/- 0.27, N = 3SE +/- 0.20, N = 3SE +/- 0.00, N = 320.7766.46382.4715.22-pie - MIN: 25.85 / MAX: 122.2-isystem -fPIC -fvisibility=hidden -std=c++14 -MD -MT -MF -shared - MIN: 381.67 / MAX: 383.431. (CXX) g++ options: -fsigned-char -ffunction-sections -fdata-sections -O3 -fno-strict-overflow -fwrapv
OpenBenchmarking.orgms, Fewer Is BetterOpenVINO 2023.1Model: Road Segmentation ADAS FP16 - Device: CPUc3d-standard-60 AMD Genoat2d-standard-60 AMD Milanc6g.16xlargem7a.16xlarge70140210280350Min: 20.71 / Avg: 20.77 / Max: 20.84Min: 65.98 / Avg: 66.46 / Max: 66.93Min: 382.15 / Avg: 382.47 / Max: 382.83Min: 15.22 / Avg: 15.22 / Max: 15.231. (CXX) g++ options: -fsigned-char -ffunction-sections -fdata-sections -O3 -fno-strict-overflow -fwrapv

OpenBenchmarking.orgFPS, More Is BetterOpenVINO 2023.1Model: Machine Translation EN To DE FP16 - Device: CPUc3d-standard-60 AMD Genoat2d-standard-60 AMD Milanc6g.16xlargem7a.16xlarge70140210280350SE +/- 0.25, N = 3SE +/- 0.37, N = 3SE +/- 0.00, N = 3SE +/- 0.11, N = 3185.2996.581.36315.14-pie-pie-pie1. (CXX) g++ options: -fsigned-char -ffunction-sections -fdata-sections -O3 -fno-strict-overflow -fwrapv
OpenBenchmarking.orgFPS, More Is BetterOpenVINO 2023.1Model: Machine Translation EN To DE FP16 - Device: CPUc3d-standard-60 AMD Genoat2d-standard-60 AMD Milanc6g.16xlargem7a.16xlarge60120180240300Min: 184.93 / Avg: 185.29 / Max: 185.76Min: 95.94 / Avg: 96.58 / Max: 97.21Min: 1.36 / Avg: 1.36 / Max: 1.36Min: 314.92 / Avg: 315.14 / Max: 315.261. (CXX) g++ options: -fsigned-char -ffunction-sections -fdata-sections -O3 -fno-strict-overflow -fwrapv

OpenBenchmarking.orgms, Fewer Is BetterOpenVINO 2023.1Model: Vehicle Detection FP16 - Device: CPUc3d-standard-60 AMD Genoat2d-standard-60 AMD Milanc6g.16xlargem7a.16xlarge306090120150SE +/- 0.04, N = 3SE +/- 0.17, N = 3SE +/- 0.09, N = 3SE +/- 0.00, N = 38.6240.67153.126.60-pie - MIN: 12.07 / MAX: 59.44-isystem -fPIC -fvisibility=hidden -std=c++14 -MD -MT -MF -shared - MIN: 152.69 / MAX: 153.751. (CXX) g++ options: -fsigned-char -ffunction-sections -fdata-sections -O3 -fno-strict-overflow -fwrapv
OpenBenchmarking.orgms, Fewer Is BetterOpenVINO 2023.1Model: Vehicle Detection FP16 - Device: CPUc3d-standard-60 AMD Genoat2d-standard-60 AMD Milanc6g.16xlargem7a.16xlarge306090120150Min: 8.55 / Avg: 8.62 / Max: 8.68Min: 40.33 / Avg: 40.67 / Max: 40.86Min: 152.99 / Avg: 153.12 / Max: 153.29Min: 6.6 / Avg: 6.6 / Max: 6.611. (CXX) g++ options: -fsigned-char -ffunction-sections -fdata-sections -O3 -fno-strict-overflow -fwrapv

OpenBenchmarking.orgFPS, More Is BetterOpenVINO 2023.1Model: Face Detection Retail FP16-INT8 - Device: CPUc3d-standard-60 AMD Genoat2d-standard-60 AMD Milanc6g.16xlargem7a.16xlarge2K4K6K8K10KSE +/- 6.52, N = 3SE +/- 2.08, N = 3SE +/- 0.01, N = 3SE +/- 3.60, N = 36605.124239.520.4610382.22-pie-pie-pie1. (CXX) g++ options: -fsigned-char -ffunction-sections -fdata-sections -O3 -fno-strict-overflow -fwrapv
OpenBenchmarking.orgFPS, More Is BetterOpenVINO 2023.1Model: Face Detection Retail FP16-INT8 - Device: CPUc3d-standard-60 AMD Genoat2d-standard-60 AMD Milanc6g.16xlargem7a.16xlarge2K4K6K8K10KMin: 6592.31 / Avg: 6605.12 / Max: 6613.67Min: 4237.32 / Avg: 4239.52 / Max: 4243.67Min: 0.45 / Avg: 0.46 / Max: 0.47Min: 10375.13 / Avg: 10382.22 / Max: 10386.821. (CXX) g++ options: -fsigned-char -ffunction-sections -fdata-sections -O3 -fno-strict-overflow -fwrapv

OpenBenchmarking.orgms, Fewer Is BetterOpenVINO 2023.1Model: Face Detection Retail FP16 - Device: CPUc3d-standard-60 AMD Genoat2d-standard-60 AMD Milanc6g.16xlargem7a.16xlarge1122334455SE +/- 0.01, N = 3SE +/- 0.14, N = 3SE +/- 0.02, N = 3SE +/- 0.00, N = 32.8711.6548.082.21-pie - MIN: 3.76 / MAX: 29.1-isystem -fPIC -fvisibility=hidden -std=c++14 -MD -MT -MF -shared - MIN: 47.55 / MAX: 50.491. (CXX) g++ options: -fsigned-char -ffunction-sections -fdata-sections -O3 -fno-strict-overflow -fwrapv
OpenBenchmarking.orgms, Fewer Is BetterOpenVINO 2023.1Model: Face Detection Retail FP16 - Device: CPUc3d-standard-60 AMD Genoat2d-standard-60 AMD Milanc6g.16xlargem7a.16xlarge1020304050Min: 2.86 / Avg: 2.87 / Max: 2.88Min: 11.46 / Avg: 11.65 / Max: 11.93Min: 48.06 / Avg: 48.08 / Max: 48.13Min: 2.2 / Avg: 2.21 / Max: 2.211. (CXX) g++ options: -fsigned-char -ffunction-sections -fdata-sections -O3 -fno-strict-overflow -fwrapv

PostgreSQL

This is a benchmark of PostgreSQL using the integrated pgbench for facilitating the database benchmarks. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgms, Fewer Is BetterPostgreSQL 16Scaling Factor: 100 - Clients: 1000 - Mode: Read Only - Average Latencyt2d-standard-60 AMD Milanc6g.16xlargem7a.16xlarge0.23090.46180.69270.92361.1545SE +/- 0.006, N = 3SE +/- 0.013, N = 3SE +/- 0.000, N = 30.4981.0260.3471. (CC) gcc options: -fno-strict-aliasing -fwrapv -O2 -lpgcommon -lpgport -lpq -lm
OpenBenchmarking.orgms, Fewer Is BetterPostgreSQL 16Scaling Factor: 100 - Clients: 1000 - Mode: Read Only - Average Latencyt2d-standard-60 AMD Milanc6g.16xlargem7a.16xlarge246810Min: 0.49 / Avg: 0.5 / Max: 0.51Min: 1 / Avg: 1.03 / Max: 1.05Min: 0.35 / Avg: 0.35 / Max: 0.351. (CC) gcc options: -fno-strict-aliasing -fwrapv -O2 -lpgcommon -lpgport -lpq -lm

OpenBenchmarking.orgTPS, More Is BetterPostgreSQL 16Scaling Factor: 100 - Clients: 1000 - Mode: Read Onlyt2d-standard-60 AMD Milanc6g.16xlargem7a.16xlarge600K1200K1800K2400K3000KSE +/- 22497.42, N = 3SE +/- 12606.16, N = 3SE +/- 2874.04, N = 3200818697503128809401. (CC) gcc options: -fno-strict-aliasing -fwrapv -O2 -lpgcommon -lpgport -lpq -lm
OpenBenchmarking.orgTPS, More Is BetterPostgreSQL 16Scaling Factor: 100 - Clients: 1000 - Mode: Read Onlyt2d-standard-60 AMD Milanc6g.16xlargem7a.16xlarge500K1000K1500K2000K2500KMin: 1965900.78 / Avg: 2008186.14 / Max: 2042646.57Min: 955053.13 / Avg: 975030.88 / Max: 998339.41Min: 2875496.58 / Avg: 2880939.91 / Max: 2885260.951. (CC) gcc options: -fno-strict-aliasing -fwrapv -O2 -lpgcommon -lpgport -lpq -lm

Scaling Factor: 100 - Clients: 1000 - Mode: Read Only

c3d-standard-60 AMD Genoa: The test run did not produce a result. E: ./pgbench: 21: pg_/bin/pgbench: not found

OpenBenchmarking.orgTPS, More Is BetterPostgreSQL 16Scaling Factor: 100 - Clients: 800 - Mode: Read Onlyt2d-standard-60 AMD Milanc6g.16xlargem7a.16xlarge600K1200K1800K2400K3000KSE +/- 20558.90, N = 3SE +/- 12058.27, N = 3SE +/- 13309.30, N = 32003784104326729230091. (CC) gcc options: -fno-strict-aliasing -fwrapv -O2 -lpgcommon -lpgport -lpq -lm
OpenBenchmarking.orgTPS, More Is BetterPostgreSQL 16Scaling Factor: 100 - Clients: 800 - Mode: Read Onlyt2d-standard-60 AMD Milanc6g.16xlargem7a.16xlarge500K1000K1500K2000K2500KMin: 1982417.57 / Avg: 2003783.9 / Max: 2044890.99Min: 1019179.32 / Avg: 1043267.49 / Max: 1056324.43Min: 2896398.33 / Avg: 2923009.14 / Max: 2936871.721. (CC) gcc options: -fno-strict-aliasing -fwrapv -O2 -lpgcommon -lpgport -lpq -lm

Scaling Factor: 100 - Clients: 800 - Mode: Read Only

c3d-standard-60 AMD Genoa: The test run did not produce a result. E: ./pgbench: 21: pg_/bin/pgbench: not found

OpenBenchmarking.orgms, Fewer Is BetterPostgreSQL 16Scaling Factor: 100 - Clients: 800 - Mode: Read Only - Average Latencyt2d-standard-60 AMD Milanc6g.16xlargem7a.16xlarge0.17260.34520.51780.69040.863SE +/- 0.004, N = 3SE +/- 0.009, N = 3SE +/- 0.001, N = 30.3990.7670.2741. (CC) gcc options: -fno-strict-aliasing -fwrapv -O2 -lpgcommon -lpgport -lpq -lm
OpenBenchmarking.orgms, Fewer Is BetterPostgreSQL 16Scaling Factor: 100 - Clients: 800 - Mode: Read Only - Average Latencyt2d-standard-60 AMD Milanc6g.16xlargem7a.16xlarge246810Min: 0.39 / Avg: 0.4 / Max: 0.4Min: 0.76 / Avg: 0.77 / Max: 0.79Min: 0.27 / Avg: 0.27 / Max: 0.281. (CC) gcc options: -fno-strict-aliasing -fwrapv -O2 -lpgcommon -lpgport -lpq -lm

GROMACS

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

OpenBenchmarking.orgNs Per Day, More Is BetterGROMACS 2023Implementation: MPI CPU - Input: water_GMX50_barec3d-standard-60 AMD Genoat2d-standard-60 AMD Milanc6g.16xlargem7a.16xlarge246810SE +/- 0.011, N = 3SE +/- 0.005, N = 3SE +/- 0.001, N = 3SE +/- 0.035, N = 34.3915.2892.7667.6551. (CXX) g++ options: -O3
OpenBenchmarking.orgNs Per Day, More Is BetterGROMACS 2023Implementation: MPI CPU - Input: water_GMX50_barec3d-standard-60 AMD Genoat2d-standard-60 AMD Milanc6g.16xlargem7a.16xlarge3691215Min: 4.37 / Avg: 4.39 / Max: 4.41Min: 5.28 / Avg: 5.29 / Max: 5.3Min: 2.76 / Avg: 2.77 / Max: 2.77Min: 7.59 / Avg: 7.65 / Max: 7.711. (CXX) g++ options: -O3

libxsmm

Libxsmm is an open-source library for specialized dense and sparse matrix operations and deep learning primitives. Libxsmm supports making use of Intel AMX, AVX-512, and other modern CPU instruction set capabilities. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgGFLOPS/s, More Is Betterlibxsmm 2-1.17-3645M N K: 32c3d-standard-60 AMD Genoat2d-standard-60 AMD Milanc6g.16xlargem7a.16xlarge140280420560700SE +/- 0.19, N = 3SE +/- 3.60, N = 4SE +/- 0.47, N = 3SE +/- 0.40, N = 3255.4289.2312.7643.4-lquadmath -msse4.2-lquadmath -msse4.2-march=armv8.1-a-lquadmath -msse4.21. (CXX) g++ options: -dynamic -Bstatic -static-libgcc -lgomp -lm -lrt -ldl -lstdc++ -pthread -fPIC -std=c++14 -O2 -fopenmp-simd -funroll-loops -ftree-vectorize -fdata-sections -ffunction-sections -fvisibility=hidden
OpenBenchmarking.orgGFLOPS/s, More Is Betterlibxsmm 2-1.17-3645M N K: 32c3d-standard-60 AMD Genoat2d-standard-60 AMD Milanc6g.16xlargem7a.16xlarge110220330440550Min: 255.2 / Avg: 255.43 / Max: 255.8Min: 278.4 / Avg: 289.18 / Max: 293.4Min: 311.8 / Avg: 312.67 / Max: 313.4Min: 642.7 / Avg: 643.4 / Max: 644.11. (CXX) g++ options: -dynamic -Bstatic -static-libgcc -lgomp -lm -lrt -ldl -lstdc++ -pthread -fPIC -std=c++14 -O2 -fopenmp-simd -funroll-loops -ftree-vectorize -fdata-sections -ffunction-sections -fvisibility=hidden

OpenBenchmarking.orgGFLOPS/s, More Is Betterlibxsmm 2-1.17-3645M N K: 64c3d-standard-60 AMD Genoat2d-standard-60 AMD Milanc6g.16xlargem7a.16xlarge30060090012001500SE +/- 0.12, N = 3SE +/- 0.25, N = 3SE +/- 0.96, N = 3SE +/- 0.52, N = 3489.7554.2589.51201.8-lquadmath -msse4.2-lquadmath -msse4.2-march=armv8.1-a-lquadmath -msse4.21. (CXX) g++ options: -dynamic -Bstatic -static-libgcc -lgomp -lm -lrt -ldl -lstdc++ -pthread -fPIC -std=c++14 -O2 -fopenmp-simd -funroll-loops -ftree-vectorize -fdata-sections -ffunction-sections -fvisibility=hidden
OpenBenchmarking.orgGFLOPS/s, More Is Betterlibxsmm 2-1.17-3645M N K: 64c3d-standard-60 AMD Genoat2d-standard-60 AMD Milanc6g.16xlargem7a.16xlarge2004006008001000Min: 489.5 / Avg: 489.73 / Max: 489.9Min: 553.7 / Avg: 554.2 / Max: 554.5Min: 587.9 / Avg: 589.47 / Max: 591.2Min: 1200.8 / Avg: 1201.83 / Max: 1202.41. (CXX) g++ options: -dynamic -Bstatic -static-libgcc -lgomp -lm -lrt -ldl -lstdc++ -pthread -fPIC -std=c++14 -O2 -fopenmp-simd -funroll-loops -ftree-vectorize -fdata-sections -ffunction-sections -fvisibility=hidden

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 Directionc3d-standard-60 AMD Genoat2d-standard-60 AMD Milanc6g.16xlargem7a.16xlarge714212835SE +/- 0.25, N = 3SE +/- 0.31, N = 12SE +/- 0.01, N = 3SE +/- 0.04, N = 328.0224.5725.8711.591. (F9X) gfortran options: -cpp -O2 -funroll-loops -floop-optimize -fcray-pointer -fbacktrace -lmpi_usempif08 -lmpi_mpifh -lmpi -lopen-rte -lopen-pal -lhwloc -levent_core -levent_pthreads -lm -lz
OpenBenchmarking.orgSeconds, Fewer Is BetterXcompact3d Incompact3d 2021-03-11Input: input.i3d 193 Cells Per Directionc3d-standard-60 AMD Genoat2d-standard-60 AMD Milanc6g.16xlargem7a.16xlarge612182430Min: 27.53 / Avg: 28.02 / Max: 28.3Min: 23.06 / Avg: 24.57 / Max: 26.45Min: 25.85 / Avg: 25.87 / Max: 25.9Min: 11.55 / Avg: 11.59 / Max: 11.671. (F9X) gfortran options: -cpp -O2 -funroll-loops -floop-optimize -fcray-pointer -fbacktrace -lmpi_usempif08 -lmpi_mpifh -lmpi -lopen-rte -lopen-pal -lhwloc -levent_core -levent_pthreads -lm -lz

Remhos

Remhos (REMap High-Order Solver) is a miniapp that solves the pure advection equations that are used to perform monotonic and conservative discontinuous field interpolation (remap) as part of the Eulerian phase in Arbitrary Lagrangian Eulerian (ALE) simulations. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgSeconds, Fewer Is BetterRemhos 1.0Test: Sample Remap Examplec3d-standard-60 AMD Genoat2d-standard-60 AMD Milanc6g.16xlargem7a.16xlarge816243240SE +/- 0.17, N = 3SE +/- 0.05, N = 3SE +/- 0.04, N = 3SE +/- 0.02, N = 333.3616.3320.8213.871. (CXX) g++ options: -O3 -std=c++11 -lmfem -lHYPRE -lmetis -lrt -lmpi_cxx -lmpi
OpenBenchmarking.orgSeconds, Fewer Is BetterRemhos 1.0Test: Sample Remap Examplec3d-standard-60 AMD Genoat2d-standard-60 AMD Milanc6g.16xlargem7a.16xlarge714212835Min: 33.17 / Avg: 33.36 / Max: 33.69Min: 16.24 / Avg: 16.33 / Max: 16.41Min: 20.76 / Avg: 20.82 / Max: 20.9Min: 13.83 / Avg: 13.87 / Max: 13.891. (CXX) g++ options: -O3 -std=c++11 -lmfem -lHYPRE -lmetis -lrt -lmpi_cxx -lmpi

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 Directionc3d-standard-60 AMD Genoat2d-standard-60 AMD Milanc6g.16xlargem7a.16xlarge1.32112.64223.96335.28446.6055SE +/- 0.04970425, N = 3SE +/- 0.02210564, N = 3SE +/- 0.01888616, N = 3SE +/- 0.03993251, N = 35.871578855.630573275.618116862.896026611. (F9X) gfortran options: -cpp -O2 -funroll-loops -floop-optimize -fcray-pointer -fbacktrace -lmpi_usempif08 -lmpi_mpifh -lmpi -lopen-rte -lopen-pal -lhwloc -levent_core -levent_pthreads -lm -lz
OpenBenchmarking.orgSeconds, Fewer Is BetterXcompact3d Incompact3d 2021-03-11Input: input.i3d 129 Cells Per Directionc3d-standard-60 AMD Genoat2d-standard-60 AMD Milanc6g.16xlargem7a.16xlarge246810Min: 5.81 / Avg: 5.87 / Max: 5.97Min: 5.6 / Avg: 5.63 / Max: 5.67Min: 5.58 / Avg: 5.62 / Max: 5.64Min: 2.84 / Avg: 2.9 / Max: 2.971. (F9X) gfortran options: -cpp -O2 -funroll-loops -floop-optimize -fcray-pointer -fbacktrace -lmpi_usempif08 -lmpi_mpifh -lmpi -lopen-rte -lopen-pal -lhwloc -levent_core -levent_pthreads -lm -lz

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 1.2c3d-standard-60 AMD Genoat2d-standard-60 AMD Milanc6g.16xlargem7a.16xlarge400M800M1200M1600M2000MSE +/- 2060519.90, N = 3SE +/- 1088162.98, N = 3SE +/- 176147.98, N = 3SE +/- 1428129.35, N = 3962889833920427767103289366718434443331. (CC) gcc options: -lparcsr_ls -lparcsr_mv -lseq_mv -lIJ_mv -lkrylov -lHYPRE_utilities -lm -fopenmp -lmpi
OpenBenchmarking.orgFigure Of Merit, More Is BetterAlgebraic Multi-Grid Benchmark 1.2c3d-standard-60 AMD Genoat2d-standard-60 AMD Milanc6g.16xlargem7a.16xlarge300M600M900M1200M1500MMin: 958790700 / Avg: 962889833.33 / Max: 965306900Min: 919131100 / Avg: 920427766.67 / Max: 922589800Min: 1032642000 / Avg: 1032893666.67 / Max: 1033233000Min: 1840680000 / Avg: 1843444333.33 / Max: 18454490001. (CC) gcc options: -lparcsr_ls -lparcsr_mv -lseq_mv -lIJ_mv -lkrylov -lHYPRE_utilities -lm -fopenmp -lmpi

OpenVINO

OpenBenchmarking.orgms, Fewer Is BetterOpenVINO 2023.1Model: Face Detection FP16 - Device: CPUc3d-standard-60 AMD Genoat2d-standard-60 AMD Milanc6g.16xlargem7a.16xlarge2K4K6K8K10KSE +/- 0.17, N = 3SE +/- 1.32, N = 3SE +/- 1.02, N = 3SE +/- 0.12, N = 3648.811393.569996.56503.38-isystem -fPIC -fvisibility=hidden -std=c++14 -MD -MT -MF -shared - MIN: 9993.58 / MAX: 10001.761. (CXX) g++ options: -fsigned-char -ffunction-sections -fdata-sections -O3 -fno-strict-overflow -fwrapv
OpenBenchmarking.orgms, Fewer Is BetterOpenVINO 2023.1Model: Face Detection FP16 - Device: CPUc3d-standard-60 AMD Genoat2d-standard-60 AMD Milanc6g.16xlargem7a.16xlarge2K4K6K8K10KMin: 648.53 / Avg: 648.81 / Max: 649.12Min: 1390.92 / Avg: 1393.56 / Max: 1395.09Min: 9994.54 / Avg: 9996.56 / Max: 9997.76Min: 503.24 / Avg: 503.38 / Max: 503.621. (CXX) g++ options: -fsigned-char -ffunction-sections -fdata-sections -O3 -fno-strict-overflow -fwrapv

OpenBenchmarking.orgms, Fewer Is BetterOpenVINO 2023.1Model: Handwritten English Recognition FP16 - Device: CPUc3d-standard-60 AMD Genoat2d-standard-60 AMD Milanc6g.16xlargem7a.16xlarge90180270360450SE +/- 0.02, N = 3SE +/- 0.21, N = 3SE +/- 2.18, N = 3SE +/- 0.01, N = 331.0881.00394.9422.53-pie - MIN: 64.65 / MAX: 134.64-isystem -fPIC -fvisibility=hidden -std=c++14 -MD -MT -MF -shared - MIN: 380.82 / MAX: 408.151. (CXX) g++ options: -fsigned-char -ffunction-sections -fdata-sections -O3 -fno-strict-overflow -fwrapv
OpenBenchmarking.orgms, Fewer Is BetterOpenVINO 2023.1Model: Handwritten English Recognition FP16 - Device: CPUc3d-standard-60 AMD Genoat2d-standard-60 AMD Milanc6g.16xlargem7a.16xlarge70140210280350Min: 31.04 / Avg: 31.08 / Max: 31.11Min: 80.78 / Avg: 81 / Max: 81.42Min: 392.48 / Avg: 394.94 / Max: 399.29Min: 22.51 / Avg: 22.53 / Max: 22.541. (CXX) g++ options: -fsigned-char -ffunction-sections -fdata-sections -O3 -fno-strict-overflow -fwrapv

OpenBenchmarking.orgms, Fewer Is BetterOpenVINO 2023.1Model: Vehicle Detection FP16-INT8 - Device: CPUc3d-standard-60 AMD Genoat2d-standard-60 AMD Milanc6g.16xlargem7a.16xlarge15003000450060007500SE +/- 0.01, N = 3SE +/- 0.01, N = 3SE +/- 27.09, N = 15SE +/- 0.00, N = 35.869.906990.104.35-isystem -fPIC -fvisibility=hidden -std=c++14 -MD -MT -MF -shared - MIN: 6842.82 / MAX: 7088.531. (CXX) g++ options: -fsigned-char -ffunction-sections -fdata-sections -O3 -fno-strict-overflow -fwrapv
OpenBenchmarking.orgms, Fewer Is BetterOpenVINO 2023.1Model: Vehicle Detection FP16-INT8 - Device: CPUc3d-standard-60 AMD Genoat2d-standard-60 AMD Milanc6g.16xlargem7a.16xlarge12002400360048006000Min: 5.84 / Avg: 5.86 / Max: 5.87Min: 9.89 / Avg: 9.9 / Max: 9.91Min: 6845.86 / Avg: 6990.1 / Max: 7087.18Min: 4.35 / Avg: 4.35 / Max: 4.361. (CXX) g++ options: -fsigned-char -ffunction-sections -fdata-sections -O3 -fno-strict-overflow -fwrapv

OpenBenchmarking.orgFPS, More Is BetterOpenVINO 2023.1Model: Face Detection FP16-INT8 - Device: CPUc3d-standard-60 AMD Genoat2d-standard-60 AMD Milanc6g.16xlargem7a.16xlarge1428425670SE +/- 0.02, N = 3SE +/- 0.02, N = 3SE +/- 0.00, N = 3SE +/- 0.00, N = 335.1926.280.0461.19-pie-pie-pie1. (CXX) g++ options: -fsigned-char -ffunction-sections -fdata-sections -O3 -fno-strict-overflow -fwrapv
OpenBenchmarking.orgFPS, More Is BetterOpenVINO 2023.1Model: Face Detection FP16-INT8 - Device: CPUc3d-standard-60 AMD Genoat2d-standard-60 AMD Milanc6g.16xlargem7a.16xlarge1224364860Min: 35.17 / Avg: 35.19 / Max: 35.22Min: 26.25 / Avg: 26.28 / Max: 26.31Min: 0.04 / Avg: 0.04 / Max: 0.04Min: 61.18 / Avg: 61.19 / Max: 61.191. (CXX) g++ options: -fsigned-char -ffunction-sections -fdata-sections -O3 -fno-strict-overflow -fwrapv

OpenBenchmarking.orgms, Fewer Is BetterOpenVINO 2023.1Model: Handwritten English Recognition FP16-INT8 - Device: CPUc3d-standard-60 AMD Genoat2d-standard-60 AMD Milanc6g.16xlargem7a.16xlarge90180270360450SE +/- 0.09, N = 3SE +/- 0.27, N = 3SE +/- 0.26, N = 3SE +/- 0.01, N = 339.3876.72423.9527.60-pie - MIN: 58.8 / MAX: 121.69-isystem -fPIC -fvisibility=hidden -std=c++14 -MD -MT -MF -shared - MIN: 411.17 / MAX: 440.571. (CXX) g++ options: -fsigned-char -ffunction-sections -fdata-sections -O3 -fno-strict-overflow -fwrapv
OpenBenchmarking.orgms, Fewer Is BetterOpenVINO 2023.1Model: Handwritten English Recognition FP16-INT8 - Device: CPUc3d-standard-60 AMD Genoat2d-standard-60 AMD Milanc6g.16xlargem7a.16xlarge80160240320400Min: 39.2 / Avg: 39.38 / Max: 39.5Min: 76.39 / Avg: 76.72 / Max: 77.26Min: 423.43 / Avg: 423.95 / Max: 424.27Min: 27.59 / Avg: 27.6 / Max: 27.611. (CXX) g++ options: -fsigned-char -ffunction-sections -fdata-sections -O3 -fno-strict-overflow -fwrapv

OpenBenchmarking.orgms, Fewer Is BetterOpenVINO 2023.1Model: Age Gender Recognition Retail 0013 FP16 - Device: CPUc3d-standard-60 AMD Genoat2d-standard-60 AMD Milanc6g.16xlargem7a.16xlarge1.25552.5113.76655.0226.2775SE +/- 0.00, N = 3SE +/- 0.00, N = 3SE +/- 0.01, N = 3SE +/- 0.00, N = 30.520.995.580.38-pie - MIN: 0.8 / MAX: 13.76-isystem -fPIC -fvisibility=hidden -std=c++14 -MD -MT -MF -shared - MIN: 5.45 / MAX: 6.481. (CXX) g++ options: -fsigned-char -ffunction-sections -fdata-sections -O3 -fno-strict-overflow -fwrapv
OpenBenchmarking.orgms, Fewer Is BetterOpenVINO 2023.1Model: Age Gender Recognition Retail 0013 FP16 - Device: CPUc3d-standard-60 AMD Genoat2d-standard-60 AMD Milanc6g.16xlargem7a.16xlarge246810Min: 0.52 / Avg: 0.52 / Max: 0.52Min: 0.99 / Avg: 0.99 / Max: 0.99Min: 5.57 / Avg: 5.58 / Max: 5.61Min: 0.38 / Avg: 0.38 / Max: 0.381. (CXX) g++ options: -fsigned-char -ffunction-sections -fdata-sections -O3 -fno-strict-overflow -fwrapv

OpenBenchmarking.orgms, Fewer Is BetterOpenVINO 2023.1Model: Machine Translation EN To DE FP16 - Device: CPUc3d-standard-60 AMD Genoat2d-standard-60 AMD Milanc6g.16xlargem7a.16xlarge160320480640800SE +/- 0.09, N = 3SE +/- 0.58, N = 3SE +/- 0.26, N = 3SE +/- 0.02, N = 364.70155.14735.5850.72-pie - MIN: 114.75 / MAX: 224.64-isystem -fPIC -fvisibility=hidden -std=c++14 -MD -MT -MF -shared - MIN: 734.34 / MAX: 738.231. (CXX) g++ options: -fsigned-char -ffunction-sections -fdata-sections -O3 -fno-strict-overflow -fwrapv
OpenBenchmarking.orgms, Fewer Is BetterOpenVINO 2023.1Model: Machine Translation EN To DE FP16 - Device: CPUc3d-standard-60 AMD Genoat2d-standard-60 AMD Milanc6g.16xlargem7a.16xlarge130260390520650Min: 64.54 / Avg: 64.7 / Max: 64.84Min: 154.15 / Avg: 155.14 / Max: 156.17Min: 735.09 / Avg: 735.58 / Max: 735.98Min: 50.7 / Avg: 50.72 / Max: 50.751. (CXX) g++ options: -fsigned-char -ffunction-sections -fdata-sections -O3 -fno-strict-overflow -fwrapv

OpenBenchmarking.orgFPS, More Is BetterOpenVINO 2023.1Model: Weld Porosity Detection FP16-INT8 - Device: CPUc3d-standard-60 AMD Genoat2d-standard-60 AMD Milanc6g.16xlargem7a.16xlarge13002600390052006500SE +/- 3.28, N = 3SE +/- 3.26, N = 3SE +/- 0.01, N = 3SE +/- 4.43, N = 33650.572646.585.506177.94-pie-pie-pie1. (CXX) g++ options: -fsigned-char -ffunction-sections -fdata-sections -O3 -fno-strict-overflow -fwrapv
OpenBenchmarking.orgFPS, More Is BetterOpenVINO 2023.1Model: Weld Porosity Detection FP16-INT8 - Device: CPUc3d-standard-60 AMD Genoat2d-standard-60 AMD Milanc6g.16xlargem7a.16xlarge11002200330044005500Min: 3644.95 / Avg: 3650.57 / Max: 3656.3Min: 2640.38 / Avg: 2646.58 / Max: 2651.41Min: 5.49 / Avg: 5.5 / Max: 5.51Min: 6169.58 / Avg: 6177.94 / Max: 6184.681. (CXX) g++ options: -fsigned-char -ffunction-sections -fdata-sections -O3 -fno-strict-overflow -fwrapv

OpenSSL

OpenSSL is an open-source toolkit that implements SSL (Secure Sockets Layer) and TLS (Transport Layer Security) protocols. This test profile makes use of the built-in "openssl speed" benchmarking capabilities. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgsign/s, More Is BetterOpenSSL 3.1Algorithm: RSA4096c3d-standard-60 AMD Genoat2d-standard-60 AMD Milanc6g.16xlargem7a.16xlarge7K14K21K28K35KSE +/- 14.62, N = 3SE +/- 11.58, N = 3SE +/- 0.09, N = 3SE +/- 24.57, N = 320079.512973.02640.031583.8-m64-m64-m641. (CC) gcc options: -pthread -O3 -lssl -lcrypto -ldl
OpenBenchmarking.orgsign/s, More Is BetterOpenSSL 3.1Algorithm: RSA4096c3d-standard-60 AMD Genoat2d-standard-60 AMD Milanc6g.16xlargem7a.16xlarge5K10K15K20K25KMin: 20051.8 / Avg: 20079.53 / Max: 20101.4Min: 12954.2 / Avg: 12972.97 / Max: 12994.1Min: 2639.8 / Avg: 2639.97 / Max: 2640.1Min: 31538.6 / Avg: 31583.8 / Max: 31623.11. (CC) gcc options: -pthread -O3 -lssl -lcrypto -ldl

OpenVINO

OpenBenchmarking.orgms, Fewer Is BetterOpenVINO 2023.1Model: Weld Porosity Detection FP16 - Device: CPUc3d-standard-60 AMD Genoat2d-standard-60 AMD Milanc6g.16xlargem7a.16xlarge306090120150SE +/- 0.00, N = 3SE +/- 0.01, N = 3SE +/- 0.07, N = 3SE +/- 0.00, N = 315.9814.76119.1710.19-isystem -fPIC -fvisibility=hidden -std=c++14 -MD -MT -MF -shared - MIN: 118.73 / MAX: 120.211. (CXX) g++ options: -fsigned-char -ffunction-sections -fdata-sections -O3 -fno-strict-overflow -fwrapv
OpenBenchmarking.orgms, Fewer Is BetterOpenVINO 2023.1Model: Weld Porosity Detection FP16 - Device: CPUc3d-standard-60 AMD Genoat2d-standard-60 AMD Milanc6g.16xlargem7a.16xlarge20406080100Min: 15.97 / Avg: 15.98 / Max: 15.98Min: 14.74 / Avg: 14.76 / Max: 14.77Min: 119.04 / Avg: 119.17 / Max: 119.25Min: 10.19 / Avg: 10.19 / Max: 10.191. (CXX) g++ options: -fsigned-char -ffunction-sections -fdata-sections -O3 -fno-strict-overflow -fwrapv

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.Cc3d-standard-60 AMD Genoat2d-standard-60 AMD Milanc6g.16xlargem7a.16xlarge20K40K60K80K100KSE +/- 45.01, N = 3SE +/- 555.92, N = 3SE +/- 0.76, N = 3SE +/- 91.17, N = 339919.7143228.119716.99102392.401. (F9X) gfortran options: -O3 -march=native -lmpi_usempif08 -lmpi_mpifh -lmpi -lopen-rte -lopen-pal -lhwloc -levent_core -levent_pthreads -lm -lz 2. Open MPI 4.1.2
OpenBenchmarking.orgTotal Mop/s, More Is BetterNAS Parallel Benchmarks 3.4Test / Class: SP.Cc3d-standard-60 AMD Genoat2d-standard-60 AMD Milanc6g.16xlargem7a.16xlarge20K40K60K80K100KMin: 39831.19 / Avg: 39919.71 / Max: 39978.2Min: 42116.86 / Avg: 43228.11 / Max: 43815.03Min: 9715.57 / Avg: 9716.99 / Max: 9718.18Min: 102218.96 / Avg: 102392.4 / Max: 102527.851. (F9X) gfortran options: -O3 -march=native -lmpi_usempif08 -lmpi_mpifh -lmpi -lopen-rte -lopen-pal -lhwloc -levent_core -levent_pthreads -lm -lz 2. Open MPI 4.1.2

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 19.8.1Time To Compilec3d-standard-60 AMD Genoat2d-standard-60 AMD Milanc6g.16xlargem7a.16xlarge60120180240300SE +/- 0.29, N = 3SE +/- 0.05, N = 3SE +/- 0.11, N = 3SE +/- 0.11, N = 3198.39191.71286.20154.44
OpenBenchmarking.orgSeconds, Fewer Is BetterTimed Node.js Compilation 19.8.1Time To Compilec3d-standard-60 AMD Genoat2d-standard-60 AMD Milanc6g.16xlargem7a.16xlarge50100150200250Min: 198.04 / Avg: 198.39 / Max: 198.96Min: 191.61 / Avg: 191.71 / Max: 191.79Min: 285.99 / Avg: 286.2 / Max: 286.36Min: 154.26 / Avg: 154.44 / Max: 154.63

OpenSSL

OpenSSL is an open-source toolkit that implements SSL (Secure Sockets Layer) and TLS (Transport Layer Security) protocols. This test profile makes use of the built-in "openssl speed" benchmarking capabilities. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgbyte/s, More Is BetterOpenSSL 3.1Algorithm: SHA512c3d-standard-60 AMD Genoat2d-standard-60 AMD Milanc6g.16xlargem7a.16xlarge6000M12000M18000M24000M30000MSE +/- 4399663.13, N = 3SE +/- 108274834.92, N = 3SE +/- 6214593.12, N = 3SE +/- 29763937.73, N = 314702270573222448041831438491786326481506820-m64-m64-m641. (CC) gcc options: -pthread -O3 -lssl -lcrypto -ldl
OpenBenchmarking.orgbyte/s, More Is BetterOpenSSL 3.1Algorithm: SHA512c3d-standard-60 AMD Genoat2d-standard-60 AMD Milanc6g.16xlargem7a.16xlarge5000M10000M15000M20000M25000MMin: 14693471250 / Avg: 14702270573.33 / Max: 14706676460Min: 22028477780 / Avg: 22244804183.33 / Max: 22361481200Min: 14372505410 / Avg: 14384917863.33 / Max: 14391682440Min: 26425668680 / Avg: 26481506820 / Max: 265272935301. (CC) gcc options: -pthread -O3 -lssl -lcrypto -ldl

OpenRadioss

OpenRadioss is an open-source AGPL-licensed finite element solver for dynamic event analysis OpenRadioss is based on Altair Radioss and open-sourced in 2022. This open-source finite element solver is benchmarked with various example models available from https://www.openradioss.org/models/ and https://github.com/OpenRadioss/ModelExchange/tree/main/Examples. This test is currently using a reference OpenRadioss binary build offered via GitHub. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgSeconds, Fewer Is BetterOpenRadioss 2023.09.15Model: Chrysler Neon 1Mc3d-standard-60 AMD Genoat2d-standard-60 AMD Milanm7a.16xlarge70140210280350SE +/- 2.03, N = 3SE +/- 1.48, N = 3SE +/- 0.61, N = 3337.70327.88190.79
OpenBenchmarking.orgSeconds, Fewer Is BetterOpenRadioss 2023.09.15Model: Chrysler Neon 1Mc3d-standard-60 AMD Genoat2d-standard-60 AMD Milanm7a.16xlarge60120180240300Min: 335.43 / Avg: 337.7 / Max: 341.75Min: 324.94 / Avg: 327.88 / Max: 329.69Min: 189.84 / Avg: 190.79 / Max: 191.92

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 Secondc3d-standard-60 AMD Genoat2d-standard-60 AMD Milanc6g.16xlargem7a.16xlarge500K1000K1500K2000K2500KSE +/- 1295.68, N = 3SE +/- 9191.61, N = 3SE +/- 635.29, N = 3SE +/- 1437.63, N = 31445843.521730658.451259870.722158639.271. (CC) gcc options: -O2 -lrt" -lrt
OpenBenchmarking.orgIterations/Sec, More Is BetterCoremark 1.0CoreMark Size 666 - Iterations Per Secondc3d-standard-60 AMD Genoat2d-standard-60 AMD Milanc6g.16xlargem7a.16xlarge400K800K1200K1600K2000KMin: 1443435.38 / Avg: 1445843.52 / Max: 1447876.45Min: 1718336.08 / Avg: 1730658.45 / Max: 1748633.88Min: 1258603.74 / Avg: 1259870.72 / Max: 1260586.96Min: 2156213.15 / Avg: 2158639.27 / Max: 2161188.651. (CC) gcc options: -O2 -lrt" -lrt

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 1.0Encoder Speed: 6c3d-standard-60 AMD Genoat2d-standard-60 AMD Milanc6g.16xlargem7a.16xlarge1.00512.01023.01534.02045.0255SE +/- 0.007, N = 3SE +/- 0.013, N = 3SE +/- 0.014, N = 3SE +/- 0.015, N = 33.2503.2054.4672.6491. (CXX) g++ options: -O3 -fPIC -lm
OpenBenchmarking.orgSeconds, Fewer Is Betterlibavif avifenc 1.0Encoder Speed: 6c3d-standard-60 AMD Genoat2d-standard-60 AMD Milanc6g.16xlargem7a.16xlarge246810Min: 3.24 / Avg: 3.25 / Max: 3.26Min: 3.19 / Avg: 3.21 / Max: 3.23Min: 4.45 / Avg: 4.47 / Max: 4.5Min: 2.63 / Avg: 2.65 / Max: 2.681. (CXX) g++ options: -O3 -fPIC -lm

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 CFD Solverc3d-standard-60 AMD Genoat2d-standard-60 AMD Milanc6g.16xlargem7a.16xlarge3691215SE +/- 0.013, N = 3SE +/- 0.034, N = 3SE +/- 0.001, N = 3SE +/- 0.007, N = 310.0257.3685.9836.4801. (CXX) g++ options: -O2 -lOpenCL
OpenBenchmarking.orgSeconds, Fewer Is BetterRodinia 3.1Test: OpenMP CFD Solverc3d-standard-60 AMD Genoat2d-standard-60 AMD Milanc6g.16xlargem7a.16xlarge3691215Min: 10 / Avg: 10.03 / Max: 10.05Min: 7.3 / Avg: 7.37 / Max: 7.4Min: 5.98 / Avg: 5.98 / Max: 5.99Min: 6.47 / Avg: 6.48 / Max: 6.491. (CXX) g++ options: -O2 -lOpenCL

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 23Jun2022Model: 20k Atomsc3d-standard-60 AMD Genoat2d-standard-60 AMD Milanc6g.16xlargem7a.16xlarge714212835SE +/- 0.04, N = 3SE +/- 0.05, N = 3SE +/- 0.08, N = 3SE +/- 0.03, N = 319.7826.7325.0631.47-lm-lm-lm1. (CXX) g++ options: -O3 -ldl
OpenBenchmarking.orgns/day, More Is BetterLAMMPS Molecular Dynamics Simulator 23Jun2022Model: 20k Atomsc3d-standard-60 AMD Genoat2d-standard-60 AMD Milanc6g.16xlargem7a.16xlarge714212835Min: 19.72 / Avg: 19.78 / Max: 19.85Min: 26.68 / Avg: 26.73 / Max: 26.83Min: 24.91 / Avg: 25.06 / Max: 25.18Min: 31.42 / Avg: 31.47 / Max: 31.521. (CXX) g++ options: -O3 -ldl

Laghos

Laghos (LAGrangian High-Order Solver) is a miniapp that solves the time-dependent Euler equations of compressible gas dynamics in a moving Lagrangian frame using unstructured high-order finite element spatial discretization and explicit high-order time-stepping. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgMajor Kernels Total Rate, More Is BetterLaghos 3.1Test: Sedov Blast Wave, ube_922_hex.meshc3d-standard-60 AMD Genoat2d-standard-60 AMD Milanc6g.16xlargem7a.16xlarge90180270360450SE +/- 0.31, N = 3SE +/- 0.62, N = 3SE +/- 0.79, N = 3SE +/- 1.29, N = 3259.55364.64321.29409.731. (CXX) g++ options: -O3 -std=c++11 -lmfem -lHYPRE -lmetis -lrt -lmpi_cxx -lmpi
OpenBenchmarking.orgMajor Kernels Total Rate, More Is BetterLaghos 3.1Test: Sedov Blast Wave, ube_922_hex.meshc3d-standard-60 AMD Genoat2d-standard-60 AMD Milanc6g.16xlargem7a.16xlarge70140210280350Min: 259.15 / Avg: 259.55 / Max: 260.15Min: 363.48 / Avg: 364.64 / Max: 365.6Min: 319.98 / Avg: 321.29 / Max: 322.7Min: 407.42 / Avg: 409.73 / Max: 411.891. (CXX) g++ options: -O3 -std=c++11 -lmfem -lHYPRE -lmetis -lrt -lmpi_cxx -lmpi

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 1.0Encoder Speed: 6, Losslessc3d-standard-60 AMD Genoat2d-standard-60 AMD Milanc6g.16xlargem7a.16xlarge246810SE +/- 0.099, N = 3SE +/- 0.031, N = 3SE +/- 0.032, N = 3SE +/- 0.008, N = 36.8897.6398.8795.6781. (CXX) g++ options: -O3 -fPIC -lm
OpenBenchmarking.orgSeconds, Fewer Is Betterlibavif avifenc 1.0Encoder Speed: 6, Losslessc3d-standard-60 AMD Genoat2d-standard-60 AMD Milanc6g.16xlargem7a.16xlarge3691215Min: 6.79 / Avg: 6.89 / Max: 7.09Min: 7.6 / Avg: 7.64 / Max: 7.7Min: 8.84 / Avg: 8.88 / Max: 8.94Min: 5.66 / Avg: 5.68 / Max: 5.691. (CXX) g++ options: -O3 -fPIC -lm

BRL-CAD

BRL-CAD is a cross-platform, open-source solid modeling system with built-in benchmark mode. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgVGR Performance Metric, More Is BetterBRL-CAD 7.36VGR Performance Metricc3d-standard-60 AMD Genoat2d-standard-60 AMD Milanm7a.16xlarge200K400K600K800K1000K5108196293637887041. (CXX) g++ options: -std=c++14 -pipe -fvisibility=hidden -fno-strict-aliasing -fno-common -fexceptions -ftemplate-depth-128 -m64 -ggdb3 -O3 -fipa-pta -fstrength-reduce -finline-functions -flto -ltcl8.6 -lregex_brl -lz_brl -lnetpbm -ldl -lm -ltk8.6

VGR Performance Metric

c6g.16xlarge: The test quit with a non-zero exit status. E: ERROR: Could not find the BRL-CAD raytracer

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 or alternatively an allmodconfig for building all possible kernel modules for the build. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgSeconds, Fewer Is BetterTimed Linux Kernel Compilation 6.1Build: allmodconfigt2d-standard-60 AMD Milanc6g.16xlargem7a.16xlarge90180270360450SE +/- 1.20, N = 3SE +/- 2.41, N = 3SE +/- 0.37, N = 3333.35409.10267.97
OpenBenchmarking.orgSeconds, Fewer Is BetterTimed Linux Kernel Compilation 6.1Build: allmodconfigt2d-standard-60 AMD Milanc6g.16xlargem7a.16xlarge70140210280350Min: 332.12 / Avg: 333.35 / Max: 335.76Min: 406.26 / Avg: 409.1 / Max: 413.89Min: 267.39 / Avg: 267.97 / Max: 268.66

Build: allmodconfig

c3d-standard-60 AMD Genoa: The test quit with a non-zero exit status. E: linux-6.1/tools/objtool/include/objtool/elf.h:10:10: fatal error: gelf.h: No such file or directory

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 LavaMDc3d-standard-60 AMD Genoat2d-standard-60 AMD Milanc6g.16xlargem7a.16xlarge1428425670SE +/- 0.18, N = 3SE +/- 0.13, N = 3SE +/- 0.03, N = 3SE +/- 0.24, N = 364.8650.9762.3043.291. (CXX) g++ options: -O2 -lOpenCL
OpenBenchmarking.orgSeconds, Fewer Is BetterRodinia 3.1Test: OpenMP LavaMDc3d-standard-60 AMD Genoat2d-standard-60 AMD Milanc6g.16xlargem7a.16xlarge1326395265Min: 64.53 / Avg: 64.86 / Max: 65.16Min: 50.72 / Avg: 50.97 / Max: 51.12Min: 62.25 / Avg: 62.3 / Max: 62.35Min: 42.96 / Avg: 43.29 / Max: 43.751. (CXX) g++ options: -O2 -lOpenCL

Apache Cassandra

This is a benchmark of the Apache Cassandra NoSQL database management system making use of cassandra-stress. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgOp/s, More Is BetterApache Cassandra 4.1.3Test: Writesc3d-standard-60 AMD Genoat2d-standard-60 AMD Milanc6g.16xlargem7a.16xlarge60K120K180K240K300KSE +/- 1129.40, N = 3SE +/- 681.76, N = 3SE +/- 3249.94, N = 12SE +/- 352.65, N = 3228640187169217355278585
OpenBenchmarking.orgOp/s, More Is BetterApache Cassandra 4.1.3Test: Writesc3d-standard-60 AMD Genoat2d-standard-60 AMD Milanc6g.16xlargem7a.16xlarge50K100K150K200K250KMin: 227154 / Avg: 228639.67 / Max: 230856Min: 185952 / Avg: 187169 / Max: 188310Min: 189461 / Avg: 217355 / Max: 230058Min: 278128 / Avg: 278585.33 / Max: 279279

OpenSSL

OpenSSL is an open-source toolkit that implements SSL (Secure Sockets Layer) and TLS (Transport Layer Security) protocols. This test profile makes use of the built-in "openssl speed" benchmarking capabilities. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgbyte/s, More Is BetterOpenSSL 3.1Algorithm: SHA256c3d-standard-60 AMD Genoat2d-standard-60 AMD Milanc6g.16xlargem7a.16xlarge13000M26000M39000M52000M65000MSE +/- 9562123.40, N = 3SE +/- 20491615.60, N = 3SE +/- 192235444.29, N = 3SE +/- 161718701.08, N = 346211821313508849971034228851397362253861197-m64-m64-m641. (CC) gcc options: -pthread -O3 -lssl -lcrypto -ldl
OpenBenchmarking.orgbyte/s, More Is BetterOpenSSL 3.1Algorithm: SHA256c3d-standard-60 AMD Genoat2d-standard-60 AMD Milanc6g.16xlargem7a.16xlarge11000M22000M33000M44000M55000MMin: 46197984480 / Avg: 46211821313.33 / Max: 46230172540Min: 50844113450 / Avg: 50884997103.33 / Max: 50907911600Min: 41904076360 / Avg: 42288513973.33 / Max: 42485113330Min: 61930893420 / Avg: 62253861196.67 / Max: 624304340301. (CC) gcc options: -pthread -O3 -lssl -lcrypto -ldl

Timed Gem5 Compilation

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

OpenBenchmarking.orgSeconds, Fewer Is BetterTimed Gem5 Compilation 21.2Time To Compilec3d-standard-60 AMD Genoat2d-standard-60 AMD Milanc6g.16xlargem7a.16xlarge50100150200250SE +/- 0.07, N = 3SE +/- 0.27, N = 3SE +/- 0.03, N = 3SE +/- 0.39, N = 3176.77170.93224.41153.80
OpenBenchmarking.orgSeconds, Fewer Is BetterTimed Gem5 Compilation 21.2Time To Compilec3d-standard-60 AMD Genoat2d-standard-60 AMD Milanc6g.16xlargem7a.16xlarge4080120160200Min: 176.66 / Avg: 176.77 / Max: 176.9Min: 170.55 / Avg: 170.93 / Max: 171.46Min: 224.38 / Avg: 224.41 / Max: 224.48Min: 153.22 / Avg: 153.8 / Max: 154.54

HeFFTe - Highly Efficient FFT for Exascale

HeFFTe is the Highly Efficient FFT for Exascale software developed as part of the Exascale Computing Project. This test profile uses HeFFTe's built-in speed benchmarks under a variety of configuration options and currently catering to CPU/processor testing. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgGFLOP/s, More Is BetterHeFFTe - Highly Efficient FFT for Exascale 2.3Test: c2c - Backend: FFTW - Precision: float - X Y Z: 128c3d-standard-60 AMD Genoat2d-standard-60 AMD Milanc6g.16xlargem7a.16xlarge306090120150SE +/- 0.52, N = 3SE +/- 0.78, N = 3SE +/- 0.11, N = 3SE +/- 1.44, N = 1588.63109.68129.17121.511. (CXX) g++ options: -O3
OpenBenchmarking.orgGFLOP/s, More Is BetterHeFFTe - Highly Efficient FFT for Exascale 2.3Test: c2c - Backend: FFTW - Precision: float - X Y Z: 128c3d-standard-60 AMD Genoat2d-standard-60 AMD Milanc6g.16xlargem7a.16xlarge20406080100Min: 87.59 / Avg: 88.63 / Max: 89.18Min: 108.11 / Avg: 109.68 / Max: 110.47Min: 128.99 / Avg: 129.17 / Max: 129.37Min: 110.47 / Avg: 121.51 / Max: 128.231. (CXX) g++ options: -O3

nginx

This is a benchmark of the lightweight Nginx HTTP(S) web-server. This Nginx web server benchmark test profile makes use of the wrk program for facilitating the HTTP requests over a fixed period time with a configurable number of concurrent clients/connections. HTTPS with a self-signed OpenSSL certificate is used by this test for local benchmarking. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgRequests Per Second, More Is Betternginx 1.23.2Connections: 1000c3d-standard-60 AMD Genoat2d-standard-60 AMD Milanc6g.16xlargem7a.16xlarge50K100K150K200K250KSE +/- 688.79, N = 3SE +/- 156.32, N = 3SE +/- 132.24, N = 3SE +/- 260.28, N = 3180537.84155609.04158700.36224859.091. (CC) gcc options: -lluajit-5.1 -lm -lssl -lcrypto -lpthread -ldl -std=c99 -O2
OpenBenchmarking.orgRequests Per Second, More Is Betternginx 1.23.2Connections: 1000c3d-standard-60 AMD Genoat2d-standard-60 AMD Milanc6g.16xlargem7a.16xlarge40K80K120K160K200KMin: 179226.04 / Avg: 180537.84 / Max: 181558Min: 155316.39 / Avg: 155609.04 / Max: 155850.64Min: 158461.36 / Avg: 158700.36 / Max: 158917.94Min: 224448.59 / Avg: 224859.09 / Max: 225341.561. (CC) gcc options: -lluajit-5.1 -lm -lssl -lcrypto -lpthread -ldl -std=c99 -O2

OpenBenchmarking.orgRequests Per Second, More Is Betternginx 1.23.2Connections: 500c3d-standard-60 AMD Genoat2d-standard-60 AMD Milanc6g.16xlargem7a.16xlarge50K100K150K200K250KSE +/- 126.15, N = 3SE +/- 394.72, N = 3SE +/- 249.05, N = 3SE +/- 451.60, N = 3187350.44162957.75162553.85233014.721. (CC) gcc options: -lluajit-5.1 -lm -lssl -lcrypto -lpthread -ldl -std=c99 -O2
OpenBenchmarking.orgRequests Per Second, More Is Betternginx 1.23.2Connections: 500c3d-standard-60 AMD Genoat2d-standard-60 AMD Milanc6g.16xlargem7a.16xlarge40K80K120K160K200KMin: 187110.72 / Avg: 187350.44 / Max: 187538.43Min: 162237.8 / Avg: 162957.75 / Max: 163598.21Min: 162079.43 / Avg: 162553.85 / Max: 162922.48Min: 232522.08 / Avg: 233014.72 / Max: 233916.651. (CC) gcc options: -lluajit-5.1 -lm -lssl -lcrypto -lpthread -ldl -std=c99 -O2

7-Zip Compression

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

OpenBenchmarking.orgMIPS, More Is Better7-Zip Compression 22.01Test: Compression Ratingc3d-standard-60 AMD Genoat2d-standard-60 AMD Milanc6g.16xlargem7a.16xlarge70K140K210K280K350KSE +/- 346.51, N = 3SE +/- 388.74, N = 3SE +/- 359.95, N = 3SE +/- 400.99, N = 32717952789732397353306331. (CXX) g++ options: -lpthread -ldl -O2 -fPIC
OpenBenchmarking.orgMIPS, More Is Better7-Zip Compression 22.01Test: Compression Ratingc3d-standard-60 AMD Genoat2d-standard-60 AMD Milanc6g.16xlargem7a.16xlarge60K120K180K240K300KMin: 271103 / Avg: 271794.67 / Max: 272178Min: 278561 / Avg: 278973 / Max: 279750Min: 239263 / Avg: 239735.33 / Max: 240442Min: 329942 / Avg: 330633 / Max: 3313311. (CXX) g++ options: -lpthread -ldl -O2 -fPIC

HeFFTe - Highly Efficient FFT for Exascale

HeFFTe is the Highly Efficient FFT for Exascale software developed as part of the Exascale Computing Project. This test profile uses HeFFTe's built-in speed benchmarks under a variety of configuration options and currently catering to CPU/processor testing. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgGFLOP/s, More Is BetterHeFFTe - Highly Efficient FFT for Exascale 2.3Test: r2c - Backend: FFTW - Precision: float - X Y Z: 128c3d-standard-60 AMD Genoat2d-standard-60 AMD Milanc6g.16xlargem7a.16xlarge4080120160200SE +/- 2.19, N = 12SE +/- 0.82, N = 3SE +/- 0.57, N = 3SE +/- 2.16, N = 15148.58196.95202.45190.601. (CXX) g++ options: -O3
OpenBenchmarking.orgGFLOP/s, More Is BetterHeFFTe - Highly Efficient FFT for Exascale 2.3Test: r2c - Backend: FFTW - Precision: float - X Y Z: 128c3d-standard-60 AMD Genoat2d-standard-60 AMD Milanc6g.16xlargem7a.16xlarge4080120160200Min: 138.04 / Avg: 148.58 / Max: 161.92Min: 195.47 / Avg: 196.95 / Max: 198.31Min: 201.49 / Avg: 202.44 / Max: 203.47Min: 182.77 / Avg: 190.6 / Max: 214.051. (CXX) g++ options: -O3

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 Leukocytec3d-standard-60 AMD Genoat2d-standard-60 AMD Milanm7a.16xlarge1020304050SE +/- 0.17, N = 3SE +/- 0.02, N = 3SE +/- 0.32, N = 345.5042.0134.661. (CXX) g++ options: -O2 -lOpenCL
OpenBenchmarking.orgSeconds, Fewer Is BetterRodinia 3.1Test: OpenMP Leukocytec3d-standard-60 AMD Genoat2d-standard-60 AMD Milanm7a.16xlarge918273645Min: 45.18 / Avg: 45.5 / Max: 45.78Min: 41.97 / Avg: 42.01 / Max: 42.05Min: 34.03 / Avg: 34.66 / Max: 35.11. (CXX) g++ options: -O2 -lOpenCL

Test: OpenMP Leukocyte

c6g.16xlarge: The test quit with a non-zero exit status.

Apache IoTDB

Apache IotDB is a time series database and this benchmark is facilitated using the IoT Benchmaark [https://github.com/thulab/iot-benchmark/]. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgpoint/sec, More Is BetterApache IoTDB 1.2Device Count: 500 - Batch Size Per Write: 100 - Sensor Count: 800 - Client Number: 400c3d-standard-60 AMD Genoat2d-standard-60 AMD Milanm7a.16xlarge10M20M30M40M50MSE +/- 188621.29, N = 3SE +/- 221111.93, N = 3SE +/- 224779.59, N = 3347625653492589944502333
OpenBenchmarking.orgpoint/sec, More Is BetterApache IoTDB 1.2Device Count: 500 - Batch Size Per Write: 100 - Sensor Count: 800 - Client Number: 400c3d-standard-60 AMD Genoat2d-standard-60 AMD Milanm7a.16xlarge8M16M24M32M40MMin: 34503885.42 / Avg: 34762564.74 / Max: 35129702.06Min: 34500639.54 / Avg: 34925899.13 / Max: 35243586.87Min: 44055819.24 / Avg: 44502333.03 / Max: 44770830.13

Device Count: 500 - Batch Size Per Write: 100 - Sensor Count: 800 - Client Number: 400

c6g.16xlarge: The test quit with a non-zero exit status.

OpenBenchmarking.orgpoint/sec, More Is BetterApache IoTDB 1.2Device Count: 800 - Batch Size Per Write: 100 - Sensor Count: 800 - Client Number: 400c3d-standard-60 AMD Genoat2d-standard-60 AMD Milanm7a.16xlarge10M20M30M40M50MSE +/- 267152.12, N = 3SE +/- 354923.23, N = 3SE +/- 99649.31, N = 3353598843506855744699315
OpenBenchmarking.orgpoint/sec, More Is BetterApache IoTDB 1.2Device Count: 800 - Batch Size Per Write: 100 - Sensor Count: 800 - Client Number: 400c3d-standard-60 AMD Genoat2d-standard-60 AMD Milanm7a.16xlarge8M16M24M32M40MMin: 34831565.91 / Avg: 35359884.22 / Max: 35693112.85Min: 34680351.11 / Avg: 35068557.46 / Max: 35777328.86Min: 44502724.78 / Avg: 44699315.07 / Max: 44825967.71

Device Count: 800 - Batch Size Per Write: 100 - Sensor Count: 800 - Client Number: 400

c6g.16xlarge: The test quit with a non-zero exit status.

Blender

OpenBenchmarking.orgSeconds, Fewer Is BetterBlender 3.6Blend File: Barbershop - Compute: CPU-Onlyt2d-standard-60 AMD Milanm7a.16xlarge80160240320400SE +/- 0.60, N = 3SE +/- 0.49, N = 3351.58276.23
OpenBenchmarking.orgSeconds, Fewer Is BetterBlender 3.6Blend File: Barbershop - Compute: CPU-Onlyt2d-standard-60 AMD Milanm7a.16xlarge60120180240300Min: 350.6 / Avg: 351.58 / Max: 352.68Min: 275.5 / Avg: 276.23 / Max: 277.16

Blend File: Barbershop - Compute: CPU-Only

c3d-standard-60 AMD Genoa: The test quit with a non-zero exit status.

Apache IoTDB

Apache IotDB is a time series database and this benchmark is facilitated using the IoT Benchmaark [https://github.com/thulab/iot-benchmark/]. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgpoint/sec, More Is BetterApache IoTDB 1.2Device Count: 800 - Batch Size Per Write: 100 - Sensor Count: 500 - Client Number: 400c3d-standard-60 AMD Genoat2d-standard-60 AMD Milanm7a.16xlarge9M18M27M36M45MSE +/- 66565.66, N = 3SE +/- 130588.20, N = 3SE +/- 111073.27, N = 3343322373412381042643903
OpenBenchmarking.orgpoint/sec, More Is BetterApache IoTDB 1.2Device Count: 800 - Batch Size Per Write: 100 - Sensor Count: 500 - Client Number: 400c3d-standard-60 AMD Genoat2d-standard-60 AMD Milanm7a.16xlarge7M14M21M28M35MMin: 34199369.37 / Avg: 34332237.31 / Max: 34405919.84Min: 33867500.37 / Avg: 34123809.65 / Max: 34295426.94Min: 42439023.24 / Avg: 42643902.58 / Max: 42820707.26

Device Count: 800 - Batch Size Per Write: 100 - Sensor Count: 500 - Client Number: 400

c6g.16xlarge: The test quit with a non-zero exit status.

Blender

OpenBenchmarking.orgSeconds, Fewer Is BetterBlender 3.6Blend File: Classroom - Compute: CPU-Onlyt2d-standard-60 AMD Milanm7a.16xlarge20406080100SE +/- 0.07, N = 3SE +/- 0.01, N = 389.3571.51
OpenBenchmarking.orgSeconds, Fewer Is BetterBlender 3.6Blend File: Classroom - Compute: CPU-Onlyt2d-standard-60 AMD Milanm7a.16xlarge20406080100Min: 89.28 / Avg: 89.35 / Max: 89.49Min: 71.49 / Avg: 71.51 / Max: 71.54

Blend File: Classroom - Compute: CPU-Only

c3d-standard-60 AMD Genoa: The test quit with a non-zero exit status.

7-Zip Compression

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

OpenBenchmarking.orgMIPS, More Is Better7-Zip Compression 22.01Test: Decompression Ratingc3d-standard-60 AMD Genoat2d-standard-60 AMD Milanc6g.16xlargem7a.16xlarge60K120K180K240K300KSE +/- 519.21, N = 3SE +/- 347.74, N = 3SE +/- 57.33, N = 3SE +/- 342.37, N = 32262112472552340462825931. (CXX) g++ options: -lpthread -ldl -O2 -fPIC
OpenBenchmarking.orgMIPS, More Is Better7-Zip Compression 22.01Test: Decompression Ratingc3d-standard-60 AMD Genoat2d-standard-60 AMD Milanc6g.16xlargem7a.16xlarge50K100K150K200K250KMin: 225430 / Avg: 226210.67 / Max: 227194Min: 246600 / Avg: 247255 / Max: 247785Min: 233936 / Avg: 234046 / Max: 234129Min: 282213 / Avg: 282592.67 / Max: 2832761. (CXX) g++ options: -lpthread -ldl -O2 -fPIC

Laghos

Laghos (LAGrangian High-Order Solver) is a miniapp that solves the time-dependent Euler equations of compressible gas dynamics in a moving Lagrangian frame using unstructured high-order finite element spatial discretization and explicit high-order time-stepping. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgMajor Kernels Total Rate, More Is BetterLaghos 3.1Test: Triple Point Problemc3d-standard-60 AMD Genoat2d-standard-60 AMD Milanc6g.16xlargem7a.16xlarge50100150200250SE +/- 0.22, N = 3SE +/- 1.77, N = 3SE +/- 0.50, N = 3SE +/- 1.67, N = 3209.00222.30179.52218.861. (CXX) g++ options: -O3 -std=c++11 -lmfem -lHYPRE -lmetis -lrt -lmpi_cxx -lmpi
OpenBenchmarking.orgMajor Kernels Total Rate, More Is BetterLaghos 3.1Test: Triple Point Problemc3d-standard-60 AMD Genoat2d-standard-60 AMD Milanc6g.16xlargem7a.16xlarge4080120160200Min: 208.59 / Avg: 209 / Max: 209.36Min: 218.83 / Avg: 222.3 / Max: 224.61Min: 178.78 / Avg: 179.52 / Max: 180.48Min: 216.51 / Avg: 218.86 / Max: 222.11. (CXX) g++ options: -O3 -std=c++11 -lmfem -lHYPRE -lmetis -lrt -lmpi_cxx -lmpi

Blender

OpenBenchmarking.orgSeconds, Fewer Is BetterBlender 3.6Blend File: BMW27 - Compute: CPU-Onlyt2d-standard-60 AMD Milanm7a.16xlarge816243240SE +/- 0.06, N = 3SE +/- 0.04, N = 334.2727.74
OpenBenchmarking.orgSeconds, Fewer Is BetterBlender 3.6Blend File: BMW27 - Compute: CPU-Onlyt2d-standard-60 AMD Milanm7a.16xlarge714212835Min: 34.19 / Avg: 34.27 / Max: 34.38Min: 27.69 / Avg: 27.74 / Max: 27.82

Blend File: BMW27 - Compute: CPU-Only

c3d-standard-60 AMD Genoa: The test quit with a non-zero exit status.

Apache IoTDB

Apache IotDB is a time series database and this benchmark is facilitated using the IoT Benchmaark [https://github.com/thulab/iot-benchmark/]. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgAverage Latency, Fewer Is BetterApache IoTDB 1.2Device Count: 500 - Batch Size Per Write: 100 - Sensor Count: 500 - Client Number: 400c3d-standard-60 AMD Genoat2d-standard-60 AMD Milanm7a.16xlarge90180270360450SE +/- 2.14, N = 3SE +/- 4.08, N = 3SE +/- 4.92, N = 3418.59415.08340.11MAX: 31920.67MAX: 28810.4MAX: 37899.66
OpenBenchmarking.orgAverage Latency, Fewer Is BetterApache IoTDB 1.2Device Count: 500 - Batch Size Per Write: 100 - Sensor Count: 500 - Client Number: 400c3d-standard-60 AMD Genoat2d-standard-60 AMD Milanm7a.16xlarge70140210280350Min: 415.5 / Avg: 418.59 / Max: 422.71Min: 407.11 / Avg: 415.08 / Max: 420.62Min: 331.69 / Avg: 340.11 / Max: 348.72

Device Count: 500 - Batch Size Per Write: 100 - Sensor Count: 500 - Client Number: 400

c6g.16xlarge: The test quit with a non-zero exit status.

OpenBenchmarking.orgpoint/sec, More Is BetterApache IoTDB 1.2Device Count: 500 - Batch Size Per Write: 100 - Sensor Count: 500 - Client Number: 400c3d-standard-60 AMD Genoat2d-standard-60 AMD Milanm7a.16xlarge9M18M27M36M45MSE +/- 154587.14, N = 3SE +/- 303573.79, N = 3SE +/- 457186.43, N = 3332681583346680440899210
OpenBenchmarking.orgpoint/sec, More Is BetterApache IoTDB 1.2Device Count: 500 - Batch Size Per Write: 100 - Sensor Count: 500 - Client Number: 400c3d-standard-60 AMD Genoat2d-standard-60 AMD Milanm7a.16xlarge7M14M21M28M35MMin: 33054825.84 / Avg: 33268157.73 / Max: 33568624.3Min: 32860342.37 / Avg: 33466803.8 / Max: 33795025.28Min: 39998858.13 / Avg: 40899209.53 / Max: 41487529.37

Device Count: 500 - Batch Size Per Write: 100 - Sensor Count: 500 - Client Number: 400

c6g.16xlarge: The test quit with a non-zero exit status.

Blender

OpenBenchmarking.orgSeconds, Fewer Is BetterBlender 3.6Blend File: Pabellon Barcelona - Compute: CPU-Onlyt2d-standard-60 AMD Milanm7a.16xlarge306090120150SE +/- 0.03, N = 3SE +/- 0.08, N = 3112.6491.88
OpenBenchmarking.orgSeconds, Fewer Is BetterBlender 3.6Blend File: Pabellon Barcelona - Compute: CPU-Onlyt2d-standard-60 AMD Milanm7a.16xlarge20406080100Min: 112.61 / Avg: 112.64 / Max: 112.69Min: 91.73 / Avg: 91.88 / Max: 91.99

Blend File: Pabellon Barcelona - Compute: CPU-Only

c3d-standard-60 AMD Genoa: The test quit with a non-zero exit status.

OpenBenchmarking.orgSeconds, Fewer Is BetterBlender 3.6Blend File: Fishy Cat - Compute: CPU-Onlyt2d-standard-60 AMD Milanm7a.16xlarge1020304050SE +/- 0.13, N = 3SE +/- 0.10, N = 345.2237.12
OpenBenchmarking.orgSeconds, Fewer Is BetterBlender 3.6Blend File: Fishy Cat - Compute: CPU-Onlyt2d-standard-60 AMD Milanm7a.16xlarge918273645Min: 45.03 / Avg: 45.22 / Max: 45.46Min: 36.99 / Avg: 37.12 / Max: 37.31

Blend File: Fishy Cat - Compute: CPU-Only

c3d-standard-60 AMD Genoa: The test quit with a non-zero exit status.

Apache IoTDB

Apache IotDB is a time series database and this benchmark is facilitated using the IoT Benchmaark [https://github.com/thulab/iot-benchmark/]. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgAverage Latency, Fewer Is BetterApache IoTDB 1.2Device Count: 500 - Batch Size Per Write: 100 - Sensor Count: 800 - Client Number: 400c3d-standard-60 AMD Genoat2d-standard-60 AMD Milanm7a.16xlarge140280420560700SE +/- 3.18, N = 3SE +/- 12.58, N = 3SE +/- 0.65, N = 3623.89633.58521.98MAX: 41831.2MAX: 54749.7MAX: 34235.44
OpenBenchmarking.orgAverage Latency, Fewer Is BetterApache IoTDB 1.2Device Count: 500 - Batch Size Per Write: 100 - Sensor Count: 800 - Client Number: 400c3d-standard-60 AMD Genoat2d-standard-60 AMD Milanm7a.16xlarge110220330440550Min: 618.47 / Avg: 623.89 / Max: 629.48Min: 619.85 / Avg: 633.58 / Max: 658.71Min: 521.15 / Avg: 521.98 / Max: 523.27

Device Count: 500 - Batch Size Per Write: 100 - Sensor Count: 800 - Client Number: 400

c6g.16xlarge: The test quit with a non-zero exit status.

PostgreSQL

This is a benchmark of PostgreSQL using the integrated pgbench for facilitating the database benchmarks. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgms, Fewer Is BetterPostgreSQL 16Scaling Factor: 100 - Clients: 1000 - Mode: Read Write - Average Latencyt2d-standard-60 AMD Milanc6g.16xlargem7a.16xlarge50100150200250SE +/- 1.44, N = 8SE +/- 6.00, N = 9SE +/- 0.59, N = 3172.72210.61188.681. (CC) gcc options: -fno-strict-aliasing -fwrapv -O2 -lpgcommon -lpgport -lpq -lm
OpenBenchmarking.orgms, Fewer Is BetterPostgreSQL 16Scaling Factor: 100 - Clients: 1000 - Mode: Read Write - Average Latencyt2d-standard-60 AMD Milanc6g.16xlargem7a.16xlarge4080120160200Min: 163.46 / Avg: 172.72 / Max: 177.16Min: 194.6 / Avg: 210.61 / Max: 251.66Min: 187.92 / Avg: 188.68 / Max: 189.841. (CC) gcc options: -fno-strict-aliasing -fwrapv -O2 -lpgcommon -lpgport -lpq -lm

OpenBenchmarking.orgms, Fewer Is BetterPostgreSQL 16Scaling Factor: 100 - Clients: 800 - Mode: Read Write - Average Latencyt2d-standard-60 AMD Milanc6g.16xlargem7a.16xlarge4080120160200SE +/- 1.23, N = 12SE +/- 3.85, N = 12SE +/- 0.39, N = 3140.92168.19150.601. (CC) gcc options: -fno-strict-aliasing -fwrapv -O2 -lpgcommon -lpgport -lpq -lm
OpenBenchmarking.orgms, Fewer Is BetterPostgreSQL 16Scaling Factor: 100 - Clients: 800 - Mode: Read Write - Average Latencyt2d-standard-60 AMD Milanc6g.16xlargem7a.16xlarge306090120150Min: 133.62 / Avg: 140.92 / Max: 147.85Min: 152.14 / Avg: 168.19 / Max: 192.32Min: 150.05 / Avg: 150.6 / Max: 151.351. (CC) gcc options: -fno-strict-aliasing -fwrapv -O2 -lpgcommon -lpgport -lpq -lm

OpenVINO

OpenBenchmarking.orgms, Fewer Is BetterOpenVINO 2023.1Model: Person Detection FP32 - Device: CPUc3d-standard-60 AMD Genoat2d-standard-60 AMD Milanc6g.16xlargem7a.16xlarge2004006008001000SE +/- 0.29, N = 3SE +/- 7.79, N = 15SE +/- 0.55, N = 3SE +/- 0.06, N = 383.91193.45947.8656.41-pie - MIN: 113.44 / MAX: 315.54-isystem -fPIC -fvisibility=hidden -std=c++14 -MD -MT -MF -shared - MIN: 944.57 / MAX: 958.261. (CXX) g++ options: -fsigned-char -ffunction-sections -fdata-sections -O3 -fno-strict-overflow -fwrapv
OpenBenchmarking.orgms, Fewer Is BetterOpenVINO 2023.1Model: Person Detection FP32 - Device: CPUc3d-standard-60 AMD Genoat2d-standard-60 AMD Milanc6g.16xlargem7a.16xlarge170340510680850Min: 83.42 / Avg: 83.91 / Max: 84.42Min: 171 / Avg: 193.45 / Max: 262.74Min: 947.13 / Avg: 947.86 / Max: 948.94Min: 56.34 / Avg: 56.41 / Max: 56.521. (CXX) g++ options: -fsigned-char -ffunction-sections -fdata-sections -O3 -fno-strict-overflow -fwrapv

OpenBenchmarking.orgFPS, More Is BetterOpenVINO 2023.1Model: Person Detection FP32 - Device: CPUc3d-standard-60 AMD Genoat2d-standard-60 AMD Milanc6g.16xlargem7a.16xlarge60120180240300SE +/- 0.48, N = 3SE +/- 2.74, N = 15SE +/- 0.00, N = 3SE +/- 0.29, N = 3142.9078.961.06283.40-pie-pie-pie1. (CXX) g++ options: -fsigned-char -ffunction-sections -fdata-sections -O3 -fno-strict-overflow -fwrapv
OpenBenchmarking.orgFPS, More Is BetterOpenVINO 2023.1Model: Person Detection FP32 - Device: CPUc3d-standard-60 AMD Genoat2d-standard-60 AMD Milanc6g.16xlargem7a.16xlarge50100150200250Min: 142.05 / Avg: 142.9 / Max: 143.72Min: 56.98 / Avg: 78.96 / Max: 87.6Min: 1.05 / Avg: 1.06 / Max: 1.06Min: 282.83 / Avg: 283.4 / Max: 283.771. (CXX) g++ options: -fsigned-char -ffunction-sections -fdata-sections -O3 -fno-strict-overflow -fwrapv

OpenBenchmarking.orgms, Fewer Is BetterOpenVINO 2023.1Model: Person Detection FP16 - Device: CPUc3d-standard-60 AMD Genoat2d-standard-60 AMD Milanc6g.16xlargem7a.16xlarge2004006008001000SE +/- 0.13, N = 3SE +/- 9.17, N = 15SE +/- 0.37, N = 3SE +/- 0.10, N = 383.99208.47947.5956.21-pie - MIN: 119.65 / MAX: 316.01-isystem -fPIC -fvisibility=hidden -std=c++14 -MD -MT -MF -shared - MIN: 943.57 / MAX: 951.681. (CXX) g++ options: -fsigned-char -ffunction-sections -fdata-sections -O3 -fno-strict-overflow -fwrapv
OpenBenchmarking.orgms, Fewer Is BetterOpenVINO 2023.1Model: Person Detection FP16 - Device: CPUc3d-standard-60 AMD Genoat2d-standard-60 AMD Milanc6g.16xlargem7a.16xlarge170340510680850Min: 83.77 / Avg: 83.99 / Max: 84.23Min: 169.06 / Avg: 208.47 / Max: 262.99Min: 947.11 / Avg: 947.59 / Max: 948.31Min: 56.01 / Avg: 56.21 / Max: 56.341. (CXX) g++ options: -fsigned-char -ffunction-sections -fdata-sections -O3 -fno-strict-overflow -fwrapv

OpenBenchmarking.orgFPS, More Is BetterOpenVINO 2023.1Model: Person Detection FP16 - Device: CPUc3d-standard-60 AMD Genoat2d-standard-60 AMD Milanc6g.16xlargem7a.16xlarge60120180240300SE +/- 0.23, N = 3SE +/- 3.12, N = 15SE +/- 0.00, N = 3SE +/- 0.53, N = 3142.7573.741.06284.42-pie-pie-pie1. (CXX) g++ options: -fsigned-char -ffunction-sections -fdata-sections -O3 -fno-strict-overflow -fwrapv
OpenBenchmarking.orgFPS, More Is BetterOpenVINO 2023.1Model: Person Detection FP16 - Device: CPUc3d-standard-60 AMD Genoat2d-standard-60 AMD Milanc6g.16xlargem7a.16xlarge50100150200250Min: 142.34 / Avg: 142.75 / Max: 143.12Min: 56.94 / Avg: 73.74 / Max: 88.62Min: 1.05 / Avg: 1.06 / Max: 1.06Min: 283.76 / Avg: 284.42 / Max: 285.461. (CXX) g++ options: -fsigned-char -ffunction-sections -fdata-sections -O3 -fno-strict-overflow -fwrapv

PostgreSQL

This is a benchmark of PostgreSQL using the integrated pgbench for facilitating the database benchmarks. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgTPS, More Is BetterPostgreSQL 16Scaling Factor: 100 - Clients: 1000 - Mode: Read Writet2d-standard-60 AMD Milanc6g.16xlargem7a.16xlarge12002400360048006000SE +/- 49.93, N = 8SE +/- 124.50, N = 9SE +/- 16.57, N = 35793477653001. (CC) gcc options: -fno-strict-aliasing -fwrapv -O2 -lpgcommon -lpgport -lpq -lm
OpenBenchmarking.orgTPS, More Is BetterPostgreSQL 16Scaling Factor: 100 - Clients: 1000 - Mode: Read Writet2d-standard-60 AMD Milanc6g.16xlargem7a.16xlarge10002000300040005000Min: 5644.75 / Avg: 5792.74 / Max: 6117.69Min: 3973.61 / Avg: 4776.42 / Max: 5138.82Min: 5267.53 / Avg: 5300.18 / Max: 5321.431. (CC) gcc options: -fno-strict-aliasing -fwrapv -O2 -lpgcommon -lpgport -lpq -lm

Scaling Factor: 100 - Clients: 1000 - Mode: Read Write

c3d-standard-60 AMD Genoa: The test run did not produce a result. E: ./pgbench: 21: pg_/bin/pgbench: not found

OpenBenchmarking.orgTPS, More Is BetterPostgreSQL 16Scaling Factor: 100 - Clients: 800 - Mode: Read Writet2d-standard-60 AMD Milanc6g.16xlargem7a.16xlarge12002400360048006000SE +/- 49.28, N = 12SE +/- 109.40, N = 12SE +/- 13.63, N = 35682478453121. (CC) gcc options: -fno-strict-aliasing -fwrapv -O2 -lpgcommon -lpgport -lpq -lm
OpenBenchmarking.orgTPS, More Is BetterPostgreSQL 16Scaling Factor: 100 - Clients: 800 - Mode: Read Writet2d-standard-60 AMD Milanc6g.16xlargem7a.16xlarge10002000300040005000Min: 5410.93 / Avg: 5681.85 / Max: 5987.25Min: 4159.81 / Avg: 4783.95 / Max: 5258.39Min: 5285.8 / Avg: 5312.14 / Max: 5331.421. (CC) gcc options: -fno-strict-aliasing -fwrapv -O2 -lpgcommon -lpgport -lpq -lm

Scaling Factor: 100 - Clients: 800 - Mode: Read Write

c3d-standard-60 AMD Genoa: The test run did not produce a result. E: ./pgbench: 21: pg_/bin/pgbench: not found

Apache IoTDB

Apache IotDB is a time series database and this benchmark is facilitated using the IoT Benchmaark [https://github.com/thulab/iot-benchmark/]. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgAverage Latency, Fewer Is BetterApache IoTDB 1.2Device Count: 800 - Batch Size Per Write: 100 - Sensor Count: 800 - Client Number: 400c3d-standard-60 AMD Genoat2d-standard-60 AMD Milanm7a.16xlarge150300450600750SE +/- 7.53, N = 3SE +/- 25.87, N = 3SE +/- 4.86, N = 3682.12709.46598.49MAX: 98294.84MAX: 113264.06MAX: 62432.53
OpenBenchmarking.orgAverage Latency, Fewer Is BetterApache IoTDB 1.2Device Count: 800 - Batch Size Per Write: 100 - Sensor Count: 800 - Client Number: 400c3d-standard-60 AMD Genoat2d-standard-60 AMD Milanm7a.16xlarge120240360480600Min: 667.23 / Avg: 682.12 / Max: 691.46Min: 667.86 / Avg: 709.46 / Max: 756.89Min: 591.51 / Avg: 598.49 / Max: 607.85

Device Count: 800 - Batch Size Per Write: 100 - Sensor Count: 800 - Client Number: 400

c6g.16xlarge: The test quit with a non-zero exit status.

OpenBenchmarking.orgAverage Latency, Fewer Is BetterApache IoTDB 1.2Device Count: 800 - Batch Size Per Write: 100 - Sensor Count: 500 - Client Number: 400c3d-standard-60 AMD Genoat2d-standard-60 AMD Milanm7a.16xlarge100200300400500SE +/- 27.08, N = 3SE +/- 35.57, N = 3SE +/- 7.15, N = 3447.68433.96355.13MAX: 95136.87MAX: 103381.73MAX: 67149.77
OpenBenchmarking.orgAverage Latency, Fewer Is BetterApache IoTDB 1.2Device Count: 800 - Batch Size Per Write: 100 - Sensor Count: 500 - Client Number: 400c3d-standard-60 AMD Genoat2d-standard-60 AMD Milanm7a.16xlarge80160240320400Min: 393.9 / Avg: 447.68 / Max: 480.18Min: 371.9 / Avg: 433.96 / Max: 495.11Min: 342.97 / Avg: 355.13 / Max: 367.73

Device Count: 800 - Batch Size Per Write: 100 - Sensor Count: 500 - Client Number: 400

c6g.16xlarge: The test quit with a non-zero exit status.

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 15Total Timec3d-standard-60 AMD Genoat2d-standard-60 AMD Milanc6g.16xlargem7a.16xlarge30M60M90M120M150MSE +/- 1450871.09, N = 3SE +/- 1618403.29, N = 14SE +/- 1645401.81, N = 15SE +/- 1001447.21, N = 310589445711295878881807706135419169-m64 -msse -msse3 -mpopcnt -mavx2 -mavx512f -mavx512bw -mavx512vnni -mavx512dq -mavx512vl -msse4.1 -mssse3 -msse2 -mbmi2-m64 -msse -msse3 -mpopcnt -mavx2 -msse4.1 -mssse3 -msse2 -mbmi2-m64 -msse -msse3 -mpopcnt -mavx2 -mavx512f -mavx512bw -mavx512vnni -mavx512dq -mavx512vl -msse4.1 -mssse3 -msse2 -mbmi21. (CXX) g++ options: -lgcov -lpthread -fno-exceptions -std=c++17 -fno-peel-loops -fno-tracer -pedantic -O3 -flto -flto=jobserver
OpenBenchmarking.orgNodes Per Second, More Is BetterStockfish 15Total Timec3d-standard-60 AMD Genoat2d-standard-60 AMD Milanc6g.16xlargem7a.16xlarge20M40M60M80M100MMin: 103063203 / Avg: 105894456.67 / Max: 107860613Min: 104054980 / Avg: 112958788.21 / Max: 124362514Min: 72392522 / Avg: 81807705.73 / Max: 93109816Min: 133983539 / Avg: 135419169 / Max: 1373464941. (CXX) g++ options: -lgcov -lpthread -fno-exceptions -std=c++17 -fno-peel-loops -fno-tracer -pedantic -O3 -flto -flto=jobserver

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 23Jun2022Model: Rhodopsin Proteinc3d-standard-60 AMD Genoat2d-standard-60 AMD Milanc6g.16xlargem7a.16xlarge816243240SE +/- 0.54, N = 12SE +/- 0.17, N = 3SE +/- 0.04, N = 3SE +/- 0.10, N = 317.4227.8326.0432.79-lm-lm-lm1. (CXX) g++ options: -O3 -ldl
OpenBenchmarking.orgns/day, More Is BetterLAMMPS Molecular Dynamics Simulator 23Jun2022Model: Rhodopsin Proteinc3d-standard-60 AMD Genoat2d-standard-60 AMD Milanc6g.16xlargem7a.16xlarge714212835Min: 15.14 / Avg: 17.42 / Max: 19.61Min: 27.49 / Avg: 27.83 / Max: 28.03Min: 25.96 / Avg: 26.04 / Max: 26.11Min: 32.64 / Avg: 32.79 / Max: 32.981. (CXX) g++ options: -O3 -ldl

nekRS

nekRS is an open-source Navier Stokes solver based on the spectral element method. NekRS supports both CPU and GPU/accelerator support though this test profile is currently configured for CPU execution. NekRS is part of Nek5000 of the Mathematics and Computer Science MCS at Argonne National Laboratory. This nekRS benchmark is primarily relevant to large core count HPC servers and otherwise may be very time consuming on smaller systems. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgflops/rank, More Is BetternekRS 23.0Input: TurboPipe Periodicc3d-standard-60 AMD Genoat2d-standard-60 AMD Milanc6g.16xlargem7a.16xlarge1000M2000M3000M4000M5000MSE +/- 201939132.13, N = 12SE +/- 481352.26, N = 3SE +/- 1790009.31, N = 3SE +/- 6657808.28, N = 347239400002730620000222171000047747966671. (CXX) g++ options: -fopenmp -O2 -march=native -mtune=native -ftree-vectorize -rdynamic -lmpi_cxx -lmpi
OpenBenchmarking.orgflops/rank, More Is BetternekRS 23.0Input: TurboPipe Periodicc3d-standard-60 AMD Genoat2d-standard-60 AMD Milanc6g.16xlargem7a.16xlarge800M1600M2400M3200M4000MMin: 3886310000 / Avg: 4723940000 / Max: 5317680000Min: 2729670000 / Avg: 2730620000 / Max: 2731230000Min: 2218390000 / Avg: 2221710000 / Max: 2224530000Min: 4763910000 / Avg: 4774796666.67 / Max: 47868800001. (CXX) g++ options: -fopenmp -O2 -march=native -mtune=native -ftree-vectorize -rdynamic -lmpi_cxx -lmpi

OpenBenchmarking.orgflops/rank, More Is BetternekRS 23.0Input: Kershawc3d-standard-60 AMD Genoat2d-standard-60 AMD Milanc6g.16xlargem7a.16xlarge1600M3200M4800M6400M8000MSE +/- 57202190.49, N = 12SE +/- 84802173.02, N = 12SE +/- 2970005.61, N = 3SE +/- 49077561.86, N = 342898583333681935833175886000076678466671. (CXX) g++ options: -fopenmp -O2 -march=native -mtune=native -ftree-vectorize -rdynamic -lmpi_cxx -lmpi
OpenBenchmarking.orgflops/rank, More Is BetternekRS 23.0Input: Kershawc3d-standard-60 AMD Genoat2d-standard-60 AMD Milanc6g.16xlargem7a.16xlarge1300M2600M3900M5200M6500MMin: 3970840000 / Avg: 4289858333.33 / Max: 4468840000Min: 2808430000 / Avg: 3681935833.33 / Max: 3868600000Min: 1755880000 / Avg: 1758860000 / Max: 1764800000Min: 7597650000 / Avg: 7667846666.67 / Max: 77623600001. (CXX) g++ options: -fopenmp -O2 -march=native -mtune=native -ftree-vectorize -rdynamic -lmpi_cxx -lmpi

OpenRadioss

OpenRadioss is an open-source AGPL-licensed finite element solver for dynamic event analysis OpenRadioss is based on Altair Radioss and open-sourced in 2022. This open-source finite element solver is benchmarked with various example models available from https://www.openradioss.org/models/ and https://github.com/OpenRadioss/ModelExchange/tree/main/Examples. This test is currently using a reference OpenRadioss binary build offered via GitHub. Learn more via the OpenBenchmarking.org test page.

Model: INIVOL and Fluid Structure Interaction Drop Container

c3d-standard-60 AMD Genoa: The test run did not produce a result. E: ** ERROR: INPUT FILE /fsi_drop_container NOT FOUND

t2d-standard-60 AMD Milan: The test run did not produce a result. E: ** ERROR: INPUT FILE /fsi_drop_container NOT FOUND

m7a.16xlarge: The test run did not produce a result. E: ** ERROR: INPUT FILE /fsi_drop_container_0001.rad NOT FOUND

OpenBenchmarking.orgSeconds, Fewer Is BetterOpenRadioss 2023.09.15Model: Rubber O-Ring Seal Installationc3d-standard-60 AMD Genoat2d-standard-60 AMD Milanm7a.16xlarge20406080100SE +/- 4.01, N = 12SE +/- 0.22, N = 3SE +/- 0.73, N = 389.6572.0659.18
OpenBenchmarking.orgSeconds, Fewer Is BetterOpenRadioss 2023.09.15Model: Rubber O-Ring Seal Installation