AMD EPYC 4th Gen AVX-512 Comparison

AMD EPYC 9654 Genoa AVX-512 benchmark comparison by Michael Larabel for a future article.

Compare your own system(s) to this result file with the Phoronix Test Suite by running the command: phoronix-test-suite benchmark 2212195-NE-AVXCOMPAR69
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AVX-512 On
December 18 2022
  20 Hours, 2 Minutes
AVX-512 Off
December 18 2022
  15 Hours, 29 Minutes
Invert Behavior (Only Show Selected Data)
  17 Hours, 45 Minutes
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AVX-512 On

Kernel Notes: Transparent Huge Pages: madvise
Environment Notes: CXXFLAGS="-O3 -march=native -mavx512f -mavx512cd -mavx512vl -mavx512bw -mavx512dq -mavx512ifma -mavx512vbmi -mprefer-vector-width=512" CFLAGS="-O3 -march=native -mavx512f -mavx512cd -mavx512vl -mavx512bw -mavx512dq -mavx512ifma -mavx512vbmi -mprefer-vector-width=512"
Compiler Notes: --build=x86_64-linux-gnu --disable-vtable-verify --disable-werror --enable-cet --enable-checking=release --enable-clocale=gnu --enable-default-pie --enable-gnu-unique-object --enable-languages=c,ada,c++,go,d,fortran,objc,obj-c++,m2 --enable-libphobos-checking=release --enable-libstdcxx-debug --enable-libstdcxx-time=yes --enable-multiarch --enable-multilib --enable-nls --enable-objc-gc=auto --enable-offload-defaulted --enable-offload-targets=nvptx-none=/build/gcc-12-U8K4Qv/gcc-12-12.2.0/debian/tmp-nvptx/usr,amdgcn-amdhsa=/build/gcc-12-U8K4Qv/gcc-12-12.2.0/debian/tmp-gcn/usr --enable-plugin --enable-shared --enable-threads=posix --host=x86_64-linux-gnu --program-prefix=x86_64-linux-gnu- --target=x86_64-linux-gnu --with-abi=m64 --with-arch-32=i686 --with-default-libstdcxx-abi=new --with-gcc-major-version-only --with-multilib-list=m32,m64,mx32 --with-target-system-zlib=auto --with-tune=generic --without-cuda-driver -v
Processor Notes: Scaling Governor: acpi-cpufreq performance (Boost: Enabled) - CPU Microcode: 0xa10110d
Python Notes: Python 3.10.7
Security Notes: 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

AVX-512 Off

Processor: 2 x AMD EPYC 9654 96-Core @ 2.40GHz (192 Cores / 384 Threads), Motherboard: AMD Titanite_4G (RTI1002E BIOS), Chipset: AMD Device 14a4, Memory: 1520GB, Disk: 800GB INTEL SSDPF21Q800GB, Graphics: ASPEED, Monitor: VGA HDMI, Network: Broadcom NetXtreme BCM5720 PCIe

OS: Ubuntu 22.10, Kernel: 6.1.0-phx (x86_64), Desktop: GNOME Shell 43.0, Display Server: X Server 1.21.1.4, Vulkan: 1.3.224, Compiler: GCC 12.2.0 + Clang 15.0.2-1, File-System: ext4, Screen Resolution: 1920x1080

Kernel Notes: Transparent Huge Pages: madvise
Environment Notes: CXXFLAGS="-O3 -march=native -mno-avx512f" CFLAGS="-O3 -march=native -mno-avx512f"
Compiler Notes: --build=x86_64-linux-gnu --disable-vtable-verify --disable-werror --enable-cet --enable-checking=release --enable-clocale=gnu --enable-default-pie --enable-gnu-unique-object --enable-languages=c,ada,c++,go,d,fortran,objc,obj-c++,m2 --enable-libphobos-checking=release --enable-libstdcxx-debug --enable-libstdcxx-time=yes --enable-multiarch --enable-multilib --enable-nls --enable-objc-gc=auto --enable-offload-defaulted --enable-offload-targets=nvptx-none=/build/gcc-12-U8K4Qv/gcc-12-12.2.0/debian/tmp-nvptx/usr,amdgcn-amdhsa=/build/gcc-12-U8K4Qv/gcc-12-12.2.0/debian/tmp-gcn/usr --enable-plugin --enable-shared --enable-threads=posix --host=x86_64-linux-gnu --program-prefix=x86_64-linux-gnu- --target=x86_64-linux-gnu --with-abi=m64 --with-arch-32=i686 --with-default-libstdcxx-abi=new --with-gcc-major-version-only --with-multilib-list=m32,m64,mx32 --with-target-system-zlib=auto --with-tune=generic --without-cuda-driver -v
Processor Notes: Scaling Governor: acpi-cpufreq performance (Boost: Enabled) - CPU Microcode: 0xa10110d
Python Notes: Python 3.10.7
Security Notes: 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

AMD EPYC 4th Gen AVX-512 ComparisonOpenBenchmarking.orgPhoronix Test Suite2 x AMD EPYC 9654 96-Core @ 2.40GHz (192 Cores / 384 Threads)AMD Titanite_4G (RTI1002E BIOS)AMD Device 14a41520GB800GB INTEL SSDPF21Q800GBASPEEDVGA HDMIBroadcom NetXtreme BCM5720 PCIeUbuntu 22.106.1.0-phx (x86_64)GNOME Shell 43.0X Server 1.21.1.41.3.224GCC 12.2.0 + Clang 15.0.2-1ext41920x1080ProcessorMotherboardChipsetMemoryDiskGraphicsMonitorNetworkOSKernelDesktopDisplay ServerVulkanCompilerFile-SystemScreen ResolutionAMD EPYC 4th Gen AVX-512 Comparison BenchmarksSystem Logs- Transparent Huge Pages: madvise- AVX-512 On: CXXFLAGS="-O3 -march=native -mavx512f -mavx512cd -mavx512vl -mavx512bw -mavx512dq -mavx512ifma -mavx512vbmi -mprefer-vector-width=512" CFLAGS="-O3 -march=native -mavx512f -mavx512cd -mavx512vl -mavx512bw -mavx512dq -mavx512ifma -mavx512vbmi -mprefer-vector-width=512" - AVX-512 Off: CXXFLAGS="-O3 -march=native -mno-avx512f" CFLAGS="-O3 -march=native -mno-avx512f" - --build=x86_64-linux-gnu --disable-vtable-verify --disable-werror --enable-cet --enable-checking=release --enable-clocale=gnu --enable-default-pie --enable-gnu-unique-object --enable-languages=c,ada,c++,go,d,fortran,objc,obj-c++,m2 --enable-libphobos-checking=release --enable-libstdcxx-debug --enable-libstdcxx-time=yes --enable-multiarch --enable-multilib --enable-nls --enable-objc-gc=auto --enable-offload-defaulted --enable-offload-targets=nvptx-none=/build/gcc-12-U8K4Qv/gcc-12-12.2.0/debian/tmp-nvptx/usr,amdgcn-amdhsa=/build/gcc-12-U8K4Qv/gcc-12-12.2.0/debian/tmp-gcn/usr --enable-plugin --enable-shared --enable-threads=posix --host=x86_64-linux-gnu --program-prefix=x86_64-linux-gnu- --target=x86_64-linux-gnu --with-abi=m64 --with-arch-32=i686 --with-default-libstdcxx-abi=new --with-gcc-major-version-only --with-multilib-list=m32,m64,mx32 --with-target-system-zlib=auto --with-tune=generic --without-cuda-driver -v - Scaling Governor: acpi-cpufreq performance (Boost: Enabled) - CPU Microcode: 0xa10110d - Python 3.10.7- 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

AVX-512 On vs. AVX-512 Off ComparisonPhoronix Test SuiteBaseline+46.4%+46.4%+92.8%+92.8%+139.2%+139.2%50.5%37.6%3.6%CPU - 16 - AlexNet185.4%R.N.N.T - bf16bf16bf16 - CPU155.1%D.T.S153.4%R.N.N.T - f32 - CPU152.5%W.P.D.F - CPU143.4%W.P.D.F - CPU143%F.D.F - CPU132.2%F.D.F - CPU131.9%A.G.R.R.0.F - CPU120%LBC, LBRY Credits117%Device AI Score115.1%M.T.E.T.D.F - CPU114.8%M.T.E.T.D.F - CPU114.7%W.P.D.F.I - CPU104.7%W.P.D.F.I - CPU104.5%F.D.F.I - CPU104.2%F.D.F.I - CPU103.9%V.D.F - CPU97.1%V.D.F - CPU97%CPU - 16 - GoogLeNet93.3%D.I.S92.8%V.D.F.I - CPU84.7%V.D.F.I - CPU84.6%D.B.s - f32 - CPU78.2%P.V.B.D.F - CPU76.5%P.V.B.D.F - CPU76.4%CPU - 16 - ResNet-5073.7%gravity_spheres_volume/dim_512/scivis/real_time71.4%Q.S.2.P70.9%P.D.F - CPU70%P.D.F - CPU69.5%P.D.F - CPU68.4%P.D.F - CPU67.7%gravity_spheres_volume/dim_512/ao/real_time67.4%scrypt62.9%A.G.R.R.0.F.I - CPU58.3%resnet-v2-5056.1%N.Q.A.B.b.u.S.1.P - A.M.S55.2%N.Q.A.B.b.u.S.1.P - A.M.S55.2%inception-v3Garlicoin46.5%OpenMP - BM144.1%OpenMP - BM144.1%N.Q.A.B.b.u.S.1.P - S.S.S41.5%N.Q.A.B.b.u.S.1.P - S.S.S41.5%C.C.R.5.I - A.M.S38.5%C.C.R.5.I - A.M.S38.4%R.N.N.I - bf16bf16bf16 - CPUA.G.R.R.0.F - CPU37.4%Skeincoin36.7%OpenMP - BM235.4%OpenMP - BM235.4%gravity_spheres_volume/dim_512/pathtracer/real_time33.8%x25x33.1%DistinctUserID30.7%PartialTweets30.4%C.D.Y.C - A.M.S24.1%C.D.Y.C - A.M.S24%Kostya23.3%2 - 1080p - 32 - Path Tracer23%2 - 4K - 16 - Path Tracer22.8%2 - 1080p - 16 - Path Tracer22.7%1 - 1080p - 32 - Path Tracer22.4%1 - 1080p - 1 - Path Tracer22.3%2 - 4K - 32 - Path Tracer22.2%1 - 4K - 1 - Path Tracer22.2%1 - 4K - 32 - Path Tracer22.1%1 - 4K - 16 - Path Tracer22.1%1 - 1080p - 16 - Path Tracer22%3 - 1080p - 16 - Path Tracer21.7%3 - 1080p - 32 - Path Tracer21.6%TopTweet21.2%3 - 4K - 1 - Path Tracer21.2%LargeRand21.2%N.T.C.B.b.u.S - A.M.S21%3 - 4K - 16 - Path Tracer21%N.T.C.B.b.u.S - A.M.S20.9%3 - 1080p - 1 - Path Tracer20.9%3 - 4K - 32 - Path Tracer20.7%Pathtracer ISPC - Asian Dragon20.4%Pathtracer ISPC - Asian Dragon Obj20.2%C.D.Y.C - S.S.S20.1%C.D.Y.C - S.S.S20.1%Pathtracer ISPC - Crown19.8%2 - 4K - 1 - Path Tracer19.5%2 - 1080p - 1 - Path Tracer19.5%N.T.C.D.m - A.M.S19%d.M.M.S - Execution Time19%N.T.C.D.m - A.M.S19%OpenMP - Points2Image18.7%super-resolution-10 - CPU - Standard17.7%N.T.C.B.b.u.S - S.S.S15.6%N.T.C.B.b.u.S - S.S.S15.6%vklBenchmark ISPC15.3%CPU - vision_transformer15%ArcFace ResNet-100 - CPU - Standard14.5%A.G.R.R.0.F.I - CPU12.8%N.T.C.B.b.u.c - S.S.S12.8%N.T.C.B.b.u.c - S.S.S12.8%N.D.C.o.b.u.o.I - S.S.S12.2%N.D.C.o.b.u.o.I - S.S.S12.2%CPU - blazeface12.1%Eigen11.4%CPU - regnety_400m9.2%F.x.A9.1%CPU - efficientnet-b08.9%fcn-resnet101-11 - CPU - Standard8.4%BLAS7.8%Fayalite-FIST6.7%SqueezeNetV1.06.6%d.M.M.S - Mesh Time6.3%N.T.C.D.m - S.S.S5.4%N.T.C.D.m - S.S.S5.4%Preset 12 - Bosphorus 4K5%4.9%JPEG - 904.6%CPU - googlenet4.6%PNG - 904.5%CPU - mnasnet4.5%B.C4.3%C.B.S.A - f32 - CPU4.2%RTLightmap.hdr.4096x4096bertsquad-12 - CPU - Standard3.4%Windowed Gaussian3.3%CPU - FastestDet3%Preset 13 - Bosphorus 4K2.8%JPEG - 1002.8%OpenMP - NDT Mapping2.7%TensorFlowoneDNNAI Benchmark AlphaoneDNNOpenVINOOpenVINOOpenVINOOpenVINOOpenVINOCpuminer-OptAI Benchmark AlphaOpenVINOOpenVINOOpenVINOOpenVINOOpenVINOOpenVINOOpenVINOOpenVINOTensorFlowAI Benchmark AlphaOpenVINOOpenVINOoneDNNOpenVINOOpenVINOTensorFlowOSPRayCpuminer-OptOpenVINOOpenVINOOpenVINOOpenVINOOSPRayCpuminer-OptOpenVINOMobile Neural NetworkNeural Magic DeepSparseNeural Magic DeepSparseMobile Neural NetworkCpuminer-OptminiBUDEminiBUDENeural Magic DeepSparseNeural Magic DeepSparseNeural Magic DeepSparseNeural Magic DeepSparseoneDNNOpenVINOCpuminer-OptminiBUDEminiBUDEOSPRayCpuminer-OptsimdjsonsimdjsonNeural Magic DeepSparseNeural Magic DeepSparsesimdjsonOSPRay StudioOSPRay StudioOSPRay StudioOSPRay StudioOSPRay StudioOSPRay StudioOSPRay StudioOSPRay StudioOSPRay StudioOSPRay StudioOSPRay StudioOSPRay StudiosimdjsonOSPRay StudiosimdjsonNeural Magic DeepSparseOSPRay StudioNeural Magic DeepSparseOSPRay StudioOSPRay StudioEmbreeEmbreeNeural Magic DeepSparseNeural Magic DeepSparseEmbreeOSPRay StudioOSPRay StudioNeural Magic DeepSparseOpenFOAMNeural Magic DeepSparseDarmstadt Automotive Parallel Heterogeneous SuiteONNX RuntimeNeural Magic DeepSparseNeural Magic DeepSparseOpenVKLNCNNONNX RuntimeOpenVINONeural Magic DeepSparseNeural Magic DeepSparseNeural Magic DeepSparseNeural Magic DeepSparseNCNNLeelaChessZeroNCNNSMHasherNCNNONNX RuntimeLeelaChessZeroCP2K Molecular DynamicsMobile Neural NetworkOpenFOAMNeural Magic DeepSparseNeural Magic DeepSparseSVT-AV1Numpy BenchmarkJPEG XL libjxlNCNNJPEG XL libjxlNCNNNumenta Anomaly BenchmarkoneDNNIntel Open Image DenoiseONNX RuntimeNumenta Anomaly BenchmarkNCNNSVT-AV1JPEG XL libjxlDarmstadt Automotive Parallel Heterogeneous SuiteAVX-512 OnAVX-512 Off

AMD EPYC 4th Gen AVX-512 Comparisontensorflow: CPU - 16 - AlexNetonednn: Recurrent Neural Network Training - bf16bf16bf16 - CPUai-benchmark: Device Training Scoreonednn: Recurrent Neural Network Training - f32 - CPUopenvino: Weld Porosity Detection FP16 - CPUopenvino: Weld Porosity Detection FP16 - CPUopenvino: Face Detection FP16 - CPUopenvino: Face Detection FP16 - CPUopenvino: Age Gender Recognition Retail 0013 FP16 - CPUcpuminer-opt: LBC, LBRY Creditsai-benchmark: Device AI Scoreopenvino: Machine Translation EN To DE FP16 - CPUopenvino: Machine Translation EN To DE FP16 - CPUopenvino: Weld Porosity Detection FP16-INT8 - CPUopenvino: Weld Porosity Detection FP16-INT8 - CPUopenvino: Face Detection FP16-INT8 - CPUopenvino: Face Detection FP16-INT8 - CPUopenvino: Vehicle Detection FP16 - CPUopenvino: Vehicle Detection FP16 - CPUai-benchmark: Device Inference Scoreopenvino: Vehicle Detection FP16-INT8 - CPUopenvino: Vehicle Detection FP16-INT8 - CPUonednn: Deconvolution Batch shapes_3d - f32 - CPUopenvino: Person Vehicle Bike Detection FP16 - CPUopenvino: Person Vehicle Bike Detection FP16 - CPUtensorflow: CPU - 16 - ResNet-50ospray: gravity_spheres_volume/dim_512/scivis/real_timecpuminer-opt: Quad SHA-256, Pyriteopenvino: Person Detection FP16 - CPUopenvino: Person Detection FP16 - CPUopenvino: Person Detection FP32 - CPUopenvino: Person Detection FP32 - CPUospray: gravity_spheres_volume/dim_512/ao/real_timecpuminer-opt: scryptopenvino: Age Gender Recognition Retail 0013 FP16-INT8 - CPUmnn: resnet-v2-50deepsparse: NLP Question Answering, BERT base uncased SQuaD 12layer Pruned90 - Asynchronous Multi-Streamdeepsparse: NLP Question Answering, BERT base uncased SQuaD 12layer Pruned90 - Asynchronous Multi-Streammnn: inception-v3cpuminer-opt: Garlicoinminibude: OpenMP - BM1minibude: OpenMP - BM1deepsparse: NLP Question Answering, BERT base uncased SQuaD 12layer Pruned90 - Synchronous Single-Streamdeepsparse: NLP Question Answering, BERT base uncased SQuaD 12layer Pruned90 - Synchronous Single-Streamdeepsparse: CV Classification, ResNet-50 ImageNet - Asynchronous Multi-Streamdeepsparse: CV Classification, ResNet-50 ImageNet - Asynchronous Multi-Streamonednn: Recurrent Neural Network Inference - bf16bf16bf16 - CPUopenvino: Age Gender Recognition Retail 0013 FP16 - CPUcpuminer-opt: Skeincoinminibude: OpenMP - BM2minibude: OpenMP - BM2ospray: gravity_spheres_volume/dim_512/pathtracer/real_timecpuminer-opt: x25xsimdjson: DistinctUserIDsimdjson: PartialTweetsdeepsparse: CV Detection,YOLOv5s COCO - Asynchronous Multi-Streamdeepsparse: CV Detection,YOLOv5s COCO - Asynchronous Multi-Streamsimdjson: Kostyaospray-studio: 2 - 1080p - 32 - Path Tracerospray-studio: 2 - 4K - 16 - Path Tracerospray-studio: 2 - 1080p - 16 - Path Tracerospray-studio: 1 - 1080p - 32 - Path Tracerospray-studio: 1 - 1080p - 1 - Path Tracerospray-studio: 2 - 4K - 32 - Path Tracerospray-studio: 1 - 4K - 1 - Path Tracerospray-studio: 1 - 4K - 32 - Path Tracerospray-studio: 1 - 4K - 16 - Path Tracerospray-studio: 1 - 1080p - 16 - Path Tracerospray-studio: 3 - 1080p - 16 - Path Tracerospray-studio: 3 - 1080p - 32 - Path Tracersimdjson: TopTweetospray-studio: 3 - 4K - 1 - Path Tracersimdjson: LargeRanddeepsparse: NLP Text Classification, BERT base uncased SST2 - Asynchronous Multi-Streamospray-studio: 3 - 4K - 16 - Path Tracerdeepsparse: NLP Text Classification, BERT base uncased SST2 - Asynchronous Multi-Streamospray-studio: 3 - 1080p - 1 - Path Tracerospray-studio: 3 - 4K - 32 - Path Tracerembree: Pathtracer ISPC - Asian Dragonembree: Pathtracer ISPC - Asian Dragon Objdeepsparse: CV Detection,YOLOv5s COCO - Synchronous Single-Streamdeepsparse: CV Detection,YOLOv5s COCO - Synchronous Single-Streamembree: Pathtracer ISPC - Crownospray-studio: 2 - 4K - 1 - Path Tracerospray-studio: 2 - 1080p - 1 - Path Tracerdeepsparse: NLP Text Classification, DistilBERT mnli - Asynchronous Multi-Streamopenfoam: drivaerFastback, Medium Mesh Size - Execution Timedeepsparse: NLP Text Classification, DistilBERT mnli - Asynchronous Multi-Streamdeepsparse: NLP Text Classification, BERT base uncased SST2 - Synchronous Single-Streamdeepsparse: NLP Text Classification, BERT base uncased SST2 - Synchronous Single-Streamopenvkl: vklBenchmark ISPCopenvino: Age Gender Recognition Retail 0013 FP16-INT8 - CPUdeepsparse: NLP Token Classification, BERT base uncased conll2003 - Synchronous Single-Streamdeepsparse: NLP Token Classification, BERT base uncased conll2003 - Synchronous Single-Streamdeepsparse: NLP Document Classification, oBERT base uncased on IMDB - Synchronous Single-Streamdeepsparse: NLP Document Classification, oBERT base uncased on IMDB - Synchronous Single-Streamncnn: CPU - blazefacelczero: Eigenncnn: CPU - regnety_400msmhasher: FarmHash32 x86_64 AVXncnn: CPU - efficientnet-b0onnx: fcn-resnet101-11 - CPU - Standardlczero: BLAScp2k: Fayalite-FISTmnn: SqueezeNetV1.0openfoam: drivaerFastback, Medium Mesh Size - Mesh Timedeepsparse: NLP Text Classification, DistilBERT mnli - Synchronous Single-Streamdeepsparse: NLP Text Classification, DistilBERT mnli - Synchronous Single-Streamnumpy: jpegxl: JPEG - 90ncnn: CPU - googlenetjpegxl: PNG - 90ncnn: CPU - mnasnetnumenta-nab: Bayesian Changepointonednn: Convolution Batch Shapes Auto - f32 - CPUoidn: RTLightmap.hdr.4096x4096onnx: bertsquad-12 - CPU - Standardnumenta-nab: Windowed Gaussianjpegxl: JPEG - 100daphne: OpenMP - NDT Mappingncnn: CPU - resnet50gromacs: MPI CPU - water_GMX50_barenumenta-nab: Relative Entropyonednn: Deconvolution Batch shapes_1d - f32 - CPUoidn: RT.hdr_alb_nrm.3840x2160oidn: RT.ldr_alb_nrm.3840x2160smhasher: FarmHash32 x86_64 AVXdaphne: OpenMP - Points2Imagesvt-av1: Preset 12 - Bosphorus 4Ksvt-av1: Preset 13 - Bosphorus 4Konnx: ArcFace ResNet-100 - CPU - Standardonnx: super-resolution-10 - CPU - Standardncnn: CPU - FastestDetncnn: CPU - vision_transformertensorflow: CPU - 16 - GoogLeNetAVX-512 OnAVX-512 Off157.291955.3927011962.064.799988.44102.04469.290.551066950621150.11956.8819800.209.63193.93246.987452.966.43351011202.624.280.9895919065.345.2922.1543.0711226068043.341100.2543.341101.0044.15664800.610.3615.441761.2241125.786045.812715537299.545291.982100.54589.940849.03281953.02552361.27148967.981951330346.0818652.00554.21877696.066.866.70857.2265111.72824.184764938523844698148188085811854692712353280456086.526941.26616.680411070155.346217722184212.9364184.4701189.56115.2712180.931560415480.0826113.637331195.936784.998811.75861332170652.7134.520628.960934.251829.189225.889096247.3239794.4457.7127190771122.7258.579135.77418187.08375.3413575.669.5572.809.9542.3016.6770.5161671.665164.7270.741371.1866.3418.7649.89822.58753.513.5126.38713677.764494843245.555246.5721051740158.9574.9360.1755.114989.1310664953.9811.664110.4943.941088.501.214917402887107.62445.599672.9419.6994.97503.503782.0812.6718216065.767.901.763365135.569.3312.7525.1354132296025.501864.9325.741845.9526.37942946.080.5724.098490.3658195.165630.436488275065.096202.60471.043714.065567.91181410.80511715.76108449.491427543255.6616391.51940.51175784.255.255.14690.8722138.58613.39586111524292457491812298571022647113212871341368205.388411.04509.446213398187.854021426785176.8831153.4476157.8196.3313151.055872218495.3347135.216481005.161573.538013.59071155151239.6030.606232.664730.526732.750529.008162270.1236483.7062.8625084231198.4089.146144.3478177.53875.6282548.839.1376.139.5244.1917.3890.5376821.724994.8820.721335.6367.4818.46710.03522.83543.503.5126.41211521.38233.944239.881918628860.7386.1631.12OpenBenchmarking.org

TensorFlow

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

OpenBenchmarking.orgimages/sec, More Is BetterTensorFlow 2.10Device: CPU - Batch Size: 16 - Model: AlexNetAVX-512 OnAVX-512 Off306090120150SE +/- 2.35, N = 12SE +/- 0.19, N = 3157.2955.11
OpenBenchmarking.orgimages/sec Per Watt, More Is BetterTensorFlow 2.10Device: CPU - Batch Size: 16 - Model: AlexNetAVX-512 OnAVX-512 Off0.11810.23620.35430.47240.59050.5250.173
MinAvgMaxAVX-512 On240034583812AVX-512 Off369437324340OpenBenchmarking.orgMegahertz, More Is BetterTensorFlow 2.10CPU Peak Freq (Highest CPU Core Frequency) Monitor11002200330044005500
MinAvgMaxAVX-512 On48.9299.7409.2AVX-512 Off169.7318.9350.5OpenBenchmarking.orgWatts, Fewer Is BetterTensorFlow 2.10CPU Power Consumption Monitor110220330440550
MinAvgMaxAVX-512 On35.040.548.9AVX-512 Off39.041.047.5OpenBenchmarking.orgCelsius, Fewer Is BetterTensorFlow 2.10CPU Temperature Monitor1428425670

oneDNN

OpenBenchmarking.orgms, Fewer Is BetteroneDNN 2.7Harness: Recurrent Neural Network Training - Data Type: bf16bf16bf16 - Engine: CPUAVX-512 OnAVX-512 Off11002200330044005500SE +/- 19.67, N = 15SE +/- 41.71, N = 31955.394989.13-mavx512f -mavx512cd -mavx512vl -mavx512bw -mavx512dq -mavx512ifma -mavx512vbmi - MIN: 1769.7-mno-avx512f - MIN: 4767.221. (CXX) g++ options: -O3 -march=native -fopenmp -msse4.1 -fPIC -pie -ldl -lpthread
OpenBenchmarking.orgMegahertz, More Is BetteroneDNN 2.7CPU Peak Freq (Highest CPU Core Frequency) MonitorAVX-512 OnAVX-512 Off7001400210028003500Min: 2400 / Avg: 3567.66 / Max: 3704Min: 3582 / Avg: 3626.86 / Max: 4223
OpenBenchmarking.orgWatts, Fewer Is BetteroneDNN 2.7CPU Power Consumption MonitorAVX-512 OnAVX-512 Off100200300400500Min: 52.5 / Avg: 419.24 / Max: 543.13Min: 195.71 / Avg: 412.52 / Max: 498.86
OpenBenchmarking.orgCelsius, Fewer Is BetteroneDNN 2.7CPU Temperature MonitorAVX-512 OnAVX-512 Off1020304050Min: 37.75 / Avg: 46.67 / Max: 51.5Min: 42.63 / Avg: 46.63 / Max: 50.63

AI Benchmark Alpha

AI Benchmark Alpha is a Python library for evaluating artificial intelligence (AI) performance on diverse hardware platforms and relies upon the TensorFlow machine learning library. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgScore, More Is BetterAI Benchmark Alpha 0.1.2Device Training ScoreAVX-512 OnAVX-512 Off600120018002400300027011066

oneDNN

OpenBenchmarking.orgms, Fewer Is BetteroneDNN 2.7Harness: Recurrent Neural Network Training - Data Type: f32 - Engine: CPUAVX-512 OnAVX-512 Off11002200330044005500SE +/- 20.13, N = 5SE +/- 60.12, N = 41962.064953.98-mavx512f -mavx512cd -mavx512vl -mavx512bw -mavx512dq -mavx512ifma -mavx512vbmi - MIN: 1899.34-mno-avx512f - MIN: 4690.851. (CXX) g++ options: -O3 -march=native -fopenmp -msse4.1 -fPIC -pie -ldl -lpthread
MinAvgMaxAVX-512 On240035713711AVX-512 Off358136233818OpenBenchmarking.orgMegahertz, More Is BetteroneDNN 2.7CPU Peak Freq (Highest CPU Core Frequency) Monitor10002000300040005000
MinAvgMaxAVX-512 On55.5418.6541.1AVX-512 Off215.2412.5499.6OpenBenchmarking.orgWatts, Fewer Is BetteroneDNN 2.7CPU Power Consumption Monitor140280420560700
MinAvgMaxAVX-512 On35.546.050.6AVX-512 Off38.645.950.1OpenBenchmarking.orgCelsius, Fewer Is BetteroneDNN 2.7CPU Temperature Monitor1428425670

OpenVINO

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

OpenBenchmarking.orgms, Fewer Is BetterOpenVINO 2022.2.devModel: Weld Porosity Detection FP16 - Device: CPUAVX-512 OnAVX-512 Off3691215SE +/- 0.01, N = 3SE +/- 0.01, N = 34.7911.66-mavx512f -mavx512cd -mavx512vl -mavx512bw -mavx512dq -mavx512ifma -mavx512vbmi - MIN: 3.98 / MAX: 28.79-mno-avx512f - MIN: 9.72 / MAX: 43.71. (CXX) g++ options: -fPIC -O3 -march=native -fsigned-char -ffunction-sections -fdata-sections -fno-strict-overflow -fwrapv -flto -shared
MinAvgMaxAVX-512 On240030603695AVX-512 Off267228483946OpenBenchmarking.orgMegahertz, More Is BetterOpenVINO 2022.2.devCPU Peak Freq (Highest CPU Core Frequency) Monitor10002000300040005000
MinAvgMaxAVX-512 On58660712AVX-512 Off221598639OpenBenchmarking.orgWatts, Fewer Is BetterOpenVINO 2022.2.devCPU Power Consumption Monitor2004006008001000
MinAvgMaxAVX-512 On43.060.964.5AVX-512 Off49.860.061.8OpenBenchmarking.orgCelsius, Fewer Is BetterOpenVINO 2022.2.devCPU Temperature Monitor20406080100

OpenBenchmarking.orgFPS, More Is BetterOpenVINO 2022.2.devModel: Weld Porosity Detection FP16 - Device: CPUAVX-512 OnAVX-512 Off2K4K6K8K10KSE +/- 6.96, N = 3SE +/- 4.29, N = 39988.444110.49-mavx512f -mavx512cd -mavx512vl -mavx512bw -mavx512dq -mavx512ifma -mavx512vbmi-mno-avx512f1. (CXX) g++ options: -fPIC -O3 -march=native -fsigned-char -ffunction-sections -fdata-sections -fno-strict-overflow -fwrapv -flto -shared

OpenBenchmarking.orgFPS, More Is BetterOpenVINO 2022.2.devModel: Face Detection FP16 - Device: CPUAVX-512 OnAVX-512 Off20406080100SE +/- 0.07, N = 3SE +/- 0.01, N = 3102.0443.94-mavx512f -mavx512cd -mavx512vl -mavx512bw -mavx512dq -mavx512ifma -mavx512vbmi-mno-avx512f1. (CXX) g++ options: -fPIC -O3 -march=native -fsigned-char -ffunction-sections -fdata-sections -fno-strict-overflow -fwrapv -flto -shared

OpenBenchmarking.orgms, Fewer Is BetterOpenVINO 2022.2.devModel: Face Detection FP16 - Device: CPUAVX-512 OnAVX-512 Off2004006008001000SE +/- 0.24, N = 3SE +/- 0.51, N = 3469.291088.50-mavx512f -mavx512cd -mavx512vl -mavx512bw -mavx512dq -mavx512ifma -mavx512vbmi - MIN: 410.93 / MAX: 547.33-mno-avx512f - MIN: 937.5 / MAX: 1231.551. (CXX) g++ options: -fPIC -O3 -march=native -fsigned-char -ffunction-sections -fdata-sections -fno-strict-overflow -fwrapv -flto -shared
MinAvgMaxAVX-512 On240031263696AVX-512 Off265229064086OpenBenchmarking.orgMegahertz, More Is BetterOpenVINO 2022.2.devCPU Peak Freq (Highest CPU Core Frequency) Monitor11002200330044005500
MinAvgMaxAVX-512 On54639725AVX-512 Off218585645OpenBenchmarking.orgWatts, Fewer Is BetterOpenVINO 2022.2.devCPU Power Consumption Monitor2004006008001000
MinAvgMaxAVX-512 On35.957.364.1AVX-512 Off41.356.261.9OpenBenchmarking.orgCelsius, Fewer Is BetterOpenVINO 2022.2.devCPU Temperature Monitor20406080100

OpenBenchmarking.orgms, Fewer Is BetterOpenVINO 2022.2.devModel: Age Gender Recognition Retail 0013 FP16 - Device: CPUAVX-512 OnAVX-512 Off0.27230.54460.81691.08921.3615SE +/- 0.00, N = 3SE +/- 0.01, N = 40.551.21-mavx512f -mavx512cd -mavx512vl -mavx512bw -mavx512dq -mavx512ifma -mavx512vbmi - MIN: 0.5 / MAX: 29.57-mno-avx512f - MIN: 0.98 / MAX: 47.371. (CXX) g++ options: -fPIC -O3 -march=native -fsigned-char -ffunction-sections -fdata-sections -fno-strict-overflow -fwrapv -flto -shared
MinAvgMaxAVX-512 On240036053828AVX-512 Off299231934056OpenBenchmarking.orgMegahertz, More Is BetterOpenVINO 2022.2.devCPU Peak Freq (Highest CPU Core Frequency) Monitor11002200330044005500
MinAvgMaxAVX-512 On48566622AVX-512 Off219592636OpenBenchmarking.orgWatts, Fewer Is BetterOpenVINO 2022.2.devCPU Power Consumption Monitor2004006008001000
MinAvgMaxAVX-512 On42.155.459.5AVX-512 Off49.359.962.6OpenBenchmarking.orgCelsius, Fewer Is BetterOpenVINO 2022.2.devCPU Temperature Monitor20406080100

Cpuminer-Opt

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

OpenBenchmarking.orgkH/s, More Is BetterCpuminer-Opt 3.20.3Algorithm: LBC, LBRY CreditsAVX-512 OnAVX-512 Off200K400K600K800K1000KSE +/- 7645.47, N = 3SE +/- 667.26, N = 31066950491740-mavx512f -mavx512cd -mavx512vl -mavx512bw -mavx512dq -mavx512ifma -mavx512vbmi-mno-avx512f1. (CXX) g++ options: -O3 -march=native -lcurl -lz -lpthread -lssl -lcrypto -lgmp
OpenBenchmarking.orgkH/s Per Watt, More Is BetterCpuminer-Opt 3.20.3Algorithm: LBC, LBRY CreditsAVX-512 OnAVX-512 Off4008001200160020001658.51802.76
MinAvgMaxAVX-512 On240030603703AVX-512 Off272929334111OpenBenchmarking.orgMegahertz, More Is BetterCpuminer-Opt 3.20.3CPU Peak Freq (Highest CPU Core Frequency) Monitor11002200330044005500
MinAvgMaxAVX-512 On59643743AVX-512 Off222613684OpenBenchmarking.orgWatts, Fewer Is BetterCpuminer-Opt 3.20.3CPU Power Consumption Monitor2004006008001000
MinAvgMaxAVX-512 On42.459.063.5AVX-512 Off47.059.262.3OpenBenchmarking.orgCelsius, Fewer Is BetterCpuminer-Opt 3.20.3CPU Temperature Monitor20406080100

AI Benchmark Alpha

AI Benchmark Alpha is a Python library for evaluating artificial intelligence (AI) performance on diverse hardware platforms and relies upon the TensorFlow machine learning library. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgScore, More Is BetterAI Benchmark Alpha 0.1.2Device AI ScoreAVX-512 OnAVX-512 Off1300260039005200650062112887
OpenBenchmarking.orgScore Per Watt, More Is BetterAI Benchmark Alpha 0.1.2Device AI ScoreAVX-512 OnAVX-512 Off51015202520.5229.349
MinAvgMaxAVX-512 On240036554107AVX-512 Off306837104285OpenBenchmarking.orgMegahertz, More Is BetterAI Benchmark Alpha 0.1.2CPU Peak Freq (Highest CPU Core Frequency) Monitor11002200330044005500
MinAvgMaxAVX-512 On52.9302.7502.0AVX-512 Off130.7308.8452.7OpenBenchmarking.orgWatts, Fewer Is BetterAI Benchmark Alpha 0.1.2CPU Power Consumption Monitor130260390520650
MinAvgMaxAVX-512 On30.139.247.0AVX-512 Off36.440.649.3OpenBenchmarking.orgCelsius, Fewer Is BetterAI Benchmark Alpha 0.1.2CPU Temperature Monitor1428425670

OpenVINO

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

OpenBenchmarking.orgms, Fewer Is BetterOpenVINO 2022.2.devModel: Machine Translation EN To DE FP16 - Device: CPUAVX-512 OnAVX-512 Off20406080100SE +/- 0.21, N = 3SE +/- 0.74, N = 350.11107.62-mavx512f -mavx512cd -mavx512vl -mavx512bw -mavx512dq -mavx512ifma -mavx512vbmi - MIN: 38.98 / MAX: 166.69-mno-avx512f - MIN: 83.48 / MAX: 216.071. (CXX) g++ options: -fPIC -O3 -march=native -fsigned-char -ffunction-sections -fdata-sections -fno-strict-overflow -fwrapv -flto -shared
MinAvgMaxAVX-512 On240032563707AVX-512 Off259229663926OpenBenchmarking.orgMegahertz, More Is BetterOpenVINO 2022.2.devCPU Peak Freq (Highest CPU Core Frequency) Monitor10002000300040005000
MinAvgMaxAVX-512 On57636701AVX-512 Off213595648OpenBenchmarking.orgWatts, Fewer Is BetterOpenVINO 2022.2.devCPU Power Consumption Monitor2004006008001000
MinAvgMaxAVX-512 On42.658.461.9AVX-512 Off46.156.361.4OpenBenchmarking.orgCelsius, Fewer Is BetterOpenVINO 2022.2.devCPU Temperature Monitor20406080100

OpenBenchmarking.orgFPS, More Is BetterOpenVINO 2022.2.devModel: Machine Translation EN To DE FP16 - Device: CPUAVX-512 OnAVX-512 Off2004006008001000SE +/- 4.00, N = 3SE +/- 3.04, N = 3956.88445.59-mavx512f -mavx512cd -mavx512vl -mavx512bw -mavx512dq -mavx512ifma -mavx512vbmi-mno-avx512f1. (CXX) g++ options: -fPIC -O3 -march=native -fsigned-char -ffunction-sections -fdata-sections -fno-strict-overflow -fwrapv -flto -shared

OpenBenchmarking.orgFPS, More Is BetterOpenVINO 2022.2.devModel: Weld Porosity Detection FP16-INT8 - Device: CPUAVX-512 OnAVX-512 Off4K8K12K16K20KSE +/- 12.72, N = 3SE +/- 1.81, N = 319800.209672.94-mavx512f -mavx512cd -mavx512vl -mavx512bw -mavx512dq -mavx512ifma -mavx512vbmi-mno-avx512f1. (CXX) g++ options: -fPIC -O3 -march=native -fsigned-char -ffunction-sections -fdata-sections -fno-strict-overflow -fwrapv -flto -shared

OpenBenchmarking.orgms, Fewer Is BetterOpenVINO 2022.2.devModel: Weld Porosity Detection FP16-INT8 - Device: CPUAVX-512 OnAVX-512 Off510152025SE +/- 0.01, N = 3SE +/- 0.01, N = 39.6319.69-mavx512f -mavx512cd -mavx512vl -mavx512bw -mavx512dq -mavx512ifma -mavx512vbmi - MIN: 8.29 / MAX: 57.53-mno-avx512f - MIN: 16.4 / MAX: 74.851. (CXX) g++ options: -fPIC -O3 -march=native -fsigned-char -ffunction-sections -fdata-sections -fno-strict-overflow -fwrapv -flto -shared
MinAvgMaxAVX-512 On240030373696AVX-512 Off293030703969OpenBenchmarking.orgMegahertz, More Is BetterOpenVINO 2022.2.devCPU Peak Freq (Highest CPU Core Frequency) Monitor11002200330044005500
MinAvgMaxAVX-512 On57639696AVX-512 Off216684729OpenBenchmarking.orgWatts, Fewer Is BetterOpenVINO 2022.2.devCPU Power Consumption Monitor2004006008001000
MinAvgMaxAVX-512 On42.659.462.8AVX-512 Off45.863.067.1OpenBenchmarking.orgCelsius, Fewer Is BetterOpenVINO 2022.2.devCPU Temperature Monitor20406080100

OpenBenchmarking.orgFPS, More Is BetterOpenVINO 2022.2.devModel: Face Detection FP16-INT8 - Device: CPUAVX-512 OnAVX-512 Off4080120160200SE +/- 0.05, N = 3SE +/- 0.02, N = 3193.9394.97-mavx512f -mavx512cd -mavx512vl -mavx512bw -mavx512dq -mavx512ifma -mavx512vbmi-mno-avx512f1. (CXX) g++ options: -fPIC -O3 -march=native -fsigned-char -ffunction-sections -fdata-sections -fno-strict-overflow -fwrapv -flto -shared

OpenBenchmarking.orgms, Fewer Is BetterOpenVINO 2022.2.devModel: Face Detection FP16-INT8 - Device: CPUAVX-512 OnAVX-512 Off110220330440550SE +/- 0.01, N = 3SE +/- 0.07, N = 3246.98503.50-mavx512f -mavx512cd -mavx512vl -mavx512bw -mavx512dq -mavx512ifma -mavx512vbmi - MIN: 204.5 / MAX: 299.54-mno-avx512f - MIN: 402.47 / MAX: 569.651. (CXX) g++ options: -fPIC -O3 -march=native -fsigned-char -ffunction-sections -fdata-sections -fno-strict-overflow -fwrapv -flto -shared
MinAvgMaxAVX-512 On240031293696AVX-512 Off292030813713OpenBenchmarking.orgMegahertz, More Is BetterOpenVINO 2022.2.devCPU Peak Freq (Highest CPU Core Frequency) Monitor10002000300040005000
MinAvgMaxAVX-512 On58612687AVX-512 Off216662733OpenBenchmarking.orgWatts, Fewer Is BetterOpenVINO 2022.2.devCPU Power Consumption Monitor2004006008001000
MinAvgMaxAVX-512 On43.058.161.9AVX-512 Off47.062.566.8OpenBenchmarking.orgCelsius, Fewer Is BetterOpenVINO 2022.2.devCPU Temperature Monitor20406080100

OpenBenchmarking.orgFPS, More Is BetterOpenVINO 2022.2.devModel: Vehicle Detection FP16 - Device: CPUAVX-512 OnAVX-512 Off16003200480064008000SE +/- 3.52, N = 3SE +/- 10.17, N = 37452.963782.08-mavx512f -mavx512cd -mavx512vl -mavx512bw -mavx512dq -mavx512ifma -mavx512vbmi-mno-avx512f1. (CXX) g++ options: -fPIC -O3 -march=native -fsigned-char -ffunction-sections -fdata-sections -fno-strict-overflow -fwrapv -flto -shared

OpenBenchmarking.orgms, Fewer Is BetterOpenVINO 2022.2.devModel: Vehicle Detection FP16 - Device: CPUAVX-512 OnAVX-512 Off3691215SE +/- 0.00, N = 3SE +/- 0.03, N = 36.4312.67-mavx512f -mavx512cd -mavx512vl -mavx512bw -mavx512dq -mavx512ifma -mavx512vbmi - MIN: 5.22 / MAX: 61.26-mno-avx512f - MIN: 9.58 / MAX: 77.911. (CXX) g++ options: -fPIC -O3 -march=native -fsigned-char -ffunction-sections -fdata-sections -fno-strict-overflow -fwrapv -flto -shared
MinAvgMaxAVX-512 On240029723706AVX-512 Off257127304230OpenBenchmarking.orgMegahertz, More Is BetterOpenVINO 2022.2.devCPU Peak Freq (Highest CPU Core Frequency) Monitor11002200330044005500
MinAvgMaxAVX-512 On59633690AVX-512 Off217613655OpenBenchmarking.orgWatts, Fewer Is BetterOpenVINO 2022.2.devCPU Power Consumption Monitor2004006008001000
MinAvgMaxAVX-512 On42.159.062.4AVX-512 Off48.959.962.3OpenBenchmarking.orgCelsius, Fewer Is BetterOpenVINO 2022.2.devCPU Temperature Monitor20406080100

AI Benchmark Alpha

AI Benchmark Alpha is a Python library for evaluating artificial intelligence (AI) performance on diverse hardware platforms and relies upon the TensorFlow machine learning library. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgScore, More Is BetterAI Benchmark Alpha 0.1.2Device Inference ScoreAVX-512 OnAVX-512 Off800160024003200400035101821

OpenVINO

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

OpenBenchmarking.orgFPS, More Is BetterOpenVINO 2022.2.devModel: Vehicle Detection FP16-INT8 - Device: CPUAVX-512 OnAVX-512 Off2K4K6K8K10KSE +/- 2.53, N = 3SE +/- 1.39, N = 311202.626065.76-mavx512f -mavx512cd -mavx512vl -mavx512bw -mavx512dq -mavx512ifma -mavx512vbmi-mno-avx512f1. (CXX) g++ options: -fPIC -O3 -march=native -fsigned-char -ffunction-sections -fdata-sections -fno-strict-overflow -fwrapv -flto -shared

OpenBenchmarking.orgms, Fewer Is BetterOpenVINO 2022.2.devModel: Vehicle Detection FP16-INT8 - Device: CPUAVX-512 OnAVX-512 Off246810SE +/- 0.00, N = 3SE +/- 0.00, N = 34.287.90-mavx512f -mavx512cd -mavx512vl -mavx512bw -mavx512dq -mavx512ifma -mavx512vbmi - MIN: 3.5 / MAX: 42.62-mno-avx512f - MIN: 6.37 / MAX: 41.531. (CXX) g++ options: -fPIC -O3 -march=native -fsigned-char -ffunction-sections -fdata-sections -fno-strict-overflow -fwrapv -flto -shared
MinAvgMaxAVX-512 On240030363900AVX-512 Off298830684270OpenBenchmarking.orgMegahertz, More Is BetterOpenVINO 2022.2.devCPU Peak Freq (Highest CPU Core Frequency) Monitor11002200330044005500
MinAvgMaxAVX-512 On33598646AVX-512 Off214634676OpenBenchmarking.orgWatts, Fewer Is BetterOpenVINO 2022.2.devCPU Power Consumption Monitor2004006008001000
MinAvgMaxAVX-512 On44.457.960.1AVX-512 Off48.061.164.0OpenBenchmarking.orgCelsius, Fewer Is BetterOpenVINO 2022.2.devCPU Temperature Monitor20406080100

oneDNN

OpenBenchmarking.orgms, Fewer Is BetteroneDNN 2.7Harness: Deconvolution Batch shapes_3d - Data Type: f32 - Engine: CPUAVX-512 OnAVX-512 Off0.39680.79361.19041.58721.984SE +/- 0.001906, N = 9SE +/- 0.004550, N = 90.9895911.763360-mavx512f -mavx512cd -mavx512vl -mavx512bw -mavx512dq -mavx512ifma -mavx512vbmi - MIN: 0.9-mno-avx512f - MIN: 1.551. (CXX) g++ options: -O3 -march=native -fopenmp -msse4.1 -fPIC -pie -ldl -lpthread
MinAvgMaxAVX-512 On240030083695AVX-512 Off356936664064OpenBenchmarking.orgMegahertz, More Is BetteroneDNN 2.7CPU Peak Freq (Highest CPU Core Frequency) Monitor11002200330044005500
MinAvgMaxAVX-512 On54.0248.8512.8AVX-512 Off215.2323.9475.6OpenBenchmarking.orgWatts, Fewer Is BetteroneDNN 2.7CPU Power Consumption Monitor130260390520650
MinAvgMaxAVX-512 On35.939.344.4AVX-512 Off39.041.443.9OpenBenchmarking.orgCelsius, Fewer Is BetteroneDNN 2.7CPU Temperature Monitor1224364860

OpenVINO

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

OpenBenchmarking.orgFPS, More Is BetterOpenVINO 2022.2.devModel: Person Vehicle Bike Detection FP16 - Device: CPUAVX-512 OnAVX-512 Off2K4K6K8K10KSE +/- 4.01, N = 3SE +/- 2.17, N = 39065.345135.56-mavx512f -mavx512cd -mavx512vl -mavx512bw -mavx512dq -mavx512ifma -mavx512vbmi-mno-avx512f1. (CXX) g++ options: -fPIC -O3 -march=native -fsigned-char -ffunction-sections -fdata-sections -fno-strict-overflow -fwrapv -flto -shared

OpenBenchmarking.orgms, Fewer Is BetterOpenVINO 2022.2.devModel: Person Vehicle Bike Detection FP16 - Device: CPUAVX-512 OnAVX-512 Off3691215SE +/- 0.00, N = 3SE +/- 0.00, N = 35.299.33-mavx512f -mavx512cd -mavx512vl -mavx512bw -mavx512dq -mavx512ifma -mavx512vbmi - MIN: 4.36 / MAX: 45.25-mno-avx512f - MIN: 7.39 / MAX: 57.571. (CXX) g++ options: -fPIC -O3 -march=native -fsigned-char -ffunction-sections -fdata-sections -fno-strict-overflow -fwrapv -flto -shared
MinAvgMaxAVX-512 On240030993699AVX-512 Off279929423941OpenBenchmarking.orgMegahertz, More Is BetterOpenVINO 2022.2.devCPU Peak Freq (Highest CPU Core Frequency) Monitor10002000300040005000
MinAvgMaxAVX-512 On51588657AVX-512 Off218588640OpenBenchmarking.orgWatts, Fewer Is BetterOpenVINO 2022.2.devCPU Power Consumption Monitor2004006008001000
MinAvgMaxAVX-512 On43.856.859.6AVX-512 Off46.658.061.4OpenBenchmarking.orgCelsius, Fewer Is BetterOpenVINO 2022.2.devCPU Temperature Monitor20406080100

TensorFlow

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

OpenBenchmarking.orgimages/sec, More Is BetterTensorFlow 2.10Device: CPU - Batch Size: 16 - Model: ResNet-50AVX-512 OnAVX-512 Off510152025SE +/- 0.11, N = 3SE +/- 0.01, N = 322.1512.75
OpenBenchmarking.orgimages/sec Per Watt, More Is BetterTensorFlow 2.10Device: CPU - Batch Size: 16 - Model: ResNet-50AVX-512 OnAVX-512 Off0.01620.03240.04860.06480.0810.0720.038
MinAvgMaxAVX-512 On240036644099AVX-512 Off369437134254OpenBenchmarking.orgMegahertz, More Is BetterTensorFlow 2.10CPU Peak Freq (Highest CPU Core Frequency) Monitor11002200330044005500
MinAvgMaxAVX-512 On53.5307.1397.4AVX-512 Off165.7338.8379.7OpenBenchmarking.orgWatts, Fewer Is BetterTensorFlow 2.10CPU Power Consumption Monitor110220330440550
MinAvgMaxAVX-512 On36.841.748.6AVX-512 Off40.943.453.5OpenBenchmarking.orgCelsius, Fewer Is BetterTensorFlow 2.10CPU Temperature Monitor1530456075

OSPRay

Intel OSPRay is a portable ray-tracing engine for high-performance, high-fidelity scientific visualizations. OSPRay builds off Intel's Embree and Intel SPMD Program Compiler (ISPC) components as part of the oneAPI rendering toolkit. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgItems Per Second, More Is BetterOSPRay 2.10Benchmark: gravity_spheres_volume/dim_512/scivis/real_timeAVX-512 OnAVX-512 Off1020304050SE +/- 0.10, N = 3SE +/- 0.04, N = 343.0725.14
OpenBenchmarking.orgItems Per Second Per Watt, More Is BetterOSPRay 2.10Benchmark: gravity_spheres_volume/dim_512/scivis/real_timeAVX-512 OnAVX-512 Off0.01670.03340.05010.06680.08350.0740.041
MinAvgMaxAVX-512 On240030513695AVX-512 Off276830834016OpenBenchmarking.orgMegahertz, More Is BetterOSPRay 2.10CPU Peak Freq (Highest CPU Core Frequency) Monitor11002200330044005500
MinAvgMaxAVX-512 On56582632AVX-512 Off177620662OpenBenchmarking.orgWatts, Fewer Is BetterOSPRay 2.10CPU Power Consumption Monitor2004006008001000
MinAvgMaxAVX-512 On41.856.860.4AVX-512 Off48.460.363.5OpenBenchmarking.orgCelsius, Fewer Is BetterOSPRay 2.10CPU Temperature Monitor20406080100

Cpuminer-Opt

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

OpenBenchmarking.orgkH/s, More Is BetterCpuminer-Opt 3.20.3Algorithm: Quad SHA-256, PyriteAVX-512 OnAVX-512 Off500K1000K1500K2000K2500KSE +/- 9040.25, N = 3SE +/- 276.83, N = 322606801322960-mavx512f -mavx512cd -mavx512vl -mavx512bw -mavx512dq -mavx512ifma -mavx512vbmi-mno-avx512f1. (CXX) g++ options: -O3 -march=native -lcurl -lz -lpthread -lssl -lcrypto -lgmp
OpenBenchmarking.orgkH/s Per Watt, More Is BetterCpuminer-Opt 3.20.3Algorithm: Quad SHA-256, PyriteAVX-512 OnAVX-512 Off80016002400320040003657.532252.99
MinAvgMaxAVX-512 On240031123695AVX-512 Off300131554285OpenBenchmarking.orgMegahertz, More Is BetterCpuminer-Opt 3.20.3CPU Peak Freq (Highest CPU Core Frequency) Monitor11002200330044005500
MinAvgMaxAVX-512 On57618724AVX-512 Off134587654OpenBenchmarking.orgWatts, Fewer Is BetterCpuminer-Opt 3.20.3CPU Power Consumption Monitor2004006008001000
MinAvgMaxAVX-512 On43.058.662.8AVX-512 Off46.657.961.4OpenBenchmarking.orgCelsius, Fewer Is BetterCpuminer-Opt 3.20.3CPU Temperature Monitor20406080100

OpenVINO

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

OpenBenchmarking.orgFPS, More Is BetterOpenVINO 2022.2.devModel: Person Detection FP16 - Device: CPUAVX-512 OnAVX-512 Off1020304050SE +/- 0.20, N = 3SE +/- 0.22, N = 343.3425.50-mavx512f -mavx512cd -mavx512vl -mavx512bw -mavx512dq -mavx512ifma -mavx512vbmi-mno-avx512f1. (CXX) g++ options: -fPIC -O3 -march=native -fsigned-char -ffunction-sections -fdata-sections -fno-strict-overflow -fwrapv -flto -shared

OpenBenchmarking.orgms, Fewer Is BetterOpenVINO 2022.2.devModel: Person Detection FP16 - Device: CPUAVX-512 OnAVX-512 Off400800120016002000SE +/- 4.83, N = 3SE +/- 15.65, N = 31100.251864.93-mavx512f -mavx512cd -mavx512vl -mavx512bw -mavx512dq -mavx512ifma -mavx512vbmi - MIN: 783.9 / MAX: 1824.92-mno-avx512f - MIN: 1371.29 / MAX: 2532.741. (CXX) g++ options: -fPIC -O3 -march=native -fsigned-char -ffunction-sections -fdata-sections -fno-strict-overflow -fwrapv -flto -shared
MinAvgMaxAVX-512 On240034803726AVX-512 Off270931503863OpenBenchmarking.orgMegahertz, More Is BetterOpenVINO 2022.2.devCPU Peak Freq (Highest CPU Core Frequency) Monitor10002000300040005000
MinAvgMaxAVX-512 On56605699AVX-512 Off114579650OpenBenchmarking.orgWatts, Fewer Is BetterOpenVINO 2022.2.devCPU Power Consumption Monitor2004006008001000
MinAvgMaxAVX-512 On39.557.465.9AVX-512 Off47.058.267.6OpenBenchmarking.orgCelsius, Fewer Is BetterOpenVINO 2022.2.devCPU Temperature Monitor20406080100

OpenBenchmarking.orgFPS, More Is BetterOpenVINO 2022.2.devModel: Person Detection FP32 - Device: CPUAVX-512 OnAVX-512 Off1020304050SE +/- 0.18, N = 3SE +/- 0.04, N = 343.3425.74-mavx512f -mavx512cd -mavx512vl -mavx512bw -mavx512dq -mavx512ifma -mavx512vbmi-mno-avx512f1. (CXX) g++ options: -fPIC -O3 -march=native -fsigned-char -ffunction-sections -fdata-sections -fno-strict-overflow -fwrapv -flto -shared

OpenBenchmarking.orgms, Fewer Is BetterOpenVINO 2022.2.devModel: Person Detection FP32 - Device: CPUAVX-512 OnAVX-512 Off400800120016002000SE +/- 4.44, N = 3SE +/- 3.32, N = 31101.001845.95-mavx512f -mavx512cd -mavx512vl -mavx512bw -mavx512dq -mavx512ifma -mavx512vbmi - MIN: 840.82 / MAX: 1792.51-mno-avx512f - MIN: 1386.31 / MAX: 27981. (CXX) g++ options: -fPIC -O3 -march=native -fsigned-char -ffunction-sections -fdata-sections -fno-strict-overflow -fwrapv -flto -shared
MinAvgMaxAVX-512 On240034663698AVX-512 Off272931003993OpenBenchmarking.orgMegahertz, More Is BetterOpenVINO 2022.2.devCPU Peak Freq (Highest CPU Core Frequency) Monitor11002200330044005500
MinAvgMaxAVX-512 On38607700AVX-512 Off215593665OpenBenchmarking.orgWatts, Fewer Is BetterOpenVINO 2022.2.devCPU Power Consumption Monitor2004006008001000
MinAvgMaxAVX-512 On42.158.067.3AVX-512 Off46.158.766.8OpenBenchmarking.orgCelsius, Fewer Is BetterOpenVINO 2022.2.devCPU Temperature Monitor20406080100

OSPRay

Intel OSPRay is a portable ray-tracing engine for high-performance, high-fidelity scientific visualizations. OSPRay builds off Intel's Embree and Intel SPMD Program Compiler (ISPC) components as part of the oneAPI rendering toolkit. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgItems Per Second, More Is BetterOSPRay 2.10Benchmark: gravity_spheres_volume/dim_512/ao/real_timeAVX-512 OnAVX-512 Off1020304050SE +/- 0.21, N = 3SE +/- 0.02, N = 344.1626.38
OpenBenchmarking.orgItems Per Second Per Watt, More Is BetterOSPRay 2.10Benchmark: gravity_spheres_volume/dim_512/ao/real_timeAVX-512 OnAVX-512 Off0.01710.03420.05130.06840.08550.0760.043
MinAvgMaxAVX-512 On240030813695AVX-512 Off277130734018OpenBenchmarking.orgMegahertz, More Is BetterOSPRay 2.10CPU Peak Freq (Highest CPU Core Frequency) Monitor11002200330044005500
MinAvgMaxAVX-512 On56580633AVX-512 Off222618662OpenBenchmarking.orgWatts, Fewer Is BetterOSPRay 2.10CPU Power Consumption Monitor2004006008001000
MinAvgMaxAVX-512 On39.956.259.5AVX-512 Off45.359.865.0OpenBenchmarking.orgCelsius, Fewer Is BetterOSPRay 2.10CPU Temperature Monitor20406080100

Cpuminer-Opt

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

OpenBenchmarking.orgkH/s, More Is BetterCpuminer-Opt 3.20.3Algorithm: scryptAVX-512 OnAVX-512 Off10002000300040005000SE +/- 0.45, N = 3SE +/- 0.31, N = 34800.612946.08-mavx512f -mavx512cd -mavx512vl -mavx512bw -mavx512dq -mavx512ifma -mavx512vbmi-mno-avx512f1. (CXX) g++ options: -O3 -march=native -lcurl -lz -lpthread -lssl -lcrypto -lgmp
OpenBenchmarking.orgkH/s Per Watt, More Is BetterCpuminer-Opt 3.20.3Algorithm: scryptAVX-512 OnAVX-512 Off2468108.0765.279
MinAvgMaxAVX-512 On240030093697AVX-512 Off293330583896OpenBenchmarking.orgMegahertz, More Is BetterCpuminer-Opt 3.20.3CPU Peak Freq (Highest CPU Core Frequency) Monitor10002000300040005000
MinAvgMaxAVX-512 On55594682AVX-512 Off215558618OpenBenchmarking.orgWatts, Fewer Is BetterCpuminer-Opt 3.20.3CPU Power Consumption Monitor2004006008001000
MinAvgMaxAVX-512 On34.152.258.3AVX-512 Off39.552.456.9OpenBenchmarking.orgCelsius, Fewer Is BetterCpuminer-Opt 3.20.3CPU Temperature Monitor1632486480

OpenVINO

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

OpenBenchmarking.orgms, Fewer Is BetterOpenVINO 2022.2.devModel: Age Gender Recognition Retail 0013 FP16-INT8 - Device: CPUAVX-512 OnAVX-512 Off0.12830.25660.38490.51320.6415SE +/- 0.00, N = 3SE +/- 0.00, N = 30.360.57-mavx512f -mavx512cd -mavx512vl -mavx512bw -mavx512dq -mavx512ifma -mavx512vbmi - MIN: 0.34 / MAX: 33.7-mno-avx512f - MIN: 0.52 / MAX: 47.931. (CXX) g++ options: -fPIC -O3 -march=native -fsigned-char -ffunction-sections -fdata-sections -fno-strict-overflow -fwrapv -flto -shared
MinAvgMaxAVX-512 On240036303754AVX-512 Off347636743707OpenBenchmarking.orgMegahertz, More Is BetterOpenVINO 2022.2.devCPU Peak Freq (Highest CPU Core Frequency) Monitor10002000300040005000
MinAvgMaxAVX-512 On29514564AVX-512 Off217592630OpenBenchmarking.orgWatts, Fewer Is BetterOpenVINO 2022.2.devCPU Power Consumption Monitor2004006008001000
MinAvgMaxAVX-512 On41.852.255.1AVX-512 Off48.059.262.3OpenBenchmarking.orgCelsius, Fewer Is BetterOpenVINO 2022.2.devCPU Temperature Monitor20406080100

Mobile Neural Network

MNN is the Mobile Neural Network as a highly efficient, lightweight deep learning framework developed by Alibaba. This MNN test profile is building the OpenMP / CPU threaded version for processor benchmarking and not any GPU-accelerated test. MNN does allow making use of AVX-512 extensions. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgms, Fewer Is BetterMobile Neural Network 2.1Model: resnet-v2-50AVX-512 OnAVX-512 Off612182430SE +/- 0.08, N = 9SE +/- 0.08, N = 815.4424.10-mavx512f -mavx512cd -mavx512vl -mavx512bw -mavx512dq -mavx512ifma -mavx512vbmi - MIN: 14.79 / MAX: 54.05-mno-avx512f - MIN: 23.44 / MAX: 71.321. (CXX) g++ options: -O3 -march=native -std=c++11 -fvisibility=hidden -fomit-frame-pointer -fstrict-aliasing -ffunction-sections -fdata-sections -ffast-math -fno-rtti -fno-exceptions -rdynamic -pthread -ldl

Neural Magic DeepSparse

OpenBenchmarking.orgitems/sec, More Is BetterNeural Magic DeepSparse 1.1Model: NLP Question Answering, BERT base uncased SQuaD 12layer Pruned90 - Scenario: Asynchronous Multi-StreamAVX-512 OnAVX-512 Off160320480640800SE +/- 0.79, N = 3SE +/- 0.61, N = 3761.22490.37

OpenBenchmarking.orgms/batch, Fewer Is BetterNeural Magic DeepSparse 1.1Model: NLP Question Answering, BERT base uncased SQuaD 12layer Pruned90 - Scenario: Asynchronous Multi-StreamAVX-512 OnAVX-512 Off4080120160200SE +/- 0.11, N = 3SE +/- 0.23, N = 3125.79195.17
MinAvgMaxAVX-512 On240029453885AVX-512 Off256832144450OpenBenchmarking.orgMegahertz, More Is BetterNeural Magic DeepSparse 1.1CPU Peak Freq (Highest CPU Core Frequency) Monitor12002400360048006000
MinAvgMaxAVX-512 On54537700AVX-512 Off114503700OpenBenchmarking.orgWatts, Fewer Is BetterNeural Magic DeepSparse 1.1CPU Power Consumption Monitor2004006008001000
MinAvgMaxAVX-512 On39.351.958.3AVX-512 Off43.551.559.1OpenBenchmarking.orgCelsius, Fewer Is BetterNeural Magic DeepSparse 1.1CPU Temperature Monitor1632486480

Mobile Neural Network

MNN is the Mobile Neural Network as a highly efficient, lightweight deep learning framework developed by Alibaba. This MNN test profile is building the OpenMP / CPU threaded version for processor benchmarking and not any GPU-accelerated test. MNN does allow making use of AVX-512 extensions. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgms, Fewer Is BetterMobile Neural Network 2.1Model: inception-v3AVX-512 OnAVX-512 Off1020304050SE +/- 0.23, N = 9SE +/- 0.13, N = 845.8130.44-mavx512f -mavx512cd -mavx512vl -mavx512bw -mavx512dq -mavx512ifma -mavx512vbmi - MIN: 44.13 / MAX: 87.28-mno-avx512f - MIN: 28.75 / MAX: 109.221. (CXX) g++ options: -O3 -march=native -std=c++11 -fvisibility=hidden -fomit-frame-pointer -fstrict-aliasing -ffunction-sections -fdata-sections -ffast-math -fno-rtti -fno-exceptions -rdynamic -pthread -ldl
OpenBenchmarking.orgMegahertz, More Is BetterMobile Neural Network 2.1CPU Peak Freq (Highest CPU Core Frequency) MonitorAVX-512 OnAVX-512 Off7001400210028003500Min: 2400 / Avg: 3679.28 / Max: 3704Min: 3694 / Avg: 3699.72 / Max: 4041
OpenBenchmarking.orgWatts, Fewer Is BetterMobile Neural Network 2.1CPU Power Consumption MonitorAVX-512 OnAVX-512 Off60120180240300Min: 53.81 / Avg: 327.57 / Max: 340Min: 165 / Avg: 334.93 / Max: 346.27
OpenBenchmarking.orgCelsius, Fewer Is BetterMobile Neural Network 2.1CPU Temperature MonitorAVX-512 OnAVX-512 Off1122334455Min: 35.88 / Avg: 48.36 / Max: 52Min: 40.38 / Avg: 49.52 / Max: 52.88

Cpuminer-Opt

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

OpenBenchmarking.orgkH/s, More Is BetterCpuminer-Opt 3.20.3Algorithm: GarlicoinAVX-512 OnAVX-512 Off15K30K45K60K75KSE +/- 89.69, N = 3SE +/- 13.33, N = 37155348827-mavx512f -mavx512cd -mavx512vl -mavx512bw -mavx512dq -mavx512ifma -mavx512vbmi-mno-avx512f1. (CXX) g++ options: -O3 -march=native -lcurl -lz -lpthread -lssl -lcrypto -lgmp
OpenBenchmarking.orgkH/s Per Watt, More Is BetterCpuminer-Opt 3.20.3Algorithm: GarlicoinAVX-512 OnAVX-512 Off306090120150119.9783.22
MinAvgMaxAVX-512 On240030793830AVX-512 Off287830303783OpenBenchmarking.orgMegahertz, More Is BetterCpuminer-Opt 3.20.3CPU Peak Freq (Highest CPU Core Frequency) Monitor10002000300040005000
MinAvgMaxAVX-512 On57596694AVX-512 Off220587657OpenBenchmarking.orgWatts, Fewer Is BetterCpuminer-Opt 3.20.3CPU Power Consumption Monitor2004006008001000
MinAvgMaxAVX-512 On41.356.360.9AVX-512 Off45.857.160.9OpenBenchmarking.orgCelsius, Fewer Is BetterCpuminer-Opt 3.20.3CPU Temperature Monitor20406080100

miniBUDE

MiniBUDE is a mini application for the the core computation of the Bristol University Docking Engine (BUDE). This test profile currently makes use of the OpenMP implementation of miniBUDE for CPU benchmarking. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgGFInst/s, More Is BetterminiBUDE 20210901Implementation: OpenMP - Input Deck: BM1AVX-512 OnAVX-512 Off16003200480064008000SE +/- 5.79, N = 10SE +/- 26.42, N = 87299.555065.101. (CC) gcc options: -std=c99 -Ofast -ffast-math -fopenmp -march=native -lm

OpenBenchmarking.orgBillion Interactions/s, More Is BetterminiBUDE 20210901Implementation: OpenMP - Input Deck: BM1AVX-512 OnAVX-512 Off60120180240300SE +/- 0.23, N = 10SE +/- 1.06, N = 8291.98202.601. (CC) gcc options: -std=c99 -Ofast -ffast-math -fopenmp -march=native -lm
OpenBenchmarking.orgBillion Interactions/s Per Watt, More Is BetterminiBUDE 20210901Implementation: OpenMP - Input Deck: BM1AVX-512 OnAVX-512 Off0.23420.46840.70260.93681.1711.0410.489
MinAvgMaxAVX-512 On240029133739AVX-512 Off310735054044OpenBenchmarking.orgMegahertz, More Is BetterminiBUDE 20210901CPU Peak Freq (Highest CPU Core Frequency) Monitor11002200330044005500
MinAvgMaxAVX-512 On52281624AVX-512 Off212414630OpenBenchmarking.orgWatts, Fewer Is BetterminiBUDE 20210901CPU Power Consumption Monitor2004006008001000
MinAvgMaxAVX-512 On31.538.547.4AVX-512 Off38.645.552.4OpenBenchmarking.orgCelsius, Fewer Is BetterminiBUDE 20210901CPU Temperature Monitor1530456075

Neural Magic DeepSparse

OpenBenchmarking.orgitems/sec, More Is BetterNeural Magic DeepSparse 1.1Model: NLP Question Answering, BERT base uncased SQuaD 12layer Pruned90 - Scenario: Synchronous Single-StreamAVX-512 OnAVX-512 Off20406080100SE +/- 0.17, N = 3SE +/- 0.17, N = 3100.5571.04

OpenBenchmarking.orgms/batch, Fewer Is BetterNeural Magic DeepSparse 1.1Model: NLP Question Answering, BERT base uncased SQuaD 12layer Pruned90 - Scenario: Synchronous Single-StreamAVX-512 OnAVX-512 Off48121620SE +/- 0.0172, N = 3SE +/- 0.0334, N = 39.940814.0655
MinAvgMaxAVX-512 On240035713764AVX-512 Off367837024150OpenBenchmarking.orgMegahertz, More Is BetterNeural Magic DeepSparse 1.1CPU Peak Freq (Highest CPU Core Frequency) Monitor11002200330044005500
MinAvgMaxAVX-512 On57.7334.2406.1AVX-512 Off124.0352.9412.6OpenBenchmarking.orgWatts, Fewer Is BetterNeural Magic DeepSparse 1.1CPU Power Consumption Monitor110220330440550
MinAvgMaxAVX-512 On38.148.554.8AVX-512 Off43.050.656.9OpenBenchmarking.orgCelsius, Fewer Is BetterNeural Magic DeepSparse 1.1CPU Temperature Monitor1632486480

OpenBenchmarking.orgms/batch, Fewer Is BetterNeural Magic DeepSparse 1.1Model: CV Classification, ResNet-50 ImageNet - Scenario: Asynchronous Multi-StreamAVX-512 OnAVX-512 Off1530456075SE +/- 0.11, N = 3SE +/- 0.02, N = 349.0367.91
MinAvgMaxAVX-512 On240030033730AVX-512 Off255229383959OpenBenchmarking.orgMegahertz, More Is BetterNeural Magic DeepSparse 1.1CPU Peak Freq (Highest CPU Core Frequency) Monitor10002000300040005000
MinAvgMaxAVX-512 On56531630AVX-512 Off216558637OpenBenchmarking.orgWatts, Fewer Is BetterNeural Magic DeepSparse 1.1CPU Power Consumption Monitor2004006008001000
MinAvgMaxAVX-512 On38.151.957.3AVX-512 Off44.454.959.1OpenBenchmarking.orgCelsius, Fewer Is BetterNeural Magic DeepSparse 1.1CPU Temperature Monitor1632486480

OpenBenchmarking.orgitems/sec, More Is BetterNeural Magic DeepSparse 1.1Model: CV Classification, ResNet-50 ImageNet - Scenario: Asynchronous Multi-StreamAVX-512 OnAVX-512 Off400800120016002000SE +/- 4.32, N = 3SE +/- 0.17, N = 31953.031410.81

oneDNN

OpenBenchmarking.orgms, Fewer Is BetteroneDNN 2.7Harness: Recurrent Neural Network Inference - Data Type: bf16bf16bf16 - Engine: CPUAVX-512 OnAVX-512 Off5001000150020002500SE +/- 24.41, N = 4SE +/- 22.32, N = 32361.271715.76-mavx512f -mavx512cd -mavx512vl -mavx512bw -mavx512dq -mavx512ifma -mavx512vbmi - MIN: 2265.7-mno-avx512f - MIN: 1607.131. (CXX) g++ options: -O3 -march=native -fopenmp -msse4.1 -fPIC -pie -ldl -lpthread
MinAvgMaxAVX-512 On240035073700AVX-512 Off357036124005OpenBenchmarking.orgMegahertz, More Is BetteroneDNN 2.7CPU Peak Freq (Highest CPU Core Frequency) Monitor11002200330044005500
MinAvgMaxAVX-512 On55.2413.8581.1AVX-512 Off204.0413.9482.1OpenBenchmarking.orgWatts, Fewer Is BetteroneDNN 2.7CPU Power Consumption Monitor160320480640800
MinAvgMaxAVX-512 On37.845.848.9AVX-512 Off42.646.849.8OpenBenchmarking.orgCelsius, Fewer Is BetteroneDNN 2.7CPU Temperature Monitor1428425670

OpenVINO

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

OpenBenchmarking.orgFPS, More Is BetterOpenVINO 2022.2.devModel: Age Gender Recognition Retail 0013 FP16 - Device: CPUAVX-512 OnAVX-512 Off30K60K90K120K150KSE +/- 1328.20, N = 3SE +/- 1130.85, N = 4148967.98108449.49-mavx512f -mavx512cd -mavx512vl -mavx512bw -mavx512dq -mavx512ifma -mavx512vbmi-mno-avx512f1. (CXX) g++ options: -fPIC -O3 -march=native -fsigned-char -ffunction-sections -fdata-sections -fno-strict-overflow -fwrapv -flto -shared

Cpuminer-Opt

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

OpenBenchmarking.orgkH/s, More Is BetterCpuminer-Opt 3.20.3Algorithm: SkeincoinAVX-512 OnAVX-512 Off400K800K1200K1600K2000KSE +/- 13005.55, N = 3SE +/- 3964.01, N = 319513301427543-mavx512f -mavx512cd -mavx512vl -mavx512bw -mavx512dq -mavx512ifma -mavx512vbmi-mno-avx512f1. (CXX) g++ options: -O3 -march=native -lcurl -lz -lpthread -lssl -lcrypto -lgmp
OpenBenchmarking.orgkH/s Per Watt, More Is BetterCpuminer-Opt 3.20.3Algorithm: SkeincoinAVX-512 OnAVX-512 Off70014002100280035003137.562381.94
MinAvgMaxAVX-512 On240030023696AVX-512 Off289530683848OpenBenchmarking.orgMegahertz, More Is BetterCpuminer-Opt 3.20.3CPU Peak Freq (Highest CPU Core Frequency) Monitor10002000300040005000
MinAvgMaxAVX-512 On58622720AVX-512 Off221599665OpenBenchmarking.orgWatts, Fewer Is BetterCpuminer-Opt 3.20.3CPU Power Consumption Monitor2004006008001000
MinAvgMaxAVX-512 On41.357.962.8AVX-512 Off47.058.761.8OpenBenchmarking.orgCelsius, Fewer Is BetterCpuminer-Opt 3.20.3CPU Temperature Monitor20406080100

miniBUDE

MiniBUDE is a mini application for the the core computation of the Bristol University Docking Engine (BUDE). This test profile currently makes use of the OpenMP implementation of miniBUDE for CPU benchmarking. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgBillion Interactions/s, More Is BetterminiBUDE 20210901Implementation: OpenMP - Input Deck: BM2AVX-512 OnAVX-512 Off80160240320400SE +/- 0.46, N = 4SE +/- 1.27, N = 3346.08255.661. (CC) gcc options: -std=c99 -Ofast -ffast-math -fopenmp -march=native -lm
OpenBenchmarking.orgBillion Interactions/s Per Watt, More Is BetterminiBUDE 20210901Implementation: OpenMP - Input Deck: BM2AVX-512 OnAVX-512 Off0.15620.31240.46860.62480.7810.6940.453
MinAvgMaxAVX-512 On240032013697AVX-512 Off290532883891OpenBenchmarking.orgMegahertz, More Is BetterminiBUDE 20210901CPU Peak Freq (Highest CPU Core Frequency) Monitor10002000300040005000
MinAvgMaxAVX-512 On54499647AVX-512 Off211564661OpenBenchmarking.orgWatts, Fewer Is BetterminiBUDE 20210901CPU Power Consumption Monitor2004006008001000
MinAvgMaxAVX-512 On32.847.756.0AVX-512 Off40.453.060.1OpenBenchmarking.orgCelsius, Fewer Is BetterminiBUDE 20210901CPU Temperature Monitor1632486480

OpenBenchmarking.orgGFInst/s, More Is BetterminiBUDE 20210901Implementation: OpenMP - Input Deck: BM2AVX-512 OnAVX-512 Off2K4K6K8K10KSE +/- 11.62, N = 4SE +/- 31.65, N = 38652.016391.521. (CC) gcc options: -std=c99 -Ofast -ffast-math -fopenmp -march=native -lm

OSPRay

Intel OSPRay is a portable ray-tracing engine for high-performance, high-fidelity scientific visualizations. OSPRay builds off Intel's Embree and Intel SPMD Program Compiler (ISPC) components as part of the oneAPI rendering toolkit. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgItems Per Second, More Is BetterOSPRay 2.10Benchmark: gravity_spheres_volume/dim_512/pathtracer/real_timeAVX-512 OnAVX-512 Off1224364860SE +/- 0.05, N = 3SE +/- 0.03, N = 354.2240.51
OpenBenchmarking.orgItems Per Second Per Watt, More Is BetterOSPRay 2.10Benchmark: gravity_spheres_volume/dim_512/pathtracer/real_timeAVX-512 OnAVX-512 Off0.02050.0410.06150.0820.10250.0910.065
MinAvgMaxAVX-512 On240030553720AVX-512 Off276631044475OpenBenchmarking.orgMegahertz, More Is BetterOSPRay 2.10CPU Peak Freq (Highest CPU Core Frequency) Monitor12002400360048006000
MinAvgMaxAVX-512 On58593646AVX-512 Off221628677OpenBenchmarking.orgWatts, Fewer Is BetterOSPRay 2.10CPU Power Consumption Monitor2004006008001000
MinAvgMaxAVX-512 On42.957.860.9AVX-512 Off47.561.364.9OpenBenchmarking.orgCelsius, Fewer Is BetterOSPRay 2.10CPU Temperature Monitor20406080100

Cpuminer-Opt

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

OpenBenchmarking.orgkH/s, More Is BetterCpuminer-Opt 3.20.3Algorithm: x25xAVX-512 OnAVX-512 Off16003200480064008000SE +/- 16.58, N = 3SE +/- 14.41, N = 37696.065784.25-mavx512f -mavx512cd -mavx512vl -mavx512bw -mavx512dq -mavx512ifma -mavx512vbmi-mno-avx512f1. (CXX) g++ options: -O3 -march=native -lcurl -lz -lpthread -lssl -lcrypto -lgmp
OpenBenchmarking.orgkH/s Per Watt, More Is BetterCpuminer-Opt 3.20.3Algorithm: x25xAVX-512 OnAVX-512 Off369121513.5489.971
MinAvgMaxAVX-512 On240031053697AVX-512 Off325633514121OpenBenchmarking.orgMegahertz, More Is BetterCpuminer-Opt 3.20.3CPU Peak Freq (Highest CPU Core Frequency) Monitor11002200330044005500
MinAvgMaxAVX-512 On39568650AVX-512 Off221580645OpenBenchmarking.orgWatts, Fewer Is BetterCpuminer-Opt 3.20.3CPU Power Consumption Monitor2004006008001000
MinAvgMaxAVX-512 On42.057.160.4AVX-512 Off46.658.260.9OpenBenchmarking.orgCelsius, Fewer Is BetterCpuminer-Opt 3.20.3CPU Temperature Monitor20406080100

simdjson

This is a benchmark of SIMDJSON, a high performance JSON parser. SIMDJSON aims to be the fastest JSON parser and is used by projects like Microsoft FishStore, Yandex ClickHouse, Shopify, and others. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgGB/s, More Is Bettersimdjson 2.0Throughput Test: DistinctUserIDAVX-512 OnAVX-512 Off246810SE +/- 0.02, N = 3SE +/- 0.01, N = 36.865.25-mavx512f -mavx512cd -mavx512vl -mavx512bw -mavx512dq -mavx512ifma -mavx512vbmi-mno-avx512f1. (CXX) g++ options: -O3 -march=native
OpenBenchmarking.orgGB/s Per Watt, More Is Bettersimdjson 2.0Throughput Test: DistinctUserIDAVX-512 OnAVX-512 Off0.00740.01480.02220.02960.0370.0330.024
MinAvgMaxAVX-512 On240036433754AVX-512 Off369437033925OpenBenchmarking.orgMegahertz, More Is Bettersimdjson 2.0CPU Peak Freq (Highest CPU Core Frequency) Monitor10002000300040005000
MinAvgMaxAVX-512 On35.8209.0219.1AVX-512 Off111.3221.2223.7OpenBenchmarking.orgWatts, Fewer Is Bettersimdjson 2.0CPU Power Consumption Monitor60120180240300
MinAvgMaxAVX-512 On32.436.237.3AVX-512 Off37.346.948.1OpenBenchmarking.orgCelsius, Fewer Is Bettersimdjson 2.0CPU Temperature Monitor1428425670

OpenBenchmarking.orgGB/s, More Is Bettersimdjson 2.0Throughput Test: PartialTweetsAVX-512 OnAVX-512 Off246810SE +/- 0.04, N = 3SE +/- 0.01, N = 36.705.14-mavx512f -mavx512cd -mavx512vl -mavx512bw -mavx512dq -mavx512ifma -mavx512vbmi-mno-avx512f1. (CXX) g++ options: -O3 -march=native
OpenBenchmarking.orgGB/s Per Watt, More Is Bettersimdjson 2.0Throughput Test: PartialTweetsAVX-512 OnAVX-512 Off0.00720.01440.02160.02880.0360.0320.023
MinAvgMaxAVX-512 On240036393702AVX-512 Off369437024016OpenBenchmarking.orgMegahertz, More Is Bettersimdjson 2.0CPU Peak Freq (Highest CPU Core Frequency) Monitor11002200330044005500
MinAvgMaxAVX-512 On50.2211.4225.1AVX-512 Off113.7224.4230.2OpenBenchmarking.orgWatts, Fewer Is Bettersimdjson 2.0CPU Power Consumption Monitor60120180240300
MinAvgMaxAVX-512 On36.440.547.5AVX-512 Off39.051.060.1OpenBenchmarking.orgCelsius, Fewer Is Bettersimdjson 2.0CPU Temperature Monitor1632486480

Neural Magic DeepSparse

OpenBenchmarking.orgitems/sec, More Is BetterNeural Magic DeepSparse 1.1Model: CV Detection,YOLOv5s COCO - Scenario: Asynchronous Multi-StreamAVX-512 OnAVX-512 Off2004006008001000SE +/- 0.77, N = 3SE +/- 1.12, N = 3857.23690.87

OpenBenchmarking.orgms/batch, Fewer Is BetterNeural Magic DeepSparse 1.1Model: CV Detection,YOLOv5s COCO - Scenario: Asynchronous Multi-StreamAVX-512 OnAVX-512 Off306090120150SE +/- 0.12, N = 3SE +/- 0.25, N = 3111.73138.59
MinAvgMaxAVX-512 On240028793730AVX-512 Off253529083834OpenBenchmarking.orgMegahertz, More Is BetterNeural Magic DeepSparse 1.1CPU Peak Freq (Highest CPU Core Frequency) Monitor10002000300040005000
MinAvgMaxAVX-512 On28553664AVX-512 Off217552656OpenBenchmarking.orgWatts, Fewer Is BetterNeural Magic DeepSparse 1.1CPU Power Consumption Monitor2004006008001000
MinAvgMaxAVX-512 On40.152.957.9AVX-512 Off44.954.461.8OpenBenchmarking.orgCelsius, Fewer Is BetterNeural Magic DeepSparse 1.1CPU Temperature Monitor20406080100

simdjson

This is a benchmark of SIMDJSON, a high performance JSON parser. SIMDJSON aims to be the fastest JSON parser and is used by projects like Microsoft FishStore, Yandex ClickHouse, Shopify, and others. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgGB/s, More Is Bettersimdjson 2.0Throughput Test: KostyaAVX-512 OnAVX-512 Off0.94051.8812.82153.7624.7025SE +/- 0.02, N = 3SE +/- 0.00, N = 34.183.39-mavx512f -mavx512cd -mavx512vl -mavx512bw -mavx512dq -mavx512ifma -mavx512vbmi-mno-avx512f1. (CXX) g++ options: -O3 -march=native
OpenBenchmarking.orgGB/s Per Watt, More Is Bettersimdjson 2.0Throughput Test: KostyaAVX-512 OnAVX-512 Off0.00450.0090.01350.0180.02250.0200.015
MinAvgMaxAVX-512 On240036253702AVX-512 Off369437043981OpenBenchmarking.orgMegahertz, More Is Bettersimdjson 2.0CPU Peak Freq (Highest CPU Core Frequency) Monitor11002200330044005500
MinAvgMaxAVX-512 On54.4209.9221.6AVX-512 Off112.5223.5225.7OpenBenchmarking.orgWatts, Fewer Is Bettersimdjson 2.0CPU Power Consumption Monitor60120180240300
MinAvgMaxAVX-512 On33.336.437.3AVX-512 Off37.346.348.6OpenBenchmarking.orgCelsius, Fewer Is Bettersimdjson 2.0CPU Temperature Monitor1428425670

OSPRay Studio

Intel OSPRay Studio is an open-source, interactive visualization and ray-tracing software package. OSPRay Studio makes use of Intel OSPRay, a portable ray-tracing engine for high-performance, high-fidelity visualizations. OSPRay builds off Intel's Embree and Intel SPMD Program Compiler (ISPC) components as part of the oneAPI rendering toolkit. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgms, Fewer Is BetterOSPRay Studio 0.11Camera: 2 - Resolution: 1080p - Samples Per Pixel: 32 - Renderer: Path TracerAVX-512 OnAVX-512 Off13002600390052006500SE +/- 6.24, N = 3SE +/- 8.25, N = 347645861-mavx512f -mavx512cd -mavx512vl -mavx512bw -mavx512dq -mavx512ifma -mavx512vbmi-mno-avx512f1. (CXX) g++ options: -O3 -march=native -ldl
MinAvgMaxAVX-512 On240029353696AVX-512 Off277129723740OpenBenchmarking.orgMegahertz, More Is BetterOSPRay Studio 0.11CPU Peak Freq (Highest CPU Core Frequency) Monitor10002000300040005000
MinAvgMaxAVX-512 On54604686AVX-512 Off224627702OpenBenchmarking.orgWatts, Fewer Is BetterOSPRay Studio 0.11CPU Power Consumption Monitor2004006008001000
MinAvgMaxAVX-512 On43.858.963.1AVX-512 Off46.661.365.8OpenBenchmarking.orgCelsius, Fewer Is BetterOSPRay Studio 0.11CPU Temperature Monitor20406080100

OpenBenchmarking.orgms, Fewer Is BetterOSPRay Studio 0.11Camera: 2 - Resolution: 4K - Samples Per Pixel: 16 - Renderer: Path TracerAVX-512 OnAVX-512 Off2K4K6K8K10KSE +/- 2.19, N = 3SE +/- 15.51, N = 3938511524-mavx512f -mavx512cd -mavx512vl -mavx512bw -mavx512dq -mavx512ifma -mavx512vbmi-mno-avx512f1. (CXX) g++ options: -O3 -march=native -ldl
MinAvgMaxAVX-512 On240029063696AVX-512 Off272129603862OpenBenchmarking.orgMegahertz, More Is BetterOSPRay Studio 0.11CPU Peak Freq (Highest CPU Core Frequency) Monitor10002000300040005000
MinAvgMaxAVX-512 On57616688AVX-512 Off114635701OpenBenchmarking.orgWatts, Fewer Is BetterOSPRay Studio 0.11CPU Power Consumption Monitor2004006008001000
MinAvgMaxAVX-512 On43.559.764.0AVX-512 Off46.161.665.4OpenBenchmarking.orgCelsius, Fewer Is BetterOSPRay Studio 0.11CPU Temperature Monitor20406080100

OpenBenchmarking.orgms, Fewer Is BetterOSPRay Studio 0.11Camera: 2 - Resolution: 1080p - Samples Per Pixel: 16 - Renderer: Path TracerAVX-512 OnAVX-512 Off6001200180024003000SE +/- 9.17, N = 3SE +/- 0.88, N = 323842924-mavx512f -mavx512cd -mavx512vl -mavx512bw -mavx512dq -mavx512ifma -mavx512vbmi-mno-avx512f1. (CXX) g++ options: -O3 -march=native -ldl
MinAvgMaxAVX-512 On240029223700AVX-512 Off278329933739OpenBenchmarking.orgMegahertz, More Is BetterOSPRay Studio 0.11CPU Peak Freq (Highest CPU Core Frequency) Monitor10002000300040005000
MinAvgMaxAVX-512 On29599684AVX-512 Off116621701OpenBenchmarking.orgWatts, Fewer Is BetterOSPRay Studio 0.11CPU Power Consumption Monitor2004006008001000
MinAvgMaxAVX-512 On43.858.462.6AVX-512 Off46.660.664.9OpenBenchmarking.orgCelsius, Fewer Is BetterOSPRay Studio 0.11CPU Temperature Monitor20406080100

OpenBenchmarking.orgms, Fewer Is BetterOSPRay Studio 0.11Camera: 1 - Resolution: 1080p - Samples Per Pixel: 32 - Renderer: Path TracerAVX-512 OnAVX-512 Off12002400360048006000SE +/- 3.71, N = 3SE +/- 6.56, N = 346985749-mavx512f -mavx512cd -mavx512vl -mavx512bw -mavx512dq -mavx512ifma -mavx512vbmi-mno-avx512f1. (CXX) g++ options: -O3 -march=native -ldl
MinAvgMaxAVX-512 On240029043702AVX-512 Off280229784050OpenBenchmarking.orgMegahertz, More Is BetterOSPRay Studio 0.11CPU Peak Freq (Highest CPU Core Frequency) Monitor11002200330044005500
MinAvgMaxAVX-512 On58606687AVX-512 Off222629702OpenBenchmarking.orgWatts, Fewer Is BetterOSPRay Studio 0.11CPU Power Consumption Monitor2004006008001000
MinAvgMaxAVX-512 On44.059.064.0AVX-512 Off46.661.368.0OpenBenchmarking.orgCelsius, Fewer Is BetterOSPRay Studio 0.11CPU Temperature Monitor20406080100

OpenBenchmarking.orgms, Fewer Is BetterOSPRay Studio 0.11Camera: 1 - Resolution: 1080p - Samples Per Pixel: 1 - Renderer: Path TracerAVX-512 OnAVX-512 Off4080120160200SE +/- 0.33, N = 3SE +/- 0.33, N = 3148181-mavx512f -mavx512cd -mavx512vl -mavx512bw -mavx512dq -mavx512ifma -mavx512vbmi-mno-avx512f1. (CXX) g++ options: -O3 -march=native -ldl
MinAvgMaxAVX-512 On240029393695AVX-512 Off270829973911OpenBenchmarking.orgMegahertz, More Is BetterOSPRay Studio 0.11CPU Peak Freq (Highest CPU Core Frequency) Monitor10002000300040005000
MinAvgMaxAVX-512 On55593680AVX-512 Off218614692OpenBenchmarking.orgWatts, Fewer Is BetterOSPRay Studio 0.11CPU Power Consumption Monitor2004006008001000
MinAvgMaxAVX-512 On36.456.362.3AVX-512 Off41.858.964.5OpenBenchmarking.orgCelsius, Fewer Is BetterOSPRay Studio 0.11CPU Temperature Monitor20406080100

OpenBenchmarking.orgms, Fewer Is BetterOSPRay Studio 0.11Camera: 2 - Resolution: 4K - Samples Per Pixel: 32 - Renderer: Path TracerAVX-512 OnAVX-512 Off5K10K15K20K25KSE +/- 20.34, N = 3SE +/- 30.02, N = 31880822985-mavx512f -mavx512cd -mavx512vl -mavx512bw -mavx512dq -mavx512ifma -mavx512vbmi-mno-avx512f1. (CXX) g++ options: -O3 -march=native -ldl
MinAvgMaxAVX-512 On240029073700AVX-512 Off272630074349OpenBenchmarking.orgMegahertz, More Is BetterOSPRay Studio 0.11CPU Peak Freq (Highest CPU Core Frequency) Monitor11002200330044005500
MinAvgMaxAVX-512 On60616683AVX-512 Off224609700OpenBenchmarking.orgWatts, Fewer Is BetterOSPRay Studio 0.11CPU Power Consumption Monitor2004006008001000
MinAvgMaxAVX-512 On45.359.864.9AVX-512 Off47.559.964.1OpenBenchmarking.orgCelsius, Fewer Is BetterOSPRay Studio 0.11CPU Temperature Monitor20406080100

OpenBenchmarking.orgms, Fewer Is BetterOSPRay Studio 0.11Camera: 1 - Resolution: 4K - Samples Per Pixel: 1 - Renderer: Path TracerAVX-512 OnAVX-512 Off150300450600750SE +/- 1.00, N = 3SE +/- 2.08, N = 3581710-mavx512f -mavx512cd -mavx512vl -mavx512bw -mavx512dq -mavx512ifma -mavx512vbmi-mno-avx512f1. (CXX) g++ options: -O3 -march=native -ldl
MinAvgMaxAVX-512 On240029503701AVX-512 Off269630013902OpenBenchmarking.orgMegahertz, More Is BetterOSPRay Studio 0.11CPU Peak Freq (Highest CPU Core Frequency) Monitor10002000300040005000
MinAvgMaxAVX-512 On51590687AVX-512 Off225610697OpenBenchmarking.orgWatts, Fewer Is BetterOSPRay Studio 0.11CPU Power Consumption Monitor2004006008001000
MinAvgMaxAVX-512 On44.157.962.3AVX-512 Off48.060.264.0OpenBenchmarking.orgCelsius, Fewer Is BetterOSPRay Studio 0.11CPU Temperature Monitor20406080100

OpenBenchmarking.orgms, Fewer Is BetterOSPRay Studio 0.11Camera: 1 - Resolution: 4K - Samples Per Pixel: 32 - Renderer: Path TracerAVX-512 OnAVX-512 Off5K10K15K20K25KSE +/- 13.75, N = 3SE +/- 27.41, N = 31854622647-mavx512f -mavx512cd -mavx512vl -mavx512bw -mavx512dq -mavx512ifma -mavx512vbmi-mno-avx512f1. (CXX) g++ options: -O3 -march=native -ldl
MinAvgMaxAVX-512 On240028763752AVX-512 Off276929893982OpenBenchmarking.orgMegahertz, More Is BetterOSPRay Studio 0.11CPU Peak Freq (Highest CPU Core Frequency) Monitor11002200330044005500
MinAvgMaxAVX-512 On58623687AVX-512 Off128610701OpenBenchmarking.orgWatts, Fewer Is BetterOSPRay Studio 0.11CPU Power Consumption Monitor2004006008001000
MinAvgMaxAVX-512 On44.960.365.4AVX-512 Off47.560.366.3OpenBenchmarking.orgCelsius, Fewer Is BetterOSPRay Studio 0.11CPU Temperature Monitor20406080100

OpenBenchmarking.orgms, Fewer Is BetterOSPRay Studio 0.11Camera: 1 - Resolution: 4K - Samples Per Pixel: 16 - Renderer: Path TracerAVX-512 OnAVX-512 Off2K4K6K8K10KSE +/- 10.17, N = 3SE +/- 24.46, N = 3927111321-mavx512f -mavx512cd -mavx512vl -mavx512bw -mavx512dq -mavx512ifma -mavx512vbmi-mno-avx512f1. (CXX) g++ options: -O3 -march=native -ldl
MinAvgMaxAVX-512 On240028883699AVX-512 Off270929373983OpenBenchmarking.orgMegahertz, More Is BetterOSPRay Studio 0.11CPU Peak Freq (Highest CPU Core Frequency) Monitor11002200330044005500
MinAvgMaxAVX-512 On56618684AVX-512 Off223638703OpenBenchmarking.orgWatts, Fewer Is BetterOSPRay Studio 0.11CPU Power Consumption Monitor2004006008001000
MinAvgMaxAVX-512 On43.859.764.9AVX-512 Off46.662.065.4OpenBenchmarking.orgCelsius, Fewer Is BetterOSPRay Studio 0.11CPU Temperature Monitor20406080100

OpenBenchmarking.orgms, Fewer Is BetterOSPRay Studio 0.11Camera: 1 - Resolution: 1080p - Samples Per Pixel: 16 - Renderer: Path TracerAVX-512 OnAVX-512 Off6001200180024003000SE +/- 2.33, N = 3SE +/- 1.20, N = 323532871-mavx512f -mavx512cd -mavx512vl -mavx512bw -mavx512dq -mavx512ifma -mavx512vbmi-mno-avx512f1. (CXX) g++ options: -O3 -march=native -ldl
MinAvgMaxAVX-512 On240029303699AVX-512 Off269629794041OpenBenchmarking.orgMegahertz, More Is BetterOSPRay Studio 0.11CPU Peak Freq (Highest CPU Core Frequency) Monitor11002200330044005500
MinAvgMaxAVX-512 On56599685AVX-512 Off223622699OpenBenchmarking.orgWatts, Fewer Is BetterOSPRay Studio 0.11CPU Power Consumption Monitor2004006008001000
MinAvgMaxAVX-512 On43.558.465.0AVX-512 Off46.660.764.9OpenBenchmarking.orgCelsius, Fewer Is BetterOSPRay Studio 0.11CPU Temperature Monitor20406080100

OpenBenchmarking.orgms, Fewer Is BetterOSPRay Studio 0.11Camera: 3 - Resolution: 1080p - Samples Per Pixel: 16 - Renderer: Path TracerAVX-512 OnAVX-512 Off7001400210028003500SE +/- 3.06, N = 3SE +/- 7.00, N = 328043413-mavx512f -mavx512cd -mavx512vl -mavx512bw -mavx512dq -mavx512ifma -mavx512vbmi-mno-avx512f1. (CXX) g++ options: -O3 -march=native -ldl
MinAvgMaxAVX-512 On240029263699AVX-512 Off272129714031OpenBenchmarking.orgMegahertz, More Is BetterOSPRay Studio 0.11CPU Peak Freq (Highest CPU Core Frequency) Monitor11002200330044005500
MinAvgMaxAVX-512 On31602684AVX-512 Off223621699OpenBenchmarking.orgWatts, Fewer Is BetterOSPRay Studio 0.11CPU Power Consumption Monitor2004006008001000
MinAvgMaxAVX-512 On43.858.765.4AVX-512 Off47.060.864.9OpenBenchmarking.orgCelsius, Fewer Is BetterOSPRay Studio 0.11CPU Temperature Monitor20406080100

OpenBenchmarking.orgms, Fewer Is BetterOSPRay Studio 0.11Camera: 3 - Resolution: 1080p - Samples Per Pixel: 32 - Renderer: Path TracerAVX-512 OnAVX-512 Off15003000450060007500SE +/- 9.54, N = 3SE +/- 5.51, N = 356086820-mavx512f -mavx512cd -mavx512vl -mavx512bw -mavx512dq -mavx512ifma -mavx512vbmi-mno-avx512f1. (CXX) g++ options: -O3 -march=native -ldl
MinAvgMaxAVX-512 On240029233697AVX-512 Off271529724286OpenBenchmarking.orgMegahertz, More Is BetterOSPRay Studio 0.11CPU Peak Freq (Highest CPU Core Frequency) Monitor11002200330044005500
MinAvgMaxAVX-512 On58611684AVX-512 Off222630700OpenBenchmarking.orgWatts, Fewer Is BetterOSPRay Studio 0.11CPU Power Consumption Monitor2004006008001000
MinAvgMaxAVX-512 On43.859.364.0AVX-512 Off46.661.366.3OpenBenchmarking.orgCelsius, Fewer Is BetterOSPRay Studio 0.11CPU Temperature Monitor20406080100

simdjson

This is a benchmark of SIMDJSON, a high performance JSON parser. SIMDJSON aims to be the fastest JSON parser and is used by projects like Microsoft FishStore, Yandex ClickHouse, Shopify, and others. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgGB/s, More Is Bettersimdjson 2.0Throughput Test: TopTweetAVX-512 OnAVX-512 Off246810SE +/- 0.08, N = 4SE +/- 0.01, N = 36.525.38-mavx512f -mavx512cd -mavx512vl -mavx512bw -mavx512dq -mavx512ifma -mavx512vbmi-mno-avx512f1. (CXX) g++ options: -O3 -march=native
OpenBenchmarking.orgGB/s Per Watt, More Is Bettersimdjson 2.0Throughput Test: TopTweetAVX-512 OnAVX-512 Off0.0070.0140.0210.0280.0350.0310.024
MinAvgMaxAVX-512 On240036403701AVX-512 Off369437013912OpenBenchmarking.orgMegahertz, More Is Bettersimdjson 2.0CPU Peak Freq (Highest CPU Core Frequency) Monitor10002000300040005000
MinAvgMaxAVX-512 On55.3209.4219.2AVX-512 Off111.2221.5223.4OpenBenchmarking.orgWatts, Fewer Is Bettersimdjson 2.0CPU Power Consumption Monitor60120180240300
MinAvgMaxAVX-512 On32.436.137.3AVX-512 Off36.846.247.5OpenBenchmarking.orgCelsius, Fewer Is Bettersimdjson 2.0CPU Temperature Monitor1428425670

OSPRay Studio

Intel OSPRay Studio is an open-source, interactive visualization and ray-tracing software package. OSPRay Studio makes use of Intel OSPRay, a portable ray-tracing engine for high-performance, high-fidelity visualizations. OSPRay builds off Intel's Embree and Intel SPMD Program Compiler (ISPC) components as part of the oneAPI rendering toolkit. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgms, Fewer Is BetterOSPRay Studio 0.11Camera: 3 - Resolution: 4K - Samples Per Pixel: 1 - Renderer: Path TracerAVX-512 OnAVX-512 Off2004006008001000SE +/- 1.53, N = 3SE +/- 1.15, N = 3694841-mavx512f -mavx512cd -mavx512vl -mavx512bw -mavx512dq -mavx512ifma -mavx512vbmi-mno-avx512f1. (CXX) g++ options: -O3 -march=native -ldl
MinAvgMaxAVX-512 On240029373698AVX-512 Off272129964398OpenBenchmarking.orgMegahertz, More Is BetterOSPRay Studio 0.11CPU Peak Freq (Highest CPU Core Frequency) Monitor11002200330044005500
MinAvgMaxAVX-512 On39591684AVX-512 Off221612698OpenBenchmarking.orgWatts, Fewer Is BetterOSPRay Studio 0.11CPU Power Consumption Monitor2004006008001000
MinAvgMaxAVX-512 On44.958.262.8AVX-512 Off46.660.064.0OpenBenchmarking.orgCelsius, Fewer Is BetterOSPRay Studio 0.11CPU Temperature Monitor20406080100

simdjson

This is a benchmark of SIMDJSON, a high performance JSON parser. SIMDJSON aims to be the fastest JSON parser and is used by projects like Microsoft FishStore, Yandex ClickHouse, Shopify, and others. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgGB/s, More Is Bettersimdjson 2.0Throughput Test: LargeRandomAVX-512 OnAVX-512 Off0.28350.5670.85051.1341.4175SE +/- 0.00, N = 3SE +/- 0.00, N = 31.261.04-mavx512f -mavx512cd -mavx512vl -mavx512bw -mavx512dq -mavx512ifma -mavx512vbmi-mno-avx512f1. (CXX) g++ options: -O3 -march=native
OpenBenchmarking.orgGB/s Per Watt, More Is Bettersimdjson 2.0Throughput Test: LargeRandomAVX-512 OnAVX-512 Off0.00140.00280.00420.00560.0070.0060.005
MinAvgMaxAVX-512 On240036013700AVX-512 Off369437013788OpenBenchmarking.orgMegahertz, More Is Bettersimdjson 2.0CPU Peak Freq (Highest CPU Core Frequency) Monitor10002000300040005000
MinAvgMaxAVX-512 On53.8207.0220.8AVX-512 Off111.6222.5224.6OpenBenchmarking.orgWatts, Fewer Is Bettersimdjson 2.0CPU Power Consumption Monitor60120180240300
MinAvgMaxAVX-512 On33.336.737.8AVX-512 Off37.847.049.8OpenBenchmarking.orgCelsius, Fewer Is Bettersimdjson 2.0CPU Temperature Monitor1428425670

Neural Magic DeepSparse

OpenBenchmarking.orgitems/sec, More Is BetterNeural Magic DeepSparse 1.1Model: NLP Text Classification, BERT base uncased SST2 - Scenario: Asynchronous Multi-StreamAVX-512 OnAVX-512 Off130260390520650SE +/- 1.92, N = 3SE +/- 0.33, N = 3616.68509.45

OSPRay Studio

Intel OSPRay Studio is an open-source, interactive visualization and ray-tracing software package. OSPRay Studio makes use of Intel OSPRay, a portable ray-tracing engine for high-performance, high-fidelity visualizations. OSPRay builds off Intel's Embree and Intel SPMD Program Compiler (ISPC) components as part of the oneAPI rendering toolkit. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgms, Fewer Is BetterOSPRay Studio 0.11Camera: 3 - Resolution: 4K - Samples Per Pixel: 16 - Renderer: Path TracerAVX-512 OnAVX-512 Off3K6K9K12K15KSE +/- 27.14, N = 3SE +/- 22.81, N = 31107013398-mavx512f -mavx512cd -mavx512vl -mavx512bw -mavx512dq -mavx512ifma -mavx512vbmi-mno-avx512f1. (CXX) g++ options: -O3 -march=native -ldl
MinAvgMaxAVX-512 On240029103697AVX-512 Off275229564184OpenBenchmarking.orgMegahertz, More Is BetterOSPRay Studio 0.11CPU Peak Freq (Highest CPU Core Frequency) Monitor11002200330044005500
MinAvgMaxAVX-512 On60618690AVX-512 Off114637703OpenBenchmarking.orgWatts, Fewer Is BetterOSPRay Studio 0.11CPU Power Consumption Monitor2004006008001000
MinAvgMaxAVX-512 On44.659.964.9AVX-512 Off46.661.664.9OpenBenchmarking.orgCelsius, Fewer Is BetterOSPRay Studio 0.11CPU Temperature Monitor20406080100

Neural Magic DeepSparse

OpenBenchmarking.orgms/batch, Fewer Is BetterNeural Magic DeepSparse 1.1Model: NLP Text Classification, BERT base uncased SST2 - Scenario: Asynchronous Multi-StreamAVX-512 OnAVX-512 Off4080120160200SE +/- 0.47, N = 3SE +/- 0.10, N = 3155.35187.85
MinAvgMaxAVX-512 On240031093928AVX-512 Off258931354299OpenBenchmarking.orgMegahertz, More Is BetterNeural Magic DeepSparse 1.1CPU Peak Freq (Highest CPU Core Frequency) Monitor11002200330044005500
MinAvgMaxAVX-512 On53479679AVX-512 Off216508705OpenBenchmarking.orgWatts, Fewer Is BetterNeural Magic DeepSparse 1.1CPU Power Consumption Monitor2004006008001000
MinAvgMaxAVX-512 On38.649.457.0AVX-512 Off41.851.560.0OpenBenchmarking.orgCelsius, Fewer Is BetterNeural Magic DeepSparse 1.1CPU Temperature Monitor1632486480

OSPRay Studio

Intel OSPRay Studio is an open-source, interactive visualization and ray-tracing software package. OSPRay Studio makes use of Intel OSPRay, a portable ray-tracing engine for high-performance, high-fidelity visualizations. OSPRay builds off Intel's Embree and Intel SPMD Program Compiler (ISPC) components as part of the oneAPI rendering toolkit. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgms, Fewer Is BetterOSPRay Studio 0.11Camera: 3 - Resolution: 1080p - Samples Per Pixel: 1 - Renderer: Path TracerAVX-512 OnAVX-512 Off50100150200250SE +/- 0.00, N = 3SE +/- 0.58, N = 3177214-mavx512f -mavx512cd -mavx512vl -mavx512bw -mavx512dq -mavx512ifma -mavx512vbmi-mno-avx512f1. (CXX) g++ options: -O3 -march=native -ldl
MinAvgMaxAVX-512 On240029313701AVX-512 Off270530013951OpenBenchmarking.orgMegahertz, More Is BetterOSPRay Studio 0.11CPU Peak Freq (Highest CPU Core Frequency) Monitor10002000300040005000
MinAvgMaxAVX-512 On38597682AVX-512 Off223621696OpenBenchmarking.orgWatts, Fewer Is BetterOSPRay Studio 0.11CPU Power Consumption Monitor2004006008001000
MinAvgMaxAVX-512 On44.158.462.3AVX-512 Off46.660.364.5OpenBenchmarking.orgCelsius, Fewer Is BetterOSPRay Studio 0.11CPU Temperature Monitor20406080100

OpenBenchmarking.orgms, Fewer Is BetterOSPRay Studio 0.11Camera: 3 - Resolution: 4K - Samples Per Pixel: 32 - Renderer: Path TracerAVX-512 OnAVX-512 Off6K12K18K24K30KSE +/- 21.63, N = 3SE +/- 15.62, N = 32218426785-mavx512f -mavx512cd -mavx512vl -mavx512bw -mavx512dq -mavx512ifma -mavx512vbmi-mno-avx512f1. (CXX) g++ options: -O3 -march=native -ldl
MinAvgMaxAVX-512 On240029433701AVX-512 Off272729733711OpenBenchmarking.orgMegahertz, More Is BetterOSPRay Studio 0.11CPU Peak Freq (Highest CPU Core Frequency) Monitor10002000300040005000
MinAvgMaxAVX-512 On57590687AVX-512 Off224620702OpenBenchmarking.orgWatts, Fewer Is BetterOSPRay Studio 0.11CPU Power Consumption Monitor2004006008001000
MinAvgMaxAVX-512 On44.657.962.6AVX-512 Off47.060.865.4OpenBenchmarking.orgCelsius, Fewer Is BetterOSPRay Studio 0.11CPU Temperature Monitor20406080100

Embree

Intel Embree is a collection of high-performance ray-tracing kernels for execution on CPUs and supporting instruction sets such as SSE, AVX, AVX2, and AVX-512. Embree also supports making use of the Intel SPMD Program Compiler (ISPC). Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgFrames Per Second, More Is BetterEmbree 3.13Binary: Pathtracer ISPC - Model: Asian DragonAVX-512 OnAVX-512 Off50100150200250SE +/- 0.22, N = 9SE +/- 0.21, N = 8212.94176.88MIN: 207.72 / MAX: 227.11MIN: 170.19 / MAX: 190
OpenBenchmarking.orgFrames Per Second Per Watt, More Is BetterEmbree 3.13Binary: Pathtracer ISPC - Model: Asian DragonAVX-512 OnAVX-512 Off0.15910.31820.47730.63640.79550.7070.431
MinAvgMaxAVX-512 On240029743695AVX-512 Off289935084437OpenBenchmarking.orgMegahertz, More Is BetterEmbree 3.13CPU Peak Freq (Highest CPU Core Frequency) Monitor12002400360048006000
MinAvgMaxAVX-512 On50301635AVX-512 Off132410637OpenBenchmarking.orgWatts, Fewer Is BetterEmbree 3.13CPU Power Consumption Monitor2004006008001000
MinAvgMaxAVX-512 On35.540.447.0AVX-512 Off41.845.851.1OpenBenchmarking.orgCelsius, Fewer Is BetterEmbree 3.13CPU Temperature Monitor1530456075

OpenBenchmarking.orgFrames Per Second, More Is BetterEmbree 3.13Binary: Pathtracer ISPC - Model: Asian Dragon ObjAVX-512 OnAVX-512 Off4080120160200SE +/- 0.62, N = 4SE +/- 0.36, N = 4184.47153.45MIN: 178.83 / MAX: 196.34MIN: 130.31 / MAX: 166.17
OpenBenchmarking.orgFrames Per Second Per Watt, More Is BetterEmbree 3.13Binary: Pathtracer ISPC - Model: Asian Dragon ObjAVX-512 OnAVX-512 Off0.16310.32620.48930.65240.81550.7250.481
MinAvgMaxAVX-512 On240033723699AVX-512 Off288935924020OpenBenchmarking.orgMegahertz, More Is BetterEmbree 3.13CPU Peak Freq (Highest CPU Core Frequency) Monitor11002200330044005500
MinAvgMaxAVX-512 On56254632AVX-512 Off217319632OpenBenchmarking.orgWatts, Fewer Is BetterEmbree 3.13CPU Power Consumption Monitor2004006008001000
MinAvgMaxAVX-512 On34.638.446.6AVX-512 Off39.942.449.3OpenBenchmarking.orgCelsius, Fewer Is BetterEmbree 3.13CPU Temperature Monitor1428425670

Neural Magic DeepSparse

OpenBenchmarking.orgitems/sec, More Is BetterNeural Magic DeepSparse 1.1Model: CV Detection,YOLOv5s COCO - Scenario: Synchronous Single-StreamAVX-512 OnAVX-512 Off4080120160200SE +/- 0.22, N = 3SE +/- 0.17, N = 3189.56157.82

OpenBenchmarking.orgms/batch, Fewer Is BetterNeural Magic DeepSparse 1.1Model: CV Detection,YOLOv5s COCO - Scenario: Synchronous Single-StreamAVX-512 OnAVX-512 Off246810SE +/- 0.0061, N = 3SE +/- 0.0068, N = 35.27126.3313
MinAvgMaxAVX-512 On240035273821AVX-512 Off306836414426OpenBenchmarking.orgMegahertz, More Is BetterNeural Magic DeepSparse 1.1CPU Peak Freq (Highest CPU Core Frequency) Monitor11002200330044005500
MinAvgMaxAVX-512 On52.3341.3408.7AVX-512 Off202.0364.8414.2OpenBenchmarking.orgWatts, Fewer Is BetterNeural Magic DeepSparse 1.1CPU Power Consumption Monitor110220330440550
MinAvgMaxAVX-512 On39.850.154.6AVX-512 Off44.452.155.6OpenBenchmarking.orgCelsius, Fewer Is BetterNeural Magic DeepSparse 1.1CPU Temperature Monitor1530456075

Embree

Intel Embree is a collection of high-performance ray-tracing kernels for execution on CPUs and supporting instruction sets such as SSE, AVX, AVX2, and AVX-512. Embree also supports making use of the Intel SPMD Program Compiler (ISPC). Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgFrames Per Second, More Is BetterEmbree 3.13Binary: Pathtracer ISPC - Model: CrownAVX-512 OnAVX-512 Off4080120160200SE +/- 0.62, N = 8SE +/- 0.25, N = 7180.93151.06MIN: 124.41 / MAX: 209.74MIN: 114.4 / MAX: 176.43
OpenBenchmarking.orgFrames Per Second Per Watt, More Is BetterEmbree 3.13Binary: Pathtracer ISPC - Model: CrownAVX-512 OnAVX-512 Off0.11790.23580.35370.47160.58950.5240.344
MinAvgMaxAVX-512 On240029283696AVX-512 Off272634465379OpenBenchmarking.orgMegahertz, More Is BetterEmbree 3.13CPU Peak Freq (Highest CPU Core Frequency) Monitor14002800420056007000
MinAvgMaxAVX-512 On54346646AVX-512 Off174439660OpenBenchmarking.orgWatts, Fewer Is BetterEmbree 3.13CPU Power Consumption Monitor2004006008001000
MinAvgMaxAVX-512 On33.340.548.0AVX-512 Off39.545.852.0OpenBenchmarking.orgCelsius, Fewer Is BetterEmbree 3.13CPU Temperature Monitor1530456075

OSPRay Studio

Intel OSPRay Studio is an open-source, interactive visualization and ray-tracing software package. OSPRay Studio makes use of Intel OSPRay, a portable ray-tracing engine for high-performance, high-fidelity visualizations. OSPRay builds off Intel's Embree and Intel SPMD Program Compiler (ISPC) components as part of the oneAPI rendering toolkit. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgms, Fewer Is BetterOSPRay Studio 0.11Camera: 2 - Resolution: 4K - Samples Per Pixel: 1 - Renderer: Path TracerAVX-512 OnAVX-512 Off160320480640800SE +/- 1.00, N = 3SE +/- 0.67, N = 3604722-mavx512f -mavx512cd -mavx512vl -mavx512bw -mavx512dq -mavx512ifma -mavx512vbmi-mno-avx512f1. (CXX) g++ options: -O3 -march=native -ldl
MinAvgMaxAVX-512 On240028683857AVX-512 Off271230043940OpenBenchmarking.orgMegahertz, More Is BetterOSPRay Studio 0.11CPU Peak Freq (Highest CPU Core Frequency) Monitor10002000300040005000
MinAvgMaxAVX-512 On55578672AVX-512 Off223609696OpenBenchmarking.orgWatts, Fewer Is BetterOSPRay Studio 0.11CPU Power Consumption Monitor2004006008001000
MinAvgMaxAVX-512 On44.457.061.4AVX-512 Off46.659.964.0OpenBenchmarking.orgCelsius, Fewer Is BetterOSPRay Studio 0.11CPU Temperature Monitor20406080100

OpenBenchmarking.orgms, Fewer Is BetterOSPRay Studio 0.11Camera: 2 - Resolution: 1080p - Samples Per Pixel: 1 - Renderer: Path TracerAVX-512 OnAVX-512 Off4080120160200SE +/- 0.00, N = 3SE +/- 0.33, N = 3154184-mavx512f -mavx512cd -mavx512vl -mavx512bw -mavx512dq -mavx512ifma -mavx512vbmi-mno-avx512f1. (CXX) g++ options: -O3 -march=native -ldl
MinAvgMaxAVX-512 On240028593697AVX-512 Off270229953808OpenBenchmarking.orgMegahertz, More Is BetterOSPRay Studio 0.11CPU Peak Freq (Highest CPU Core Frequency) Monitor10002000300040005000
MinAvgMaxAVX-512 On59591670AVX-512 Off203613697OpenBenchmarking.orgWatts, Fewer Is BetterOSPRay Studio 0.11CPU Power Consumption Monitor2004006008001000
MinAvgMaxAVX-512 On44.957.761.8AVX-512 Off47.059.964.0OpenBenchmarking.orgCelsius, Fewer Is BetterOSPRay Studio 0.11CPU Temperature Monitor20406080100

Neural Magic DeepSparse

OpenBenchmarking.orgms/batch, Fewer Is BetterNeural Magic DeepSparse 1.1Model: NLP Text Classification, DistilBERT mnli - Scenario: Asynchronous Multi-StreamAVX-512 OnAVX-512 Off20406080100SE +/- 0.14, N = 3SE +/- 0.05, N = 380.0895.33
MinAvgMaxAVX-512 On240028683737AVX-512 Off262329874137OpenBenchmarking.orgMegahertz, More Is BetterNeural Magic DeepSparse 1.1CPU Peak Freq (Highest CPU Core Frequency) Monitor11002200330044005500
MinAvgMaxAVX-512 On49517625AVX-512 Off217552659OpenBenchmarking.orgWatts, Fewer Is BetterNeural Magic DeepSparse 1.1CPU Power Consumption Monitor2004006008001000
MinAvgMaxAVX-512 On39.951.255.5AVX-512 Off43.954.459.1OpenBenchmarking.orgCelsius, Fewer Is BetterNeural Magic DeepSparse 1.1CPU Temperature Monitor1632486480

OpenFOAM

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

OpenBenchmarking.orgSeconds, Fewer Is BetterOpenFOAM 10Input: drivaerFastback, Medium Mesh Size - Execution TimeAVX-512 OnAVX-512 Off306090120150113.64135.221. (CXX) g++ options: -std=c++14 -m64 -O3 -ftemplate-depth-100 -fPIC -fuse-ld=bfd -Xlinker --add-needed --no-as-needed -lfiniteVolume -lmeshTools -lparallel -llagrangian -lregionModels -lgenericPatchFields -lOpenFOAM -ldl -lm
MinAvgMaxAVX-512 On240031863701AVX-512 Off291732653714OpenBenchmarking.orgMegahertz, More Is BetterOpenFOAM 10CPU Peak Freq (Highest CPU Core Frequency) Monitor10002000300040005000
MinAvgMaxAVX-512 On57662731AVX-512 Off220674735OpenBenchmarking.orgWatts, Fewer Is BetterOpenFOAM 10CPU Power Consumption Monitor2004006008001000
MinAvgMaxAVX-512 On41.362.668.5AVX-512 Off47.064.970.3OpenBenchmarking.orgCelsius, Fewer Is BetterOpenFOAM 10CPU Temperature Monitor20406080100

Neural Magic DeepSparse

OpenBenchmarking.orgitems/sec, More Is BetterNeural Magic DeepSparse 1.1Model: NLP Text Classification, DistilBERT mnli - Scenario: Asynchronous Multi-StreamAVX-512 OnAVX-512 Off30060090012001500SE +/- 2.39, N = 3SE +/- 0.78, N = 31195.941005.16

OpenBenchmarking.orgitems/sec, More Is BetterNeural Magic DeepSparse 1.1Model: NLP Text Classification, BERT base uncased SST2 - Scenario: Synchronous Single-StreamAVX-512 OnAVX-512 Off20406080100SE +/- 0.45, N = 3SE +/- 0.27, N = 385.0073.54

OpenBenchmarking.orgms/batch, Fewer Is BetterNeural Magic DeepSparse 1.1Model: NLP Text Classification, BERT base uncased SST2 - Scenario: Synchronous Single-StreamAVX-512 OnAVX-512 Off3691215SE +/- 0.06, N = 3SE +/- 0.05, N = 311.7613.59
MinAvgMaxAVX-512 On240035593801AVX-512 Off350736983967OpenBenchmarking.orgMegahertz, More Is BetterNeural Magic DeepSparse 1.1CPU Peak Freq (Highest CPU Core Frequency) Monitor11002200330044005500
MinAvgMaxAVX-512 On50.9306.4407.9AVX-512 Off111.5321.8409.9OpenBenchmarking.orgWatts, Fewer Is BetterNeural Magic DeepSparse 1.1CPU Power Consumption Monitor110220330440550
MinAvgMaxAVX-512 On32.443.751.5AVX-512 Off36.845.252.4OpenBenchmarking.orgCelsius, Fewer Is BetterNeural Magic DeepSparse 1.1CPU Temperature Monitor1530456075

OpenVKL

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

OpenBenchmarking.orgItems / Sec, More Is BetterOpenVKL 1.3.1Benchmark: vklBenchmark ISPCAVX-512 OnAVX-512 Off30060090012001500SE +/- 13.58, N = 3SE +/- 8.11, N = 313321155MIN: 329 / MAX: 4770MIN: 251 / MAX: 5181
OpenBenchmarking.orgItems / Sec Per Watt, More Is BetterOpenVKL 1.3.1Benchmark: vklBenchmark ISPCAVX-512 OnAVX-512 Off0.64191.28381.92572.56763.20952.8532.355
OpenBenchmarking.orgMegahertz, More Is BetterOpenVKL 1.3.1CPU Peak Freq (Highest CPU Core Frequency) MonitorAVX-512 OnAVX-512 Off7001400210028003500Min: 2400 / Avg: 3408.84 / Max: 3732Min: 2621 / Avg: 3373.13 / Max: 4085
OpenBenchmarking.orgWatts, Fewer Is BetterOpenVKL 1.3.1CPU Power Consumption MonitorAVX-512 OnAVX-512 Off120240360480600Min: 55.92 / Avg: 466.92 / Max: 669.54Min: 113.56 / Avg: 490.53 / Max: 691.71
OpenBenchmarking.orgCelsius, Fewer Is BetterOpenVKL 1.3.1CPU Temperature MonitorAVX-512 OnAVX-512 Off1224364860Min: 41.25 / Avg: 49.91 / Max: 58.25Min: 42.63 / Avg: 52.24 / Max: 60.88

OpenVINO

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

OpenBenchmarking.orgFPS, More Is BetterOpenVINO 2022.2.devModel: Age Gender Recognition Retail 0013 FP16-INT8 - Device: CPUAVX-512 OnAVX-512 Off40K80K120K160K200KSE +/- 127.59, N = 3SE +/- 1455.37, N = 3170652.71151239.60-mavx512f -mavx512cd -mavx512vl -mavx512bw -mavx512dq -mavx512ifma -mavx512vbmi-mno-avx512f1. (CXX) g++ options: -fPIC -O3 -march=native -fsigned-char -ffunction-sections -fdata-sections -fno-strict-overflow -fwrapv -flto -shared

Neural Magic DeepSparse

OpenBenchmarking.orgitems/sec, More Is BetterNeural Magic DeepSparse 1.1Model: NLP Token Classification, BERT base uncased conll2003 - Scenario: Synchronous Single-StreamAVX-512 OnAVX-512 Off816243240SE +/- 0.03, N = 3SE +/- 0.03, N = 334.5230.61

OpenBenchmarking.orgms/batch, Fewer Is BetterNeural Magic DeepSparse 1.1Model: NLP Token Classification, BERT base uncased conll2003 - Scenario: Synchronous Single-StreamAVX-512 OnAVX-512 Off816243240SE +/- 0.03, N = 3SE +/- 0.04, N = 328.9632.66
MinAvgMaxAVX-512 On240035513868AVX-512 Off368637114893OpenBenchmarking.orgMegahertz, More Is BetterNeural Magic DeepSparse 1.1CPU Peak Freq (Highest CPU Core Frequency) Monitor12002400360048006000
MinAvgMaxAVX-512 On49.8321.8419.4AVX-512 Off110.4350.8422.9OpenBenchmarking.orgWatts, Fewer Is BetterNeural Magic DeepSparse 1.1CPU Power Consumption Monitor110220330440550
MinAvgMaxAVX-512 On38.947.853.8AVX-512 Off43.950.755.5OpenBenchmarking.orgCelsius, Fewer Is BetterNeural Magic DeepSparse 1.1CPU Temperature Monitor1530456075

OpenBenchmarking.orgitems/sec, More Is BetterNeural Magic DeepSparse 1.1Model: NLP Document Classification, oBERT base uncased on IMDB - Scenario: Synchronous Single-StreamAVX-512 OnAVX-512 Off816243240SE +/- 0.08, N = 3SE +/- 0.10, N = 334.2530.53

OpenBenchmarking.orgms/batch, Fewer Is BetterNeural Magic DeepSparse 1.1Model: NLP Document Classification, oBERT base uncased on IMDB - Scenario: Synchronous Single-StreamAVX-512 OnAVX-512 Off816243240SE +/- 0.07, N = 3SE +/- 0.11, N = 329.1932.75
MinAvgMaxAVX-512 On240035333703AVX-512 Off308936794336OpenBenchmarking.orgMegahertz, More Is BetterNeural Magic DeepSparse 1.1CPU Peak Freq (Highest CPU Core Frequency) Monitor11002200330044005500
MinAvgMaxAVX-512 On30.2328.4418.5AVX-512 Off210.0351.1423.9OpenBenchmarking.orgWatts, Fewer Is BetterNeural Magic DeepSparse 1.1CPU Power Consumption Monitor110220330440550
MinAvgMaxAVX-512 On40.648.754.3AVX-512 Off43.550.756.9OpenBenchmarking.orgCelsius, Fewer Is BetterNeural Magic DeepSparse 1.1CPU Temperature Monitor1632486480

NCNN

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

OpenBenchmarking.orgms, Fewer Is BetterNCNN 20220729Target: CPU - Model: blazefaceAVX-512 OnAVX-512 Off714212835SE +/- 0.18, N = 8SE +/- 0.54, N = 325.8829.00-mavx512f -mavx512cd -mavx512vl -mavx512bw -mavx512dq -mavx512ifma -mavx512vbmi - MIN: 24.45 / MAX: 112.37-mno-avx512f - MIN: 26.03 / MAX: 144.121. (CXX) g++ options: -O3 -march=native -rdynamic -lgomp -lpthread

LeelaChessZero

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

OpenBenchmarking.orgNodes Per Second, More Is BetterLeelaChessZero 0.28Backend: EigenAVX-512 OnAVX-512 Off2K4K6K8K10KSE +/- 45.37, N = 3SE +/- 43.59, N = 390968162-mavx512f -mavx512cd -mavx512vl -mavx512bw -mavx512dq -mavx512ifma -mavx512vbmi-mno-avx512f1. (CXX) g++ options: -flto -O3 -march=native -pthread
OpenBenchmarking.orgNodes Per Second Per Watt, More Is BetterLeelaChessZero 0.28Backend: EigenAVX-512 OnAVX-512 Off61218243024.8921.29
MinAvgMaxAVX-512 On240036854074AVX-512 Off369436994052OpenBenchmarking.orgMegahertz, More Is BetterLeelaChessZero 0.28CPU Peak Freq (Highest CPU Core Frequency) Monitor11002200330044005500
MinAvgMaxAVX-512 On56.3365.4500.1AVX-512 Off112.5383.3519.6OpenBenchmarking.orgWatts, Fewer Is BetterLeelaChessZero 0.28CPU Power Consumption Monitor130260390520650
MinAvgMaxAVX-512 On32.453.461.0AVX-512 Off37.339.956.9OpenBenchmarking.orgCelsius, Fewer Is BetterLeelaChessZero 0.28CPU Temperature Monitor20406080100

NCNN

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

OpenBenchmarking.orgms, Fewer Is BetterNCNN 20220729Target: CPU - Model: regnety_400mAVX-512 OnAVX-512 Off60120180240300SE +/- 2.25, N = 8SE +/- 3.75, N = 3247.32270.12-mavx512f -mavx512cd -mavx512vl -mavx512bw -mavx512dq -mavx512ifma -mavx512vbmi - MIN: 232.61 / MAX: 506.55-mno-avx512f - MIN: 245.47 / MAX: 498.81. (CXX) g++ options: -O3 -march=native -rdynamic -lgomp -lpthread

SMHasher

SMHasher is a hash function tester supporting various algorithms and able to make use of AVX and other modern CPU instruction set extensions. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgMiB/sec, More Is BetterSMHasher 2022-08-22Hash: FarmHash32 x86_64 AVXAVX-512 OnAVX-512 Off9K18K27K36K45KSE +/- 0.46, N = 5SE +/- 28.78, N = 539794.4436483.70-mavx512f -mavx512cd -mavx512vl -mavx512bw -mavx512dq -mavx512ifma -mavx512vbmi-mno-avx512f1. (CXX) g++ options: -O3 -march=native -flto=auto -fno-fat-lto-objects
OpenBenchmarking.orgcycles/hash, Fewer Is BetterSMHasher 2022-08-22Hash: FarmHash32 x86_64 AVXAVX-512 OnAVX-512 Off612182430SE +/- 0.00, N = 5SE +/- 0.00, N = 526.3926.41-mavx512f -mavx512cd -mavx512vl -mavx512bw -mavx512dq -mavx512ifma -mavx512vbmi-mno-avx512f1. (CXX) g++ options: -O3 -march=native -flto=auto -fno-fat-lto-objects

NCNN

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

OpenBenchmarking.orgms, Fewer Is BetterNCNN 20220729Target: CPU - Model: efficientnet-b0AVX-512 OnAVX-512 Off1428425670SE +/- 0.35, N = 8SE +/- 0.31, N = 357.7162.86-mavx512f -mavx512cd -mavx512vl -mavx512bw -mavx512dq -mavx512ifma -mavx512vbmi - MIN: 54.52 / MAX: 522.74-mno-avx512f - MIN: 59.46 / MAX: 154.821. (CXX) g++ options: -O3 -march=native -rdynamic -lgomp -lpthread

ONNX Runtime

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

OpenBenchmarking.orgInferences Per Minute, More Is BetterONNX Runtime 1.11Model: fcn-resnet101-11 - Device: CPU - Executor: StandardAVX-512 OnAVX-512 Off60120180240300SE +/- 0.44, N = 3SE +/- 2.36, N = 12271250-mavx512f -mavx512cd -mavx512vl -mavx512bw -mavx512dq -mavx512ifma -mavx512vbmi-mno-avx512f1. (CXX) g++ options: -O3 -march=native -ffunction-sections -fdata-sections -mtune=native -flto=auto -fno-fat-lto-objects -ldl -lrt
OpenBenchmarking.orgInferences Per Minute Per Watt, More Is BetterONNX Runtime 1.11Model: fcn-resnet101-11 - Device: CPU - Executor: StandardAVX-512 OnAVX-512 Off0.12330.24660.36990.49320.61650.5480.497
MinAvgMaxAVX-512 On240035773696AVX-512 Off304736124291OpenBenchmarking.orgMegahertz, More Is BetterONNX Runtime 1.11CPU Peak Freq (Highest CPU Core Frequency) Monitor11002200330044005500
MinAvgMaxAVX-512 On51.7494.2532.0AVX-512 Off211.3503.0528.2OpenBenchmarking.orgWatts, Fewer Is BetterONNX Runtime 1.11CPU Power Consumption Monitor140280420560700
MinAvgMaxAVX-512 On37.851.157.5AVX-512 Off43.053.459.3OpenBenchmarking.orgCelsius, Fewer Is BetterONNX Runtime 1.11CPU Temperature Monitor1632486480

LeelaChessZero

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

OpenBenchmarking.orgNodes Per Second, More Is BetterLeelaChessZero 0.28Backend: BLASAVX-512 OnAVX-512 Off2K4K6K8K10KSE +/- 103.04, N = 4SE +/- 21.53, N = 390778423-mavx512f -mavx512cd -mavx512vl -mavx512bw -mavx512dq -mavx512ifma -mavx512vbmi-mno-avx512f1. (CXX) g++ options: -flto -O3 -march=native -pthread
OpenBenchmarking.orgNodes Per Second Per Watt, More Is BetterLeelaChessZero 0.28Backend: BLASAVX-512 OnAVX-512 Off61218243023.7821.93
OpenBenchmarking.orgMegahertz, More Is BetterLeelaChessZero 0.28CPU Peak Freq (Highest CPU Core Frequency) MonitorAVX-512 OnAVX-512 Off9001800270036004500Min: 2400 / Avg: 3683.95 / Max: 3952Min: 3383 / Avg: 3700.34 / Max: 4961
OpenBenchmarking.orgWatts, Fewer Is BetterLeelaChessZero 0.28CPU Power Consumption MonitorAVX-512 OnAVX-512 Off90180270360450Min: 55.6 / Avg: 381.67 / Max: 513.97Min: 153.23 / Avg: 384.04 / Max: 522.79
OpenBenchmarking.orgCelsius, Fewer Is BetterLeelaChessZero 0.28CPU Temperature MonitorAVX-512 OnAVX-512 Off1326395265Min: 36.75 / Avg: 51.98 / Max: 63.13Min: 47.5 / Avg: 57.42 / Max: 64.5

CP2K Molecular Dynamics

CP2K is an open-source molecular dynamics software package focused on quantum chemistry and solid-state physics. This test profile currently uses the SSMP (OpenMP) version of cp2k. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgSeconds, Fewer Is BetterCP2K Molecular Dynamics 8.2Input: Fayalite-FISTAVX-512 OnAVX-512 Off300600900120015001122.731198.41
MinAvgMaxAVX-512 On240036613700AVX-512 Off356936653808OpenBenchmarking.orgMegahertz, More Is BetterCP2K Molecular Dynamics 8.2CPU Peak Freq (Highest CPU Core Frequency) Monitor10002000300040005000
MinAvgMaxAVX-512 On58.1358.0402.6AVX-512 Off118.3361.5403.0OpenBenchmarking.orgWatts, Fewer Is BetterCP2K Molecular Dynamics 8.2CPU Power Consumption Monitor110220330440550
MinAvgMaxAVX-512 On42.144.553.5AVX-512 Off42.144.456.9OpenBenchmarking.orgCelsius, Fewer Is BetterCP2K Molecular Dynamics 8.2CPU Temperature Monitor1632486480

Mobile Neural Network

MNN is the Mobile Neural Network as a highly efficient, lightweight deep learning framework developed by Alibaba. This MNN test profile is building the OpenMP / CPU threaded version for processor benchmarking and not any GPU-accelerated test. MNN does allow making use of AVX-512 extensions. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgms, Fewer Is BetterMobile Neural Network 2.1Model: SqueezeNetV1.0AVX-512 OnAVX-512 Off3691215SE +/- 0.147, N = 9SE +/- 0.091, N = 88.5799.146-mavx512f -mavx512cd -mavx512vl -mavx512bw -mavx512dq -mavx512ifma -mavx512vbmi - MIN: 6.67 / MAX: 21.5-mno-avx512f - MIN: 7.72 / MAX: 19.031. (CXX) g++ options: -O3 -march=native -std=c++11 -fvisibility=hidden -fomit-frame-pointer -fstrict-aliasing -ffunction-sections -fdata-sections -ffast-math -fno-rtti -fno-exceptions -rdynamic -pthread -ldl

OpenFOAM

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

OpenBenchmarking.orgSeconds, Fewer Is BetterOpenFOAM 10Input: drivaerFastback, Medium Mesh Size - Mesh TimeAVX-512 OnAVX-512 Off306090120150135.77144.351. (CXX) g++ options: -std=c++14 -m64 -O3 -ftemplate-depth-100 -fPIC -fuse-ld=bfd -Xlinker --add-needed --no-as-needed -lfiniteVolume -lmeshTools -lparallel -llagrangian -lregionModels -lgenericPatchFields -lOpenFOAM -ldl -lm

Neural Magic DeepSparse

OpenBenchmarking.orgitems/sec, More Is BetterNeural Magic DeepSparse 1.1Model: NLP Text Classification, DistilBERT mnli - Scenario: Synchronous Single-StreamAVX-512 OnAVX-512 Off4080120160200SE +/- 0.11, N = 3SE +/- 0.29, N = 3187.08177.54

OpenBenchmarking.orgms/batch, Fewer Is BetterNeural Magic DeepSparse 1.1Model: NLP Text Classification, DistilBERT mnli - Scenario: Synchronous Single-StreamAVX-512 OnAVX-512 Off1.26632.53263.79895.06526.3315SE +/- 0.0031, N = 3SE +/- 0.0091, N = 35.34135.6282
MinAvgMaxAVX-512 On240035413702AVX-512 Off369237124154OpenBenchmarking.orgMegahertz, More Is BetterNeural Magic DeepSparse 1.1CPU Peak Freq (Highest CPU Core Frequency) Monitor11002200330044005500
MinAvgMaxAVX-512 On37.8324.6394.5AVX-512 Off197.4352.2401.6OpenBenchmarking.orgWatts, Fewer Is BetterNeural Magic DeepSparse 1.1CPU Power Consumption Monitor110220330440550
MinAvgMaxAVX-512 On39.048.052.4AVX-512 Off43.050.554.3OpenBenchmarking.orgCelsius, Fewer Is BetterNeural Magic DeepSparse 1.1CPU Temperature Monitor1530456075

Numpy Benchmark

This is a test to obtain the general Numpy performance. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgScore, More Is BetterNumpy BenchmarkAVX-512 OnAVX-512 Off120240360480600SE +/- 2.18, N = 3SE +/- 0.59, N = 3575.66548.83
OpenBenchmarking.orgScore Per Watt, More Is BetterNumpy BenchmarkAVX-512 OnAVX-512 Off0.60461.20921.81382.41843.0232.6872.474
MinAvgMaxAVX-512 On240036733705AVX-512 Off369437024024OpenBenchmarking.orgMegahertz, More Is BetterNumpy BenchmarkCPU Peak Freq (Highest CPU Core Frequency) Monitor11002200330044005500
MinAvgMaxAVX-512 On54.1214.2222.9AVX-512 Off110.9221.9228.1OpenBenchmarking.orgWatts, Fewer Is BetterNumpy BenchmarkCPU Power Consumption Monitor60120180240300
MinAvgMaxAVX-512 On32.836.340.4AVX-512 Off36.437.943.5OpenBenchmarking.orgCelsius, Fewer Is BetterNumpy BenchmarkCPU Temperature Monitor1224364860

JPEG XL libjxl

The JPEG XL Image Coding System is designed to provide next-generation JPEG image capabilities with JPEG XL offering better image quality and compression over legacy JPEG. This test profile is currently focused on the multi-threaded JPEG XL image encode performance using the reference libjxl library. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgMP/s, More Is BetterJPEG XL libjxl 0.7Input: JPEG - Quality: 90AVX-512 OnAVX-512 Off3691215SE +/- 0.04, N = 3SE +/- 0.03, N = 39.559.13-mavx512f -mavx512cd -mavx512vl -mavx512bw -mavx512dq -mavx512ifma -mavx512vbmi-mno-avx512f1. (CXX) g++ options: -O3 -march=native -fno-rtti -funwind-tables -O2 -fPIE -pie -lm -latomic
OpenBenchmarking.orgMP/s Per Watt, More Is BetterJPEG XL libjxl 0.7Input: JPEG - Quality: 90AVX-512 OnAVX-512 Off0.00970.01940.02910.03880.04850.0430.039
MinAvgMaxAVX-512 On240036573712AVX-512 Off366937013814OpenBenchmarking.orgMegahertz, More Is BetterJPEG XL libjxl 0.7CPU Peak Freq (Highest CPU Core Frequency) Monitor10002000300040005000
MinAvgMaxAVX-512 On54.8223.4308.1AVX-512 Off142.6233.9323.3OpenBenchmarking.orgWatts, Fewer Is BetterJPEG XL libjxl 0.7CPU Power Consumption Monitor80160240320400
MinAvgMaxAVX-512 On35.039.746.6AVX-512 Off36.839.448.9OpenBenchmarking.orgCelsius, Fewer Is BetterJPEG XL libjxl 0.7CPU Temperature Monitor1428425670

NCNN

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

OpenBenchmarking.orgms, Fewer Is BetterNCNN 20220729Target: CPU - Model: googlenetAVX-512 OnAVX-512 Off20406080100SE +/- 0.76, N = 8SE +/- 1.35, N = 372.8076.13-mavx512f -mavx512cd -mavx512vl -mavx512bw -mavx512dq -mavx512ifma -mavx512vbmi - MIN: 67.13 / MAX: 388.52-mno-avx512f - MIN: 70.13 / MAX: 155.611. (CXX) g++ options: -O3 -march=native -rdynamic -lgomp -lpthread

JPEG XL libjxl

The JPEG XL Image Coding System is designed to provide next-generation JPEG image capabilities with JPEG XL offering better image quality and compression over legacy JPEG. This test profile is currently focused on the multi-threaded JPEG XL image encode performance using the reference libjxl library. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgMP/s, More Is BetterJPEG XL libjxl 0.7Input: PNG - Quality: 90AVX-512 OnAVX-512 Off3691215SE +/- 0.02, N = 3SE +/- 0.02, N = 39.959.52-mavx512f -mavx512cd -mavx512vl -mavx512bw -mavx512dq -mavx512ifma -mavx512vbmi-mno-avx512f1. (CXX) g++ options: -O3 -march=native -fno-rtti -funwind-tables -O2 -fPIE -pie -lm -latomic
OpenBenchmarking.orgMP/s Per Watt, More Is BetterJPEG XL libjxl 0.7Input: PNG - Quality: 90AVX-512 OnAVX-512 Off0.01010.02020.03030.04040.05050.0450.041
MinAvgMaxAVX-512 On240036433712AVX-512 Off243936963828OpenBenchmarking.orgMegahertz, More Is BetterJPEG XL libjxl 0.7CPU Peak Freq (Highest CPU Core Frequency) Monitor10002000300040005000
MinAvgMaxAVX-512 On56.1222.2318.2AVX-512 Off134.0232.4317.2OpenBenchmarking.orgWatts, Fewer Is BetterJPEG XL libjxl 0.7CPU Power Consumption Monitor80160240320400
MinAvgMaxAVX-512 On32.437.049.3AVX-512 Off35.936.744.9OpenBenchmarking.orgCelsius, Fewer Is BetterJPEG XL libjxl 0.7CPU Temperature Monitor1428425670

NCNN

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

OpenBenchmarking.orgms, Fewer Is BetterNCNN 20220729Target: CPU - Model: mnasnetAVX-512 OnAVX-512 Off1020304050SE +/- 0.26, N = 8SE +/- 0.49, N = 342.3044.19-mavx512f -mavx512cd -mavx512vl -mavx512bw -mavx512dq -mavx512ifma -mavx512vbmi - MIN: 39.64 / MAX: 571.78-mno-avx512f - MIN: 41.56 / MAX: 148.981. (CXX) g++ options: -O3 -march=native -rdynamic -lgomp -lpthread

Numenta Anomaly Benchmark

Numenta Anomaly Benchmark (NAB) is a benchmark for evaluating algorithms for anomaly detection in streaming, real-time applications. It is comprised of over 50 labeled real-world and artificial time-series data files plus a novel scoring mechanism designed for real-time applications. This test profile currently measures the time to run various detectors. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgSeconds, Fewer Is BetterNumenta Anomaly Benchmark 1.1Detector: Bayesian ChangepointAVX-512 OnAVX-512 Off48121620SE +/- 0.21, N = 4SE +/- 0.19, N = 516.6817.39
MinAvgMaxAVX-512 On240035323699AVX-512 Off369437074079OpenBenchmarking.orgMegahertz, More Is BetterNumenta Anomaly Benchmark 1.1CPU Peak Freq (Highest CPU Core Frequency) Monitor11002200330044005500
MinAvgMaxAVX-512 On55.1216.0378.8AVX-512 Off137.1251.1391.0OpenBenchmarking.orgWatts, Fewer Is BetterNumenta Anomaly Benchmark 1.1CPU Power Consumption Monitor100200300400500
MinAvgMaxAVX-512 On32.440.450.1AVX-512 Off38.643.249.9OpenBenchmarking.orgCelsius, Fewer Is BetterNumenta Anomaly Benchmark 1.1CPU Temperature Monitor1428425670

oneDNN

OpenBenchmarking.orgms, Fewer Is BetteroneDNN 2.7Harness: Convolution Batch Shapes Auto - Data Type: f32 - Engine: CPUAVX-512 OnAVX-512 Off0.1210.2420.3630.4840.605SE +/- 0.004067, N = 7SE +/- 0.004200, N = 150.5161670.537682-mavx512f -mavx512cd -mavx512vl -mavx512bw -mavx512dq -mavx512ifma -mavx512vbmi - MIN: 0.42-mno-avx512f - MIN: 0.421. (CXX) g++ options: -O3 -march=native -fopenmp -msse4.1 -fPIC -pie -ldl -lpthread
MinAvgMaxAVX-512 On240031823695AVX-512 Off286033483869OpenBenchmarking.orgMegahertz, More Is BetteroneDNN 2.7CPU Peak Freq (Highest CPU Core Frequency) Monitor10002000300040005000
MinAvgMaxAVX-512 On54.1327.3548.8AVX-512 Off216.4379.5540.9OpenBenchmarking.orgWatts, Fewer Is BetteroneDNN 2.7CPU Power Consumption Monitor140280420560700
MinAvgMaxAVX-512 On40.946.051.1AVX-512 Off43.547.753.8OpenBenchmarking.orgCelsius, Fewer Is BetteroneDNN 2.7CPU Temperature Monitor1530456075

Intel Open Image Denoise

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

OpenBenchmarking.orgImages / Sec, More Is BetterIntel Open Image Denoise 1.4.0Run: RTLightmap.hdr.4096x4096AVX-512 OnAVX-512 Off0.3870.7741.1611.5481.935SE +/- 0.01, N = 3SE +/- 0.01, N = 31.661.72
OpenBenchmarking.orgImages / Sec Per Watt, More Is BetterIntel Open Image Denoise 1.4.0Run: RTLightmap.hdr.4096x4096AVX-512 OnAVX-512 Off0.00110.00220.00330.00440.00550.0050.004
MinAvgMaxAVX-512 On240032163699AVX-512 Off301736364215OpenBenchmarking.orgMegahertz, More Is BetterIntel Open Image Denoise 1.4.0CPU Peak Freq (Highest CPU Core Frequency) Monitor11002200330044005500
MinAvgMaxAVX-512 On52.8325.6574.0AVX-512 Off207.2399.0572.6OpenBenchmarking.orgWatts, Fewer Is BetterIntel Open Image Denoise 1.4.0CPU Power Consumption Monitor140280420560700
MinAvgMaxAVX-512 On32.839.846.4AVX-512 Off39.944.749.8OpenBenchmarking.orgCelsius, Fewer Is BetterIntel Open Image Denoise 1.4.0CPU Temperature Monitor1428425670

ONNX Runtime

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

OpenBenchmarking.orgInferences Per Minute, More Is BetterONNX Runtime 1.11Model: bertsquad-12 - Device: CPU - Executor: StandardAVX-512 OnAVX-512 Off110220330440550SE +/- 1.86, N = 3SE +/- 3.11, N = 3516499-mavx512f -mavx512cd -mavx512vl -mavx512bw -mavx512dq -mavx512ifma -mavx512vbmi-mno-avx512f1. (CXX) g++ options: -O3 -march=native -ffunction-sections -fdata-sections -mtune=native -flto=auto -fno-fat-lto-objects -ldl -lrt
OpenBenchmarking.orgInferences Per Minute Per Watt, More Is BetterONNX Runtime 1.11Model: bertsquad-12 - Device: CPU - Executor: StandardAVX-512 OnAVX-512 Off0.31340.62680.94021.25361.5671.3931.315
MinAvgMaxAVX-512 On240036633709AVX-512 Off369437013978OpenBenchmarking.orgMegahertz, More Is BetterONNX Runtime 1.11CPU Peak Freq (Highest CPU Core Frequency) Monitor11002200330044005500
MinAvgMaxAVX-512 On50.3370.5385.5AVX-512 Off193.6379.6388.9OpenBenchmarking.orgWatts, Fewer Is BetterONNX Runtime 1.11CPU Power Consumption Monitor100200300400500
MinAvgMaxAVX-512 On34.646.548.9AVX-512 Off39.048.452.0OpenBenchmarking.orgCelsius, Fewer Is BetterONNX Runtime 1.11CPU Temperature Monitor1530456075

Numenta Anomaly Benchmark

Numenta Anomaly Benchmark (NAB) is a benchmark for evaluating algorithms for anomaly detection in streaming, real-time applications. It is comprised of over 50 labeled real-world and artificial time-series data files plus a novel scoring mechanism designed for real-time applications. This test profile currently measures the time to run various detectors. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgSeconds, Fewer Is BetterNumenta Anomaly Benchmark 1.1Detector: Windowed GaussianAVX-512 OnAVX-512 Off1.09852.1973.29554.3945.4925SE +/- 0.032, N = 15SE +/- 0.044, N = 74.7274.882
MinAvgMaxAVX-512 On240032373715AVX-512 Off369437183948OpenBenchmarking.orgMegahertz, More Is BetterNumenta Anomaly Benchmark 1.1CPU Peak Freq (Highest CPU Core Frequency) Monitor10002000300040005000
MinAvgMaxAVX-512 On53.3184.7388.1AVX-512 Off212.5259.2394.2OpenBenchmarking.orgWatts, Fewer Is BetterNumenta Anomaly Benchmark 1.1CPU Power Consumption Monitor110220330440550
MinAvgMaxAVX-512 On32.439.253.3AVX-512 Off37.842.860.4OpenBenchmarking.orgCelsius, Fewer Is BetterNumenta Anomaly Benchmark 1.1CPU Temperature Monitor20406080100

JPEG XL libjxl

The JPEG XL Image Coding System is designed to provide next-generation JPEG image capabilities with JPEG XL offering better image quality and compression over legacy JPEG. This test profile is currently focused on the multi-threaded JPEG XL image encode performance using the reference libjxl library. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgMP/s, More Is BetterJPEG XL libjxl 0.7Input: JPEG - Quality: 100AVX-512 OnAVX-512 Off0.16650.3330.49950.6660.8325SE +/- 0.01, N = 9SE +/- 0.01, N = 90.740.72-mavx512f -mavx512cd -mavx512vl -mavx512bw -mavx512dq -mavx512ifma -mavx512vbmi-mno-avx512f1. (CXX) g++ options: -O3 -march=native -fno-rtti -funwind-tables -O2 -fPIE -pie -lm -latomic
OpenBenchmarking.orgMP/s Per Watt, More Is BetterJPEG XL libjxl 0.7Input: JPEG - Quality: 100AVX-512 OnAVX-512 Off0.00070.00140.00210.00280.00350.0030.003
OpenBenchmarking.orgMegahertz, More Is BetterJPEG XL libjxl 0.7CPU Peak Freq (Highest CPU Core Frequency) MonitorAVX-512 OnAVX-512 Off8001600240032004000Min: 2400 / Avg: 3682.16 / Max: 4023Min: 3414 / Avg: 3701.38 / Max: 4381
OpenBenchmarking.orgWatts, Fewer Is BetterJPEG XL libjxl 0.7CPU Power Consumption MonitorAVX-512 OnAVX-512 Off50100150200250Min: 28.84 / Avg: 217.33 / Max: 256.47Min: 110.34 / Avg: 222.62 / Max: 261.2
OpenBenchmarking.orgCelsius, Fewer Is BetterJPEG XL libjxl 0.7CPU Temperature MonitorAVX-512 OnAVX-512 Off1020304050Min: 32.75 / Avg: 36.48 / Max: 49.75Min: 35.5 / Avg: 36.56 / Max: 46.63

Darmstadt Automotive Parallel Heterogeneous Suite

DAPHNE is the Darmstadt Automotive Parallel HeterogeNEous Benchmark Suite with OpenCL / CUDA / OpenMP test cases for these automotive benchmarks for evaluating programming models in context to vehicle autonomous driving capabilities. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgTest Cases Per Minute, More Is BetterDarmstadt Automotive Parallel Heterogeneous SuiteBackend: OpenMP - Kernel: NDT MappingAVX-512 OnAVX-512 Off30060090012001500SE +/- 5.94, N = 3SE +/- 8.66, N = 31371.181335.631. (CXX) g++ options: -O3 -std=c++11 -fopenmp
OpenBenchmarking.orgTest Cases Per Minute Per Watt, More Is BetterDarmstadt Automotive Parallel Heterogeneous SuiteBackend: OpenMP - Kernel: NDT MappingAVX-512 OnAVX-512 Off2468106.4165.455
MinAvgMaxAVX-512 On240035163702AVX-512 Off369437194426OpenBenchmarking.orgMegahertz, More Is BetterDarmstadt Automotive Parallel Heterogeneous SuiteCPU Peak Freq (Highest CPU Core Frequency) Monitor11002200330044005500
MinAvgMaxAVX-512 On37.8213.7282.2AVX-512 Off215.0244.8282.7OpenBenchmarking.orgWatts, Fewer Is BetterDarmstadt Automotive Parallel Heterogeneous SuiteCPU Power Consumption Monitor70140210280350
MinAvgMaxAVX-512 On32.435.436.4AVX-512 Off37.839.449.5OpenBenchmarking.orgCelsius, Fewer Is BetterDarmstadt Automotive Parallel Heterogeneous SuiteCPU Temperature Monitor1428425670

NCNN

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

OpenBenchmarking.orgms, Fewer Is BetterNCNN 20220729Target: CPU - Model: resnet50AVX-512 OnAVX-512 Off1530456075SE +/- 0.50, N = 8SE +/- 0.89, N = 366.3467.48-mavx512f -mavx512cd -mavx512vl -mavx512bw -mavx512dq -mavx512ifma -mavx512vbmi - MIN: 62.92 / MAX: 194.74-mno-avx512f - MIN: 63.4 / MAX: 170.141. (CXX) g++ options: -O3 -march=native -rdynamic -lgomp -lpthread

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 2022.1Implementation: MPI CPU - Input: water_GMX50_bareAVX-512 OnAVX-512 Off510152025SE +/- 0.24, N = 3SE +/- 0.10, N = 318.7618.47-mavx512f -mavx512cd -mavx512vl -mavx512bw -mavx512dq -mavx512ifma -mavx512vbmi-mno-avx512f1. (CXX) g++ options: -O3 -march=native
OpenBenchmarking.orgNs Per Day Per Watt, More Is BetterGROMACS 2022.1Implementation: MPI CPU - Input: water_GMX50_bareAVX-512 OnAVX-512 Off0.00790.01580.02370.03160.03950.0350.033
MinAvgMaxAVX-512 On240031683725AVX-512 Off287533584145OpenBenchmarking.orgMegahertz, More Is BetterGROMACS 2022.1CPU Peak Freq (Highest CPU Core Frequency) Monitor11002200330044005500
MinAvgMaxAVX-512 On58535698AVX-512 Off216553700OpenBenchmarking.orgWatts, Fewer Is BetterGROMACS 2022.1CPU Power Consumption Monitor2004006008001000
MinAvgMaxAVX-512 On43.356.162.6AVX-512 Off43.054.864.5OpenBenchmarking.orgCelsius, Fewer Is BetterGROMACS 2022.1CPU Temperature Monitor20406080100

Numenta Anomaly Benchmark

Numenta Anomaly Benchmark (NAB) is a benchmark for evaluating algorithms for anomaly detection in streaming, real-time applications. It is comprised of over 50 labeled real-world and artificial time-series data files plus a novel scoring mechanism designed for real-time applications. This test profile currently measures the time to run various detectors. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgSeconds, Fewer Is BetterNumenta Anomaly Benchmark 1.1Detector: Relative EntropyAVX-512 OnAVX-512 Off3691215SE +/- 0.089, N = 5SE +/- 0.082, N = 59.89810.035
MinAvgMaxAVX-512 On240034373911AVX-512 Off369437023768OpenBenchmarking.orgMegahertz, More Is BetterNumenta Anomaly Benchmark 1.1CPU Peak Freq (Highest CPU Core Frequency) Monitor10002000300040005000
MinAvgMaxAVX-512 On53.6202.8367.2AVX-512 Off213.2250.8339.2OpenBenchmarking.orgWatts, Fewer Is BetterNumenta Anomaly Benchmark 1.1CPU Power Consumption Monitor100200300400500
MinAvgMaxAVX-512 On31.538.847.0AVX-512 Off37.841.550.4OpenBenchmarking.orgCelsius, Fewer Is BetterNumenta Anomaly Benchmark 1.1CPU Temperature Monitor1428425670

oneDNN

OpenBenchmarking.orgms, Fewer Is BetteroneDNN 2.7Harness: Deconvolution Batch shapes_1d - Data Type: f32 - Engine: CPUAVX-512 OnAVX-512 Off510152025SE +/- 0.16, N = 3SE +/- 0.06, N = 322.5922.84-mavx512f -mavx512cd -mavx512vl -mavx512bw -mavx512dq -mavx512ifma -mavx512vbmi - MIN: 19.6-mno-avx512f - MIN: 20.221. (CXX) g++ options: -O3 -march=native -fopenmp -msse4.1 -fPIC -pie -ldl -lpthread
MinAvgMaxAVX-512 On240033943729AVX-512 Off293335263802OpenBenchmarking.orgMegahertz, More Is BetteroneDNN 2.7CPU Peak Freq (Highest CPU Core Frequency) Monitor10002000300040005000
MinAvgMaxAVX-512 On52.1376.1492.5AVX-512 Off215.5392.5509.7OpenBenchmarking.orgWatts, Fewer Is BetteroneDNN 2.7CPU Power Consumption Monitor130260390520650
MinAvgMaxAVX-512 On37.343.546.1AVX-512 Off39.543.847.0OpenBenchmarking.orgCelsius, Fewer Is BetteroneDNN 2.7CPU Temperature Monitor1428425670

Intel Open Image Denoise

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

OpenBenchmarking.orgImages / Sec, More Is BetterIntel Open Image Denoise 1.4.0Run: RT.hdr_alb_nrm.3840x2160AVX-512 OnAVX-512 Off0.78981.57962.36943.15923.949SE +/- 0.01, N = 5SE +/- 0.03, N = 53.513.50
OpenBenchmarking.orgImages / Sec Per Watt, More Is BetterIntel Open Image Denoise 1.4.0Run: RT.hdr_alb_nrm.3840x2160AVX-512 OnAVX-512 Off0.00270.00540.00810.01080.01350.0120.010
MinAvgMaxAVX-512 On240031243699AVX-512 Off271836264090OpenBenchmarking.orgMegahertz, More Is BetterIntel Open Image Denoise 1.4.0CPU Peak Freq (Highest CPU Core Frequency) Monitor11002200330044005500
MinAvgMaxAVX-512 On48.8287.6572.9AVX-512 Off206.5366.7574.9OpenBenchmarking.orgWatts, Fewer Is BetterIntel Open Image Denoise 1.4.0CPU Power Consumption Monitor140280420560700
MinAvgMaxAVX-512 On32.438.144.9AVX-512 Off36.841.647.0OpenBenchmarking.orgCelsius, Fewer Is BetterIntel Open Image Denoise 1.4.0CPU Temperature Monitor1428425670

OpenBenchmarking.orgImages / Sec, More Is BetterIntel Open Image Denoise 1.4.0Run: RT.ldr_alb_nrm.3840x2160AVX-512 OnAVX-512 Off0.78981.57962.36943.15923.949SE +/- 0.01, N = 5SE +/- 0.01, N = 53.513.51
OpenBenchmarking.orgImages / Sec Per Watt, More Is BetterIntel Open Image Denoise 1.4.0Run: RT.ldr_alb_nrm.3840x2160AVX-512 OnAVX-512 Off0.00270.00540.00810.01080.01350.0120.010
MinAvgMaxAVX-512 On240032123702AVX-512 Off285436103919OpenBenchmarking.orgMegahertz, More Is BetterIntel Open Image Denoise 1.4.0CPU Peak Freq (Highest CPU Core Frequency) Monitor10002000300040005000
MinAvgMaxAVX-512 On52.1288.6574.3AVX-512 Off208.7365.6577.3OpenBenchmarking.orgWatts, Fewer Is BetterIntel Open Image Denoise 1.4.0CPU Power Consumption Monitor140280420560700
MinAvgMaxAVX-512 On32.838.244.1AVX-512 Off39.543.348.4OpenBenchmarking.orgCelsius, Fewer Is BetterIntel Open Image Denoise 1.4.0CPU Temperature Monitor1428425670

CPU Temperature Monitor

OpenBenchmarking.orgCelsiusCPU Temperature MonitorPhoronix Test Suite System MonitoringAVX-512 OnAVX-512 Off1428425670Min: 30.13 / Avg: 49.97 / Max: 73.38Min: 35.5 / Avg: 51.26 / Max: 73.75

CPU Power Consumption Monitor

OpenBenchmarking.orgWattsCPU Power Consumption MonitorPhoronix Test Suite System MonitoringAVX-512 OnAVX-512 Off130260390520650Min: 26.37 / Avg: 434.8 / Max: 766.01Min: 106.95 / Avg: 449.58 / Max: 735.32

Darmstadt Automotive Parallel Heterogeneous Suite

OpenBenchmarking.orgCelsius, Fewer Is BetterDarmstadt Automotive Parallel Heterogeneous SuiteCPU Temperature MonitorAVX-512 OnAVX-512 Off1020304050Min: 31.25 / Avg: 38.03 / Max: 47.5Min: 36.75 / Avg: 39.2 / Max: 49.75

OpenBenchmarking.orgWatts, Fewer Is BetterDarmstadt Automotive Parallel Heterogeneous SuiteCPU Power Consumption MonitorAVX-512 OnAVX-512 Off50100150200250Min: 49.36 / Avg: 258.94 / Max: 283.12Min: 136.19 / Avg: 273.1 / Max: 289.31

OpenBenchmarking.orgMegahertz, More Is BetterDarmstadt Automotive Parallel Heterogeneous SuiteCPU Peak Freq (Highest CPU Core Frequency) MonitorAVX-512 OnAVX-512 Off8001600240032004000Min: 2400 / Avg: 3647.5 / Max: 3715Min: 3694 / Avg: 3698.64 / Max: 4768

OpenBenchmarking.orgTest Cases Per Minute Per Watt, More Is BetterDarmstadt Automotive Parallel Heterogeneous SuiteBackend: OpenMP - Kernel: Points2ImageAVX-512 OnAVX-512 Off122436486052.8242.19

OpenBenchmarking.orgTest Cases Per Minute, More Is BetterDarmstadt Automotive Parallel Heterogeneous SuiteBackend: OpenMP - Kernel: Points2ImageAVX-512 OnAVX-512 Off3K6K9K12K15KSE +/- 126.17, N = 15SE +/- 269.82, N = 1513677.7611521.381. (CXX) g++ options: -O3 -std=c++11 -fopenmp
OpenBenchmarking.orgTest Cases Per Minute Per Watt, More Is BetterDarmstadt Automotive Parallel Heterogeneous SuiteBackend: OpenMP - Kernel: Points2ImageAVX-512 OnAVX-512 Off122436486052.8242.19
OpenBenchmarking.orgMegahertz, More Is BetterDarmstadt Automotive Parallel Heterogeneous SuiteCPU Peak Freq (Highest CPU Core Frequency) MonitorAVX-512 OnAVX-512 Off8001600240032004000Min: 2400 / Avg: 3647.5 / Max: 3715Min: 3694 / Avg: 3698.64 / Max: 4768
OpenBenchmarking.orgWatts, Fewer Is BetterDarmstadt Automotive Parallel Heterogeneous SuiteCPU Power Consumption MonitorAVX-512 OnAVX-512 Off50100150200250Min: 49.36 / Avg: 258.94 / Max: 283.12Min: 136.19 / Avg: 273.1 / Max: 289.31
OpenBenchmarking.orgCelsius, Fewer Is BetterDarmstadt Automotive Parallel Heterogeneous SuiteCPU Temperature MonitorAVX-512 OnAVX-512 Off1020304050Min: 31.25 / Avg: 38.03 / Max: 47.5Min: 36.75 / Avg: 39.2 / Max: 49.75

SVT-AV1

MinAvgMaxAVX-512 On30.634.643.0AVX-512 Off37.840.548.1OpenBenchmarking.orgCelsius, Fewer Is BetterSVT-AV1 1.4CPU Temperature Monitor1428425670

MinAvgMaxAVX-512 On52.7175.4338.1AVX-512 Off127.1241.8338.9OpenBenchmarking.orgWatts, Fewer Is BetterSVT-AV1 1.4CPU Power Consumption Monitor80160240320400

MinAvgMaxAVX-512 On240032743770AVX-512 Off369437183985OpenBenchmarking.orgMegahertz, More Is BetterSVT-AV1 1.4CPU Peak Freq (Highest CPU Core Frequency) Monitor11002200330044005500

OpenBenchmarking.orgFrames Per Second Per Watt, More Is BetterSVT-AV1 1.4Encoder Mode: Preset 12 - Input: Bosphorus 4KAVX-512 OnAVX-512 Off0.3150.630.9451.261.5751.4000.968

OpenBenchmarking.orgFrames Per Second, More Is BetterSVT-AV1 1.4Encoder Mode: Preset 12 - Input: Bosphorus 4KAVX-512 OnAVX-512 Off50100150200250SE +/- 4.78, N = 15SE +/- 3.57, N = 15245.56233.94
OpenBenchmarking.orgFrames Per Second Per Watt, More Is BetterSVT-AV1 1.4Encoder Mode: Preset 12 - Input: Bosphorus 4KAVX-512 OnAVX-512 Off0.3150.630.9451.261.5751.4000.968
MinAvgMaxAVX-512 On240032743770AVX-512 Off369437183985OpenBenchmarking.orgMegahertz, More Is BetterSVT-AV1 1.4CPU Peak Freq (Highest CPU Core Frequency) Monitor11002200330044005500
MinAvgMaxAVX-512 On52.7175.4338.1AVX-512 Off127.1241.8338.9OpenBenchmarking.orgWatts, Fewer Is BetterSVT-AV1 1.4CPU Power Consumption Monitor80160240320400
MinAvgMaxAVX-512 On30.634.643.0AVX-512 Off37.840.548.1OpenBenchmarking.orgCelsius, Fewer Is BetterSVT-AV1 1.4CPU Temperature Monitor1428425670

MinAvgMaxAVX-512 On32.436.849.3AVX-512 Off39.042.449.3OpenBenchmarking.orgCelsius, Fewer Is BetterSVT-AV1 1.4CPU Temperature Monitor1428425670

MinAvgMaxAVX-512 On52.7162.9323.1AVX-512 Off108.8243.3325.0OpenBenchmarking.orgWatts, Fewer Is BetterSVT-AV1 1.4CPU Power Consumption Monitor80160240320400

MinAvgMaxAVX-512 On240032023756AVX-512 Off369437284349OpenBenchmarking.orgMegahertz, More Is BetterSVT-AV1 1.4CPU Peak Freq (Highest CPU Core Frequency) Monitor11002200330044005500

OpenBenchmarking.orgFrames Per Second Per Watt, More Is BetterSVT-AV1 1.4Encoder Mode: Preset 13 - Input: Bosphorus 4KAVX-512 OnAVX-512 Off0.34040.68081.02121.36161.7021.5130.986

OpenBenchmarking.orgFrames Per Second, More Is BetterSVT-AV1 1.4Encoder Mode: Preset 13 - Input: Bosphorus 4KAVX-512 OnAVX-512 Off50100150200250SE +/- 4.74, N = 15SE +/- 4.01, N = 15246.57239.88
OpenBenchmarking.orgFrames Per Second Per Watt, More Is BetterSVT-AV1 1.4Encoder Mode: Preset 13 - Input: Bosphorus 4KAVX-512 OnAVX-512 Off0.34040.68081.02121.36161.7021.5130.986
MinAvgMaxAVX-512 On240032023756AVX-512 Off369437284349OpenBenchmarking.orgMegahertz, More Is BetterSVT-AV1 1.4CPU Peak Freq (Highest CPU Core Frequency) Monitor11002200330044005500
MinAvgMaxAVX-512 On52.7162.9323.1AVX-512 Off108.8243.3325.0OpenBenchmarking.orgWatts, Fewer Is BetterSVT-AV1 1.4CPU Power Consumption Monitor80160240320400
MinAvgMaxAVX-512 On32.436.849.3AVX-512 Off39.042.449.3OpenBenchmarking.orgCelsius, Fewer Is BetterSVT-AV1 1.4CPU Temperature Monitor1428425670

ONNX Runtime

OpenBenchmarking.orgCelsius, Fewer Is BetterONNX Runtime 1.11CPU Temperature MonitorAVX-512 OnAVX-512 Off1122334455Min: 32.75 / Avg: 48.03 / Max: 50.63Min: 38.13 / Avg: 50.46 / Max: 57.25

OpenBenchmarking.orgWatts, Fewer Is BetterONNX Runtime 1.11CPU Power Consumption MonitorAVX-512 OnAVX-512 Off80160240320400Min: 51.25 / Avg: 441.77 / Max: 464.82Min: 107.66 / Avg: 447.6 / Max: 464.67

OpenBenchmarking.orgMegahertz, More Is BetterONNX Runtime 1.11CPU Peak Freq (Highest CPU Core Frequency) MonitorAVX-512 OnAVX-512 Off7001400210028003500Min: 2400 / Avg: 3571.99 / Max: 3770Min: 3593 / Avg: 3607.6 / Max: 4285

OpenBenchmarking.orgInferences Per Minute Per Watt, More Is BetterONNX Runtime 1.11Model: ArcFace ResNet-100 - Device: CPU - Executor: StandardAVX-512 OnAVX-512 Off0.53531.07061.60592.14122.67652.3792.051

OpenBenchmarking.orgInferences Per Minute, More Is BetterONNX Runtime 1.11Model: ArcFace ResNet-100 - Device: CPU - Executor: StandardAVX-512 OnAVX-512 Off2004006008001000SE +/- 39.92, N = 12SE +/- 20.83, N = 121051918-mavx512f -mavx512cd -mavx512vl -mavx512bw -mavx512dq -mavx512ifma -mavx512vbmi-mno-avx512f1. (CXX) g++ options: -O3 -march=native -ffunction-sections -fdata-sections -mtune=native -flto=auto -fno-fat-lto-objects -ldl -lrt
OpenBenchmarking.orgInferences Per Minute Per Watt, More Is BetterONNX Runtime 1.11Model: ArcFace ResNet-100 - Device: CPU - Executor: StandardAVX-512 OnAVX-512 Off0.53531.07061.60592.14122.67652.3792.051
OpenBenchmarking.orgMegahertz, More Is BetterONNX Runtime 1.11CPU Peak Freq (Highest CPU Core Frequency) MonitorAVX-512 OnAVX-512 Off7001400210028003500Min: 2400 / Avg: 3571.99 / Max: 3770Min: 3593 / Avg: 3607.6 / Max: 4285
OpenBenchmarking.orgWatts, Fewer Is BetterONNX Runtime 1.11CPU Power Consumption MonitorAVX-512 OnAVX-512 Off80160240320400Min: 51.25 / Avg: 441.77 / Max: 464.82Min: 107.66 / Avg: 447.6 / Max: 464.67
OpenBenchmarking.orgCelsius, Fewer Is BetterONNX Runtime 1.11CPU Temperature MonitorAVX-512 OnAVX-512 Off1122334455Min: 32.75 / Avg: 48.03 / Max: 50.63Min: 38.13 / Avg: 50.46 / Max: 57.25

MinAvgMaxAVX-512 On36.439.942.6AVX-512 Off39.543.253.0OpenBenchmarking.orgCelsius, Fewer Is BetterONNX Runtime 1.11CPU Temperature Monitor1530456075

MinAvgMaxAVX-512 On53.2259.3268.4AVX-512 Off132.5266.8278.0OpenBenchmarking.orgWatts, Fewer Is BetterONNX Runtime 1.11CPU Power Consumption Monitor70140210280350

MinAvgMaxAVX-512 On240036653710AVX-512 Off369337024397OpenBenchmarking.orgMegahertz, More Is BetterONNX Runtime 1.11CPU Peak Freq (Highest CPU Core Frequency) Monitor11002200330044005500

OpenBenchmarking.orgInferences Per Minute Per Watt, More Is BetterONNX Runtime 1.11Model: super-resolution-10 - Device: CPU - Executor: StandardAVX-512 OnAVX-512 Off71421283528.5423.57

OpenBenchmarking.orgInferences Per Minute, More Is BetterONNX Runtime 1.11Model: super-resolution-10 - Device: CPU - Executor: StandardAVX-512 OnAVX-512 Off16003200480064008000SE +/- 5.46, N = 3SE +/- 260.54, N = 1274016288-mavx512f -mavx512cd -mavx512vl -mavx512bw -mavx512dq -mavx512ifma -mavx512vbmi-mno-avx512f1. (CXX) g++ options: -O3 -march=native -ffunction-sections -fdata-sections -mtune=native -flto=auto -fno-fat-lto-objects -ldl -lrt
OpenBenchmarking.orgInferences Per Minute Per Watt, More Is BetterONNX Runtime 1.11Model: super-resolution-10 - Device: CPU - Executor: StandardAVX-512 OnAVX-512 Off71421283528.5423.57
MinAvgMaxAVX-512 On240036653710AVX-512 Off369337024397OpenBenchmarking.orgMegahertz, More Is BetterONNX Runtime 1.11CPU Peak Freq (Highest CPU Core Frequency) Monitor11002200330044005500
MinAvgMaxAVX-512 On53.2259.3268.4AVX-512 Off132.5266.8278.0OpenBenchmarking.orgWatts, Fewer Is BetterONNX Runtime 1.11CPU Power Consumption Monitor70140210280350
MinAvgMaxAVX-512 On36.439.942.6AVX-512 Off39.543.253.0OpenBenchmarking.orgCelsius, Fewer Is BetterONNX Runtime 1.11CPU Temperature Monitor1530456075

NCNN

OpenBenchmarking.orgCelsius, Fewer Is BetterNCNN 20220729CPU Temperature MonitorAVX-512 OnAVX-512 Off1020304050Min: 38.63 / Avg: 44.45 / Max: 48Min: 43 / Avg: 46.1 / Max: 50.13

OpenBenchmarking.orgWatts, Fewer Is BetterNCNN 20220729CPU Power Consumption MonitorAVX-512 OnAVX-512 Off80160240320400Min: 54.96 / Avg: 396.44 / Max: 451.5Min: 199.1 / Avg: 400.13 / Max: 450.41

OpenBenchmarking.orgMegahertz, More Is BetterNCNN 20220729CPU Peak Freq (Highest CPU Core Frequency) MonitorAVX-512 OnAVX-512 Off7001400210028003500Min: 2400 / Avg: 3565.67 / Max: 3699Min: 3563 / Avg: 3574.38 / Max: 3815

OpenBenchmarking.orgms, Fewer Is BetterNCNN 20220729Target: CPU - Model: FastestDetAVX-512 OnAVX-512 Off1428425670SE +/- 0.49, N = 8SE +/- 2.90, N = 358.9560.73-mavx512f -mavx512cd -mavx512vl -mavx512bw -mavx512dq -mavx512ifma -mavx512vbmi - MIN: 55.11 / MAX: 282.72-mno-avx512f - MIN: 52.89 / MAX: 236.851. (CXX) g++ options: -O3 -march=native -rdynamic -lgomp -lpthread
OpenBenchmarking.orgMegahertz, More Is BetterNCNN 20220729CPU Peak Freq (Highest CPU Core Frequency) MonitorAVX-512 OnAVX-512 Off7001400210028003500Min: 2400 / Avg: 3565.67 / Max: 3699Min: 3563 / Avg: 3574.38 / Max: 3815
OpenBenchmarking.orgWatts, Fewer Is BetterNCNN 20220729CPU Power Consumption MonitorAVX-512 OnAVX-512 Off80160240320400Min: 54.96 / Avg: 396.44 / Max: 451.5Min: 199.1 / Avg: 400.13 / Max: 450.41
OpenBenchmarking.orgCelsius, Fewer Is BetterNCNN 20220729CPU Temperature MonitorAVX-512 OnAVX-512 Off1020304050Min: 38.63 / Avg: 44.45 / Max: 48Min: 43 / Avg: 46.1 / Max: 50.13

OpenBenchmarking.orgms, Fewer Is BetterNCNN 20220729Target: CPU - Model: vision_transformerAVX-512 OnAVX-512 Off20406080100SE +/- 1.59, N = 8SE +/- 5.82, N = 374.9386.16-mavx512f -mavx512cd -mavx512vl -mavx512bw -mavx512dq -mavx512ifma -mavx512vbmi - MIN: 65.04 / MAX: 2154.62-mno-avx512f - MIN: 73.72 / MAX: 1760.741. (CXX) g++ options: -O3 -march=native -rdynamic -lgomp -lpthread

TensorFlow

MinAvgMaxAVX-512 On34.641.748.9AVX-512 Off38.640.550.4OpenBenchmarking.orgCelsius, Fewer Is BetterTensorFlow 2.10CPU Temperature Monitor1428425670

MinAvgMaxAVX-512 On53.1308.0379.5AVX-512 Off156.1298.9329.3OpenBenchmarking.orgWatts, Fewer Is BetterTensorFlow 2.10CPU Power Consumption Monitor100200300400500

MinAvgMaxAVX-512 On240035864161AVX-512 Off369437274474OpenBenchmarking.orgMegahertz, More Is BetterTensorFlow 2.10CPU Peak Freq (Highest CPU Core Frequency) Monitor12002400360048006000

OpenBenchmarking.orgimages/sec Per Watt, More Is BetterTensorFlow 2.10Device: CPU - Batch Size: 16 - Model: GoogLeNetAVX-512 OnAVX-512 Off0.04390.08780.13170.17560.21950.1950.104

OpenBenchmarking.orgimages/sec, More Is BetterTensorFlow 2.10Device: CPU - Batch Size: 16 - Model: GoogLeNetAVX-512 OnAVX-512 Off1326395265SE +/- 1.01, N = 15SE +/- 0.25, N = 360.1731.12
OpenBenchmarking.orgimages/sec Per Watt, More Is BetterTensorFlow 2.10Device: CPU - Batch Size: 16 - Model: GoogLeNetAVX-512 OnAVX-512 Off0.04390.08780.13170.17560.21950.1950.104
MinAvgMaxAVX-512 On240035864161AVX-512 Off369437274474OpenBenchmarking.orgMegahertz, More Is BetterTensorFlow 2.10CPU Peak Freq (Highest CPU Core Frequency) Monitor12002400360048006000
MinAvgMaxAVX-512 On53.1308.0379.5AVX-512 Off156.1298.9329.3OpenBenchmarking.orgWatts, Fewer Is BetterTensorFlow 2.10CPU Power Consumption Monitor100200300400500
MinAvgMaxAVX-512 On34.641.748.9AVX-512 Off38.640.550.4OpenBenchmarking.orgCelsius, Fewer Is BetterTensorFlow 2.10CPU Temperature Monitor1428425670

163 Results Shown

TensorFlow
oneDNN
AI Benchmark Alpha
oneDNN
OpenVINO:
  Weld Porosity Detection FP16 - CPU:
    ms
    FPS
  Face Detection FP16 - CPU:
    FPS
    ms
  Age Gender Recognition Retail 0013 FP16 - CPU:
    ms
Cpuminer-Opt
AI Benchmark Alpha
OpenVINO:
  Machine Translation EN To DE FP16 - CPU:
    ms
    FPS
  Weld Porosity Detection FP16-INT8 - CPU:
    FPS
    ms
  Face Detection FP16-INT8 - CPU:
    FPS
    ms
  Vehicle Detection FP16 - CPU:
    FPS
    ms
AI Benchmark Alpha
OpenVINO:
  Vehicle Detection FP16-INT8 - CPU:
    FPS
    ms
oneDNN
OpenVINO:
  Person Vehicle Bike Detection FP16 - CPU:
    FPS
    ms
TensorFlow
OSPRay
Cpuminer-Opt
OpenVINO:
  Person Detection FP16 - CPU:
    FPS
    ms
  Person Detection FP32 - CPU:
    FPS
    ms
OSPRay
Cpuminer-Opt
OpenVINO
Mobile Neural Network
Neural Magic DeepSparse:
  NLP Question Answering, BERT base uncased SQuaD 12layer Pruned90 - Asynchronous Multi-Stream:
    items/sec
    ms/batch
Mobile Neural Network
Cpuminer-Opt
miniBUDE:
  OpenMP - BM1:
    GFInst/s
    Billion Interactions/s
Neural Magic DeepSparse:
  NLP Question Answering, BERT base uncased SQuaD 12layer Pruned90 - Synchronous Single-Stream:
    items/sec
    ms/batch
  CV Classification, ResNet-50 ImageNet - Asynchronous Multi-Stream:
    ms/batch
    items/sec
oneDNN
OpenVINO
Cpuminer-Opt
miniBUDE:
  OpenMP - BM2:
    Billion Interactions/s
    GFInst/s
OSPRay
Cpuminer-Opt
simdjson:
  DistinctUserID
  PartialTweets
Neural Magic DeepSparse:
  CV Detection,YOLOv5s COCO - Asynchronous Multi-Stream:
    items/sec
    ms/batch
simdjson
OSPRay Studio:
  2 - 1080p - 32 - Path Tracer
  2 - 4K - 16 - Path Tracer
  2 - 1080p - 16 - Path Tracer
  1 - 1080p - 32 - Path Tracer
  1 - 1080p - 1 - Path Tracer
  2 - 4K - 32 - Path Tracer
  1 - 4K - 1 - Path Tracer
  1 - 4K - 32 - Path Tracer
  1 - 4K - 16 - Path Tracer
  1 - 1080p - 16 - Path Tracer
  3 - 1080p - 16 - Path Tracer
  3 - 1080p - 32 - Path Tracer
simdjson
OSPRay Studio
simdjson
Neural Magic DeepSparse
OSPRay Studio
Neural Magic DeepSparse
OSPRay Studio:
  3 - 1080p - 1 - Path Tracer
  3 - 4K - 32 - Path Tracer
Embree:
  Pathtracer ISPC - Asian Dragon
  Pathtracer ISPC - Asian Dragon Obj
Neural Magic DeepSparse:
  CV Detection,YOLOv5s COCO - Synchronous Single-Stream:
    items/sec
    ms/batch
Embree
OSPRay Studio:
  2 - 4K - 1 - Path Tracer
  2 - 1080p - 1 - Path Tracer
Neural Magic DeepSparse
OpenFOAM
Neural Magic DeepSparse:
  NLP Text Classification, DistilBERT mnli - Asynchronous Multi-Stream
  NLP Text Classification, BERT base uncased SST2 - Synchronous Single-Stream
  NLP Text Classification, BERT base uncased SST2 - Synchronous Single-Stream
OpenVKL
OpenVINO
Neural Magic DeepSparse:
  NLP Token Classification, BERT base uncased conll2003 - Synchronous Single-Stream:
    items/sec
    ms/batch
  NLP Document Classification, oBERT base uncased on IMDB - Synchronous Single-Stream:
    items/sec
    ms/batch
NCNN
LeelaChessZero
NCNN
SMHasher
NCNN
ONNX Runtime
LeelaChessZero
CP2K Molecular Dynamics
Mobile Neural Network
OpenFOAM
Neural Magic DeepSparse:
  NLP Text Classification, DistilBERT mnli - Synchronous Single-Stream:
    items/sec
    ms/batch
Numpy Benchmark
JPEG XL libjxl
NCNN
JPEG XL libjxl
NCNN
Numenta Anomaly Benchmark
oneDNN
Intel Open Image Denoise
ONNX Runtime
Numenta Anomaly Benchmark
JPEG XL libjxl
Darmstadt Automotive Parallel Heterogeneous Suite
NCNN
GROMACS
Numenta Anomaly Benchmark
oneDNN
Intel Open Image Denoise:
  RT.hdr_alb_nrm.3840x2160
  RT.ldr_alb_nrm.3840x2160
CPU Temperature Monitor:
  Phoronix Test Suite System Monitoring:
    Celsius
    Watts
  CPU Temp Monitor:
    Celsius
  CPU Power Consumption Monitor:
    Watts
  CPU Peak Freq (Highest CPU Core Frequency) Monitor:
    Megahertz
  OpenMP - Points2Image:
    Test Cases Per Minute Per Watt
Darmstadt Automotive Parallel Heterogeneous Suite
SVT-AV1:
  CPU Temp Monitor
  CPU Power Consumption Monitor
  CPU Peak Freq (Highest CPU Core Frequency) Monitor
  Preset 12 - Bosphorus 4K
SVT-AV1
SVT-AV1:
  CPU Temp Monitor
  CPU Power Consumption Monitor
  CPU Peak Freq (Highest CPU Core Frequency) Monitor
  Preset 13 - Bosphorus 4K
SVT-AV1
ONNX Runtime:
  CPU Temp Monitor
  CPU Power Consumption Monitor
  CPU Peak Freq (Highest CPU Core Frequency) Monitor
  ArcFace ResNet-100 - CPU - Standard
ONNX Runtime
ONNX Runtime:
  CPU Temp Monitor
  CPU Power Consumption Monitor
  CPU Peak Freq (Highest CPU Core Frequency) Monitor
  super-resolution-10 - CPU - Standard
ONNX Runtime
NCNN:
  CPU Temp Monitor
  CPU Power Consumption Monitor
  CPU Peak Freq (Highest CPU Core Frequency) Monitor
NCNN:
  CPU - FastestDet
  CPU - vision_transformer
TensorFlow:
  CPU Temp Monitor
  CPU Power Consumption Monitor
  CPU Peak Freq (Highest CPU Core Frequency) Monitor
  CPU - 16 - GoogLeNet
TensorFlow

AVX-512 On

Kernel Notes: Transparent Huge Pages: madvise
Environment Notes: CXXFLAGS="-O3 -march=native -mavx512f -mavx512cd -mavx512vl -mavx512bw -mavx512dq -mavx512ifma -mavx512vbmi -mprefer-vector-width=512" CFLAGS="-O3 -march=native -mavx512f -mavx512cd -mavx512vl -mavx512bw -mavx512dq -mavx512ifma -mavx512vbmi -mprefer-vector-width=512"
Compiler Notes: --build=x86_64-linux-gnu --disable-vtable-verify --disable-werror --enable-cet --enable-checking=release --enable-clocale=gnu --enable-default-pie --enable-gnu-unique-object --enable-languages=c,ada,c++,go,d,fortran,objc,obj-c++,m2 --enable-libphobos-checking=release --enable-libstdcxx-debug --enable-libstdcxx-time=yes --enable-multiarch --enable-multilib --enable-nls --enable-objc-gc=auto --enable-offload-defaulted --enable-offload-targets=nvptx-none=/build/gcc-12-U8K4Qv/gcc-12-12.2.0/debian/tmp-nvptx/usr,amdgcn-amdhsa=/build/gcc-12-U8K4Qv/gcc-12-12.2.0/debian/tmp-gcn/usr --enable-plugin --enable-shared --enable-threads=posix --host=x86_64-linux-gnu --program-prefix=x86_64-linux-gnu- --target=x86_64-linux-gnu --with-abi=m64 --with-arch-32=i686 --with-default-libstdcxx-abi=new --with-gcc-major-version-only --with-multilib-list=m32,m64,mx32 --with-target-system-zlib=auto --with-tune=generic --without-cuda-driver -v
Processor Notes: Scaling Governor: acpi-cpufreq performance (Boost: Enabled) - CPU Microcode: 0xa10110d
Python Notes: Python 3.10.7
Security Notes: 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

Testing initiated at 18 December 2022 08:13 by user phoronix.

AVX-512 Off

Processor: 2 x AMD EPYC 9654 96-Core @ 2.40GHz (192 Cores / 384 Threads), Motherboard: AMD Titanite_4G (RTI1002E BIOS), Chipset: AMD Device 14a4, Memory: 1520GB, Disk: 800GB INTEL SSDPF21Q800GB, Graphics: ASPEED, Monitor: VGA HDMI, Network: Broadcom NetXtreme BCM5720 PCIe

OS: Ubuntu 22.10, Kernel: 6.1.0-phx (x86_64), Desktop: GNOME Shell 43.0, Display Server: X Server 1.21.1.4, Vulkan: 1.3.224, Compiler: GCC 12.2.0 + Clang 15.0.2-1, File-System: ext4, Screen Resolution: 1920x1080

Kernel Notes: Transparent Huge Pages: madvise
Environment Notes: CXXFLAGS="-O3 -march=native -mno-avx512f" CFLAGS="-O3 -march=native -mno-avx512f"
Compiler Notes: --build=x86_64-linux-gnu --disable-vtable-verify --disable-werror --enable-cet --enable-checking=release --enable-clocale=gnu --enable-default-pie --enable-gnu-unique-object --enable-languages=c,ada,c++,go,d,fortran,objc,obj-c++,m2 --enable-libphobos-checking=release --enable-libstdcxx-debug --enable-libstdcxx-time=yes --enable-multiarch --enable-multilib --enable-nls --enable-objc-gc=auto --enable-offload-defaulted --enable-offload-targets=nvptx-none=/build/gcc-12-U8K4Qv/gcc-12-12.2.0/debian/tmp-nvptx/usr,amdgcn-amdhsa=/build/gcc-12-U8K4Qv/gcc-12-12.2.0/debian/tmp-gcn/usr --enable-plugin --enable-shared --enable-threads=posix --host=x86_64-linux-gnu --program-prefix=x86_64-linux-gnu- --target=x86_64-linux-gnu --with-abi=m64 --with-arch-32=i686 --with-default-libstdcxx-abi=new --with-gcc-major-version-only --with-multilib-list=m32,m64,mx32 --with-target-system-zlib=auto --with-tune=generic --without-cuda-driver -v
Processor Notes: Scaling Governor: acpi-cpufreq performance (Boost: Enabled) - CPU Microcode: 0xa10110d
Python Notes: Python 3.10.7
Security Notes: 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

Testing initiated at 18 December 2022 08:13 by user phoronix.