AMD EPYC 9754 Bergamo AVX-512

AMD EPYC 9754 1P benchmarks with AVX-512 benchmarking and then AVX-512 disabled. Tests 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 2307197-NE-AMDBERGAM43
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AVX512 On
July 16 2023
  7 Hours, 54 Minutes
AVX512 Off
July 16 2023
  11 Hours, 27 Minutes
Invert Behavior (Only Show Selected Data)
  9 Hours, 40 Minutes
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AMD EPYC 9754 Bergamo AVX-512OpenBenchmarking.orgPhoronix Test SuiteAMD EPYC 9754 128-Core @ 2.25GHz (128 Cores / 256 Threads)AMD Titanite_4G (RTI1007B BIOS)AMD Device 14a4768GB2 x 1920GB SAMSUNG MZWLJ1T9HBJR-00007ASPEEDBroadcom NetXtreme BCM5720 PCIeUbuntu 22.045.19.0-41-generic (x86_64)GNOME Shell 42.5X Server 1.21.1.41.3.224GCC 11.3.0ext41024x768ProcessorMotherboardChipsetMemoryDiskGraphicsNetworkOSKernelDesktopDisplay ServerVulkanCompilerFile-SystemScreen ResolutionAMD EPYC 9754 Bergamo AVX-512 BenchmarksSystem Logs- Transparent Huge Pages: madvise- --build=x86_64-linux-gnu --disable-vtable-verify --disable-werror --enable-bootstrap --enable-cet --enable-checking=release --enable-clocale=gnu --enable-default-pie --enable-gnu-unique-object --enable-languages=c,ada,c++,go,brig,d,fortran,objc,obj-c++,m2 --enable-libphobos-checking=release --enable-libstdcxx-debug --enable-libstdcxx-time=yes --enable-link-serialization=2 --enable-multiarch --enable-multilib --enable-nls --enable-objc-gc=auto --enable-offload-targets=nvptx-none=/build/gcc-11-xKiWfi/gcc-11-11.3.0/debian/tmp-nvptx/usr,amdgcn-amdhsa=/build/gcc-11-xKiWfi/gcc-11-11.3.0/debian/tmp-gcn/usr --enable-plugin --enable-shared --enable-threads=posix --host=x86_64-linux-gnu --program-prefix=x86_64-linux-gnu- --target=x86_64-linux-gnu --with-abi=m64 --with-arch-32=i686 --with-build-config=bootstrap-lto-lean --with-default-libstdcxx-abi=new --with-gcc-major-version-only --with-multilib-list=m32,m64,mx32 --with-target-system-zlib=auto --with-tune=generic --without-cuda-driver -v - Scaling Governor: acpi-cpufreq performance (Boost: Enabled) - CPU Microcode: 0xaa0010b - Python 3.10.6- 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

AVX512 On vs. AVX512 Off ComparisonPhoronix Test SuiteBaseline+346.4%+346.4%+692.8%+692.8%+1039.2%+1039.2%CPU - 512 - GoogLeNet789.3%CPU - 64 - AlexNet778.7%CPU - 32 - AlexNet562.1%CPU - 256 - ResNet-50499.9%CPU - 64 - GoogLeNet499%CPU - 512 - ResNet-50491%CPU - 64 - ResNet-50423.7%CPU - 16 - AlexNet389.1%CPU - 32 - ResNet-50309.7%CPU - 32 - GoogLeNet306.6%CPU - 16 - ResNet-50171%CPU - 16 - GoogLeNet164.3%W.P.D.F - CPU138.2%W.P.D.F - CPU138%F.D.F - CPU132%F.D.F - CPU131.2%M.T.E.T.D.F - CPU130.3%M.T.E.T.D.F - CPU130.2%W.P.D.F.I - CPU107.7%W.P.D.F.I - CPU107.6%F.D.F.I - CPU103.6%F.D.F.I - CPU102.6%P.V.B.D.F - CPU100.2%P.V.B.D.F - CPU100.1%CPU - 512 - AlexNet1385.6%CPU - 256 - AlexNet1238.3%CPU - 256 - GoogLeNet986.6%LBC, LBRY Credits98.6%A.G.R.R.0.F - CPU92.9%N.S.A.8.P.Q.B.B.U - A.M.S92.3%N.S.A.8.P.Q.B.B.U - A.M.S92.2%C.S.9.P.Y.P - A.M.S83.3%C.S.9.P.Y.P - A.M.S81.9%P.D.F - CPU80.2%P.D.F - CPU79.8%P.D.F - CPU78.2%P.D.F - CPU77.9%A.G.R.R.0.F - CPU76.2%gravity_spheres_volume/dim_512/scivis/real_time75.8%Q.S.2.P71.1%gravity_spheres_volume/dim_512/ao/real_time70.8%x25x65.4%Blake-2 S58.9%scrypt47.2%V.D.F.I - CPU43.9%V.D.F.I - CPU43.6%gravity_spheres_volume/dim_512/pathtracer/real_time43.1%25638.4%Garlicoin34.5%OpenMP - BM231.9%OpenMP - BM231.9%OpenMP - BM126.7%OpenMP - BM126.7%Skeincoin25.3%N.T.C.B.b.u.S - A.M.S21.2%N.T.C.B.b.u.S - A.M.S21.1%Myriad-Groestl20.7%V.D.F - CPU20.1%V.D.F - CPU20%N.D.C.o.b.u.o.I - A.M.S19.8%N.T.C.D.m - A.M.S19.7%N.T.C.D.m - A.M.S19.6%N.T.C.B.b.u.c - A.M.S19.6%N.T.C.B.b.u.c - A.M.S19.3%N.D.C.o.b.u.o.I - A.M.S19.2%vklBenchmark ISPC18.6%Pathtracer ISPC - Asian Dragon18.6%Pathtracer ISPC - Asian Dragon Obj17%N.Q.A.B.b.u.S.1.P - A.M.S16.1%N.Q.A.B.b.u.S.1.P - A.M.S14.8%R.N.N.T - bf16bf16bf16 - CPU12.2%Pathtracer ISPC - Crown11.9%A.G.R.R.0.F.I - CPU11.4%C.C.R.5.I - A.M.S11.4%C.C.R.5.I - A.M.S11.3%A.G.R.R.0.F.I - CPU10.6%1284.6%TensorFlowTensorFlowTensorFlowTensorFlowTensorFlowTensorFlowTensorFlowTensorFlowTensorFlowTensorFlowTensorFlowTensorFlowOpenVINOOpenVINOOpenVINOOpenVINOOpenVINOOpenVINOOpenVINOOpenVINOOpenVINOOpenVINOOpenVINOOpenVINOTensorFlowTensorFlowTensorFlowCpuminer-OptOpenVINONeural Magic DeepSparseNeural Magic DeepSparseNeural Magic DeepSparseNeural Magic DeepSparseOpenVINOOpenVINOOpenVINOOpenVINOOpenVINOOSPRayCpuminer-OptOSPRayCpuminer-OptCpuminer-OptCpuminer-OptOpenVINOOpenVINOOSPRaylibxsmmCpuminer-OptminiBUDEminiBUDEminiBUDEminiBUDECpuminer-OptNeural Magic DeepSparseNeural Magic DeepSparseCpuminer-OptOpenVINOOpenVINONeural Magic DeepSparseNeural Magic DeepSparseNeural Magic DeepSparseNeural Magic DeepSparseNeural Magic DeepSparseNeural Magic DeepSparseOpenVKLEmbreeEmbreeNeural Magic DeepSparseNeural Magic DeepSparseoneDNNEmbreeOpenVINONeural Magic DeepSparseNeural Magic DeepSparseOpenVINOlibxsmmAVX512 OnAVX512 Off

AMD EPYC 9754 Bergamo AVX-512tensorflow: CPU - 512 - GoogLeNettensorflow: CPU - 64 - AlexNettensorflow: CPU - 32 - AlexNettensorflow: CPU - 256 - ResNet-50tensorflow: CPU - 64 - GoogLeNettensorflow: CPU - 512 - ResNet-50tensorflow: CPU - 64 - ResNet-50tensorflow: CPU - 16 - AlexNettensorflow: CPU - 32 - ResNet-50tensorflow: CPU - 16 - ResNet-50openvino: Weld Porosity Detection FP16 - CPUopenvino: Weld Porosity Detection FP16 - CPUopenvino: Face Detection FP16 - CPUopenvino: Face Detection FP16 - CPUopenvino: 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: Person Vehicle Bike Detection FP16 - CPUopenvino: Person Vehicle Bike Detection FP16 - CPUtensorflow: CPU - 512 - AlexNettensorflow: CPU - 256 - AlexNettensorflow: CPU - 256 - GoogLeNetcpuminer-opt: LBC, LBRY Creditsopenvino: Age Gender Recognition Retail 0013 FP16 - CPUdeepsparse: NLP Sentiment Analysis, 80% Pruned Quantized BERT Base Uncased - Asynchronous Multi-Streamdeepsparse: NLP Sentiment Analysis, 80% Pruned Quantized BERT Base Uncased - Asynchronous Multi-Streamdeepsparse: CV Segmentation, 90% Pruned YOLACT Pruned - Asynchronous Multi-Streamdeepsparse: CV Segmentation, 90% Pruned YOLACT Pruned - Asynchronous Multi-Streamopenvino: Person Detection FP32 - CPUopenvino: Person Detection FP16 - CPUopenvino: Person Detection FP32 - CPUopenvino: Person Detection FP16 - CPUopenvino: Age Gender Recognition Retail 0013 FP16 - CPUospray: gravity_spheres_volume/dim_512/scivis/real_timecpuminer-opt: Quad SHA-256, Pyriteospray: gravity_spheres_volume/dim_512/ao/real_timecpuminer-opt: x25xcpuminer-opt: Blake-2 Scpuminer-opt: scryptopenvino: Vehicle Detection FP16-INT8 - CPUospray: gravity_spheres_volume/dim_512/pathtracer/real_timelibxsmm: 256cpuminer-opt: Garlicoinminibude: OpenMP - BM2minibude: OpenMP - BM2minibude: OpenMP - BM1minibude: OpenMP - BM1cpuminer-opt: Skeincoindeepsparse: NLP Text Classification, BERT base uncased SST2 - Asynchronous Multi-Streamdeepsparse: NLP Text Classification, BERT base uncased SST2 - Asynchronous Multi-Streamopenvino: Vehicle Detection FP16 - CPUdeepsparse: NLP Document Classification, oBERT base uncased on IMDB - Asynchronous Multi-Streamdeepsparse: NLP Text Classification, DistilBERT mnli - Asynchronous Multi-Streamdeepsparse: NLP Text Classification, DistilBERT mnli - Asynchronous Multi-Streamdeepsparse: NLP Token Classification, BERT base uncased conll2003 - Asynchronous Multi-Streamdeepsparse: NLP Token Classification, BERT base uncased conll2003 - Asynchronous Multi-Streamdeepsparse: NLP Document Classification, oBERT base uncased on IMDB - Asynchronous Multi-Streamopenvkl: vklBenchmark ISPCembree: Pathtracer ISPC - Asian Dragonembree: Pathtracer ISPC - Asian Dragon Objonednn: Recurrent Neural Network Training - bf16bf16bf16 - CPUembree: Pathtracer ISPC - Crownopenvino: Age Gender Recognition Retail 0013 FP16-INT8 - CPUdeepsparse: CV Classification, ResNet-50 ImageNet - Asynchronous Multi-Streamdeepsparse: CV Classification, ResNet-50 ImageNet - Asynchronous Multi-Streamopenvino: Age Gender Recognition Retail 0013 FP16-INT8 - CPUlibxsmm: 128openvino: Vehicle Detection FP16-INT8 - CPUopenvino: Vehicle Detection FP16 - CPUdeepsparse: NLP Question Answering, BERT base uncased SQuaD 12layer Pruned90 - Asynchronous Multi-Streamdeepsparse: NLP Question Answering, BERT base uncased SQuaD 12layer Pruned90 - Asynchronous Multi-Streamtensorflow: CPU - 32 - GoogLeNettensorflow: CPU - 16 - GoogLeNetcpuminer-opt: Myriad-GroestlAVX512 OnAVX512 Off417.25857.55562.48119.32277.24122.8196.63342.8871.6243.1110.526073.2260.731048.37580.40110.3510.8211818.33118.00540.359.636638.711632.401422.36501.676606600.991381.566946.2608127.0611498.477927.0127.082339.812334.29110240.8931.6753149893732.75574977.8972386502993.2111.2627.97153342.5530905972.187238.887237.0275925.6701174953316.1679201.596444.8473.5393624.7370102.223873.1459859.7119858.40291398157.6450134.83961174.75125.54141.58970.056865.890973970.122690.75690.341430.45259.6468247.9653180.77104.778628.7646.9297.5984.9619.8946.2820.7818.4570.1017.4815.9125.062551.7026.182423.39251.97254.0122.475692.9957.951094.5219.283317.34109.88106.2846.173326671.91718.303288.909369.3341906.941414.9915.064170.494153.5962564.1618.020387613719.17313010.3745555802033.1516.1719.54632415.3394734528.305181.132187.1074677.682937977260.7671244.151353.7961.3689522.1104122.229561.17551025.48061023.16901179132.9504115.26821317.57112.22741.76870.954173.350266895.492573.33954.901190.91298.0628213.639344.4639.647149.95OpenBenchmarking.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 if desired for complementary metrics. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgimages/sec, More Is BetterTensorFlow 2.12Device: CPU - Batch Size: 512 - Model: GoogLeNetAVX512 OnAVX512 Off90180270360450SE +/- 5.30, N = 12SE +/- 0.05, N = 3417.2546.92

OpenBenchmarking.orgimages/sec, More Is BetterTensorFlow 2.12Device: CPU - Batch Size: 64 - Model: AlexNetAVX512 OnAVX512 Off2004006008001000SE +/- 1.99, N = 5SE +/- 0.08, N = 3857.5597.59

OpenBenchmarking.orgimages/sec, More Is BetterTensorFlow 2.12Device: CPU - Batch Size: 32 - Model: AlexNetAVX512 OnAVX512 Off120240360480600SE +/- 2.06, N = 6SE +/- 0.16, N = 3562.4884.96

OpenBenchmarking.orgimages/sec, More Is BetterTensorFlow 2.12Device: CPU - Batch Size: 256 - Model: ResNet-50AVX512 OnAVX512 Off306090120150SE +/- 1.01, N = 12SE +/- 0.02, N = 3119.3219.89

OpenBenchmarking.orgimages/sec, More Is BetterTensorFlow 2.12Device: CPU - Batch Size: 64 - Model: GoogLeNetAVX512 OnAVX512 Off60120180240300SE +/- 2.62, N = 15SE +/- 0.18, N = 3277.2446.28

OpenBenchmarking.orgimages/sec, More Is BetterTensorFlow 2.12Device: CPU - Batch Size: 512 - Model: ResNet-50AVX512 OnAVX512 Off306090120150SE +/- 0.99, N = 3SE +/- 0.04, N = 3122.8120.78

OpenBenchmarking.orgimages/sec, More Is BetterTensorFlow 2.12Device: CPU - Batch Size: 64 - Model: ResNet-50AVX512 OnAVX512 Off20406080100SE +/- 0.06, N = 3SE +/- 0.03, N = 396.6318.45

OpenBenchmarking.orgimages/sec, More Is BetterTensorFlow 2.12Device: CPU - Batch Size: 16 - Model: AlexNetAVX512 OnAVX512 Off70140210280350SE +/- 0.70, N = 6SE +/- 0.29, N = 3342.8870.10

OpenBenchmarking.orgimages/sec, More Is BetterTensorFlow 2.12Device: CPU - Batch Size: 32 - Model: ResNet-50AVX512 OnAVX512 Off1632486480SE +/- 0.23, N = 3SE +/- 0.04, N = 371.6217.48

OpenBenchmarking.orgimages/sec, More Is BetterTensorFlow 2.12Device: CPU - Batch Size: 16 - Model: ResNet-50AVX512 OnAVX512 Off1020304050SE +/- 0.03, N = 3SE +/- 0.05, N = 343.1115.91

OpenVINO

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

OpenBenchmarking.orgms, Fewer Is BetterOpenVINO 2022.3Model: Weld Porosity Detection FP16 - Device: CPUAVX512 OnAVX512 Off612182430SE +/- 0.00, N = 3SE +/- 0.01, N = 310.5225.06MIN: 5.11 / MAX: 34.37MIN: 13.08 / MAX: 57.021. (CXX) g++ options: -isystem -fsigned-char -ffunction-sections -fdata-sections -msse4.1 -msse4.2 -O3 -fno-strict-overflow -fwrapv -fPIC -fvisibility=hidden -Os -std=c++11 -MD -MT -MF

OpenBenchmarking.orgFPS, More Is BetterOpenVINO 2022.3Model: Weld Porosity Detection FP16 - Device: CPUAVX512 OnAVX512 Off13002600390052006500SE +/- 1.32, N = 3SE +/- 0.56, N = 36073.222551.701. (CXX) g++ options: -isystem -fsigned-char -ffunction-sections -fdata-sections -msse4.1 -msse4.2 -O3 -fno-strict-overflow -fwrapv -fPIC -fvisibility=hidden -Os -std=c++11 -MD -MT -MF

OpenBenchmarking.orgFPS, More Is BetterOpenVINO 2022.3Model: Face Detection FP16 - Device: CPUAVX512 OnAVX512 Off1428425670SE +/- 0.06, N = 3SE +/- 0.36, N = 360.7326.181. (CXX) g++ options: -isystem -fsigned-char -ffunction-sections -fdata-sections -msse4.1 -msse4.2 -O3 -fno-strict-overflow -fwrapv -fPIC -fvisibility=hidden -Os -std=c++11 -MD -MT -MF

OpenBenchmarking.orgms, Fewer Is BetterOpenVINO 2022.3Model: Face Detection FP16 - Device: CPUAVX512 OnAVX512 Off5001000150020002500SE +/- 0.42, N = 3SE +/- 26.84, N = 31048.372423.39MIN: 508.1 / MAX: 1159.4MIN: 1130.42 / MAX: 2937.221. (CXX) g++ options: -isystem -fsigned-char -ffunction-sections -fdata-sections -msse4.1 -msse4.2 -O3 -fno-strict-overflow -fwrapv -fPIC -fvisibility=hidden -Os -std=c++11 -MD -MT -MF

OpenBenchmarking.orgFPS, More Is BetterOpenVINO 2022.3Model: Machine Translation EN To DE FP16 - Device: CPUAVX512 OnAVX512 Off130260390520650SE +/- 7.10, N = 15SE +/- 3.15, N = 15580.40251.971. (CXX) g++ options: -isystem -fsigned-char -ffunction-sections -fdata-sections -msse4.1 -msse4.2 -O3 -fno-strict-overflow -fwrapv -fPIC -fvisibility=hidden -Os -std=c++11 -MD -MT -MF

OpenBenchmarking.orgms, Fewer Is BetterOpenVINO 2022.3Model: Machine Translation EN To DE FP16 - Device: CPUAVX512 OnAVX512 Off60120180240300SE +/- 1.22, N = 15SE +/- 2.83, N = 15110.35254.01MIN: 49.7 / MAX: 183.59MIN: 116.71 / MAX: 398.881. (CXX) g++ options: -isystem -fsigned-char -ffunction-sections -fdata-sections -msse4.1 -msse4.2 -O3 -fno-strict-overflow -fwrapv -fPIC -fvisibility=hidden -Os -std=c++11 -MD -MT -MF

OpenBenchmarking.orgms, Fewer Is BetterOpenVINO 2022.3Model: Weld Porosity Detection FP16-INT8 - Device: CPUAVX512 OnAVX512 Off510152025SE +/- 0.00, N = 3SE +/- 0.01, N = 310.8222.47MIN: 5 / MAX: 31.44MIN: 10.87 / MAX: 43.51. (CXX) g++ options: -isystem -fsigned-char -ffunction-sections -fdata-sections -msse4.1 -msse4.2 -O3 -fno-strict-overflow -fwrapv -fPIC -fvisibility=hidden -Os -std=c++11 -MD -MT -MF

OpenBenchmarking.orgFPS, More Is BetterOpenVINO 2022.3Model: Weld Porosity Detection FP16-INT8 - Device: CPUAVX512 OnAVX512 Off3K6K9K12K15KSE +/- 1.17, N = 3SE +/- 1.65, N = 311818.335692.991. (CXX) g++ options: -isystem -fsigned-char -ffunction-sections -fdata-sections -msse4.1 -msse4.2 -O3 -fno-strict-overflow -fwrapv -fPIC -fvisibility=hidden -Os -std=c++11 -MD -MT -MF

OpenBenchmarking.orgFPS, More Is BetterOpenVINO 2022.3Model: Face Detection FP16-INT8 - Device: CPUAVX512 OnAVX512 Off306090120150SE +/- 0.02, N = 3SE +/- 0.03, N = 3118.0057.951. (CXX) g++ options: -isystem -fsigned-char -ffunction-sections -fdata-sections -msse4.1 -msse4.2 -O3 -fno-strict-overflow -fwrapv -fPIC -fvisibility=hidden -Os -std=c++11 -MD -MT -MF

OpenBenchmarking.orgms, Fewer Is BetterOpenVINO 2022.3Model: Face Detection FP16-INT8 - Device: CPUAVX512 OnAVX512 Off2004006008001000SE +/- 0.07, N = 3SE +/- 0.34, N = 3540.351094.52MIN: 257.81 / MAX: 586.56MIN: 509.48 / MAX: 1179.631. (CXX) g++ options: -isystem -fsigned-char -ffunction-sections -fdata-sections -msse4.1 -msse4.2 -O3 -fno-strict-overflow -fwrapv -fPIC -fvisibility=hidden -Os -std=c++11 -MD -MT -MF

OpenBenchmarking.orgms, Fewer Is BetterOpenVINO 2022.3Model: Person Vehicle Bike Detection FP16 - Device: CPUAVX512 OnAVX512 Off510152025SE +/- 0.02, N = 3SE +/- 0.14, N = 159.6319.28MIN: 6.4 / MAX: 33.26MIN: 10.31 / MAX: 50.611. (CXX) g++ options: -isystem -fsigned-char -ffunction-sections -fdata-sections -msse4.1 -msse4.2 -O3 -fno-strict-overflow -fwrapv -fPIC -fvisibility=hidden -Os -std=c++11 -MD -MT -MF

OpenBenchmarking.orgFPS, More Is BetterOpenVINO 2022.3Model: Person Vehicle Bike Detection FP16 - Device: CPUAVX512 OnAVX512 Off14002800420056007000SE +/- 13.51, N = 3SE +/- 26.07, N = 156638.713317.341. (CXX) g++ options: -isystem -fsigned-char -ffunction-sections -fdata-sections -msse4.1 -msse4.2 -O3 -fno-strict-overflow -fwrapv -fPIC -fvisibility=hidden -Os -std=c++11 -MD -MT -MF

TensorFlow

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

OpenBenchmarking.orgimages/sec, More Is BetterTensorFlow 2.12Device: CPU - Batch Size: 512 - Model: AlexNetAVX512 OnAVX512 Off400800120016002000SE +/- 1.53, N = 3SE +/- 0.06, N = 31632.40109.88

OpenBenchmarking.orgimages/sec, More Is BetterTensorFlow 2.12Device: CPU - Batch Size: 256 - Model: AlexNetAVX512 OnAVX512 Off30060090012001500SE +/- 6.55, N = 3SE +/- 0.24, N = 31422.36106.28

OpenBenchmarking.orgimages/sec, More Is BetterTensorFlow 2.12Device: CPU - Batch Size: 256 - Model: GoogLeNetAVX512 OnAVX512 Off110220330440550SE +/- 4.92, N = 3SE +/- 0.06, N = 3501.6746.17

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 CreditsAVX512 OnAVX512 Off140K280K420K560K700KSE +/- 76.38, N = 3SE +/- 141.93, N = 36606603326671. (CXX) g++ options: -O2 -lcurl -lz -lpthread -lssl -lcrypto -lgmp

OpenVINO

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

OpenBenchmarking.orgms, Fewer Is BetterOpenVINO 2022.3Model: Age Gender Recognition Retail 0013 FP16 - Device: CPUAVX512 OnAVX512 Off0.42980.85961.28941.71922.149SE +/- 0.00, N = 3SE +/- 0.01, N = 30.991.91MIN: 0.35 / MAX: 19.47MIN: 0.67 / MAX: 19.481. (CXX) g++ options: -isystem -fsigned-char -ffunction-sections -fdata-sections -msse4.1 -msse4.2 -O3 -fno-strict-overflow -fwrapv -fPIC -fvisibility=hidden -Os -std=c++11 -MD -MT -MF

Neural Magic DeepSparse

This is a benchmark of Neural Magic's DeepSparse using its built-in deepsparse.benchmark utility and various models from their SparseZoo (https://sparsezoo.neuralmagic.com/). Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgitems/sec, More Is BetterNeural Magic DeepSparse 1.5Model: NLP Sentiment Analysis, 80% Pruned Quantized BERT Base Uncased - Scenario: Asynchronous Multi-StreamAVX512 OnAVX512 Off30060090012001500SE +/- 1.58, N = 3SE +/- 5.33, N = 31381.57718.30

OpenBenchmarking.orgms/batch, Fewer Is BetterNeural Magic DeepSparse 1.5Model: NLP Sentiment Analysis, 80% Pruned Quantized BERT Base Uncased - Scenario: Asynchronous Multi-StreamAVX512 OnAVX512 Off20406080100SE +/- 0.05, N = 3SE +/- 0.67, N = 346.2688.91

OpenBenchmarking.orgitems/sec, More Is BetterNeural Magic DeepSparse 1.5Model: CV Segmentation, 90% Pruned YOLACT Pruned - Scenario: Asynchronous Multi-StreamAVX512 OnAVX512 Off306090120150SE +/- 0.01, N = 3SE +/- 0.03, N = 3127.0669.33

OpenBenchmarking.orgms/batch, Fewer Is BetterNeural Magic DeepSparse 1.5Model: CV Segmentation, 90% Pruned YOLACT Pruned - Scenario: Asynchronous Multi-StreamAVX512 OnAVX512 Off2004006008001000SE +/- 0.16, N = 3SE +/- 0.94, N = 3498.48906.94

OpenVINO

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

OpenBenchmarking.orgFPS, More Is BetterOpenVINO 2022.3Model: Person Detection FP32 - Device: CPUAVX512 OnAVX512 Off612182430SE +/- 0.18, N = 12SE +/- 0.16, N = 527.0114.991. (CXX) g++ options: -isystem -fsigned-char -ffunction-sections -fdata-sections -msse4.1 -msse4.2 -O3 -fno-strict-overflow -fwrapv -fPIC -fvisibility=hidden -Os -std=c++11 -MD -MT -MF

OpenBenchmarking.orgFPS, More Is BetterOpenVINO 2022.3Model: Person Detection FP16 - Device: CPUAVX512 OnAVX512 Off612182430SE +/- 0.30, N = 12SE +/- 0.21, N = 327.0815.061. (CXX) g++ options: -isystem -fsigned-char -ffunction-sections -fdata-sections -msse4.1 -msse4.2 -O3 -fno-strict-overflow -fwrapv -fPIC -fvisibility=hidden -Os -std=c++11 -MD -MT -MF

OpenBenchmarking.orgms, Fewer Is BetterOpenVINO 2022.3Model: Person Detection FP32 - Device: CPUAVX512 OnAVX512 Off9001800270036004500SE +/- 14.83, N = 12SE +/- 41.79, N = 52339.814170.49MIN: 1045.35 / MAX: 3232.69MIN: 1759.65 / MAX: 4969.51. (CXX) g++ options: -isystem -fsigned-char -ffunction-sections -fdata-sections -msse4.1 -msse4.2 -O3 -fno-strict-overflow -fwrapv -fPIC -fvisibility=hidden -Os -std=c++11 -MD -MT -MF

OpenBenchmarking.orgms, Fewer Is BetterOpenVINO 2022.3Model: Person Detection FP16 - Device: CPUAVX512 OnAVX512 Off9001800270036004500SE +/- 22.79, N = 12SE +/- 59.43, N = 32334.294153.59MIN: 1017.83 / MAX: 3101.05MIN: 1975.28 / MAX: 5152.661. (CXX) g++ options: -isystem -fsigned-char -ffunction-sections -fdata-sections -msse4.1 -msse4.2 -O3 -fno-strict-overflow -fwrapv -fPIC -fvisibility=hidden -Os -std=c++11 -MD -MT -MF

OpenBenchmarking.orgFPS, More Is BetterOpenVINO 2022.3Model: Age Gender Recognition Retail 0013 FP16 - Device: CPUAVX512 OnAVX512 Off20K40K60K80K100KSE +/- 314.35, N = 3SE +/- 278.13, N = 3110240.8962564.161. (CXX) g++ options: -isystem -fsigned-char -ffunction-sections -fdata-sections -msse4.1 -msse4.2 -O3 -fno-strict-overflow -fwrapv -fPIC -fvisibility=hidden -Os -std=c++11 -MD -MT -MF

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 2.12Benchmark: gravity_spheres_volume/dim_512/scivis/real_timeAVX512 OnAVX512 Off714212835SE +/- 0.02, N = 3SE +/- 0.00, N = 331.6818.02

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, PyriteAVX512 OnAVX512 Off300K600K900K1200K1500KSE +/- 3455.26, N = 3SE +/- 2198.34, N = 314989378761371. (CXX) g++ options: -O2 -lcurl -lz -lpthread -lssl -lcrypto -lgmp

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 2.12Benchmark: gravity_spheres_volume/dim_512/ao/real_timeAVX512 OnAVX512 Off816243240SE +/- 0.01, N = 3SE +/- 0.02, N = 332.7619.17

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: x25xAVX512 OnAVX512 Off11002200330044005500SE +/- 15.71, N = 3SE +/- 35.48, N = 44977.893010.371. (CXX) g++ options: -O2 -lcurl -lz -lpthread -lssl -lcrypto -lgmp

OpenBenchmarking.orgkH/s, More Is BetterCpuminer-Opt 3.20.3Algorithm: Blake-2 SAVX512 OnAVX512 Off1.6M3.2M4.8M6.4M8MSE +/- 3854.05, N = 3SE +/- 37514.23, N = 15723865045555801. (CXX) g++ options: -O2 -lcurl -lz -lpthread -lssl -lcrypto -lgmp

OpenBenchmarking.orgkH/s, More Is BetterCpuminer-Opt 3.20.3Algorithm: scryptAVX512 OnAVX512 Off6001200180024003000SE +/- 1.66, N = 3SE +/- 0.24, N = 32993.212033.151. (CXX) g++ options: -O2 -lcurl -lz -lpthread -lssl -lcrypto -lgmp

OpenVINO

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

OpenBenchmarking.orgms, Fewer Is BetterOpenVINO 2022.3Model: Vehicle Detection FP16-INT8 - Device: CPUAVX512 OnAVX512 Off48121620SE +/- 0.15, N = 15SE +/- 0.01, N = 311.2616.17MIN: 4.37 / MAX: 45.06MIN: 8.44 / MAX: 56.881. (CXX) g++ options: -isystem -fsigned-char -ffunction-sections -fdata-sections -msse4.1 -msse4.2 -O3 -fno-strict-overflow -fwrapv -fPIC -fvisibility=hidden -Os -std=c++11 -MD -MT -MF

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 2.12Benchmark: gravity_spheres_volume/dim_512/pathtracer/real_timeAVX512 OnAVX512 Off714212835SE +/- 0.01, N = 3SE +/- 0.01, N = 327.9719.55

libxsmm

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

OpenBenchmarking.orgGFLOPS/s, More Is Betterlibxsmm 2-1.17-3645M N K: 256AVX512 OnAVX512 Off7001400210028003500SE +/- 5.78, N = 3SE +/- 6.53, N = 33342.52415.31. (CXX) g++ options: -dynamic -Bstatic -static-libgcc -lgomp -lm -lrt -ldl -lquadmath -lstdc++ -pthread -fPIC -std=c++14 -O2 -fopenmp-simd -funroll-loops -ftree-vectorize -fdata-sections -ffunction-sections -fvisibility=hidden -msse4.2

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: GarlicoinAVX512 OnAVX512 Off11K22K33K44K55KSE +/- 110.15, N = 3SE +/- 102.69, N = 353090394731. (CXX) g++ options: -O2 -lcurl -lz -lpthread -lssl -lcrypto -lgmp

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: BM2AVX512 OnAVX512 Off13002600390052006500SE +/- 0.44, N = 3SE +/- 15.49, N = 35972.194528.311. (CC) gcc options: -std=c99 -Ofast -ffast-math -fopenmp -march=native -lm

OpenBenchmarking.orgBillion Interactions/s, More Is BetterminiBUDE 20210901Implementation: OpenMP - Input Deck: BM2AVX512 OnAVX512 Off50100150200250SE +/- 0.02, N = 3SE +/- 0.62, N = 3238.89181.131. (CC) gcc options: -std=c99 -Ofast -ffast-math -fopenmp -march=native -lm

OpenBenchmarking.orgBillion Interactions/s, More Is BetterminiBUDE 20210901Implementation: OpenMP - Input Deck: BM1AVX512 OnAVX512 Off50100150200250SE +/- 0.09, N = 9SE +/- 0.72, N = 8237.03187.111. (CC) gcc options: -std=c99 -Ofast -ffast-math -fopenmp -march=native -lm

OpenBenchmarking.orgGFInst/s, More Is BetterminiBUDE 20210901Implementation: OpenMP - Input Deck: BM1AVX512 OnAVX512 Off13002600390052006500SE +/- 2.27, N = 9SE +/- 18.03, N = 85925.674677.681. (CC) gcc options: -std=c99 -Ofast -ffast-math -fopenmp -march=native -lm

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: SkeincoinAVX512 OnAVX512 Off300K600K900K1200K1500KSE +/- 4577.90, N = 3SE +/- 1811.04, N = 311749539379771. (CXX) g++ options: -O2 -lcurl -lz -lpthread -lssl -lcrypto -lgmp

Neural Magic DeepSparse

This is a benchmark of Neural Magic's DeepSparse using its built-in deepsparse.benchmark utility and various models from their SparseZoo (https://sparsezoo.neuralmagic.com/). Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgitems/sec, More Is BetterNeural Magic DeepSparse 1.5Model: NLP Text Classification, BERT base uncased SST2 - Scenario: Asynchronous Multi-StreamAVX512 OnAVX512 Off70140210280350SE +/- 0.78, N = 3SE +/- 0.63, N = 3316.17260.77

OpenBenchmarking.orgms/batch, Fewer Is BetterNeural Magic DeepSparse 1.5Model: NLP Text Classification, BERT base uncased SST2 - Scenario: Asynchronous Multi-StreamAVX512 OnAVX512 Off50100150200250SE +/- 0.47, N = 3SE +/- 0.64, N = 3201.60244.15

OpenVINO

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

OpenBenchmarking.orgms, Fewer Is BetterOpenVINO 2022.3Model: Vehicle Detection FP16 - Device: CPUAVX512 OnAVX512 Off1224364860SE +/- 0.60, N = 15SE +/- 0.62, N = 1444.8453.79MIN: 8.1 / MAX: 137.01MIN: 13.85 / MAX: 136.831. (CXX) g++ options: -isystem -fsigned-char -ffunction-sections -fdata-sections -msse4.1 -msse4.2 -O3 -fno-strict-overflow -fwrapv -fPIC -fvisibility=hidden -Os -std=c++11 -MD -MT -MF

Neural Magic DeepSparse

This is a benchmark of Neural Magic's DeepSparse using its built-in deepsparse.benchmark utility and various models from their SparseZoo (https://sparsezoo.neuralmagic.com/). Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgitems/sec, More Is BetterNeural Magic DeepSparse 1.5Model: NLP Document Classification, oBERT base uncased on IMDB - Scenario: Asynchronous Multi-StreamAVX512 OnAVX512 Off1632486480SE +/- 0.14, N = 3SE +/- 0.02, N = 373.5461.37

OpenBenchmarking.orgitems/sec, More Is BetterNeural Magic DeepSparse 1.5Model: NLP Text Classification, DistilBERT mnli - Scenario: Asynchronous Multi-StreamAVX512 OnAVX512 Off130260390520650SE +/- 0.52, N = 3SE +/- 0.58, N = 3624.74522.11

OpenBenchmarking.orgms/batch, Fewer Is BetterNeural Magic DeepSparse 1.5Model: NLP Text Classification, DistilBERT mnli - Scenario: Asynchronous Multi-StreamAVX512 OnAVX512 Off306090120150SE +/- 0.07, N = 3SE +/- 0.15, N = 3102.22122.23

OpenBenchmarking.orgitems/sec, More Is BetterNeural Magic DeepSparse 1.5Model: NLP Token Classification, BERT base uncased conll2003 - Scenario: Asynchronous Multi-StreamAVX512 OnAVX512 Off1632486480SE +/- 0.19, N = 3SE +/- 0.13, N = 373.1561.18

OpenBenchmarking.orgms/batch, Fewer Is BetterNeural Magic DeepSparse 1.5Model: NLP Token Classification, BERT base uncased conll2003 - Scenario: Asynchronous Multi-StreamAVX512 OnAVX512 Off2004006008001000SE +/- 0.45, N = 3SE +/- 1.31, N = 3859.711025.48

OpenBenchmarking.orgms/batch, Fewer Is BetterNeural Magic DeepSparse 1.5Model: NLP Document Classification, oBERT base uncased on IMDB - Scenario: Asynchronous Multi-StreamAVX512 OnAVX512 Off2004006008001000SE +/- 0.33, N = 3SE +/- 1.40, N = 3858.401023.17

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 ISPCAVX512 OnAVX512 Off30060090012001500SE +/- 2.65, N = 3SE +/- 0.33, N = 313981179MIN: 229 / MAX: 11779MIN: 178 / MAX: 10473

Embree

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

OpenBenchmarking.orgFrames Per Second, More Is BetterEmbree 4.1Binary: Pathtracer ISPC - Model: Asian DragonAVX512 OnAVX512 Off306090120150SE +/- 0.09, N = 8SE +/- 0.11, N = 7157.65132.95MIN: 155.33 / MAX: 162.92MIN: 130.4 / MAX: 138.16

OpenBenchmarking.orgFrames Per Second, More Is BetterEmbree 4.1Binary: Pathtracer ISPC - Model: Asian Dragon ObjAVX512 OnAVX512 Off306090120150SE +/- 0.16, N = 4SE +/- 0.08, N = 4134.84115.27MIN: 132.49 / MAX: 139MIN: 113.48 / MAX: 119.15

oneDNN

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

OpenBenchmarking.orgms, Fewer Is BetteroneDNN 3.1Harness: Recurrent Neural Network Training - Data Type: bf16bf16bf16 - Engine: CPUAVX512 OnAVX512 Off30060090012001500SE +/- 12.60, N = 4SE +/- 1.80, N = 31174.751317.57MIN: 1143.88MIN: 1299.381. (CXX) g++ options: -O3 -march=native -fopenmp -msse4.1 -fPIC -pie -ldl -lpthread

Embree

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

OpenBenchmarking.orgFrames Per Second, More Is BetterEmbree 4.1Binary: Pathtracer ISPC - Model: CrownAVX512 OnAVX512 Off306090120150SE +/- 0.09, N = 7SE +/- 0.11, N = 7125.54112.23MIN: 122.35 / MAX: 131.95MIN: 109.49 / MAX: 117.02

OpenVINO

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

OpenBenchmarking.orgms, Fewer Is BetterOpenVINO 2022.3Model: Age Gender Recognition Retail 0013 FP16-INT8 - Device: CPUAVX512 OnAVX512 Off0.3960.7921.1881.5841.98SE +/- 0.00, N = 3SE +/- 0.00, N = 31.581.76MIN: 0.55 / MAX: 17.78MIN: 0.64 / MAX: 19.61. (CXX) g++ options: -isystem -fsigned-char -ffunction-sections -fdata-sections -msse4.1 -msse4.2 -O3 -fno-strict-overflow -fwrapv -fPIC -fvisibility=hidden -Os -std=c++11 -MD -MT -MF

Neural Magic DeepSparse

This is a benchmark of Neural Magic's DeepSparse using its built-in deepsparse.benchmark utility and various models from their SparseZoo (https://sparsezoo.neuralmagic.com/). Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgitems/sec, More Is BetterNeural Magic DeepSparse 1.5Model: CV Classification, ResNet-50 ImageNet - Scenario: Asynchronous Multi-StreamAVX512 OnAVX512 Off2004006008001000SE +/- 0.42, N = 3SE +/- 0.45, N = 3970.06870.95

OpenBenchmarking.orgms/batch, Fewer Is BetterNeural Magic DeepSparse 1.5Model: CV Classification, ResNet-50 ImageNet - Scenario: Asynchronous Multi-StreamAVX512 OnAVX512 Off1632486480SE +/- 0.03, N = 3SE +/- 0.04, N = 365.8973.35

OpenVINO

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

OpenBenchmarking.orgFPS, More Is BetterOpenVINO 2022.3Model: Age Gender Recognition Retail 0013 FP16-INT8 - Device: CPUAVX512 OnAVX512 Off16K32K48K64K80KSE +/- 95.74, N = 3SE +/- 20.10, N = 373970.1266895.491. (CXX) g++ options: -isystem -fsigned-char -ffunction-sections -fdata-sections -msse4.1 -msse4.2 -O3 -fno-strict-overflow -fwrapv -fPIC -fvisibility=hidden -Os -std=c++11 -MD -MT -MF

libxsmm

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

OpenBenchmarking.orgGFLOPS/s, More Is Betterlibxsmm 2-1.17-3645M N K: 128AVX512 OnAVX512 Off6001200180024003000SE +/- 12.20, N = 3SE +/- 2.70, N = 32690.72573.31. (CXX) g++ options: -dynamic -Bstatic -static-libgcc -lgomp -lm -lrt -ldl -lquadmath -lstdc++ -pthread -fPIC -std=c++14 -O2 -fopenmp-simd -funroll-loops -ftree-vectorize -fdata-sections -ffunction-sections -fvisibility=hidden -msse4.2

CPU Temperature Monitor

OpenBenchmarking.orgCelsiusCPU Temperature MonitorPhoronix Test Suite System MonitoringAVX512 OffAVX512 On1530456075Min: 20.75 / Avg: 44.22 / Max: 76.13Min: 23.25 / Avg: 51.4 / Max: 74.25

CPU Power Consumption Monitor

OpenBenchmarking.orgWattsCPU Power Consumption MonitorPhoronix Test Suite System MonitoringAVX512 OffAVX512 On70140210280350Min: 10.15 / Avg: 179.15 / Max: 378.14Min: 10.25 / Avg: 231.36 / Max: 398.39

CPU Peak Freq (Highest CPU Core Frequency) Monitor

OpenBenchmarking.orgMegahertzCPU Peak Freq (Highest CPU Core Frequency) MonitorPhoronix Test Suite System MonitoringAVX512 OnAVX512 Off6001200180024003000Min: 2250 / Avg: 2918.06 / Max: 3532Min: 2203 / Avg: 2979.69 / Max: 3559

OpenVINO

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

OpenBenchmarking.orgFPS, More Is BetterOpenVINO 2022.3Model: Vehicle Detection FP16-INT8 - Device: CPUAVX512 OnAVX512 Off12002400360048006000SE +/- 89.26, N = 15SE +/- 2.12, N = 35690.343954.901. (CXX) g++ options: -isystem -fsigned-char -ffunction-sections -fdata-sections -msse4.1 -msse4.2 -O3 -fno-strict-overflow -fwrapv -fPIC -fvisibility=hidden -Os -std=c++11 -MD -MT -MF

OpenBenchmarking.orgFPS, More Is BetterOpenVINO 2022.3Model: Vehicle Detection FP16 - Device: CPUAVX512 OnAVX512 Off30060090012001500SE +/- 22.93, N = 15SE +/- 15.59, N = 141430.451190.911. (CXX) g++ options: -isystem -fsigned-char -ffunction-sections -fdata-sections -msse4.1 -msse4.2 -O3 -fno-strict-overflow -fwrapv -fPIC -fvisibility=hidden -Os -std=c++11 -MD -MT -MF

Neural Magic DeepSparse

MinAvgMaxAVX512 Off38.152.965.8AVX512 On38.653.166.5OpenBenchmarking.orgCelsius, Fewer Is BetterNeural Magic DeepSparse 1.5CPU Temperature Monitor20406080100

MinAvgMaxAVX512 Off21.0228.6329.0AVX512 On10.5234.1342.4OpenBenchmarking.orgWatts, Fewer Is BetterNeural Magic DeepSparse 1.5CPU Power Consumption Monitor80160240320400

MinAvgMaxAVX512 Off225030233152AVX512 On225030023416OpenBenchmarking.orgMegahertz, More Is BetterNeural Magic DeepSparse 1.5CPU Peak Freq (Highest CPU Core Frequency) Monitor8001600240032004000

OpenBenchmarking.orgms/batch, Fewer Is BetterNeural Magic DeepSparse 1.5Model: NLP Question Answering, BERT base uncased SQuaD 12layer Pruned90 - Scenario: Asynchronous Multi-StreamAVX512 OnAVX512 Off60120180240300SE +/- 6.02, N = 15SE +/- 0.24, N = 3259.65298.06

OpenBenchmarking.orgitems/sec, More Is BetterNeural Magic DeepSparse 1.5Model: NLP Question Answering, BERT base uncased SQuaD 12layer Pruned90 - Scenario: Asynchronous Multi-StreamAVX512 OnAVX512 Off50100150200250SE +/- 7.49, N = 15SE +/- 0.14, N = 3247.97213.64

TensorFlow

MinAvgMaxAVX512 Off29.335.347.1AVX512 On30.840.349.9OpenBenchmarking.orgCelsius, Fewer Is BetterTensorFlow 2.12CPU Temperature Monitor1428425670

MinAvgMaxAVX512 Off20.2123.6149.7AVX512 On20.3158.9208.4OpenBenchmarking.orgWatts, Fewer Is BetterTensorFlow 2.12CPU Power Consumption Monitor60120180240300

MinAvgMaxAVX512 Off225030643197AVX512 On225029923472OpenBenchmarking.orgMegahertz, More Is BetterTensorFlow 2.12CPU Peak Freq (Highest CPU Core Frequency) Monitor8001600240032004000

OpenBenchmarking.orgimages/sec Per Watt, More Is BetterTensorFlow 2.12Device: CPU - Batch Size: 32 - Model: GoogLeNetAVX512 OnAVX512 Off0.25610.51220.76831.02441.28051.1380.360

OpenBenchmarking.orgimages/sec, More Is BetterTensorFlow 2.12Device: CPU - Batch Size: 32 - Model: GoogLeNetAVX512 OnAVX512 Off4080120160200SE +/- 3.09, N = 15SE +/- 0.10, N = 3180.7744.46

MinAvgMaxAVX512 Off29.135.747.9AVX512 On33.038.545.8OpenBenchmarking.orgCelsius, Fewer Is BetterTensorFlow 2.12CPU Temperature Monitor1428425670

MinAvgMaxAVX512 Off20.1118.4140.5AVX512 On19.8135.4179.1OpenBenchmarking.orgWatts, Fewer Is BetterTensorFlow 2.12CPU Power Consumption Monitor50100150200250

MinAvgMaxAVX512 Off225030323208AVX512 On225029773320OpenBenchmarking.orgMegahertz, More Is BetterTensorFlow 2.12CPU Peak Freq (Highest CPU Core Frequency) Monitor8001600240032004000

OpenBenchmarking.orgimages/sec Per Watt, More Is BetterTensorFlow 2.12Device: CPU - Batch Size: 16 - Model: GoogLeNetAVX512 OnAVX512 Off0.17420.34840.52260.69680.8710.7740.335

OpenBenchmarking.orgimages/sec, More Is BetterTensorFlow 2.12Device: CPU - Batch Size: 16 - Model: GoogLeNetAVX512 OnAVX512 Off20406080100SE +/- 1.96, N = 15SE +/- 0.17, N = 3104.7739.64

Cpuminer-Opt

MinAvgMaxAVX512 Off33.940.944.6AVX512 On34.942.247.0OpenBenchmarking.orgCelsius, Fewer Is BetterCpuminer-Opt 3.20.3CPU Temperature Monitor1428425670

MinAvgMaxAVX512 Off20.4160.1173.0AVX512 On19.9167.1199.7OpenBenchmarking.orgWatts, Fewer Is BetterCpuminer-Opt 3.20.3CPU Power Consumption Monitor50100150200250

MinAvgMaxAVX512 Off225030463099AVX512 On225030213097OpenBenchmarking.orgMegahertz, More Is BetterCpuminer-Opt 3.20.3CPU Peak Freq (Highest CPU Core Frequency) Monitor8001600240032004000

OpenBenchmarking.orgkH/s Per Watt, More Is BetterCpuminer-Opt 3.20.3Algorithm: Myriad-GroestlAVX512 OnAVX512 Off122436486051.6544.67

OpenBenchmarking.orgkH/s, More Is BetterCpuminer-Opt 3.20.3Algorithm: Myriad-GroestlAVX512 OnAVX512 Off2K4K6K8K10KSE +/- 340.56, N = 15SE +/- 21.55, N = 38628.767149.951. (CXX) g++ options: -O2 -lcurl -lz -lpthread -lssl -lcrypto -lgmp

95 Results Shown

TensorFlow:
  CPU - 512 - GoogLeNet
  CPU - 64 - AlexNet
  CPU - 32 - AlexNet
  CPU - 256 - ResNet-50
  CPU - 64 - GoogLeNet
  CPU - 512 - ResNet-50
  CPU - 64 - ResNet-50
  CPU - 16 - AlexNet
  CPU - 32 - ResNet-50
  CPU - 16 - ResNet-50
OpenVINO:
  Weld Porosity Detection FP16 - CPU:
    ms
    FPS
  Face Detection FP16 - CPU:
    FPS
    ms
  Machine Translation EN To DE FP16 - CPU:
    FPS
    ms
  Weld Porosity Detection FP16-INT8 - CPU:
    ms
    FPS
  Face Detection FP16-INT8 - CPU:
    FPS
    ms
  Person Vehicle Bike Detection FP16 - CPU:
    ms
    FPS
TensorFlow:
  CPU - 512 - AlexNet
  CPU - 256 - AlexNet
  CPU - 256 - GoogLeNet
Cpuminer-Opt
OpenVINO
Neural Magic DeepSparse:
  NLP Sentiment Analysis, 80% Pruned Quantized BERT Base Uncased - Asynchronous Multi-Stream:
    items/sec
    ms/batch
  CV Segmentation, 90% Pruned YOLACT Pruned - Asynchronous Multi-Stream:
    items/sec
    ms/batch
OpenVINO:
  Person Detection FP32 - CPU
  Person Detection FP16 - CPU
  Person Detection FP32 - CPU
  Person Detection FP16 - CPU
  Age Gender Recognition Retail 0013 FP16 - CPU
OSPRay
Cpuminer-Opt
OSPRay
Cpuminer-Opt:
  x25x
  Blake-2 S
  scrypt
OpenVINO
OSPRay
libxsmm
Cpuminer-Opt
miniBUDE:
  OpenMP - BM2:
    GFInst/s
    Billion Interactions/s
  OpenMP - BM1:
    Billion Interactions/s
    GFInst/s
Cpuminer-Opt
Neural Magic DeepSparse:
  NLP Text Classification, BERT base uncased SST2 - Asynchronous Multi-Stream:
    items/sec
    ms/batch
OpenVINO
Neural Magic DeepSparse:
  NLP Document Classification, oBERT base uncased on IMDB - Asynchronous Multi-Stream
  NLP Text Classification, DistilBERT mnli - Asynchronous Multi-Stream
  NLP Text Classification, DistilBERT mnli - Asynchronous Multi-Stream
  NLP Token Classification, BERT base uncased conll2003 - Asynchronous Multi-Stream
  NLP Token Classification, BERT base uncased conll2003 - Asynchronous Multi-Stream
  NLP Document Classification, oBERT base uncased on IMDB - Asynchronous Multi-Stream
OpenVKL
Embree:
  Pathtracer ISPC - Asian Dragon
  Pathtracer ISPC - Asian Dragon Obj
oneDNN
Embree
OpenVINO
Neural Magic DeepSparse:
  CV Classification, ResNet-50 ImageNet - Asynchronous Multi-Stream:
    items/sec
    ms/batch
OpenVINO
libxsmm
CPU Temperature Monitor:
  Phoronix Test Suite System Monitoring:
    Celsius
    Watts
    Megahertz
OpenVINO:
  Vehicle Detection FP16-INT8 - CPU
  Vehicle Detection FP16 - CPU
Neural Magic DeepSparse:
  CPU Temp Monitor
  CPU Power Consumption Monitor
  CPU Peak Freq (Highest CPU Core Frequency) Monitor
Neural Magic DeepSparse:
  NLP Question Answering, BERT base uncased SQuaD 12layer Pruned90 - Asynchronous Multi-Stream:
    ms/batch
    items/sec
TensorFlow:
  CPU Temp Monitor
  CPU Power Consumption Monitor
  CPU Peak Freq (Highest CPU Core Frequency) Monitor
  CPU - 32 - GoogLeNet
TensorFlow
TensorFlow:
  CPU Temp Monitor
  CPU Power Consumption Monitor
  CPU Peak Freq (Highest CPU Core Frequency) Monitor
  CPU - 16 - GoogLeNet
TensorFlow
Cpuminer-Opt:
  CPU Temp Monitor
  CPU Power Consumption Monitor
  CPU Peak Freq (Highest CPU Core Frequency) Monitor
  Myriad-Groestl
Cpuminer-Opt