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
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  9 Hours, 40 Minutes
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AVX512 On

Kernel Notes: Transparent Huge Pages: madvise
Compiler Notes: --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
Processor Notes: Scaling Governor: acpi-cpufreq performance (Boost: Enabled) - CPU Microcode: 0xaa0010b
Python Notes: Python 3.10.6
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

AVX512 Off

Processor: AMD EPYC 9754 128-Core @ 2.25GHz (128 Cores / 256 Threads), Motherboard: AMD Titanite_4G (RTI1007B BIOS), Chipset: AMD Device 14a4, Memory: 768GB, Disk: 2 x 1920GB SAMSUNG MZWLJ1T9HBJR-00007, Graphics: ASPEED, Network: Broadcom NetXtreme BCM5720 PCIe

OS: Ubuntu 22.04, Kernel: 5.19.0-41-generic (x86_64), Desktop: GNOME Shell 42.5, Display Server: X Server 1.21.1.4, Vulkan: 1.3.224, Compiler: GCC 11.3.0, File-System: ext4, Screen Resolution: 1024x768

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 OffAVX512 On90180270360450SE +/- 0.05, N = 3SE +/- 5.30, N = 1246.92417.25
OpenBenchmarking.orgimages/sec Per Watt, More Is BetterTensorFlow 2.12Device: CPU - Batch Size: 512 - Model: GoogLeNetAVX512 OffAVX512 On0.39740.79481.19221.58961.9870.3691.766
OpenBenchmarking.orgMegahertz, More Is BetterTensorFlow 2.12CPU Peak Freq (Highest CPU Core Frequency) MonitorAVX512 OnAVX512 Off6001200180024003000Min: 2250 / Avg: 2973.8 / Max: 3207Min: 2250 / Avg: 3083.42 / Max: 3336
OpenBenchmarking.orgWatts, Fewer Is BetterTensorFlow 2.12CPU Power Consumption MonitorAVX512 OnAVX512 Off50100150200250Min: 10.84 / Avg: 236.33 / Max: 283.4Min: 19.97 / Avg: 127.28 / Max: 218.041. AVX512 On: Approximate power consumption of 32654 Joules per run.2. AVX512 Off: Approximate power consumption of 152954 Joules per run.
OpenBenchmarking.orgCelsius, Fewer Is BetterTensorFlow 2.12CPU Temperature MonitorAVX512 OnAVX512 Off1224364860Min: 34.63 / Avg: 50.93 / Max: 58.38Min: 30.13 / Avg: 36.83 / Max: 51.13

OpenBenchmarking.orgimages/sec, More Is BetterTensorFlow 2.12Device: CPU - Batch Size: 64 - Model: AlexNetAVX512 OffAVX512 On2004006008001000SE +/- 0.08, N = 3SE +/- 1.99, N = 597.59857.55
OpenBenchmarking.orgimages/sec Per Watt, More Is BetterTensorFlow 2.12Device: CPU - Batch Size: 64 - Model: AlexNetAVX512 OffAVX512 On1.33612.67224.00835.34446.68050.7785.938
MinAvgMaxAVX512 On225027513111AVX512 Off225030573377OpenBenchmarking.orgMegahertz, More Is BetterTensorFlow 2.12CPU Peak Freq (Highest CPU Core Frequency) Monitor8001600240032004000
MinAvgMaxAVX512 On20.2144.4224.5AVX512 Off19.9125.4141.0OpenBenchmarking.orgWatts, Fewer Is BetterTensorFlow 2.12CPU Power Consumption Monitor601201802403001. AVX512 On: Approximate power consumption of 2079 Joules per run.2. AVX512 Off: Approximate power consumption of 9780 Joules per run.
MinAvgMaxAVX512 On30.638.345.5AVX512 Off30.436.546.4OpenBenchmarking.orgCelsius, Fewer Is BetterTensorFlow 2.12CPU Temperature Monitor1428425670

OpenBenchmarking.orgimages/sec, More Is BetterTensorFlow 2.12Device: CPU - Batch Size: 32 - Model: AlexNetAVX512 OffAVX512 On120240360480600SE +/- 0.16, N = 3SE +/- 2.06, N = 684.96562.48
OpenBenchmarking.orgimages/sec Per Watt, More Is BetterTensorFlow 2.12Device: CPU - Batch Size: 32 - Model: AlexNetAVX512 OffAVX512 On0.98461.96922.95383.93844.9230.6914.376
MinAvgMaxAVX512 On225028363101AVX512 Off225030393146OpenBenchmarking.orgMegahertz, More Is BetterTensorFlow 2.12CPU Peak Freq (Highest CPU Core Frequency) Monitor8001600240032004000
MinAvgMaxAVX512 On20.3128.6210.9AVX512 Off20.5123.0139.4OpenBenchmarking.orgWatts, Fewer Is BetterTensorFlow 2.12CPU Power Consumption Monitor601201802403001. AVX512 On: Approximate power consumption of 1585 Joules per run.2. AVX512 Off: Approximate power consumption of 5861 Joules per run.
MinAvgMaxAVX512 On32.037.845.3AVX512 Off30.537.145.6OpenBenchmarking.orgCelsius, Fewer Is BetterTensorFlow 2.12CPU Temperature Monitor1224364860

OpenBenchmarking.orgimages/sec, More Is BetterTensorFlow 2.12Device: CPU - Batch Size: 256 - Model: ResNet-50AVX512 OffAVX512 On306090120150SE +/- 0.02, N = 3SE +/- 1.01, N = 1219.89119.32
OpenBenchmarking.orgimages/sec Per Watt, More Is BetterTensorFlow 2.12Device: CPU - Batch Size: 256 - Model: ResNet-50AVX512 OffAVX512 On0.12080.24160.36240.48320.6040.1430.537
OpenBenchmarking.orgMegahertz, More Is BetterTensorFlow 2.12CPU Peak Freq (Highest CPU Core Frequency) MonitorAVX512 OnAVX512 Off6001200180024003000Min: 2250 / Avg: 2956.33 / Max: 3308Min: 2250 / Avg: 3085.27 / Max: 3559
OpenBenchmarking.orgWatts, Fewer Is BetterTensorFlow 2.12CPU Power Consumption MonitorAVX512 OnAVX512 Off50100150200250Min: 20.59 / Avg: 222.08 / Max: 272.77Min: 20.06 / Avg: 139.18 / Max: 198.981. AVX512 On: Approximate power consumption of 52984 Joules per run.2. AVX512 Off: Approximate power consumption of 197083 Joules per run.
OpenBenchmarking.orgCelsius, Fewer Is BetterTensorFlow 2.12CPU Temperature MonitorAVX512 OnAVX512 Off1122334455Min: 37.63 / Avg: 48.39 / Max: 57.63Min: 29 / Avg: 38.33 / Max: 53.13

OpenBenchmarking.orgimages/sec, More Is BetterTensorFlow 2.12Device: CPU - Batch Size: 64 - Model: GoogLeNetAVX512 OffAVX512 On60120180240300SE +/- 0.18, N = 3SE +/- 2.62, N = 1546.28277.24
OpenBenchmarking.orgimages/sec Per Watt, More Is BetterTensorFlow 2.12Device: CPU - Batch Size: 64 - Model: GoogLeNetAVX512 OffAVX512 On0.33210.66420.99631.32841.66050.3691.476
MinAvgMaxAVX512 On225029953532AVX512 Off225030753309OpenBenchmarking.orgMegahertz, More Is BetterTensorFlow 2.12CPU Peak Freq (Highest CPU Core Frequency) Monitor10002000300040005000
MinAvgMaxAVX512 On20.1187.9236.9AVX512 Off19.9125.3152.5OpenBenchmarking.orgWatts, Fewer Is BetterTensorFlow 2.12CPU Power Consumption Monitor601201802403001. AVX512 On: Approximate power consumption of 6163 Joules per run.2. AVX512 Off: Approximate power consumption of 19961 Joules per run.
MinAvgMaxAVX512 On32.544.352.8AVX512 Off29.935.949.0OpenBenchmarking.orgCelsius, Fewer Is BetterTensorFlow 2.12CPU Temperature Monitor1530456075

OpenBenchmarking.orgimages/sec, More Is BetterTensorFlow 2.12Device: CPU - Batch Size: 512 - Model: ResNet-50AVX512 OffAVX512 On306090120150SE +/- 0.04, N = 3SE +/- 0.99, N = 320.78122.81
OpenBenchmarking.orgimages/sec Per Watt, More Is BetterTensorFlow 2.12Device: CPU - Batch Size: 512 - Model: ResNet-50AVX512 OffAVX512 On0.1220.2440.3660.4880.610.1480.542
OpenBenchmarking.orgMegahertz, More Is BetterTensorFlow 2.12CPU Peak Freq (Highest CPU Core Frequency) MonitorAVX512 OnAVX512 Off6001200180024003000Min: 2250 / Avg: 2958.12 / Max: 3370Min: 2243 / Avg: 3085.93 / Max: 3295
OpenBenchmarking.orgWatts, Fewer Is BetterTensorFlow 2.12CPU Power Consumption MonitorAVX512 OnAVX512 Off50100150200250Min: 20.5 / Avg: 226.78 / Max: 289.01Min: 20.22 / Avg: 140.06 / Max: 209.421. AVX512 On: Approximate power consumption of 102427 Joules per run.2. AVX512 Off: Approximate power consumption of 378535 Joules per run.
OpenBenchmarking.orgCelsius, Fewer Is BetterTensorFlow 2.12CPU Temperature MonitorAVX512 OnAVX512 Off1122334455Min: 35.38 / Avg: 48.79 / Max: 57.5Min: 29.38 / Avg: 39.11 / Max: 54.13

OpenBenchmarking.orgimages/sec, More Is BetterTensorFlow 2.12Device: CPU - Batch Size: 64 - Model: ResNet-50AVX512 OffAVX512 On20406080100SE +/- 0.03, N = 3SE +/- 0.06, N = 318.4596.63
OpenBenchmarking.orgimages/sec Per Watt, More Is BetterTensorFlow 2.12Device: CPU - Batch Size: 64 - Model: ResNet-50AVX512 OffAVX512 On0.10870.21740.32610.43480.54350.1310.483
MinAvgMaxAVX512 On225030213283AVX512 Off225030903249OpenBenchmarking.orgMegahertz, More Is BetterTensorFlow 2.12CPU Peak Freq (Highest CPU Core Frequency) Monitor8001600240032004000
MinAvgMaxAVX512 On20.6200.2230.6AVX512 Off20.1140.4179.7OpenBenchmarking.orgWatts, Fewer Is BetterTensorFlow 2.12CPU Power Consumption Monitor601201802403001. AVX512 On: Approximate power consumption of 16285 Joules per run.2. AVX512 Off: Approximate power consumption of 54525 Joules per run.
MinAvgMaxAVX512 On33.545.353.3AVX512 Off28.838.151.6OpenBenchmarking.orgCelsius, Fewer Is BetterTensorFlow 2.12CPU Temperature Monitor1530456075

OpenBenchmarking.orgimages/sec, More Is BetterTensorFlow 2.12Device: CPU - Batch Size: 16 - Model: AlexNetAVX512 OffAVX512 On70140210280350SE +/- 0.29, N = 3SE +/- 0.70, N = 670.10342.88
OpenBenchmarking.orgimages/sec Per Watt, More Is BetterTensorFlow 2.12Device: CPU - Batch Size: 16 - Model: AlexNetAVX512 OffAVX512 On0.66741.33482.00222.66963.3370.5762.966
MinAvgMaxAVX512 On225028013254AVX512 Off225029923136OpenBenchmarking.orgMegahertz, More Is BetterTensorFlow 2.12CPU Peak Freq (Highest CPU Core Frequency) Monitor8001600240032004000
MinAvgMaxAVX512 Off20.6121.7145.6AVX512 On10.4115.6199.6OpenBenchmarking.orgWatts, Fewer Is BetterTensorFlow 2.12CPU Power Consumption Monitor501001502002501. AVX512 Off: Approximate power consumption of 3812 Joules per run.2. AVX512 On: Approximate power consumption of 1291 Joules per run.
MinAvgMaxAVX512 On34.941.149.4AVX512 Off33.940.349.4OpenBenchmarking.orgCelsius, Fewer Is BetterTensorFlow 2.12CPU Temperature Monitor1428425670

OpenBenchmarking.orgimages/sec, More Is BetterTensorFlow 2.12Device: CPU - Batch Size: 32 - Model: ResNet-50AVX512 OffAVX512 On1632486480SE +/- 0.04, N = 3SE +/- 0.23, N = 317.4871.62
OpenBenchmarking.orgimages/sec Per Watt, More Is BetterTensorFlow 2.12Device: CPU - Batch Size: 32 - Model: ResNet-50AVX512 OffAVX512 On0.09160.18320.27480.36640.4580.1240.407
MinAvgMaxAVX512 On225030663438AVX512 Off225030843221OpenBenchmarking.orgMegahertz, More Is BetterTensorFlow 2.12CPU Peak Freq (Highest CPU Core Frequency) Monitor8001600240032004000
MinAvgMaxAVX512 On20.0176.0204.8AVX512 Off20.1141.1172.9OpenBenchmarking.orgWatts, Fewer Is BetterTensorFlow 2.12CPU Power Consumption Monitor501001502002501. AVX512 On: Approximate power consumption of 10151 Joules per run.2. AVX512 Off: Approximate power consumption of 29590 Joules per run.
MinAvgMaxAVX512 On31.341.848.6AVX512 Off28.337.551.6OpenBenchmarking.orgCelsius, Fewer Is BetterTensorFlow 2.12CPU Temperature Monitor1530456075

OpenBenchmarking.orgimages/sec, More Is BetterTensorFlow 2.12Device: CPU - Batch Size: 16 - Model: ResNet-50AVX512 OffAVX512 On1020304050SE +/- 0.05, N = 3SE +/- 0.03, N = 315.9143.11
OpenBenchmarking.orgimages/sec Per Watt, More Is BetterTensorFlow 2.12Device: CPU - Batch Size: 16 - Model: ResNet-50AVX512 OffAVX512 On0.06620.13240.19860.26480.3310.1130.294
MinAvgMaxAVX512 On225030413348AVX512 Off225030753217OpenBenchmarking.orgMegahertz, More Is BetterTensorFlow 2.12CPU Peak Freq (Highest CPU Core Frequency) Monitor8001600240032004000
MinAvgMaxAVX512 On20.1146.6171.4AVX512 Off20.2140.3151.8OpenBenchmarking.orgWatts, Fewer Is BetterTensorFlow 2.12CPU Power Consumption Monitor501001502002501. AVX512 On: Approximate power consumption of 7281 Joules per run.2. AVX512 Off: Approximate power consumption of 16692 Joules per run.
MinAvgMaxAVX512 On30.438.144.6AVX512 Off28.837.248.8OpenBenchmarking.orgCelsius, Fewer Is BetterTensorFlow 2.12CPU 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 2022.3Model: Weld Porosity Detection FP16 - Device: CPUAVX512 OffAVX512 On612182430SE +/- 0.01, N = 3SE +/- 0.00, N = 325.0610.52MIN: 13.08 / MAX: 57.02MIN: 5.11 / MAX: 34.371. (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
MinAvgMaxAVX512 Off225023733112AVX512 On225027183095OpenBenchmarking.orgMegahertz, More Is BetterOpenVINO 2022.3CPU Peak Freq (Highest CPU Core Frequency) Monitor8001600240032004000
MinAvgMaxAVX512 On21.2327.7354.4AVX512 Off21.3288.2311.1OpenBenchmarking.orgWatts, Fewer Is BetterOpenVINO 2022.3CPU Power Consumption Monitor1002003004005001. AVX512 On: Approximate power consumption of 20970 Joules per run.2. AVX512 Off: Approximate power consumption of 18446 Joules per run.
MinAvgMaxAVX512 On36.864.269.9AVX512 Off41.961.164.3OpenBenchmarking.orgCelsius, Fewer Is BetterOpenVINO 2022.3CPU Temperature Monitor20406080100

OpenBenchmarking.orgFPS, More Is BetterOpenVINO 2022.3Model: Weld Porosity Detection FP16 - Device: CPUAVX512 OffAVX512 On13002600390052006500SE +/- 0.56, N = 3SE +/- 1.32, N = 32551.706073.221. (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: Face Detection FP16 - Device: CPUAVX512 OffAVX512 On1428425670SE +/- 0.36, N = 3SE +/- 0.06, N = 326.1860.731. (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 OffAVX512 On5001000150020002500SE +/- 26.84, N = 3SE +/- 0.42, N = 32423.391048.37MIN: 1130.42 / MAX: 2937.22MIN: 508.1 / MAX: 1159.41. (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
MinAvgMaxAVX512 Off225024913096AVX512 On225027083101OpenBenchmarking.orgMegahertz, More Is BetterOpenVINO 2022.3CPU Peak Freq (Highest CPU Core Frequency) Monitor8001600240032004000
MinAvgMaxAVX512 On21.1315.2358.6AVX512 Off21.1286.8325.8OpenBenchmarking.orgWatts, Fewer Is BetterOpenVINO 2022.3CPU Power Consumption Monitor1002003004005001. AVX512 On: Approximate power consumption of 21962 Joules per run.2. AVX512 Off: Approximate power consumption of 20458 Joules per run.
MinAvgMaxAVX512 On38.663.170.0AVX512 Off39.859.368.1OpenBenchmarking.orgCelsius, Fewer Is BetterOpenVINO 2022.3CPU Temperature Monitor20406080100

OpenBenchmarking.orgFPS, More Is BetterOpenVINO 2022.3Model: Machine Translation EN To DE FP16 - Device: CPUAVX512 OffAVX512 On130260390520650SE +/- 3.15, N = 15SE +/- 7.10, N = 15251.97580.401. (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 OffAVX512 On60120180240300SE +/- 2.83, N = 15SE +/- 1.22, N = 15254.01110.35MIN: 116.71 / MAX: 398.88MIN: 49.7 / MAX: 183.591. (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
MinAvgMaxAVX512 Off221425373101AVX512 On225026613111OpenBenchmarking.orgMegahertz, More Is BetterOpenVINO 2022.3CPU Peak Freq (Highest CPU Core Frequency) Monitor8001600240032004000
MinAvgMaxAVX512 On10.9295.1345.9AVX512 Off21.2292.9331.3OpenBenchmarking.orgWatts, Fewer Is BetterOpenVINO 2022.3CPU Power Consumption Monitor1002003004005001. AVX512 On: Approximate power consumption of 19339 Joules per run.2. AVX512 Off: Approximate power consumption of 19276 Joules per run.
MinAvgMaxAVX512 On40.557.365.8AVX512 Off41.056.764.6OpenBenchmarking.orgCelsius, Fewer Is BetterOpenVINO 2022.3CPU Temperature Monitor20406080100

OpenBenchmarking.orgms, Fewer Is BetterOpenVINO 2022.3Model: Weld Porosity Detection FP16-INT8 - Device: CPUAVX512 OffAVX512 On510152025SE +/- 0.01, N = 3SE +/- 0.00, N = 322.4710.82MIN: 10.87 / MAX: 43.5MIN: 5 / MAX: 31.441. (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
MinAvgMaxAVX512 On225026193137AVX512 Off225026713102OpenBenchmarking.orgMegahertz, More Is BetterOpenVINO 2022.3CPU Peak Freq (Highest CPU Core Frequency) Monitor8001600240032004000
MinAvgMaxAVX512 Off21.1336.6365.0AVX512 On21.1306.8333.5OpenBenchmarking.orgWatts, Fewer Is BetterOpenVINO 2022.3CPU Power Consumption Monitor1002003004005001. AVX512 Off: Approximate power consumption of 21653 Joules per run.2. AVX512 On: Approximate power consumption of 19739 Joules per run.
MinAvgMaxAVX512 Off36.867.473.3AVX512 On36.861.366.1OpenBenchmarking.orgCelsius, Fewer Is BetterOpenVINO 2022.3CPU Temperature Monitor20406080100

OpenBenchmarking.orgFPS, More Is BetterOpenVINO 2022.3Model: Weld Porosity Detection FP16-INT8 - Device: CPUAVX512 OffAVX512 On3K6K9K12K15KSE +/- 1.65, N = 3SE +/- 1.17, N = 35692.9911818.331. (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 OffAVX512 On306090120150SE +/- 0.03, N = 3SE +/- 0.02, N = 357.95118.001. (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 OffAVX512 On2004006008001000SE +/- 0.34, N = 3SE +/- 0.07, N = 31094.52540.35MIN: 509.48 / MAX: 1179.63MIN: 257.81 / MAX: 586.561. (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
MinAvgMaxAVX512 Off225026883124AVX512 On225026963116OpenBenchmarking.orgMegahertz, More Is BetterOpenVINO 2022.3CPU Peak Freq (Highest CPU Core Frequency) Monitor8001600240032004000
MinAvgMaxAVX512 Off21.2323.5369.0AVX512 On20.5295.4336.3OpenBenchmarking.orgWatts, Fewer Is BetterOpenVINO 2022.3CPU Power Consumption Monitor1002003004005001. AVX512 Off: Approximate power consumption of 22863 Joules per run.2. AVX512 On: Approximate power consumption of 20678 Joules per run.
MinAvgMaxAVX512 Off35.865.576.1AVX512 On34.459.570.5OpenBenchmarking.orgCelsius, Fewer Is BetterOpenVINO 2022.3CPU Temperature Monitor20406080100

OpenBenchmarking.orgms, Fewer Is BetterOpenVINO 2022.3Model: Person Vehicle Bike Detection FP16 - Device: CPUAVX512 OffAVX512 On510152025SE +/- 0.14, N = 15SE +/- 0.02, N = 319.289.63MIN: 10.31 / MAX: 50.61MIN: 6.4 / MAX: 33.261. (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
MinAvgMaxAVX512 Off225024833131AVX512 On225026793096OpenBenchmarking.orgMegahertz, More Is BetterOpenVINO 2022.3CPU Peak Freq (Highest CPU Core Frequency) Monitor8001600240032004000
MinAvgMaxAVX512 On21.6308.5346.7AVX512 Off21.1293.4328.1OpenBenchmarking.orgWatts, Fewer Is BetterOpenVINO 2022.3CPU Power Consumption Monitor1002003004005001. AVX512 On: Approximate power consumption of 20465 Joules per run.2. AVX512 Off: Approximate power consumption of 19264 Joules per run.
MinAvgMaxAVX512 On40.560.666.6AVX512 Off41.057.164.8OpenBenchmarking.orgCelsius, Fewer Is BetterOpenVINO 2022.3CPU Temperature Monitor20406080100

OpenBenchmarking.orgFPS, More Is BetterOpenVINO 2022.3Model: Person Vehicle Bike Detection FP16 - Device: CPUAVX512 OffAVX512 On14002800420056007000SE +/- 26.07, N = 15SE +/- 13.51, N = 33317.346638.711. (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 OffAVX512 On400800120016002000SE +/- 0.06, N = 3SE +/- 1.53, N = 3109.881632.40
OpenBenchmarking.orgimages/sec Per Watt, More Is BetterTensorFlow 2.12Device: CPU - Batch Size: 512 - Model: AlexNetAVX512 OffAVX512 On2468100.8657.097
MinAvgMaxAVX512 On225027543095AVX512 Off220330793359OpenBenchmarking.orgMegahertz, More Is BetterTensorFlow 2.12CPU Peak Freq (Highest CPU Core Frequency) Monitor8001600240032004000
MinAvgMaxAVX512 On20.3230.0283.1AVX512 Off20.3127.0189.9OpenBenchmarking.orgWatts, Fewer Is BetterTensorFlow 2.12CPU Power Consumption Monitor701402102803501. AVX512 On: Approximate power consumption of 9354 Joules per run.2. AVX512 Off: Approximate power consumption of 65553 Joules per run.
MinAvgMaxAVX512 On33.949.855.8AVX512 Off28.836.247.4OpenBenchmarking.orgCelsius, Fewer Is BetterTensorFlow 2.12CPU Temperature Monitor1632486480

OpenBenchmarking.orgimages/sec, More Is BetterTensorFlow 2.12Device: CPU - Batch Size: 256 - Model: AlexNetAVX512 OffAVX512 On30060090012001500SE +/- 0.24, N = 3SE +/- 6.55, N = 3106.281422.36
OpenBenchmarking.orgimages/sec Per Watt, More Is BetterTensorFlow 2.12Device: CPU - Batch Size: 256 - Model: AlexNetAVX512 OffAVX512 On2468100.8396.984
MinAvgMaxAVX512 On225027423102AVX512 Off225030733166OpenBenchmarking.orgMegahertz, More Is BetterTensorFlow 2.12CPU Peak Freq (Highest CPU Core Frequency) Monitor8001600240032004000
MinAvgMaxAVX512 On20.1203.7257.0AVX512 Off20.0126.7155.1OpenBenchmarking.orgWatts, Fewer Is BetterTensorFlow 2.12CPU Power Consumption Monitor701402102803501. AVX512 On: Approximate power consumption of 5160 Joules per run.2. AVX512 Off: Approximate power consumption of 34203 Joules per run.
MinAvgMaxAVX512 On30.944.852.3AVX512 Off28.836.047.9OpenBenchmarking.orgCelsius, Fewer Is BetterTensorFlow 2.12CPU Temperature Monitor1530456075

OpenBenchmarking.orgimages/sec, More Is BetterTensorFlow 2.12Device: CPU - Batch Size: 256 - Model: GoogLeNetAVX512 OffAVX512 On110220330440550SE +/- 0.06, N = 3SE +/- 4.92, N = 346.17501.67
OpenBenchmarking.orgimages/sec Per Watt, More Is BetterTensorFlow 2.12Device: CPU - Batch Size: 256 - Model: GoogLeNetAVX512 OffAVX512 On0.46760.93521.40281.87042.3380.3622.078
MinAvgMaxAVX512 On225029163157AVX512 Off225030863417OpenBenchmarking.orgMegahertz, More Is BetterTensorFlow 2.12CPU Peak Freq (Highest CPU Core Frequency) Monitor8001600240032004000
MinAvgMaxAVX512 On19.9241.5277.9AVX512 Off20.1127.4214.3OpenBenchmarking.orgWatts, Fewer Is BetterTensorFlow 2.12CPU Power Consumption Monitor701402102803501. AVX512 On: Approximate power consumption of 15453 Joules per run.2. AVX512 Off: Approximate power consumption of 78367 Joules per run.
MinAvgMaxAVX512 On34.450.958.9AVX512 Off29.836.452.1OpenBenchmarking.orgCelsius, Fewer Is BetterTensorFlow 2.12CPU Temperature Monitor1632486480

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 OffAVX512 On140K280K420K560K700KSE +/- 141.93, N = 3SE +/- 76.38, N = 33326676606601. (CXX) g++ options: -O2 -lcurl -lz -lpthread -lssl -lcrypto -lgmp
OpenBenchmarking.orgkH/s Per Watt, More Is BetterCpuminer-Opt 3.20.3Algorithm: LBC, LBRY CreditsAVX512 OffAVX512 On4008001200160020001052.192003.50
MinAvgMaxAVX512 Off225027463096AVX512 On225028863096OpenBenchmarking.orgMegahertz, More Is BetterCpuminer-Opt 3.20.3CPU Peak Freq (Highest CPU Core Frequency) Monitor8001600240032004000
MinAvgMaxAVX512 On20.3329.8380.7AVX512 Off20.7316.2362.0OpenBenchmarking.orgWatts, Fewer Is BetterCpuminer-Opt 3.20.3CPU Power Consumption Monitor1002003004005001. AVX512 On: Approximate power consumption of 10992 Joules per run.2. AVX512 Off: Approximate power consumption of 10750 Joules per run.
MinAvgMaxAVX512 On32.063.272.8AVX512 Off30.659.571.9OpenBenchmarking.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.orgms, Fewer Is BetterOpenVINO 2022.3Model: Age Gender Recognition Retail 0013 FP16 - Device: CPUAVX512 OffAVX512 On0.42980.85961.28941.71922.149SE +/- 0.01, N = 3SE +/- 0.00, N = 31.910.99MIN: 0.67 / MAX: 19.48MIN: 0.35 / MAX: 19.471. (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
MinAvgMaxAVX512 Off225025903101AVX512 On225028923097OpenBenchmarking.orgMegahertz, More Is BetterOpenVINO 2022.3CPU Peak Freq (Highest CPU Core Frequency) Monitor8001600240032004000
MinAvgMaxAVX512 On21.2316.4347.6AVX512 Off21.0298.9332.9OpenBenchmarking.orgWatts, Fewer Is BetterOpenVINO 2022.3CPU Power Consumption Monitor1002003004005001. AVX512 On: Approximate power consumption of 20569 Joules per run.2. AVX512 Off: Approximate power consumption of 19729 Joules per run.
MinAvgMaxAVX512 On41.064.670.0AVX512 Off37.361.868.0OpenBenchmarking.orgCelsius, Fewer Is BetterOpenVINO 2022.3CPU Temperature Monitor20406080100

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 OffAVX512 On30060090012001500SE +/- 5.33, N = 3SE +/- 1.58, N = 3718.301381.57

OpenBenchmarking.orgms/batch, Fewer Is BetterNeural Magic DeepSparse 1.5Model: NLP Sentiment Analysis, 80% Pruned Quantized BERT Base Uncased - Scenario: Asynchronous Multi-StreamAVX512 OffAVX512 On20406080100SE +/- 0.67, N = 3SE +/- 0.05, N = 388.9146.26
MinAvgMaxAVX512 Off225030153127AVX512 On225030263124OpenBenchmarking.orgMegahertz, More Is BetterNeural Magic DeepSparse 1.5CPU Peak Freq (Highest CPU Core Frequency) Monitor8001600240032004000
MinAvgMaxAVX512 On21.1250.2321.3AVX512 Off21.3234.7326.7OpenBenchmarking.orgWatts, Fewer Is BetterNeural Magic DeepSparse 1.5CPU Power Consumption Monitor801602403204001. AVX512 On: Approximate power consumption of 12009 Joules per run.2. AVX512 Off: Approximate power consumption of 12985 Joules per run.
MinAvgMaxAVX512 On39.458.167.6AVX512 Off38.153.864.3OpenBenchmarking.orgCelsius, Fewer Is BetterNeural Magic DeepSparse 1.5CPU Temperature Monitor20406080100

OpenBenchmarking.orgitems/sec, More Is BetterNeural Magic DeepSparse 1.5Model: CV Segmentation, 90% Pruned YOLACT Pruned - Scenario: Asynchronous Multi-StreamAVX512 OffAVX512 On306090120150SE +/- 0.03, N = 3SE +/- 0.01, N = 369.33127.06

OpenBenchmarking.orgms/batch, Fewer Is BetterNeural Magic DeepSparse 1.5Model: CV Segmentation, 90% Pruned YOLACT Pruned - Scenario: Asynchronous Multi-StreamAVX512 OffAVX512 On2004006008001000SE +/- 0.94, N = 3SE +/- 0.16, N = 3906.94498.48
MinAvgMaxAVX512 On225030063115AVX512 Off225030483116OpenBenchmarking.orgMegahertz, More Is BetterNeural Magic DeepSparse 1.5CPU Peak Freq (Highest CPU Core Frequency) Monitor8001600240032004000
MinAvgMaxAVX512 Off21.5235.2340.9AVX512 On20.6228.3324.5OpenBenchmarking.orgWatts, Fewer Is BetterNeural Magic DeepSparse 1.5CPU Power Consumption Monitor801602403204001. AVX512 Off: Approximate power consumption of 15600 Joules per run.2. AVX512 On: Approximate power consumption of 13469 Joules per run.
MinAvgMaxAVX512 Off40.054.069.1AVX512 On38.153.166.1OpenBenchmarking.orgCelsius, Fewer Is BetterNeural Magic DeepSparse 1.5CPU 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 2022.3Model: Person Detection FP32 - Device: CPUAVX512 OffAVX512 On612182430SE +/- 0.16, N = 5SE +/- 0.18, N = 1214.9927.011. (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 OffAVX512 On612182430SE +/- 0.21, N = 3SE +/- 0.30, N = 1215.0627.081. (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 OffAVX512 On9001800270036004500SE +/- 41.79, N = 5SE +/- 14.83, N = 124170.492339.81MIN: 1759.65 / MAX: 4969.5MIN: 1045.35 / MAX: 3232.691. (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
MinAvgMaxAVX512 Off225026453103AVX512 On225029363426OpenBenchmarking.orgMegahertz, More Is BetterOpenVINO 2022.3CPU Peak Freq (Highest CPU Core Frequency) Monitor8001600240032004000
MinAvgMaxAVX512 On20.8306.2358.4AVX512 Off21.0292.7340.3OpenBenchmarking.orgWatts, Fewer Is BetterOpenVINO 2022.3CPU Power Consumption Monitor1002003004005001. AVX512 On: Approximate power consumption of 21691 Joules per run.2. AVX512 Off: Approximate power consumption of 21659 Joules per run.
MinAvgMaxAVX512 On37.660.672.9AVX512 Off36.558.072.4OpenBenchmarking.orgCelsius, Fewer Is BetterOpenVINO 2022.3CPU Temperature Monitor20406080100

OpenBenchmarking.orgms, Fewer Is BetterOpenVINO 2022.3Model: Person Detection FP16 - Device: CPUAVX512 OffAVX512 On9001800270036004500SE +/- 59.43, N = 3SE +/- 22.79, N = 124153.592334.29MIN: 1975.28 / MAX: 5152.66MIN: 1017.83 / MAX: 3101.051. (CXX) g++ options: -isystem -fsigned-char -ffunction-sections -fdata-sections -msse4.1 -msse4.2 -O3 -fno-strict-overflow -fwrapv -fPIC -fvisibility=hidden -Os -std=c++11 -MD -MT -MF
MinAvgMaxAVX512 Off225026493132AVX512 On225029313185OpenBenchmarking.orgMegahertz, More Is BetterOpenVINO 2022.3CPU Peak Freq (Highest CPU Core Frequency) Monitor8001600240032004000
MinAvgMaxAVX512 On19.8306.5359.5AVX512 Off21.3283.3329.0OpenBenchmarking.orgWatts, Fewer Is BetterOpenVINO 2022.3CPU Power Consumption Monitor1002003004005001. AVX512 On: Approximate power consumption of 21785 Joules per run.2. AVX512 Off: Approximate power consumption of 21245 Joules per run.
MinAvgMaxAVX512 On41.361.273.4AVX512 Off37.657.467.6OpenBenchmarking.orgCelsius, Fewer Is BetterOpenVINO 2022.3CPU Temperature Monitor20406080100

OpenBenchmarking.orgFPS, More Is BetterOpenVINO 2022.3Model: Age Gender Recognition Retail 0013 FP16 - Device: CPUAVX512 OffAVX512 On20K40K60K80K100KSE +/- 278.13, N = 3SE +/- 314.35, N = 362564.16110240.891. (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 OffAVX512 On714212835SE +/- 0.00, N = 3SE +/- 0.02, N = 318.0231.68
OpenBenchmarking.orgItems Per Second Per Watt, More Is BetterOSPRay 2.12Benchmark: gravity_spheres_volume/dim_512/scivis/real_timeAVX512 OffAVX512 On0.02570.05140.07710.10280.12850.0620.114
MinAvgMaxAVX512 On225028753096AVX512 Off225029253101OpenBenchmarking.orgMegahertz, More Is BetterOSPRay 2.12CPU Peak Freq (Highest CPU Core Frequency) Monitor8001600240032004000
MinAvgMaxAVX512 Off20.9292.2347.0AVX512 On20.9278.8332.5OpenBenchmarking.orgWatts, Fewer Is BetterOSPRay 2.12CPU Power Consumption Monitor1002003004005001. AVX512 Off: Approximate power consumption of 17047 Joules per run.2. AVX512 On: Approximate power consumption of 15522 Joules per run.
MinAvgMaxAVX512 Off39.459.766.1AVX512 On39.457.264.3OpenBenchmarking.orgCelsius, Fewer Is BetterOSPRay 2.12CPU 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, PyriteAVX512 OffAVX512 On300K600K900K1200K1500KSE +/- 2198.34, N = 3SE +/- 3455.26, N = 387613714989371. (CXX) g++ options: -O2 -lcurl -lz -lpthread -lssl -lcrypto -lgmp
OpenBenchmarking.orgkH/s Per Watt, More Is BetterCpuminer-Opt 3.20.3Algorithm: Quad SHA-256, PyriteAVX512 OffAVX512 On90018002700360045002825.314347.58
MinAvgMaxAVX512 Off225029193027AVX512 On225029663080OpenBenchmarking.orgMegahertz, More Is BetterCpuminer-Opt 3.20.3CPU Peak Freq (Highest CPU Core Frequency) Monitor8001600240032004000
MinAvgMaxAVX512 On21.1344.8398.4AVX512 Off11.0310.1352.7OpenBenchmarking.orgWatts, Fewer Is BetterCpuminer-Opt 3.20.3CPU Power Consumption Monitor1102203304405501. AVX512 On: Approximate power consumption of 11722 Joules per run.2. AVX512 Off: Approximate power consumption of 10440 Joules per run.
MinAvgMaxAVX512 On40.568.774.3AVX512 Off38.662.068.1OpenBenchmarking.orgCelsius, Fewer Is BetterCpuminer-Opt 3.20.3CPU 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 2.12Benchmark: gravity_spheres_volume/dim_512/ao/real_timeAVX512 OffAVX512 On816243240SE +/- 0.02, N = 3SE +/- 0.01, N = 319.1732.76
OpenBenchmarking.orgItems Per Second Per Watt, More Is BetterOSPRay 2.12Benchmark: gravity_spheres_volume/dim_512/ao/real_timeAVX512 OffAVX512 On0.02660.05320.07980.10640.1330.0660.118
MinAvgMaxAVX512 On225028853099AVX512 Off225029263096OpenBenchmarking.orgMegahertz, More Is BetterOSPRay 2.12CPU Peak Freq (Highest CPU Core Frequency) Monitor8001600240032004000
MinAvgMaxAVX512 Off20.8290.6346.2AVX512 On20.1276.9329.8OpenBenchmarking.orgWatts, Fewer Is BetterOSPRay 2.12CPU Power Consumption Monitor1002003004005001. AVX512 Off: Approximate power consumption of 16755 Joules per run.2. AVX512 On: Approximate power consumption of 15324 Joules per run.
MinAvgMaxAVX512 Off32.057.565.3AVX512 On33.555.163.3OpenBenchmarking.orgCelsius, Fewer Is BetterOSPRay 2.12CPU 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: x25xAVX512 OffAVX512 On11002200330044005500SE +/- 35.48, N = 4SE +/- 15.71, N = 33010.374977.891. (CXX) g++ options: -O2 -lcurl -lz -lpthread -lssl -lcrypto -lgmp
OpenBenchmarking.orgkH/s Per Watt, More Is BetterCpuminer-Opt 3.20.3Algorithm: x25xAVX512 OffAVX512 On4812162010.8116.85
MinAvgMaxAVX512 On225029093099AVX512 Off225030193099OpenBenchmarking.orgMegahertz, More Is BetterCpuminer-Opt 3.20.3CPU Peak Freq (Highest CPU Core Frequency) Monitor8001600240032004000
MinAvgMaxAVX512 On20.4295.4341.0AVX512 Off21.0278.5321.6OpenBenchmarking.orgWatts, Fewer Is BetterCpuminer-Opt 3.20.3CPU Power Consumption Monitor801602403204001. AVX512 On: Approximate power consumption of 10042 Joules per run.2. AVX512 Off: Approximate power consumption of 9328 Joules per run.
MinAvgMaxAVX512 On39.458.764.3AVX512 Off37.655.259.5OpenBenchmarking.orgCelsius, Fewer Is BetterCpuminer-Opt 3.20.3CPU Temperature Monitor20406080100

OpenBenchmarking.orgkH/s, More Is BetterCpuminer-Opt 3.20.3Algorithm: Blake-2 SAVX512 OffAVX512 On1.6M3.2M4.8M6.4M8MSE +/- 37514.23, N = 15SE +/- 3854.05, N = 3455558072386501. (CXX) g++ options: -O2 -lcurl -lz -lpthread -lssl -lcrypto -lgmp
OpenBenchmarking.orgkH/s Per Watt, More Is BetterCpuminer-Opt 3.20.3Algorithm: Blake-2 SAVX512 OffAVX512 On5K10K15K20K25K14551.2422160.82
MinAvgMaxAVX512 Off225027793096AVX512 On225029253002OpenBenchmarking.orgMegahertz, More Is BetterCpuminer-Opt 3.20.3CPU Peak Freq (Highest CPU Core Frequency) Monitor8001600240032004000
MinAvgMaxAVX512 On20.4326.6376.0AVX512 Off21.0313.1358.1OpenBenchmarking.orgWatts, Fewer Is BetterCpuminer-Opt 3.20.3CPU Power Consumption Monitor1002003004005001. AVX512 On: Approximate power consumption of 10997 Joules per run.2. AVX512 Off: Approximate power consumption of 10519 Joules per run.
MinAvgMaxAVX512 On33.964.072.8AVX512 Off31.164.070.0OpenBenchmarking.orgCelsius, Fewer Is BetterCpuminer-Opt 3.20.3CPU Temperature Monitor20406080100

OpenBenchmarking.orgkH/s, More Is BetterCpuminer-Opt 3.20.3Algorithm: scryptAVX512 OffAVX512 On6001200180024003000SE +/- 0.24, N = 3SE +/- 1.66, N = 32033.152993.211. (CXX) g++ options: -O2 -lcurl -lz -lpthread -lssl -lcrypto -lgmp
OpenBenchmarking.orgkH/s Per Watt, More Is BetterCpuminer-Opt 3.20.3Algorithm: scryptAVX512 OffAVX512 On2468106.4768.913
MinAvgMaxAVX512 Off225029523091AVX512 On225029593095OpenBenchmarking.orgMegahertz, More Is BetterCpuminer-Opt 3.20.3CPU Peak Freq (Highest CPU Core Frequency) Monitor8001600240032004000
MinAvgMaxAVX512 On20.9335.8385.3AVX512 Off20.9314.0361.0OpenBenchmarking.orgWatts, Fewer Is BetterCpuminer-Opt 3.20.3CPU Power Consumption Monitor1002003004005001. AVX512 On: Approximate power consumption of 11306 Joules per run.2. AVX512 Off: Approximate power consumption of 10675 Joules per run.
MinAvgMaxAVX512 On39.566.473.3AVX512 Off38.163.670.0OpenBenchmarking.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.orgms, Fewer Is BetterOpenVINO 2022.3Model: Vehicle Detection FP16-INT8 - Device: CPUAVX512 OffAVX512 On48121620SE +/- 0.01, N = 3SE +/- 0.15, N = 1516.1711.26MIN: 8.44 / MAX: 56.88MIN: 4.37 / MAX: 45.061. (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
MinAvgMaxAVX512 Off225026593098AVX512 On225027053121OpenBenchmarking.orgMegahertz, More Is BetterOpenVINO 2022.3CPU Peak Freq (Highest CPU Core Frequency) Monitor8001600240032004000
MinAvgMaxAVX512 Off21.2330.4358.0AVX512 On20.8306.3336.2OpenBenchmarking.orgWatts, Fewer Is BetterOpenVINO 2022.3CPU Power Consumption Monitor1002003004005001. AVX512 Off: Approximate power consumption of 21257 Joules per run.2. AVX512 On: Approximate power consumption of 19708 Joules per run.
MinAvgMaxAVX512 Off42.167.772.8AVX512 On40.059.266.6OpenBenchmarking.orgCelsius, Fewer Is BetterOpenVINO 2022.3CPU 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 2.12Benchmark: gravity_spheres_volume/dim_512/pathtracer/real_timeAVX512 OffAVX512 On714212835SE +/- 0.01, N = 3SE +/- 0.01, N = 319.5527.97
OpenBenchmarking.orgItems Per Second Per Watt, More Is BetterOSPRay 2.12Benchmark: gravity_spheres_volume/dim_512/pathtracer/real_timeAVX512 OffAVX512 On0.02390.04780.07170.09560.11950.0720.106
MinAvgMaxAVX512 On225030243099AVX512 Off225030523098OpenBenchmarking.orgMegahertz, More Is BetterOSPRay 2.12CPU Peak Freq (Highest CPU Core Frequency) Monitor8001600240032004000
MinAvgMaxAVX512 Off21.2271.7321.8AVX512 On21.1263.0313.6OpenBenchmarking.orgWatts, Fewer Is BetterOSPRay 2.12CPU Power Consumption Monitor801602403204001. AVX512 Off: Approximate power consumption of 15576 Joules per run.2. AVX512 On: Approximate power consumption of 14640 Joules per run.
MinAvgMaxAVX512 Off40.057.062.8AVX512 On40.055.661.3OpenBenchmarking.orgCelsius, Fewer Is BetterOSPRay 2.12CPU Temperature Monitor20406080100

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 OffAVX512 On7001400210028003500SE +/- 6.53, N = 3SE +/- 5.78, N = 32415.33342.51. (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
OpenBenchmarking.orgGFLOPS/s Per Watt, More Is Betterlibxsmm 2-1.17-3645M N K: 256AVX512 OffAVX512 On4812162011.4015.90
MinAvgMaxAVX512 Off223930383143AVX512 On225030543135OpenBenchmarking.orgMegahertz, More Is Betterlibxsmm 2-1.17-3645CPU Peak Freq (Highest CPU Core Frequency) Monitor8001600240032004000
MinAvgMaxAVX512 Off20.7211.9335.7AVX512 On20.5210.2340.2OpenBenchmarking.orgWatts, Fewer Is Betterlibxsmm 2-1.17-3645CPU Power Consumption Monitor801602403204001. AVX512 Off: Approximate power consumption of 39198 Joules per run.2. AVX512 On: Approximate power consumption of 38260 Joules per run.
MinAvgMaxAVX512 On34.449.754.3AVX512 Off33.549.453.3OpenBenchmarking.orgCelsius, Fewer Is Betterlibxsmm 2-1.17-3645CPU Temperature Monitor1530456075

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 OffAVX512 On11K22K33K44K55KSE +/- 102.69, N = 3SE +/- 110.15, N = 339473530901. (CXX) g++ options: -O2 -lcurl -lz -lpthread -lssl -lcrypto -lgmp
OpenBenchmarking.orgkH/s Per Watt, More Is BetterCpuminer-Opt 3.20.3Algorithm: GarlicoinAVX512 OffAVX512 On60120180240300202.32272.43
MinAvgMaxAVX512 On225030583102AVX512 Off225030653102OpenBenchmarking.orgMegahertz, More Is BetterCpuminer-Opt 3.20.3CPU Peak Freq (Highest CPU Core Frequency) Monitor8001600240032004000
MinAvgMaxAVX512 Off20.8195.1204.9AVX512 On20.7194.9210.1OpenBenchmarking.orgWatts, Fewer Is BetterCpuminer-Opt 3.20.3CPU Power Consumption Monitor601201802403001. AVX512 Off: Approximate power consumption of 22112 Joules per run.2. AVX512 On: Approximate power consumption of 13966 Joules per run.
MinAvgMaxAVX512 On38.145.447.9AVX512 Off36.843.746.6OpenBenchmarking.orgCelsius, Fewer Is BetterCpuminer-Opt 3.20.3CPU Temperature Monitor1428425670

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 OffAVX512 On13002600390052006500SE +/- 15.49, N = 3SE +/- 0.44, N = 34528.315972.191. (CC) gcc options: -std=c99 -Ofast -ffast-math -fopenmp -march=native -lm

OpenBenchmarking.orgBillion Interactions/s, More Is BetterminiBUDE 20210901Implementation: OpenMP - Input Deck: BM2AVX512 OffAVX512 On50100150200250SE +/- 0.62, N = 3SE +/- 0.02, N = 3181.13238.891. (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: BM2AVX512 OffAVX512 On0.20030.40060.60090.80121.00150.620.89
MinAvgMaxAVX512 Off225026963098AVX512 On225027963014OpenBenchmarking.orgMegahertz, More Is BetterminiBUDE 20210901CPU Peak Freq (Highest CPU Core Frequency) Monitor8001600240032004000
MinAvgMaxAVX512 Off19.7292.3341.7AVX512 On19.7268.3323.2OpenBenchmarking.orgWatts, Fewer Is BetterminiBUDE 20210901CPU Power Consumption Monitor801602403204001. AVX512 Off: Approximate power consumption of 9353 Joules per run.2. AVX512 On: Approximate power consumption of 6886 Joules per run.
MinAvgMaxAVX512 Off27.955.164.1AVX512 On29.353.462.3OpenBenchmarking.orgCelsius, Fewer Is BetterminiBUDE 20210901CPU Temperature Monitor20406080100

OpenBenchmarking.orgBillion Interactions/s, More Is BetterminiBUDE 20210901Implementation: OpenMP - Input Deck: BM1AVX512 OffAVX512 On50100150200250SE +/- 0.72, N = 8SE +/- 0.09, N = 9187.11237.031. (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: BM1AVX512 OffAVX512 On0.34880.69761.04641.39521.7441.0261.550
MinAvgMaxAVX512 Off225025293096AVX512 On225025973098OpenBenchmarking.orgMegahertz, More Is BetterminiBUDE 20210901CPU Peak Freq (Highest CPU Core Frequency) Monitor8001600240032004000
MinAvgMaxAVX512 Off19.5182.4337.5AVX512 On19.2152.9317.5OpenBenchmarking.orgWatts, Fewer Is BetterminiBUDE 20210901CPU Power Consumption Monitor801602403204001. AVX512 Off: Approximate power consumption of 1505 Joules per run.2. AVX512 On: Approximate power consumption of 1138 Joules per run.
MinAvgMaxAVX512 Off20.837.052.8AVX512 On23.336.350.8OpenBenchmarking.orgCelsius, Fewer Is BetterminiBUDE 20210901CPU Temperature Monitor1530456075

OpenBenchmarking.orgGFInst/s, More Is BetterminiBUDE 20210901Implementation: OpenMP - Input Deck: BM1AVX512 OffAVX512 On13002600390052006500SE +/- 18.03, N = 8SE +/- 2.27, N = 94677.685925.671. (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 OffAVX512 On300K600K900K1200K1500KSE +/- 1811.04, N = 3SE +/- 4577.90, N = 393797711749531. (CXX) g++ options: -O2 -lcurl -lz -lpthread -lssl -lcrypto -lgmp
OpenBenchmarking.orgkH/s Per Watt, More Is BetterCpuminer-Opt 3.20.3Algorithm: SkeincoinAVX512 OffAVX512 On80016002400320040002892.873691.56
MinAvgMaxAVX512 On225028043143AVX512 Off225028993096OpenBenchmarking.orgMegahertz, More Is BetterCpuminer-Opt 3.20.3CPU Peak Freq (Highest CPU Core Frequency) Monitor8001600240032004000
MinAvgMaxAVX512 Off20.2324.2376.0AVX512 On20.2318.3370.8OpenBenchmarking.orgWatts, Fewer Is BetterCpuminer-Opt 3.20.3CPU Power Consumption Monitor1002003004005001. AVX512 Off: Approximate power consumption of 11024 Joules per run.2. AVX512 On: Approximate power consumption of 10822 Joules per run.
MinAvgMaxAVX512 On34.463.471.9AVX512 Off33.062.971.9OpenBenchmarking.orgCelsius, Fewer Is BetterCpuminer-Opt 3.20.3CPU Temperature Monitor20406080100

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 OffAVX512 On70140210280350SE +/- 0.63, N = 3SE +/- 0.78, N = 3260.77316.17

OpenBenchmarking.orgms/batch, Fewer Is BetterNeural Magic DeepSparse 1.5Model: NLP Text Classification, BERT base uncased SST2 - Scenario: Asynchronous Multi-StreamAVX512 OffAVX512 On50100150200250SE +/- 0.64, N = 3SE +/- 0.47, N = 3244.15201.60
MinAvgMaxAVX512 Off225029403122AVX512 On225030133127OpenBenchmarking.orgMegahertz, More Is BetterNeural Magic DeepSparse 1.5CPU Peak Freq (Highest CPU Core Frequency) Monitor8001600240032004000
MinAvgMaxAVX512 On20.6247.7358.6AVX512 Off20.8247.7347.3OpenBenchmarking.orgWatts, Fewer Is BetterNeural Magic DeepSparse 1.5CPU Power Consumption Monitor1002003004005001. AVX512 On: Approximate power consumption of 13294 Joules per run.2. AVX512 Off: Approximate power consumption of 13127 Joules per run.
MinAvgMaxAVX512 Off38.458.370.5AVX512 On36.057.770.9OpenBenchmarking.orgCelsius, Fewer Is BetterNeural Magic DeepSparse 1.5CPU 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.orgms, Fewer Is BetterOpenVINO 2022.3Model: Vehicle Detection FP16 - Device: CPUAVX512 OffAVX512 On1224364860SE +/- 0.62, N = 14SE +/- 0.60, N = 1553.7944.84MIN: 13.85 / MAX: 136.83MIN: 8.1 / MAX: 137.011. (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
MinAvgMaxAVX512 Off224129183105AVX512 On225030293257OpenBenchmarking.orgMegahertz, More Is BetterOpenVINO 2022.3CPU Peak Freq (Highest CPU Core Frequency) Monitor8001600240032004000
MinAvgMaxAVX512 Off21.0266.8326.8AVX512 On20.7256.0333.9OpenBenchmarking.orgWatts, Fewer Is BetterOpenVINO 2022.3CPU Power Consumption Monitor801602403204001. AVX512 Off: Approximate power consumption of 17056 Joules per run.2. AVX512 On: Approximate power consumption of 16419 Joules per run.
MinAvgMaxAVX512 Off36.853.962.3AVX512 On36.851.757.5OpenBenchmarking.orgCelsius, Fewer Is BetterOpenVINO 2022.3CPU Temperature Monitor20406080100

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 OffAVX512 On1632486480SE +/- 0.02, N = 3SE +/- 0.14, N = 361.3773.54

OpenBenchmarking.orgitems/sec, More Is BetterNeural Magic DeepSparse 1.5Model: NLP Text Classification, DistilBERT mnli - Scenario: Asynchronous Multi-StreamAVX512 OffAVX512 On130260390520650SE +/- 0.58, N = 3SE +/- 0.52, N = 3522.11624.74

OpenBenchmarking.orgms/batch, Fewer Is BetterNeural Magic DeepSparse 1.5Model: NLP Text Classification, DistilBERT mnli - Scenario: Asynchronous Multi-StreamAVX512 OffAVX512 On306090120150SE +/- 0.15, N = 3SE +/- 0.07, N = 3122.23102.22
MinAvgMaxAVX512 Off225029313101AVX512 On225030343099OpenBenchmarking.orgMegahertz, More Is BetterNeural Magic DeepSparse 1.5CPU Peak Freq (Highest CPU Core Frequency) Monitor8001600240032004000
MinAvgMaxAVX512 Off21.0256.2320.4AVX512 On20.8255.7320.6OpenBenchmarking.orgWatts, Fewer Is BetterNeural Magic DeepSparse 1.5CPU Power Consumption Monitor801602403204001. AVX512 Off: Approximate power consumption of 11359 Joules per run.2. AVX512 On: Approximate power consumption of 11253 Joules per run.
MinAvgMaxAVX512 Off41.060.768.5AVX512 On39.160.467.1OpenBenchmarking.orgCelsius, Fewer Is BetterNeural Magic DeepSparse 1.5CPU Temperature Monitor20406080100

OpenBenchmarking.orgitems/sec, More Is BetterNeural Magic DeepSparse 1.5Model: NLP Token Classification, BERT base uncased conll2003 - Scenario: Asynchronous Multi-StreamAVX512 OffAVX512 On1632486480SE +/- 0.13, N = 3SE +/- 0.19, N = 361.1873.15

OpenBenchmarking.orgms/batch, Fewer Is BetterNeural Magic DeepSparse 1.5Model: NLP Token Classification, BERT base uncased conll2003 - Scenario: Asynchronous Multi-StreamAVX512 OffAVX512 On2004006008001000SE +/- 1.31, N = 3SE +/- 0.45, N = 31025.48859.71
MinAvgMaxAVX512 Off225029523146AVX512 On225030063135OpenBenchmarking.orgMegahertz, More Is BetterNeural Magic DeepSparse 1.5CPU Peak Freq (Highest CPU Core Frequency) Monitor8001600240032004000
MinAvgMaxAVX512 Off21.2245.5344.8AVX512 On20.7244.3357.9OpenBenchmarking.orgWatts, Fewer Is BetterNeural Magic DeepSparse 1.5CPU Power Consumption Monitor1002003004005001. AVX512 Off: Approximate power consumption of 13586 Joules per run.2. AVX512 On: Approximate power consumption of 13764 Joules per run.
MinAvgMaxAVX512 Off38.958.370.9AVX512 On37.357.670.9OpenBenchmarking.orgCelsius, Fewer Is BetterNeural Magic DeepSparse 1.5CPU Temperature Monitor20406080100

OpenBenchmarking.orgms/batch, Fewer Is BetterNeural Magic DeepSparse 1.5Model: NLP Document Classification, oBERT base uncased on IMDB - Scenario: Asynchronous Multi-StreamAVX512 OffAVX512 On2004006008001000SE +/- 1.40, N = 3SE +/- 0.33, N = 31023.17858.40
MinAvgMaxAVX512 Off225029333136AVX512 On225030113136OpenBenchmarking.orgMegahertz, More Is BetterNeural Magic DeepSparse 1.5CPU Peak Freq (Highest CPU Core Frequency) Monitor8001600240032004000
MinAvgMaxAVX512 On20.4253.4358.2AVX512 Off20.7244.1344.4OpenBenchmarking.orgWatts, Fewer Is BetterNeural Magic DeepSparse 1.5CPU Power Consumption Monitor1002003004005001. AVX512 On: Approximate power consumption of 13937 Joules per run.2. AVX512 Off: Approximate power consumption of 13506 Joules per run.
MinAvgMaxAVX512 On34.657.571.4AVX512 Off30.654.570.5OpenBenchmarking.orgCelsius, Fewer Is BetterNeural Magic DeepSparse 1.5CPU Temperature Monitor20406080100

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 OffAVX512 On30060090012001500SE +/- 0.33, N = 3SE +/- 2.65, N = 311791398MIN: 178 / MAX: 10473MIN: 229 / MAX: 11779
OpenBenchmarking.orgItems / Sec Per Watt, More Is BetterOpenVKL 1.3.1Benchmark: vklBenchmark ISPCAVX512 OffAVX512 On1.31812.63623.95435.27246.59054.5695.858
OpenBenchmarking.orgMegahertz, More Is BetterOpenVKL 1.3.1CPU Peak Freq (Highest CPU Core Frequency) MonitorAVX512 OffAVX512 On5001000150020002500Min: 2250 / Avg: 2958.42 / Max: 3128Min: 2250 / Avg: 2983.53 / Max: 3118
OpenBenchmarking.orgWatts, Fewer Is BetterOpenVKL 1.3.1CPU Power Consumption MonitorAVX512 OffAVX512 On60120180240300Min: 10.21 / Avg: 258.07 / Max: 348.15Min: 19.9 / Avg: 238.66 / Max: 322.171. AVX512 Off: Approximate power consumption of 105723 Joules per run.2. AVX512 On: Approximate power consumption of 95462 Joules per run.
OpenBenchmarking.orgCelsius, Fewer Is BetterOpenVKL 1.3.1CPU Temperature MonitorAVX512 OffAVX512 On1326395265Min: 30.38 / Avg: 54.49 / Max: 64.75Min: 30.63 / Avg: 53.11 / Max: 62.25

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 OffAVX512 On306090120150SE +/- 0.11, N = 7SE +/- 0.09, N = 8132.95157.65MIN: 130.4 / MAX: 138.16MIN: 155.33 / MAX: 162.92
OpenBenchmarking.orgFrames Per Second Per Watt, More Is BetterEmbree 4.1Binary: Pathtracer ISPC - Model: Asian DragonAVX512 OffAVX512 On0.2070.4140.6210.8281.0350.7150.920
MinAvgMaxAVX512 On225025653098AVX512 Off225025843096OpenBenchmarking.orgMegahertz, More Is BetterEmbree 4.1CPU Peak Freq (Highest CPU Core Frequency) Monitor8001600240032004000
MinAvgMaxAVX512 Off20.4186.1333.2AVX512 On20.1171.3327.2OpenBenchmarking.orgWatts, Fewer Is BetterEmbree 4.1CPU Power Consumption Monitor801602403204001. AVX512 Off: Approximate power consumption of 1754 Joules per run.2. AVX512 On: Approximate power consumption of 1478 Joules per run.
MinAvgMaxAVX512 Off33.542.250.0AVX512 On33.541.448.9OpenBenchmarking.orgCelsius, Fewer Is BetterEmbree 4.1CPU Temperature Monitor1428425670

OpenBenchmarking.orgFrames Per Second, More Is BetterEmbree 4.1Binary: Pathtracer ISPC - Model: Asian Dragon ObjAVX512 OffAVX512 On306090120150SE +/- 0.08, N = 4SE +/- 0.16, N = 4115.27134.84MIN: 113.48 / MAX: 119.15MIN: 132.49 / MAX: 139
OpenBenchmarking.orgFrames Per Second Per Watt, More Is BetterEmbree 4.1Binary: Pathtracer ISPC - Model: Asian Dragon ObjAVX512 OffAVX512 On0.24080.48160.72240.96321.2040.8421.070
MinAvgMaxAVX512 On225028413101AVX512 Off225028553098OpenBenchmarking.orgMegahertz, More Is BetterEmbree 4.1CPU Peak Freq (Highest CPU Core Frequency) Monitor8001600240032004000
MinAvgMaxAVX512 Off20.2136.9330.7AVX512 On20.3126.0325.6OpenBenchmarking.orgWatts, Fewer Is BetterEmbree 4.1CPU Power Consumption Monitor801602403204001. AVX512 Off: Approximate power consumption of 2773 Joules per run.2. AVX512 On: Approximate power consumption of 2426 Joules per run.
MinAvgMaxAVX512 On32.539.347.0AVX512 Off32.536.747.0OpenBenchmarking.orgCelsius, Fewer Is BetterEmbree 4.1CPU Temperature Monitor1428425670

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 OffAVX512 On30060090012001500SE +/- 1.80, N = 3SE +/- 12.60, N = 41317.571174.75MIN: 1299.38MIN: 1143.881. (CXX) g++ options: -O3 -march=native -fopenmp -msse4.1 -fPIC -pie -ldl -lpthread
MinAvgMaxAVX512 Off225028243100AVX512 On225029983097OpenBenchmarking.orgMegahertz, More Is BetteroneDNN 3.1CPU Peak Freq (Highest CPU Core Frequency) Monitor8001600240032004000
MinAvgMaxAVX512 Off19.8202.0272.5AVX512 On20.0176.7277.9OpenBenchmarking.orgWatts, Fewer Is BetteroneDNN 3.1CPU Power Consumption Monitor701402102803501. AVX512 Off: Approximate power consumption of 17643 Joules per run.2. AVX512 On: Approximate power consumption of 15289 Joules per run.
MinAvgMaxAVX512 Off24.539.845.1AVX512 On30.439.245.3OpenBenchmarking.orgCelsius, Fewer Is BetteroneDNN 3.1CPU Temperature Monitor1224364860

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 OffAVX512 On306090120150SE +/- 0.11, N = 7SE +/- 0.09, N = 7112.23125.54MIN: 109.49 / MAX: 117.02MIN: 122.35 / MAX: 131.95
OpenBenchmarking.orgFrames Per Second Per Watt, More Is BetterEmbree 4.1Binary: Pathtracer ISPC - Model: CrownAVX512 OffAVX512 On0.15120.30240.45360.60480.7560.5600.672
MinAvgMaxAVX512 On225025113101AVX512 Off225026273097OpenBenchmarking.orgMegahertz, More Is BetterEmbree 4.1CPU Peak Freq (Highest CPU Core Frequency) Monitor8001600240032004000
MinAvgMaxAVX512 Off20.6200.3339.8AVX512 On20.3186.8333.7OpenBenchmarking.orgWatts, Fewer Is BetterEmbree 4.1CPU Power Consumption Monitor801602403204001. AVX512 Off: Approximate power consumption of 2061 Joules per run.2. AVX512 On: Approximate power consumption of 1761 Joules per run.
MinAvgMaxAVX512 Off33.344.252.8AVX512 On33.543.251.3OpenBenchmarking.orgCelsius, Fewer Is BetterEmbree 4.1CPU Temperature Monitor1530456075

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 OffAVX512 On0.3960.7921.1881.5841.98SE +/- 0.00, N = 3SE +/- 0.00, N = 31.761.58MIN: 0.64 / MAX: 19.6MIN: 0.55 / MAX: 17.781. (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
MinAvgMaxAVX512 Off225026263099AVX512 On225027613119OpenBenchmarking.orgMegahertz, More Is BetterOpenVINO 2022.3CPU Peak Freq (Highest CPU Core Frequency) Monitor8001600240032004000
MinAvgMaxAVX512 On21.4311.4336.9AVX512 Off21.2308.2334.1OpenBenchmarking.orgWatts, Fewer Is BetterOpenVINO 2022.3CPU Power Consumption Monitor801602403204001. AVX512 On: Approximate power consumption of 20032 Joules per run.2. AVX512 Off: Approximate power consumption of 19931 Joules per run.
MinAvgMaxAVX512 Off41.063.969.0AVX512 On41.463.468.1OpenBenchmarking.orgCelsius, Fewer Is BetterOpenVINO 2022.3CPU Temperature Monitor20406080100

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 OffAVX512 On2004006008001000SE +/- 0.45, N = 3SE +/- 0.42, N = 3870.95970.06

OpenBenchmarking.orgms/batch, Fewer Is BetterNeural Magic DeepSparse 1.5Model: CV Classification, ResNet-50 ImageNet - Scenario: Asynchronous Multi-StreamAVX512 OffAVX512 On1632486480SE +/- 0.04, N = 3SE +/- 0.03, N = 373.3565.89
MinAvgMaxAVX512 Off225029623101AVX512 On225030123134OpenBenchmarking.orgMegahertz, More Is BetterNeural Magic DeepSparse 1.5CPU Peak Freq (Highest CPU Core Frequency) Monitor8001600240032004000
MinAvgMaxAVX512 Off21.0284.5342.1AVX512 On21.1279.2332.9OpenBenchmarking.orgWatts, Fewer Is BetterNeural Magic DeepSparse 1.5CPU Power Consumption Monitor801602403204001. AVX512 Off: Approximate power consumption of 11855 Joules per run.2. AVX512 On: Approximate power consumption of 11726 Joules per run.
MinAvgMaxAVX512 Off40.065.272.9AVX512 On39.862.870.4OpenBenchmarking.orgCelsius, Fewer Is BetterNeural Magic DeepSparse 1.5CPU 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 2022.3Model: Age Gender Recognition Retail 0013 FP16-INT8 - Device: CPUAVX512 OffAVX512 On16K32K48K64K80KSE +/- 20.10, N = 3SE +/- 95.74, N = 366895.4973970.121. (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 OffAVX512 On6001200180024003000SE +/- 2.70, N = 3SE +/- 12.20, N = 32573.32690.71. (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
OpenBenchmarking.orgGFLOPS/s Per Watt, More Is Betterlibxsmm 2-1.17-3645M N K: 128AVX512 OffAVX512 On369121512.5313.07
OpenBenchmarking.orgMegahertz, More Is Betterlibxsmm 2-1.17-3645CPU Peak Freq (Highest CPU Core Frequency) MonitorAVX512 OffAVX512 On5001000150020002500Min: 2250 / Avg: 3086 / Max: 3117Min: 2250 / Avg: 3087.64 / Max: 3133
OpenBenchmarking.orgWatts, Fewer Is Betterlibxsmm 2-1.17-3645CPU Power Consumption MonitorAVX512 OnAVX512 Off60120180240300Min: 20.28 / Avg: 205.93 / Max: 329.89Min: 20.58 / Avg: 205.43 / Max: 327.081. AVX512 On: Approximate power consumption of 106125 Joules per run.2. AVX512 Off: Approximate power consumption of 105932 Joules per run.
OpenBenchmarking.orgCelsius, Fewer Is Betterlibxsmm 2-1.17-3645CPU Temperature MonitorAVX512 OnAVX512 Off1122334455Min: 35.75 / Avg: 50.34 / Max: 53.25Min: 35.5 / Avg: 49.14 / Max: 50.88

CPU Temperature Monitor

OpenBenchmarking.orgCelsiusCPU Temperature MonitorPhoronix Test Suite System MonitoringAVX512 OnAVX512 Off1530456075Min: 23.25 / Avg: 51.4 / Max: 74.25Min: 20.75 / Avg: 44.22 / Max: 76.13

CPU Power Consumption Monitor

OpenBenchmarking.orgWattsCPU Power Consumption MonitorPhoronix Test Suite System MonitoringAVX512 OnAVX512 Off70140210280350Min: 10.25 / Avg: 231.36 / Max: 398.39Min: 10.15 / Avg: 179.15 / Max: 378.14

CPU Peak Freq (Highest CPU Core Frequency) Monitor

OpenBenchmarking.orgMegahertzCPU Peak Freq (Highest CPU Core Frequency) MonitorPhoronix Test Suite System MonitoringAVX512 OffAVX512 On6001200180024003000Min: 2203 / Avg: 2979.69 / Max: 3559Min: 2250 / Avg: 2918.06 / Max: 3532

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 OffAVX512 On12002400360048006000SE +/- 2.12, N = 3SE +/- 89.26, N = 153954.905690.341. (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

OpenBenchmarking.orgFPS, More Is BetterOpenVINO 2022.3Model: Vehicle Detection FP16 - Device: CPUAVX512 OffAVX512 On30060090012001500SE +/- 15.59, N = 14SE +/- 22.93, N = 151190.911430.451. (CXX) g++ options: -isystem -fsigned-char -ffunction-sections -fdata-sections -msse4.1 -msse4.2 -O3 -fno-strict-overflow -fwrapv -fPIC -fvisibility=hidden -Os -std=c++11 -MD -MT -MF

Neural Magic DeepSparse

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

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

MinAvgMaxAVX512 On225030023416AVX512 Off225030233152OpenBenchmarking.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 OffAVX512 On60120180240300SE +/- 0.24, N = 3SE +/- 6.02, N = 15298.06259.65
MinAvgMaxAVX512 On225030023416AVX512 Off225030233152OpenBenchmarking.orgMegahertz, More Is BetterNeural Magic DeepSparse 1.5CPU Peak Freq (Highest CPU Core Frequency) Monitor8001600240032004000
MinAvgMaxAVX512 On10.5234.1342.4AVX512 Off21.0228.6329.0OpenBenchmarking.orgWatts, Fewer Is BetterNeural Magic DeepSparse 1.5CPU Power Consumption Monitor801602403204001. AVX512 On: Approximate power consumption of 11484 Joules per run.2. AVX512 Off: Approximate power consumption of 14249 Joules per run.
MinAvgMaxAVX512 On38.653.166.5AVX512 Off38.152.965.8OpenBenchmarking.orgCelsius, Fewer Is BetterNeural Magic DeepSparse 1.5CPU Temperature Monitor20406080100

OpenBenchmarking.orgitems/sec, More Is BetterNeural Magic DeepSparse 1.5Model: NLP Question Answering, BERT base uncased SQuaD 12layer Pruned90 - Scenario: Asynchronous Multi-StreamAVX512 OffAVX512 On50100150200250SE +/- 0.14, N = 3SE +/- 7.49, N = 15213.64247.97

TensorFlow

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

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

MinAvgMaxAVX512 On225029923472AVX512 Off225030643197OpenBenchmarking.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 OffAVX512 On0.25610.51220.76831.02441.28050.3601.138

OpenBenchmarking.orgimages/sec, More Is BetterTensorFlow 2.12Device: CPU - Batch Size: 32 - Model: GoogLeNetAVX512 OffAVX512 On4080120160200SE +/- 0.10, N = 3SE +/- 3.09, N = 1544.46180.77
OpenBenchmarking.orgimages/sec Per Watt, More Is BetterTensorFlow 2.12Device: CPU - Batch Size: 32 - Model: GoogLeNetAVX512 OffAVX512 On0.25610.51220.76831.02441.28050.3601.138
MinAvgMaxAVX512 On225029923472AVX512 Off225030643197OpenBenchmarking.orgMegahertz, More Is BetterTensorFlow 2.12CPU Peak Freq (Highest CPU Core Frequency) Monitor8001600240032004000
MinAvgMaxAVX512 On20.3158.9208.4AVX512 Off20.2123.6149.7OpenBenchmarking.orgWatts, Fewer Is BetterTensorFlow 2.12CPU Power Consumption Monitor601201802403001. AVX512 On: Approximate power consumption of 4258 Joules per run.2. AVX512 Off: Approximate power consumption of 10709 Joules per run.
MinAvgMaxAVX512 On30.840.349.9AVX512 Off29.335.347.1OpenBenchmarking.orgCelsius, Fewer Is BetterTensorFlow 2.12CPU Temperature Monitor1428425670

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

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

MinAvgMaxAVX512 On225029773320AVX512 Off225030323208OpenBenchmarking.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 OffAVX512 On0.17420.34840.52260.69680.8710.3350.774

OpenBenchmarking.orgimages/sec, More Is BetterTensorFlow 2.12Device: CPU - Batch Size: 16 - Model: GoogLeNetAVX512 OffAVX512 On20406080100SE +/- 0.17, N = 3SE +/- 1.96, N = 1539.64104.77
OpenBenchmarking.orgimages/sec Per Watt, More Is BetterTensorFlow 2.12Device: CPU - Batch Size: 16 - Model: GoogLeNetAVX512 OffAVX512 On0.17420.34840.52260.69680.8710.3350.774
MinAvgMaxAVX512 On225029773320AVX512 Off225030323208OpenBenchmarking.orgMegahertz, More Is BetterTensorFlow 2.12CPU Peak Freq (Highest CPU Core Frequency) Monitor8001600240032004000
MinAvgMaxAVX512 On19.8135.4179.1AVX512 Off20.1118.4140.5OpenBenchmarking.orgWatts, Fewer Is BetterTensorFlow 2.12CPU Power Consumption Monitor501001502002501. AVX512 On: Approximate power consumption of 3259 Joules per run.2. AVX512 Off: Approximate power consumption of 6158 Joules per run.
MinAvgMaxAVX512 On33.038.545.8AVX512 Off29.135.747.9OpenBenchmarking.orgCelsius, Fewer Is BetterTensorFlow 2.12CPU Temperature Monitor1428425670

Cpuminer-Opt

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

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

MinAvgMaxAVX512 On225030213097AVX512 Off225030463099OpenBenchmarking.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 OffAVX512 On122436486044.6751.65

OpenBenchmarking.orgkH/s, More Is BetterCpuminer-Opt 3.20.3Algorithm: Myriad-GroestlAVX512 OffAVX512 On2K4K6K8K10KSE +/- 21.55, N = 3SE +/- 340.56, N = 157149.958628.761. (CXX) g++ options: -O2 -lcurl -lz -lpthread -lssl -lcrypto -lgmp
OpenBenchmarking.orgkH/s Per Watt, More Is BetterCpuminer-Opt 3.20.3Algorithm: Myriad-GroestlAVX512 OffAVX512 On122436486044.6751.65
MinAvgMaxAVX512 On225030213097AVX512 Off225030463099OpenBenchmarking.orgMegahertz, More Is BetterCpuminer-Opt 3.20.3CPU Peak Freq (Highest CPU Core Frequency) Monitor8001600240032004000
MinAvgMaxAVX512 On19.9167.1199.7AVX512 Off20.4160.1173.0OpenBenchmarking.orgWatts, Fewer Is BetterCpuminer-Opt 3.20.3CPU Power Consumption Monitor501001502002501. AVX512 On: Approximate power consumption of 6282 Joules per run.2. AVX512 Off: Approximate power consumption of 9871 Joules per run.
MinAvgMaxAVX512 On34.942.247.0AVX512 Off33.940.944.6OpenBenchmarking.orgCelsius, Fewer Is BetterCpuminer-Opt 3.20.3CPU Temperature Monitor1428425670

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

AVX512 On

Kernel Notes: Transparent Huge Pages: madvise
Compiler Notes: --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
Processor Notes: Scaling Governor: acpi-cpufreq performance (Boost: Enabled) - CPU Microcode: 0xaa0010b
Python Notes: Python 3.10.6
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 16 July 2023 06:38 by user phoronix.

AVX512 Off

Processor: AMD EPYC 9754 128-Core @ 2.25GHz (128 Cores / 256 Threads), Motherboard: AMD Titanite_4G (RTI1007B BIOS), Chipset: AMD Device 14a4, Memory: 768GB, Disk: 2 x 1920GB SAMSUNG MZWLJ1T9HBJR-00007, Graphics: ASPEED, Network: Broadcom NetXtreme BCM5720 PCIe

OS: Ubuntu 22.04, Kernel: 5.19.0-41-generic (x86_64), Desktop: GNOME Shell 42.5, Display Server: X Server 1.21.1.4, Vulkan: 1.3.224, Compiler: GCC 11.3.0, File-System: ext4, Screen Resolution: 1024x768

Kernel Notes: Transparent Huge Pages: madvise
Compiler Notes: --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
Processor Notes: Scaling Governor: acpi-cpufreq performance (Boost: Enabled) - CPU Microcode: 0xaa0010b
Python Notes: Python 3.10.6
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 16 July 2023 14:04 by user phoronix.