Xeon Max AMX HBM2e

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EPYC 9654 2P
June 28 2023
  6 Hours, 59 Minutes
EPYC 9554 2P
June 28 2023
  5 Hours, 42 Minutes
Xeon Max 9480 2P, HBM Caching
June 29 2023
  13 Hours, 47 Minutes
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  8 Hours, 49 Minutes

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Xeon Max AMX HBM2eProcessorMotherboardChipsetMemoryDiskGraphicsMonitorNetworkOSKernelDesktopDisplay ServerCompilerFile-SystemScreen ResolutionEPYC 9654 2PEPYC 9554 2PXeon Max 9480 2P, HBM Caching2 x AMD EPYC 9654 96-Core @ 2.40GHz (192 Cores / 384 Threads)AMD Titanite_4G (RTI1007B BIOS)AMD Device 14a41520GB7682GB INTEL SSDPF2KX076TZASPEEDVGA HDMIBroadcom NetXtreme BCM5720 PCIeUbuntu 23.046.2.0-20-generic (x86_64)GNOME Shell 44.0X Server 1.21.1.7GCC 12.2.0ext41920x10802 x AMD EPYC 9554 64-Core @ 3.10GHz (128 Cores / 256 Threads)2 x Intel Xeon Max 9480 @ 3.50GHz (112 Cores / 224 Threads)Supermicro X13DEM v1.10 (1.3 BIOS)Intel Device 1bce512GBVE2282 x Broadcom BCM57508 NetXtreme-E 10Gb/25Gb/40Gb/50Gb/100Gb/200GbOpenBenchmarking.orgKernel Details- Transparent Huge Pages: madviseCompiler Details- --build=x86_64-linux-gnu --disable-vtable-verify --disable-werror --enable-cet --enable-checking=release --enable-clocale=gnu --enable-default-pie --enable-gnu-unique-object --enable-languages=c,ada,c++,go,d,fortran,objc,obj-c++,m2 --enable-libphobos-checking=release --enable-libstdcxx-debug --enable-libstdcxx-time=yes --enable-multiarch --enable-multilib --enable-nls --enable-objc-gc=auto --enable-offload-defaulted --enable-offload-targets=nvptx-none=/build/gcc-12-Pa930Z/gcc-12-12.2.0/debian/tmp-nvptx/usr,amdgcn-amdhsa=/build/gcc-12-Pa930Z/gcc-12-12.2.0/debian/tmp-gcn/usr --enable-plugin --enable-shared --enable-threads=posix --host=x86_64-linux-gnu --program-prefix=x86_64-linux-gnu- --target=x86_64-linux-gnu --with-abi=m64 --with-arch-32=i686 --with-default-libstdcxx-abi=new --with-gcc-major-version-only --with-multilib-list=m32,m64,mx32 --with-target-system-zlib=auto --with-tune=generic --without-cuda-driver -v Processor Details- EPYC 9654 2P: Scaling Governor: acpi-cpufreq performance (Boost: Enabled) - CPU Microcode: 0xa101121- EPYC 9554 2P: Scaling Governor: acpi-cpufreq performance (Boost: Enabled) - CPU Microcode: 0xa101121- Xeon Max 9480 2P, HBM Caching: Scaling Governor: intel_cpufreq performance - CPU Microcode: 0x2c0001d1Python Details- Python 3.11.2Security Details- EPYC 9654 2P: 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 - EPYC 9554 2P: 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 - Xeon Max 9480 2P, HBM Caching: 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 Enhanced IBRS IBPB: conditional RSB filling PBRSB-eIBRS: SW sequence + srbds: Not affected + tsx_async_abort: Not affected

EPYC 9654 2PEPYC 9554 2PXeon Max 9480 2P, HBM CachingResult OverviewPhoronix Test Suite100%171%242%313%384%oneDNNlibxsmmTensorFlowONNX RuntimeOpenVINO

EPYC 9654 2PEPYC 9554 2PXeon Max 9480 2P, HBM CachingPer Watt Result OverviewPhoronix Test Suite100%168%236%303%libxsmmTensorFlowTensorFlowTensorFlowTensorFlowTensorFlowTensorFlowTensorFlowTensorFlow128CPU - 16 - VGG-16CPU - 16 - AlexNetCPU - 512 - VGG-16CPU - 512 - AlexNetCPU - 16 - GoogLeNetCPU - 16 - ResNet-50CPU - 512 - GoogLeNetCPU - 512 - ResNet-50

Xeon Max AMX HBM2eopenvino: Face Detection FP16 - CPUopenvino: Person Detection FP16 - CPUopenvino: Person Detection FP32 - CPUopenvino: Vehicle Detection FP16 - CPUopenvino: Face Detection FP16-INT8 - CPUopenvino: Vehicle Detection FP16-INT8 - CPUopenvino: Weld Porosity Detection FP16 - CPUopenvino: Machine Translation EN To DE FP16 - CPUopenvino: Weld Porosity Detection FP16-INT8 - CPUopenvino: Person Vehicle Bike Detection FP16 - CPUopenvino: Age Gender Recognition Retail 0013 FP16 - CPUopenvino: Age Gender Recognition Retail 0013 FP16-INT8 - CPUlibxsmm: 128libxsmm: 256libxsmm: 32libxsmm: 64tensorflow: CPU - 16 - VGG-16tensorflow: CPU - 16 - AlexNettensorflow: CPU - 512 - VGG-16tensorflow: CPU - 512 - AlexNettensorflow: CPU - 16 - GoogLeNettensorflow: CPU - 16 - ResNet-50tensorflow: CPU - 512 - GoogLeNettensorflow: CPU - 512 - ResNet-50onnx: GPT-2 - CPU - Standardonnx: yolov4 - CPU - Standardonnx: bertsquad-12 - CPU - Standardonnx: CaffeNet 12-int8 - CPU - Standardonnx: fcn-resnet101-11 - CPU - Standardonnx: ArcFace ResNet-100 - CPU - Standardonnx: ResNet50 v1-12-int8 - CPU - Standardonnx: GPT-2 - CPU - Standardonnx: yolov4 - CPU - Standardonnx: bertsquad-12 - CPU - Standardonnx: CaffeNet 12-int8 - CPU - Standardonnx: fcn-resnet101-11 - CPU - Standardonnx: ArcFace ResNet-100 - CPU - Standardonnx: ResNet50 v1-12-int8 - CPU - Standardonednn: IP Shapes 1D - bf16bf16bf16 - CPUonednn: IP Shapes 3D - bf16bf16bf16 - CPUonednn: Convolution Batch Shapes Auto - bf16bf16bf16 - CPUonednn: Deconvolution Batch shapes_1d - bf16bf16bf16 - CPUonednn: Deconvolution Batch shapes_3d - bf16bf16bf16 - CPUonednn: Recurrent Neural Network Training - bf16bf16bf16 - CPUonednn: Recurrent Neural Network Inference - bf16bf16bf16 - CPUopenvino: Face Detection FP16 - CPUopenvino: Person Detection FP16 - CPUopenvino: Person Detection FP32 - CPUopenvino: Vehicle Detection FP16 - CPUopenvino: Face Detection FP16-INT8 - CPUopenvino: Vehicle Detection FP16-INT8 - CPUopenvino: Weld Porosity Detection FP16 - CPUopenvino: Machine Translation EN To DE FP16 - CPUopenvino: Weld Porosity Detection FP16-INT8 - CPUopenvino: Person Vehicle Bike Detection FP16 - CPUopenvino: Age Gender Recognition Retail 0013 FP16 - CPUopenvino: Age Gender Recognition Retail 0013 FP16-INT8 - CPUEPYC 9654 2PEPYC 9554 2PXeon Max 9480 2P, HBM Caching101.5643.6443.407390.97191.4110985.179843.03950.9419170.619133.22146867.48124618.323426.14379.61298.02270.247.27166.20120.621757.1664.4925.25535.52171.56103.1844.9003310.17944435.1944.6979719.3084146.5559.68904204.09198.99572.30611212.86351.78986.8705316.98233.802090.4610532.533260.7321002492.692790.90471.821092.971098.966.49250.394.364.8650.429.955.250.550.9982.0438.2438.535981.57155.289010.458039.57786.0115659.327447.60162207.97128593.244112.94603.31402.22692.760.31257.94109.891813.6894.4133.40593.20188.17132.7215.1050511.6871495.2404.6598224.0122152.4397.64735195.89985.90092.01949214.60641.64456.5598911.196692.205960.3113781.761620.4572721305.66925.767389.53832.02825.525.34205.713.543.9740.678.094.290.520.88120.4033.4033.972315.12334.895528.0316941.99590.9230938.506265.77108515.1259457.141814.321.09230.1130.19718.5498.4340.15236.4476.93218.6927.7004611.4576562.2185.3351423.7729125.2844.70849130.37087.76381.78296191.62342.18018.021667.8801691.98143.673560.4830753.5352515294.61325.45232.01834.97819.7612.07333.5120.236.4447.293.4717.830.441.40OpenBenchmarking.org

CPU Peak Freq (Highest CPU Core Frequency) Monitor

OpenBenchmarking.orgMegahertzCPU Peak Freq (Highest CPU Core Frequency) MonitorPhoronix Test Suite System MonitoringXeon Max 9480 2P, HBM Caching6001200180024003000Min: 1100 / Avg: 3207.85 / Max: 3577

CPU Power Consumption Monitor

OpenBenchmarking.orgWattsCPU Power Consumption MonitorPhoronix Test Suite System MonitoringEPYC 9554 2PEPYC 9654 2PXeon Max 9480 2P, HBM Caching160320480640800Min: 34.39 / Avg: 413.82 / Max: 710.63Min: 31.88 / Avg: 448.81 / Max: 725.51Min: 87.33 / Avg: 548.37 / Max: 899.87

System Power Consumption Monitor

OpenBenchmarking.orgWattsSystem Power Consumption MonitorPhoronix Test Suite System MonitoringXeon Max 9480 2P, HBM Caching160320480640800Min: 260 / Avg: 751.74 / Max: 907

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: Face Detection FP16 - Device: CPUXeon Max 9480 2P, HBM CachingEPYC 9654 2PEPYC 9554 2P306090120150SE +/- 0.41, N = 3SE +/- 0.25, N = 3SE +/- 0.04, N = 3120.40101.5682.041. (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: CPUEPYC 9654 2PEPYC 9554 2PXeon Max 9480 2P, HBM Caching1020304050SE +/- 0.21, N = 3SE +/- 0.23, N = 3SE +/- 0.24, N = 343.6438.2433.401. (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.orgFPS, More Is BetterOpenVINO 2022.3Model: Person Detection FP32 - Device: CPUEPYC 9654 2PEPYC 9554 2PXeon Max 9480 2P, HBM Caching1020304050SE +/- 0.20, N = 3SE +/- 0.04, N = 3SE +/- 0.31, N = 343.4038.5333.971. (CXX) g++ options: -isystem -fsigned-char -ffunction-sections -fdata-sections -msse4.1 -msse4.2 -O3 -fno-strict-overflow -fwrapv -fPIC -fvisibility=hidden -Os -std=c++11 -MD -MT -MF

OpenBenchmarking.orgFPS, More Is BetterOpenVINO 2022.3Model: Vehicle Detection FP16 - Device: CPUEPYC 9654 2PEPYC 9554 2PXeon Max 9480 2P, HBM Caching16003200480064008000SE +/- 2.12, N = 3SE +/- 3.49, N = 3SE +/- 17.29, N = 137390.975981.572315.121. (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

OpenBenchmarking.orgFPS, More Is BetterOpenVINO 2022.3Model: Face Detection FP16-INT8 - Device: CPUXeon Max 9480 2P, HBM CachingEPYC 9654 2PEPYC 9554 2P70140210280350SE +/- 0.45, N = 3SE +/- 0.06, N = 3SE +/- 0.14, N = 3334.89191.41155.281. (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-INT8 - Device: CPUEPYC 9654 2PEPYC 9554 2PXeon Max 9480 2P, HBM Caching2K4K6K8K10KSE +/- 0.53, N = 3SE +/- 2.20, N = 3SE +/- 25.18, N = 310985.179010.455528.031. (CXX) g++ options: -isystem -fsigned-char -ffunction-sections -fdata-sections -msse4.1 -msse4.2 -O3 -fno-strict-overflow -fwrapv -fPIC -fvisibility=hidden -Os -std=c++11 -MD -MT -MF

OpenBenchmarking.orgFPS, More Is BetterOpenVINO 2022.3Model: Weld Porosity Detection FP16 - Device: CPUXeon Max 9480 2P, HBM CachingEPYC 9654 2PEPYC 9554 2P4K8K12K16K20KSE +/- 13.63, N = 3SE +/- 2.32, N = 3SE +/- 1.22, N = 316941.999843.038039.571. (CXX) g++ options: -isystem -fsigned-char -ffunction-sections -fdata-sections -msse4.1 -msse4.2 -O3 -fno-strict-overflow -fwrapv -fPIC -fvisibility=hidden -Os -std=c++11 -MD -MT -MF

OpenBenchmarking.orgFPS, More Is BetterOpenVINO 2022.3Model: Machine Translation EN To DE FP16 - Device: CPUEPYC 9654 2PEPYC 9554 2PXeon Max 9480 2P, HBM Caching2004006008001000SE +/- 0.77, N = 3SE +/- 1.56, N = 3SE +/- 0.19, N = 3950.94786.01590.921. (CXX) g++ options: -isystem -fsigned-char -ffunction-sections -fdata-sections -msse4.1 -msse4.2 -O3 -fno-strict-overflow -fwrapv -fPIC -fvisibility=hidden -Os -std=c++11 -MD -MT -MF

OpenBenchmarking.orgFPS, More Is BetterOpenVINO 2022.3Model: Weld Porosity Detection FP16-INT8 - Device: CPUXeon Max 9480 2P, HBM CachingEPYC 9654 2PEPYC 9554 2P7K14K21K28K35KSE +/- 38.32, N = 3SE +/- 4.81, N = 3SE +/- 3.60, N = 330938.5019170.6115659.321. (CXX) g++ options: -isystem -fsigned-char -ffunction-sections -fdata-sections -msse4.1 -msse4.2 -O3 -fno-strict-overflow -fwrapv -fPIC -fvisibility=hidden -Os -std=c++11 -MD -MT -MF

OpenBenchmarking.orgFPS, More Is BetterOpenVINO 2022.3Model: Person Vehicle Bike Detection FP16 - Device: CPUEPYC 9654 2PEPYC 9554 2PXeon Max 9480 2P, HBM Caching2K4K6K8K10KSE +/- 3.38, N = 3SE +/- 8.54, N = 3SE +/- 8.17, N = 39133.227447.606265.771. (CXX) g++ options: -isystem -fsigned-char -ffunction-sections -fdata-sections -msse4.1 -msse4.2 -O3 -fno-strict-overflow -fwrapv -fPIC -fvisibility=hidden -Os -std=c++11 -MD -MT -MF

OpenBenchmarking.orgFPS, More Is BetterOpenVINO 2022.3Model: Age Gender Recognition Retail 0013 FP16 - Device: CPUEPYC 9554 2PEPYC 9654 2PXeon Max 9480 2P, HBM Caching30K60K90K120K150KSE +/- 685.52, N = 3SE +/- 1825.86, N = 3SE +/- 967.90, N = 3162207.97146867.48108515.121. (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

OpenBenchmarking.orgFPS, More Is BetterOpenVINO 2022.3Model: Age Gender Recognition Retail 0013 FP16-INT8 - Device: CPUEPYC 9554 2PEPYC 9654 2PXeon Max 9480 2P, HBM Caching30K60K90K120K150KSE +/- 574.97, N = 3SE +/- 611.95, N = 3SE +/- 1694.26, N = 12128593.24124618.3259457.141. (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

OpenBenchmarking.orgGFLOPS/s Per Watt, More Is Betterlibxsmm 2-1.17-3645M N K: 256EPYC 9554 2PEPYC 9654 2P369121511.6710.07

OpenBenchmarking.orgGFLOPS/s Per Watt, More Is Betterlibxsmm 2-1.17-3645M N K: 32EPYC 9554 2PEPYC 9654 2P1.0762.1523.2284.3045.384.7823.609

OpenBenchmarking.orgGFLOPS/s Per Watt, More Is Betterlibxsmm 2-1.17-3645M N K: 64EPYC 9554 2PEPYC 9654 2P2468107.8395.975

OpenBenchmarking.orgGFLOPS/s, More Is Betterlibxsmm 2-1.17-3645M N K: 128EPYC 9554 2PEPYC 9654 2PXeon Max 9480 2P, HBM Caching9001800270036004500SE +/- 21.03, N = 3SE +/- 29.11, N = 3SE +/- 22.78, N = 94112.93426.11814.31. (CXX) g++ options: -dynamic -Bstatic -static-libgcc -lgomp -lm -lrt -ldl -lquadmath -lstdc++ -pthread -fPIC -std=c++14 -O2 -fopenmp-simd -funroll-loops -ftree-vectorize -fdata-sections -ffunction-sections -fvisibility=hidden -msse4.2

OpenBenchmarking.orgGFLOPS/s, More Is Betterlibxsmm 2-1.17-3645M N K: 256EPYC 9554 2PEPYC 9654 2P10002000300040005000SE +/- 34.70, N = 3SE +/- 47.44, N = 54603.34379.61. (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, More Is Betterlibxsmm 2-1.17-3645M N K: 32EPYC 9554 2PEPYC 9654 2P30060090012001500SE +/- 4.06, N = 8SE +/- 9.98, N = 151402.21298.01. (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, More Is Betterlibxsmm 2-1.17-3645M N K: 64EPYC 9554 2PEPYC 9654 2P6001200180024003000SE +/- 5.63, N = 7SE +/- 33.30, N = 152692.72270.21. (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

TensorFlow

OpenBenchmarking.orgimages/sec Per Watt, More Is BetterTensorFlow 2.12Device: CPU - Batch Size: 16 - Model: VGG-16EPYC 9554 2PEPYC 9654 2PXeon Max 9480 2P, HBM Caching0.03170.06340.09510.12680.15850.1410.1110.038

OpenBenchmarking.orgimages/sec, More Is BetterTensorFlow 2.12Device: CPU - Batch Size: 16 - Model: VGG-16EPYC 9554 2PEPYC 9654 2PXeon Max 9480 2P, HBM Caching1326395265SE +/- 0.59, N = 3SE +/- 0.39, N = 3SE +/- 0.61, N = 1560.3147.2721.09

OpenBenchmarking.orgimages/sec, More Is BetterTensorFlow 2.12Device: CPU - Batch Size: 16 - Model: AlexNetEPYC 9554 2PXeon Max 9480 2P, HBM CachingEPYC 9654 2P60120180240300SE +/- 3.19, N = 15SE +/- 1.10, N = 5SE +/- 2.70, N = 15257.94230.11166.20

OpenBenchmarking.orgimages/sec Per Watt, More Is BetterTensorFlow 2.12Device: CPU - Batch Size: 512 - Model: VGG-16EPYC 9654 2PEPYC 9554 2PXeon Max 9480 2P, HBM Caching0.04410.08820.13230.17640.22050.1960.1840.056

OpenBenchmarking.orgimages/sec Per Watt, More Is BetterTensorFlow 2.12Device: CPU - Batch Size: 512 - Model: AlexNetEPYC 9554 2PEPYC 9654 2PXeon Max 9480 2P, HBM Caching0.88271.76542.64813.53084.41353.9233.8501.305

OpenBenchmarking.orgimages/sec Per Watt, More Is BetterTensorFlow 2.12Device: CPU - Batch Size: 16 - Model: GoogLeNetEPYC 9554 2PEPYC 9654 2PXeon Max 9480 2P, HBM Caching0.07540.15080.22620.30160.3770.3350.1960.193

OpenBenchmarking.orgimages/sec Per Watt, More Is BetterTensorFlow 2.12Device: CPU - Batch Size: 16 - Model: ResNet-50EPYC 9554 2PEPYC 9654 2PXeon Max 9480 2P, HBM Caching0.02590.05180.07770.10360.12950.1150.0770.074

OpenBenchmarking.orgimages/sec, More Is BetterTensorFlow 2.12Device: CPU - Batch Size: 512 - Model: VGG-16EPYC 9654 2PEPYC 9554 2PXeon Max 9480 2P, HBM Caching306090120150SE +/- 0.08, N = 3SE +/- 1.46, N = 3SE +/- 0.33, N = 5120.62109.8930.19

OpenBenchmarking.orgimages/sec, More Is BetterTensorFlow 2.12Device: CPU - Batch Size: 512 - Model: AlexNetEPYC 9554 2PEPYC 9654 2PXeon Max 9480 2P, HBM Caching400800120016002000SE +/- 12.94, N = 3SE +/- 16.13, N = 7SE +/- 9.04, N = 31813.681757.16718.54

OpenBenchmarking.orgimages/sec, More Is BetterTensorFlow 2.12Device: CPU - Batch Size: 16 - Model: GoogLeNetXeon Max 9480 2P, HBM CachingEPYC 9554 2PEPYC 9654 2P20406080100SE +/- 0.98, N = 3SE +/- 0.91, N = 15SE +/- 1.21, N = 1598.4394.4164.49

OpenBenchmarking.orgimages/sec, More Is BetterTensorFlow 2.12Device: CPU - Batch Size: 16 - Model: ResNet-50Xeon Max 9480 2P, HBM CachingEPYC 9554 2PEPYC 9654 2P918273645SE +/- 0.32, N = 3SE +/- 0.23, N = 3SE +/- 0.31, N = 340.1533.4025.25

OpenBenchmarking.orgimages/sec, More Is BetterTensorFlow 2.12Device: CPU - Batch Size: 512 - Model: GoogLeNetEPYC 9554 2PEPYC 9654 2PXeon Max 9480 2P, HBM Caching130260390520650SE +/- 0.96, N = 3SE +/- 0.69, N = 3SE +/- 1.79, N = 3593.20535.52236.44

OpenBenchmarking.orgimages/sec, More Is BetterTensorFlow 2.12Device: CPU - Batch Size: 512 - Model: ResNet-50EPYC 9554 2PEPYC 9654 2PXeon Max 9480 2P, HBM Caching4080120160200SE +/- 0.70, N = 3SE +/- 0.26, N = 3SE +/- 0.66, N = 3188.17171.5676.93

ONNX Runtime

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

OpenBenchmarking.orgInferences Per Second, More Is BetterONNX Runtime 1.14Model: GPT-2 - Device: CPU - Executor: StandardXeon Max 9480 2P, HBM CachingEPYC 9554 2PEPYC 9654 2P50100150200250SE +/- 9.23, N = 15SE +/- 4.25, N = 15SE +/- 0.03, N = 3218.69132.72103.181. (CXX) g++ options: -ffunction-sections -fdata-sections -march=native -mtune=native -O3 -flto=auto -fno-fat-lto-objects -ldl -lrt

OpenBenchmarking.orgInferences Per Second, More Is BetterONNX Runtime 1.14Model: yolov4 - Device: CPU - Executor: StandardXeon Max 9480 2P, HBM CachingEPYC 9554 2PEPYC 9654 2P246810SE +/- 0.13594, N = 12SE +/- 0.03523, N = 3SE +/- 0.04001, N = 37.700465.105054.900331. (CXX) g++ options: -ffunction-sections -fdata-sections -march=native -mtune=native -O3 -flto=auto -fno-fat-lto-objects -ldl -lrt

OpenBenchmarking.orgInferences Per Second, More Is BetterONNX Runtime 1.14Model: bertsquad-12 - Device: CPU - Executor: StandardEPYC 9554 2PXeon Max 9480 2P, HBM CachingEPYC 9654 2P3691215SE +/- 0.19, N = 15SE +/- 0.23, N = 15SE +/- 0.24, N = 1511.6911.4610.181. (CXX) g++ options: -ffunction-sections -fdata-sections -march=native -mtune=native -O3 -flto=auto -fno-fat-lto-objects -ldl -lrt

OpenBenchmarking.orgInferences Per Second, More Is BetterONNX Runtime 1.14Model: CaffeNet 12-int8 - Device: CPU - Executor: StandardXeon Max 9480 2P, HBM CachingEPYC 9554 2PEPYC 9654 2P120240360480600SE +/- 8.12, N = 15SE +/- 5.94, N = 4SE +/- 7.41, N = 15562.22495.24435.191. (CXX) g++ options: -ffunction-sections -fdata-sections -march=native -mtune=native -O3 -flto=auto -fno-fat-lto-objects -ldl -lrt

OpenBenchmarking.orgInferences Per Second, More Is BetterONNX Runtime 1.14Model: fcn-resnet101-11 - Device: CPU - Executor: StandardXeon Max 9480 2P, HBM CachingEPYC 9654 2PEPYC 9554 2P1.20042.40083.60124.80166.002SE +/- 0.18914, N = 15SE +/- 0.02211, N = 3SE +/- 0.02211, N = 35.335144.697974.659821. (CXX) g++ options: -ffunction-sections -fdata-sections -march=native -mtune=native -O3 -flto=auto -fno-fat-lto-objects -ldl -lrt

OpenBenchmarking.orgInferences Per Second, More Is BetterONNX Runtime 1.14Model: ArcFace ResNet-100 - Device: CPU - Executor: StandardEPYC 9554 2PXeon Max 9480 2P, HBM CachingEPYC 9654 2P612182430SE +/- 0.09, N = 3SE +/- 0.34, N = 15SE +/- 0.09, N = 324.0123.7719.311. (CXX) g++ options: -ffunction-sections -fdata-sections -march=native -mtune=native -O3 -flto=auto -fno-fat-lto-objects -ldl -lrt

OpenBenchmarking.orgInferences Per Second, More Is BetterONNX Runtime 1.14Model: ResNet50 v1-12-int8 - Device: CPU - Executor: StandardEPYC 9554 2PEPYC 9654 2PXeon Max 9480 2P, HBM Caching306090120150SE +/- 1.11, N = 3SE +/- 3.31, N = 15SE +/- 2.29, N = 15152.44146.56125.281. (CXX) g++ options: -ffunction-sections -fdata-sections -march=native -mtune=native -O3 -flto=auto -fno-fat-lto-objects -ldl -lrt

oneDNN

MinAvgMaxXeon Max 9480 2P, HBM Caching260027973507OpenBenchmarking.orgMegahertz, More Is BetteroneDNN 3.1CPU Peak Freq (Highest CPU Core Frequency) Monitor10002000300040005000

MinAvgMaxXeon Max 9480 2P, HBM Caching260030873508OpenBenchmarking.orgMegahertz, More Is BetteroneDNN 3.1CPU Peak Freq (Highest CPU Core Frequency) Monitor10002000300040005000

MinAvgMaxXeon Max 9480 2P, HBM Caching209629513506OpenBenchmarking.orgMegahertz, More Is BetteroneDNN 3.1CPU Peak Freq (Highest CPU Core Frequency) Monitor10002000300040005000

MinAvgMaxXeon Max 9480 2P, HBM Caching216626513508OpenBenchmarking.orgMegahertz, More Is BetteroneDNN 3.1CPU Peak Freq (Highest CPU Core Frequency) Monitor10002000300040005000

MinAvgMaxXeon Max 9480 2P, HBM Caching190031073507OpenBenchmarking.orgMegahertz, More Is BetteroneDNN 3.1CPU Peak Freq (Highest CPU Core Frequency) Monitor10002000300040005000

OpenBenchmarking.orgMegahertz, More Is BetteroneDNN 3.1CPU Peak Freq (Highest CPU Core Frequency) MonitorXeon Max 9480 2P, HBM Caching6001200180024003000Min: 1951 / Avg: 2982.06 / Max: 3514

MinAvgMaxXeon Max 9480 2P, HBM Caching230027023507OpenBenchmarking.orgMegahertz, More Is BetteroneDNN 3.1CPU Peak Freq (Highest CPU Core Frequency) Monitor10002000300040005000

OpenVINO

MinAvgMaxXeon Max 9480 2P, HBM Caching120017403505OpenBenchmarking.orgMegahertz, More Is BetterOpenVINO 2022.3CPU Peak Freq (Highest CPU Core Frequency) Monitor10002000300040005000

MinAvgMaxXeon Max 9480 2P, HBM Caching190030233512OpenBenchmarking.orgMegahertz, More Is BetterOpenVINO 2022.3CPU Peak Freq (Highest CPU Core Frequency) Monitor10002000300040005000

MinAvgMaxXeon Max 9480 2P, HBM Caching190030743506OpenBenchmarking.orgMegahertz, More Is BetterOpenVINO 2022.3CPU Peak Freq (Highest CPU Core Frequency) Monitor10002000300040005000

MinAvgMaxXeon Max 9480 2P, HBM Caching130017383501OpenBenchmarking.orgMegahertz, More Is BetterOpenVINO 2022.3CPU Peak Freq (Highest CPU Core Frequency) Monitor10002000300040005000

MinAvgMaxXeon Max 9480 2P, HBM Caching170023703505OpenBenchmarking.orgMegahertz, More Is BetterOpenVINO 2022.3CPU Peak Freq (Highest CPU Core Frequency) Monitor10002000300040005000

MinAvgMaxXeon Max 9480 2P, HBM Caching130016853500OpenBenchmarking.orgMegahertz, More Is BetterOpenVINO 2022.3CPU Peak Freq (Highest CPU Core Frequency) Monitor10002000300040005000

MinAvgMaxXeon Max 9480 2P, HBM Caching170019003500OpenBenchmarking.orgMegahertz, More Is BetterOpenVINO 2022.3CPU Peak Freq (Highest CPU Core Frequency) Monitor10002000300040005000

MinAvgMaxXeon Max 9480 2P, HBM Caching170020893501OpenBenchmarking.orgMegahertz, More Is BetterOpenVINO 2022.3CPU Peak Freq (Highest CPU Core Frequency) Monitor10002000300040005000

MinAvgMaxXeon Max 9480 2P, HBM Caching150019023504OpenBenchmarking.orgMegahertz, More Is BetterOpenVINO 2022.3CPU Peak Freq (Highest CPU Core Frequency) Monitor10002000300040005000

MinAvgMaxXeon Max 9480 2P, HBM Caching160021253502OpenBenchmarking.orgMegahertz, More Is BetterOpenVINO 2022.3CPU Peak Freq (Highest CPU Core Frequency) Monitor10002000300040005000

MinAvgMaxXeon Max 9480 2P, HBM Caching190034263501OpenBenchmarking.orgMegahertz, More Is BetterOpenVINO 2022.3CPU Peak Freq (Highest CPU Core Frequency) Monitor10002000300040005000

MinAvgMaxXeon Max 9480 2P, HBM Caching110020993500OpenBenchmarking.orgMegahertz, More Is BetterOpenVINO 2022.3CPU Peak Freq (Highest CPU Core Frequency) Monitor10002000300040005000

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: IP Shapes 1D - Data Type: bf16bf16bf16 - Engine: CPUXeon Max 9480 2P, HBM CachingEPYC 9554 2PEPYC 9654 2P48121620SE +/- 0.22497, N = 15SE +/- 0.95058, N = 12SE +/- 0.81790, N = 157.8801611.1966916.98230MIN: 4.45MIN: 5.64MIN: 8.091. (CXX) g++ options: -O3 -march=native -fopenmp -msse4.1 -fPIC -pie -ldl -lpthread

OpenBenchmarking.orgms, Fewer Is BetteroneDNN 3.1Harness: IP Shapes 3D - Data Type: bf16bf16bf16 - Engine: CPUEPYC 9554 2PEPYC 9654 2PXeon Max 9480 2P, HBM Caching20406080100SE +/- 0.02374, N = 15SE +/- 0.03459, N = 15SE +/- 0.61972, N = 52.205963.8020991.98140MIN: 79.161. (CXX) g++ options: -O3 -march=native -fopenmp -msse4.1 -fPIC -pie -ldl -lpthread

OpenBenchmarking.orgms, Fewer Is BetteroneDNN 3.1Harness: Convolution Batch Shapes Auto - Data Type: bf16bf16bf16 - Engine: CPUEPYC 9554 2PEPYC 9654 2PXeon Max 9480 2P, HBM Caching0.82661.65322.47983.30644.133SE +/- 0.002531, N = 7SE +/- 0.003345, N = 15SE +/- 0.025287, N = 70.3113780.4610533.673560MIN: 3.031. (CXX) g++ options: -O3 -march=native -fopenmp -msse4.1 -fPIC -pie -ldl -lpthread

OpenBenchmarking.orgms, Fewer Is BetteroneDNN 3.1Harness: Deconvolution Batch shapes_1d - Data Type: bf16bf16bf16 - Engine: CPUXeon Max 9480 2P, HBM CachingEPYC 9554 2PEPYC 9654 2P0.571.141.712.282.85SE +/- 0.009112, N = 15SE +/- 0.003878, N = 3SE +/- 0.004515, N = 30.4830751.7616202.533260MIN: 1.59MIN: 1.71. (CXX) g++ options: -O3 -march=native -fopenmp -msse4.1 -fPIC -pie -ldl -lpthread

OpenBenchmarking.orgms, Fewer Is BetteroneDNN 3.1Harness: Deconvolution Batch shapes_3d - Data Type: bf16bf16bf16 - Engine: CPUEPYC 9554 2PEPYC 9654 2PXeon Max 9480 2P, HBM Caching0.79541.59082.38623.18163.977SE +/- 0.002054, N = 9SE +/- 0.004782, N = 9SE +/- 0.029518, N = 150.4572720.7321003.535250MIN: 2.461. (CXX) g++ options: -O3 -march=native -fopenmp -msse4.1 -fPIC -pie -ldl -lpthread

OpenBenchmarking.orgms, Fewer Is BetteroneDNN 3.1Harness: Recurrent Neural Network Training - Data Type: bf16bf16bf16 - Engine: CPUEPYC 9554 2PEPYC 9654 2PXeon Max 9480 2P, HBM Caching3K6K9K12K15KSE +/- 13.50, N = 5SE +/- 18.00, N = 3SE +/- 507.18, N = 101305.662492.6915294.60MIN: 7750.751. (CXX) g++ options: -O3 -march=native -fopenmp -msse4.1 -fPIC -pie -ldl -lpthread

OpenBenchmarking.orgms, Fewer Is BetteroneDNN 3.1Harness: Recurrent Neural Network Inference - Data Type: bf16bf16bf16 - Engine: CPUEPYC 9554 2PXeon Max 9480 2P, HBM CachingEPYC 9654 2P6001200180024003000SE +/- 2.71, N = 3SE +/- 20.64, N = 12SE +/- 29.80, N = 15925.771325.452790.90MIN: 909.67MIN: 1025.18MIN: 2391.981. (CXX) g++ options: -O3 -march=native -fopenmp -msse4.1 -fPIC -pie -ldl -lpthread

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: Face Detection FP16 - Device: CPUXeon Max 9480 2P, HBM CachingEPYC 9554 2PEPYC 9654 2P100200300400500SE +/- 0.80, N = 3SE +/- 0.19, N = 3SE +/- 0.93, N = 3232.01389.53471.82MIN: 138.61 / MAX: 770.45MIN: 380.82 / MAX: 432.57MIN: 431.51 / MAX: 569.31. (CXX) g++ options: -isystem -fsigned-char -ffunction-sections -fdata-sections -msse4.1 -msse4.2 -O3 -fno-strict-overflow -fwrapv -fPIC -fvisibility=hidden -Os -std=c++11 -MD -MT -MF

OpenBenchmarking.orgms, Fewer Is BetterOpenVINO 2022.3Model: Person Detection FP16 - Device: CPUEPYC 9554 2PXeon Max 9480 2P, HBM CachingEPYC 9654 2P2004006008001000SE +/- 5.30, N = 3SE +/- 6.17, N = 3SE +/- 5.11, N = 3832.02834.971092.97MIN: 743.95 / MAX: 1258.17MIN: 558.93 / MAX: 2258.39MIN: 825.28 / MAX: 1814.821. (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: CPUXeon Max 9480 2P, HBM CachingEPYC 9554 2PEPYC 9654 2P2004006008001000SE +/- 7.20, N = 3SE +/- 1.07, N = 3SE +/- 5.33, N = 3819.76825.521098.96MIN: 516.88 / MAX: 2598.39MIN: 747.05 / MAX: 1238.39MIN: 825.62 / MAX: 1835.761. (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: Vehicle Detection FP16 - Device: CPUEPYC 9554 2PEPYC 9654 2PXeon Max 9480 2P, HBM Caching3691215SE +/- 0.00, N = 3SE +/- 0.00, N = 3SE +/- 0.08, N = 135.346.4912.07MIN: 4.89 / MAX: 34.7MIN: 5.03 / MAX: 55.65MIN: 7.38 / MAX: 250.921. (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: CPUEPYC 9554 2PEPYC 9654 2PXeon Max 9480 2P, HBM Caching70140210280350SE +/- 0.22, N = 3SE +/- 0.04, N = 3SE +/- 0.44, N = 3205.71250.39333.51MIN: 202.38 / MAX: 252.14MIN: 222.36 / MAX: 303.72MIN: 285.32 / MAX: 516.281. (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: Vehicle Detection FP16-INT8 - Device: CPUEPYC 9554 2PEPYC 9654 2PXeon Max 9480 2P, HBM Caching510152025SE +/- 0.00, N = 3SE +/- 0.00, N = 3SE +/- 0.09, N = 33.544.3620.23MIN: 3.45 / MAX: 21.7MIN: 3.52 / MAX: 38.49MIN: 12.69 / MAX: 166.761. (CXX) g++ options: -isystem -fsigned-char -ffunction-sections -fdata-sections -msse4.1 -msse4.2 -O3 -fno-strict-overflow -fwrapv -fPIC -fvisibility=hidden -Os -std=c++11 -MD -MT -MF

OpenBenchmarking.orgms, Fewer Is BetterOpenVINO 2022.3Model: Weld Porosity Detection FP16 - Device: CPUEPYC 9554 2PEPYC 9654 2PXeon Max 9480 2P, HBM Caching246810SE +/- 0.00, N = 3SE +/- 0.00, N = 3SE +/- 0.01, N = 33.974.866.44MIN: 3.87 / MAX: 17.35MIN: 4.02 / MAX: 36.01MIN: 4.24 / MAX: 49.431. (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: CPUEPYC 9554 2PXeon Max 9480 2P, HBM CachingEPYC 9654 2P1122334455SE +/- 0.08, N = 3SE +/- 0.01, N = 3SE +/- 0.04, N = 340.6747.2950.42MIN: 34.96 / MAX: 124.31MIN: 32.14 / MAX: 577.78MIN: 39.07 / MAX: 280.941. (CXX) g++ options: -isystem -fsigned-char -ffunction-sections -fdata-sections -msse4.1 -msse4.2 -O3 -fno-strict-overflow -fwrapv -fPIC -fvisibility=hidden -Os -std=c++11 -MD -MT -MF

OpenBenchmarking.orgms, Fewer Is BetterOpenVINO 2022.3Model: Weld Porosity Detection FP16-INT8 - Device: CPUXeon Max 9480 2P, HBM CachingEPYC 9554 2PEPYC 9654 2P3691215SE +/- 0.00, N = 3SE +/- 0.00, N = 3SE +/- 0.00, N = 33.478.099.95MIN: 2.48 / MAX: 56.57MIN: 7.89 / MAX: 45.39MIN: 8.36 / MAX: 40.391. (CXX) g++ options: -isystem -fsigned-char -ffunction-sections -fdata-sections -msse4.1 -msse4.2 -O3 -fno-strict-overflow -fwrapv -fPIC -fvisibility=hidden -Os -std=c++11 -MD -MT -MF

OpenBenchmarking.orgms, Fewer Is BetterOpenVINO 2022.3Model: Person Vehicle Bike Detection FP16 - Device: CPUEPYC 9554 2PEPYC 9654 2PXeon Max 9480 2P, HBM Caching48121620SE +/- 0.01, N = 3SE +/- 0.00, N = 3SE +/- 0.02, N = 34.295.2517.83MIN: 4.11 / MAX: 21.83MIN: 4.36 / MAX: 23.21MIN: 13.06 / MAX: 147.361. (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: Age Gender Recognition Retail 0013 FP16 - Device: CPUXeon Max 9480 2P, HBM CachingEPYC 9554 2PEPYC 9654 2P0.12380.24760.37140.49520.619SE +/- 0.00, N = 3SE +/- 0.00, N = 3SE +/- 0.00, N = 30.440.520.55MIN: 0.33 / MAX: 42.85MIN: 0.49 / MAX: 50.12MIN: 0.5 / MAX: 45.731. (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: Age Gender Recognition Retail 0013 FP16-INT8 - Device: CPUEPYC 9554 2PEPYC 9654 2PXeon Max 9480 2P, HBM Caching0.3150.630.9451.261.575SE +/- 0.00, N = 3SE +/- 0.00, N = 3SE +/- 0.04, N = 120.880.991.40MIN: 0.83 / MAX: 24.85MIN: 0.85 / MAX: 37.79MIN: 0.7 / MAX: 123.261. (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

80 Results Shown

CPU Peak Freq (Highest CPU Core Frequency) Monitor:
  Phoronix Test Suite System Monitoring:
    Megahertz
    Watts
    Watts
OpenVINO:
  Face Detection FP16 - CPU
  Person Detection FP16 - CPU
  Person Detection FP32 - CPU
  Vehicle Detection FP16 - CPU
  Face Detection FP16-INT8 - CPU
  Vehicle Detection FP16-INT8 - CPU
  Weld Porosity Detection FP16 - CPU
  Machine Translation EN To DE FP16 - CPU
  Weld Porosity Detection FP16-INT8 - CPU
  Person Vehicle Bike Detection FP16 - CPU
  Age Gender Recognition Retail 0013 FP16 - CPU
  Age Gender Recognition Retail 0013 FP16-INT8 - CPU
libxsmm:
  256
  32
  64
libxsmm:
  128
  256
  32
  64
TensorFlow
TensorFlow:
  CPU - 16 - VGG-16
  CPU - 16 - AlexNet
TensorFlow:
  CPU - 512 - VGG-16
  CPU - 512 - AlexNet
  CPU - 16 - GoogLeNet
  CPU - 16 - ResNet-50
TensorFlow:
  CPU - 512 - VGG-16
  CPU - 512 - AlexNet
  CPU - 16 - GoogLeNet
  CPU - 16 - ResNet-50
  CPU - 512 - GoogLeNet
  CPU - 512 - ResNet-50
ONNX Runtime:
  GPT-2 - CPU - Standard
  yolov4 - CPU - Standard
  bertsquad-12 - CPU - Standard
  CaffeNet 12-int8 - CPU - Standard
  fcn-resnet101-11 - CPU - Standard
  ArcFace ResNet-100 - CPU - Standard
  ResNet50 v1-12-int8 - CPU - Standard
oneDNN:
  CPU Peak Freq (Highest CPU Core Frequency) Monitor:
    Megahertz
    Megahertz
    Megahertz
    Megahertz
    Megahertz
    Megahertz
    Megahertz
    Megahertz
    Megahertz
    Megahertz
    Megahertz
    Megahertz
    Megahertz
    Megahertz
    Megahertz
    Megahertz
    Megahertz
    Megahertz
    Megahertz
oneDNN:
  IP Shapes 1D - bf16bf16bf16 - CPU
  IP Shapes 3D - bf16bf16bf16 - CPU
  Convolution Batch Shapes Auto - bf16bf16bf16 - CPU
  Deconvolution Batch shapes_1d - bf16bf16bf16 - CPU
  Deconvolution Batch shapes_3d - bf16bf16bf16 - CPU
  Recurrent Neural Network Training - bf16bf16bf16 - CPU
  Recurrent Neural Network Inference - bf16bf16bf16 - CPU
OpenVINO:
  Face Detection FP16 - CPU
  Person Detection FP16 - CPU
  Person Detection FP32 - CPU
  Vehicle Detection FP16 - CPU
  Face Detection FP16-INT8 - CPU
  Vehicle Detection FP16-INT8 - CPU
  Weld Porosity Detection FP16 - CPU
  Machine Translation EN To DE FP16 - CPU
  Weld Porosity Detection FP16-INT8 - CPU
  Person Vehicle Bike Detection FP16 - CPU
  Age Gender Recognition Retail 0013 FP16 - CPU
  Age Gender Recognition Retail 0013 FP16-INT8 - CPU