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2 x Intel Xeon Max 9468 testing with a Supermicro X13DEM v1.10 (1.3 BIOS) and ASPEED on Ubuntu 23.04 via the Phoronix Test Suite.

Compare your own system(s) to this result file with the Phoronix Test Suite by running the command: phoronix-test-suite benchmark 2306210-NE-AI780463786
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a
June 21 2023
  1 Hour, 3 Minutes
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June 21 2023
  1 Hour, 2 Minutes
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June 21 2023
  3 Hours, 56 Minutes
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June 21 2023
  1 Hour, 2 Minutes
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aiOpenBenchmarking.orgPhoronix Test Suite2 x Intel Xeon Max 9468 @ 3.50GHz (96 Cores / 192 Threads)Supermicro X13DEM v1.10 (1.3 BIOS)Intel Device 1bce512GB7682GB INTEL SSDPF2KX076TZASPEEDVE2282 x Broadcom BCM57508 NetXtreme-E 10Gb/25Gb/40Gb/50Gb/100Gb/200GbUbuntu 23.046.2.0-20-generic (x86_64)GNOME Shell 44.0X Server 1.21.1.7GCC 12.2.0ext41920x1080ProcessorMotherboardChipsetMemoryDiskGraphicsMonitorNetworkOSKernelDesktopDisplay ServerCompilerFile-SystemScreen ResolutionAi BenchmarksSystem Logs- Transparent Huge Pages: madvise- --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 - Scaling Governor: intel_cpufreq performance - CPU Microcode: 0x2c0001d1- Python 3.11.2- 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

abcdResult OverviewPhoronix Test Suite100%102%104%106%109%TensorFlowTensorFlowTensorFlowTensorFlowOpenVINOOpenVINOTensorFlowTensorFlowTensorFlowOpenVINOTensorFlowTensorFlowTensorFlowTensorFlowTensorFlowOpenVINOOpenVINOTensorFlowTensorFlowOpenVINOOpenVINOOpenVINOOpenVINOOpenVINOOpenVINOOpenVINOTensorFlowOpenVINOOpenVINOOpenVINOOpenVINOOpenVINOOpenVINOOpenVINOOpenVINOOpenVINOOpenVINOOpenVINOOpenVINOCPU - 32 - GoogLeNetCPU - 32 - AlexNetCPU - 512 - ResNet-50CPU - 32 - ResNet-50F.D.F - CPUF.D.F - CPUCPU - 64 - AlexNetCPU - 16 - AlexNetCPU - 256 - GoogLeNetA.G.R.R.0.F.I - CPUCPU - 256 - AlexNetCPU - 64 - GoogLeNetCPU - 16 - GoogLeNetCPU - 64 - ResNet-50CPU - 512 - AlexNetP.D.F - CPUP.D.F - CPUCPU - 256 - ResNet-50CPU - 512 - GoogLeNetP.D.F - CPUP.D.F - CPUA.G.R.R.0.F - CPUP.V.B.D.F - CPUW.P.D.F.I - CPUP.V.B.D.F - CPUA.G.R.R.0.F.I - CPUCPU - 16 - ResNet-50F.D.F.I - CPUV.D.F.I - CPUV.D.F.I - CPUF.D.F.I - CPUW.P.D.F - CPUW.P.D.F - CPUM.T.E.T.D.F - CPUM.T.E.T.D.F - CPUV.D.F - CPUV.D.F - CPUW.P.D.F.I - CPUA.G.R.R.0.F - CPU

aitensorflow: CPU - 16 - AlexNettensorflow: CPU - 32 - AlexNettensorflow: CPU - 64 - AlexNettensorflow: CPU - 256 - AlexNettensorflow: CPU - 512 - AlexNettensorflow: CPU - 16 - GoogLeNettensorflow: CPU - 16 - ResNet-50tensorflow: CPU - 32 - GoogLeNettensorflow: CPU - 32 - ResNet-50tensorflow: CPU - 64 - GoogLeNettensorflow: CPU - 64 - ResNet-50tensorflow: CPU - 256 - GoogLeNettensorflow: CPU - 256 - ResNet-50tensorflow: CPU - 512 - GoogLeNettensorflow: CPU - 512 - ResNet-50openvino: Face Detection FP16 - CPUopenvino: Face Detection FP16 - CPUopenvino: Person Detection FP16 - CPUopenvino: Person Detection FP16 - CPUopenvino: Person Detection FP32 - CPUopenvino: Person Detection FP32 - CPUopenvino: Vehicle Detection FP16 - CPUopenvino: Vehicle Detection FP16 - CPUopenvino: Face Detection FP16-INT8 - CPUopenvino: Face Detection FP16-INT8 - CPUopenvino: Vehicle Detection FP16-INT8 - CPUopenvino: Vehicle Detection FP16-INT8 - CPUopenvino: Weld Porosity Detection FP16 - CPUopenvino: Weld Porosity 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: Person Vehicle Bike Detection FP16 - CPUopenvino: Person Vehicle Bike Detection FP16 - CPUopenvino: Age Gender Recognition Retail 0013 FP16 - CPUopenvino: Age Gender Recognition Retail 0013 FP16 - CPUopenvino: Age Gender Recognition Retail 0013 FP16-INT8 - CPUopenvino: Age Gender Recognition Retail 0013 FP16-INT8 - CPUabcd240373.54431.07585.76685.25104.3940.35129.1350.86159.0557.69209.5370.97232.3672.6159.92149.9234.12700.1634.32696.172922.388.19325.25294.465630.2917.0215718.165.97643.4537.2431933.232.966280.3415.25110460.510.468911.421.12229.08361.25450.94593.27671.22105.3940.64138.147.79154.8959.23200.669.57234.3576.96158.39151.3533.97703.8534.35696.772926.318.18324.86294.875637.811715755.635.94641.2137.3632169.372.956303.615.19111897.590.469578.861.13240.69356.69445.77609.80666.10104.2640.35136.9950.61157.3157.17206.5370.31237.4877.77151.47158.8834.20699.3833.70709.072920.108.19325.91293.865628.2017.0315763.435.94640.3937.4132075.692.966270.5715.27112093.020.469611.401.13229.92347.6453.77599.68679.84101.5440.5140.1550.58152.9257.12206.771.32235.2177.76159.12150.6634.48693.1433.4715.442931.838.16326.61293.135661.2616.9315797.25.94641.2337.3732249.872.956240.1715.34112095.520.466799.281.13OpenBenchmarking.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: 16 - Model: AlexNetabcd50100150200250SE +/- 2.42, N = 15240.00229.08240.69229.92

OpenBenchmarking.orgimages/sec, More Is BetterTensorFlow 2.12Device: CPU - Batch Size: 32 - Model: AlexNetabcd80160240320400SE +/- 3.63, N = 3373.54361.25356.69347.60

OpenBenchmarking.orgimages/sec, More Is BetterTensorFlow 2.12Device: CPU - Batch Size: 64 - Model: AlexNetabcd100200300400500SE +/- 5.55, N = 4431.07450.94445.77453.77

OpenBenchmarking.orgimages/sec, More Is BetterTensorFlow 2.12Device: CPU - Batch Size: 256 - Model: AlexNetabcd130260390520650SE +/- 5.92, N = 6585.76593.27609.80599.68

OpenBenchmarking.orgimages/sec, More Is BetterTensorFlow 2.12Device: CPU - Batch Size: 512 - Model: AlexNetabcd150300450600750SE +/- 1.85, N = 3685.25671.22666.10679.84

OpenBenchmarking.orgimages/sec, More Is BetterTensorFlow 2.12Device: CPU - Batch Size: 16 - Model: GoogLeNetabcd20406080100SE +/- 1.06, N = 15104.39105.39104.26101.54

OpenBenchmarking.orgimages/sec, More Is BetterTensorFlow 2.12Device: CPU - Batch Size: 16 - Model: ResNet-50abcd918273645SE +/- 0.34, N = 340.3540.6440.3540.50

OpenBenchmarking.orgimages/sec, More Is BetterTensorFlow 2.12Device: CPU - Batch Size: 32 - Model: GoogLeNetabcd306090120150SE +/- 1.50, N = 4129.13138.10136.99140.15

OpenBenchmarking.orgimages/sec, More Is BetterTensorFlow 2.12Device: CPU - Batch Size: 32 - Model: ResNet-50abcd1122334455SE +/- 0.52, N = 550.8647.7950.6150.58

OpenBenchmarking.orgimages/sec, More Is BetterTensorFlow 2.12Device: CPU - Batch Size: 64 - Model: GoogLeNetabcd4080120160200SE +/- 1.59, N = 15159.05154.89157.31152.92

OpenBenchmarking.orgimages/sec, More Is BetterTensorFlow 2.12Device: CPU - Batch Size: 64 - Model: ResNet-50abcd1326395265SE +/- 0.48, N = 357.6959.2357.1757.12

OpenBenchmarking.orgimages/sec, More Is BetterTensorFlow 2.12Device: CPU - Batch Size: 256 - Model: GoogLeNetabcd50100150200250SE +/- 2.48, N = 4209.53200.60206.53206.70

OpenBenchmarking.orgimages/sec, More Is BetterTensorFlow 2.12Device: CPU - Batch Size: 256 - Model: ResNet-50abcd1632486480SE +/- 0.46, N = 370.9769.5770.3171.32

OpenBenchmarking.orgimages/sec, More Is BetterTensorFlow 2.12Device: CPU - Batch Size: 512 - Model: GoogLeNetabcd50100150200250SE +/- 2.29, N = 3232.36234.35237.48235.21

OpenBenchmarking.orgimages/sec, More Is BetterTensorFlow 2.12Device: CPU - Batch Size: 512 - Model: ResNet-50abcd20406080100SE +/- 0.46, N = 372.6076.9677.7777.76

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: CPUabcd4080120160200SE +/- 2.51, N = 15159.92158.39151.47159.121. (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.orgms, Fewer Is BetterOpenVINO 2022.3Model: Face Detection FP16 - Device: CPUabcd4080120160200SE +/- 2.76, N = 15149.92151.35158.88150.66MIN: 119.1 / MAX: 310.39MIN: 120.35 / MAX: 358.51MIN: 113.05 / MAX: 433.03MIN: 119.46 / MAX: 358.121. (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: Person Detection FP16 - Device: CPUabcd816243240SE +/- 0.19, N = 334.1233.9734.2034.481. (CXX) g++ options: -isystem -fsigned-char -ffunction-sections -fdata-sections -msse4.1 -msse4.2 -O3 -fno-strict-overflow -fwrapv -fPIC -fvisibility=hidden -Os -std=c++11 -MD -MT -MF

OpenBenchmarking.orgms, Fewer Is BetterOpenVINO 2022.3Model: Person Detection FP16 - Device: CPUabcd150300450600750SE +/- 4.13, N = 3700.16703.85699.38693.14MIN: 452.33 / MAX: 1789.1MIN: 448.43 / MAX: 1668.72MIN: 514.52 / MAX: 1681.15MIN: 410.77 / MAX: 1590.991. (CXX) g++ options: -isystem -fsigned-char -ffunction-sections -fdata-sections -msse4.1 -msse4.2 -O3 -fno-strict-overflow -fwrapv -fPIC -fvisibility=hidden -Os -std=c++11 -MD -MT -MF

OpenBenchmarking.orgFPS, More Is BetterOpenVINO 2022.3Model: Person Detection FP32 - Device: CPUabcd816243240SE +/- 0.21, N = 334.3234.3533.7033.401. (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: Person Detection FP32 - Device: CPUabcd150300450600750SE +/- 4.23, N = 3696.17696.77709.07715.44MIN: 486.45 / MAX: 1616.8MIN: 507.9 / MAX: 1821.8MIN: 484.14 / MAX: 1950.13MIN: 545.06 / MAX: 1928.171. (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: CPUabcd6001200180024003000SE +/- 4.50, N = 32922.382926.312920.102931.831. (CXX) g++ options: -isystem -fsigned-char -ffunction-sections -fdata-sections -msse4.1 -msse4.2 -O3 -fno-strict-overflow -fwrapv -fPIC -fvisibility=hidden -Os -std=c++11 -MD -MT -MF

OpenBenchmarking.orgms, Fewer Is BetterOpenVINO 2022.3Model: Vehicle Detection FP16 - Device: CPUabcd246810SE +/- 0.01, N = 38.198.188.198.16MIN: 6.68 / MAX: 62.91MIN: 6.61 / MAX: 66.24MIN: 6.58 / MAX: 70.46MIN: 6.73 / MAX: 68.571. (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: Face Detection FP16-INT8 - Device: CPUabcd70140210280350SE +/- 0.30, N = 3325.25324.86325.91326.611. (CXX) g++ options: -isystem -fsigned-char -ffunction-sections -fdata-sections -msse4.1 -msse4.2 -O3 -fno-strict-overflow -fwrapv -fPIC -fvisibility=hidden -Os -std=c++11 -MD -MT -MF

OpenBenchmarking.orgms, Fewer Is BetterOpenVINO 2022.3Model: Face Detection FP16-INT8 - Device: CPUabcd60120180240300SE +/- 0.27, N = 3294.46294.87293.86293.13MIN: 247.31 / MAX: 419.59MIN: 226.08 / MAX: 443.68MIN: 243.71 / MAX: 469.02MIN: 263.72 / MAX: 522.861. (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: CPUabcd12002400360048006000SE +/- 10.49, N = 35630.295637.815628.205661.261. (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

OpenBenchmarking.orgms, Fewer Is BetterOpenVINO 2022.3Model: Vehicle Detection FP16-INT8 - Device: CPUabcd48121620SE +/- 0.03, N = 317.0217.0017.0316.93MIN: 12.75 / MAX: 119.51MIN: 12.73 / MAX: 119.86MIN: 12.56 / MAX: 127.18MIN: 13.05 / MAX: 111.311. (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: CPUabcd3K6K9K12K15KSE +/- 46.70, N = 315718.1615755.6315763.4315797.201. (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: CPUabcd1.34332.68664.02995.37326.7165SE +/- 0.02, N = 35.975.945.945.94MIN: 4.29 / MAX: 50.42MIN: 4.34 / MAX: 46.22MIN: 4.05 / MAX: 48.91MIN: 4.16 / MAX: 39.511. (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: CPUabcd140280420560700SE +/- 1.24, N = 3643.45641.21640.39641.231. (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: CPUabcd918273645SE +/- 0.07, N = 337.2437.3637.4137.37MIN: 29.9 / MAX: 223.47MIN: 29.38 / MAX: 311.72MIN: 30.15 / MAX: 313.15MIN: 29.21 / MAX: 165.631. (CXX) g++ options: -isystem -fsigned-char -ffunction-sections -fdata-sections -msse4.1 -msse4.2 -O3 -fno-strict-overflow -fwrapv -fPIC -fvisibility=hidden -Os -std=c++11 -MD -MT -MF

OpenBenchmarking.orgFPS, More Is BetterOpenVINO 2022.3Model: Weld Porosity Detection FP16-INT8 - Device: CPUabcd7K14K21K28K35KSE +/- 77.08, N = 331933.2332169.3732075.6932249.871. (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: CPUabcd0.6661.3321.9982.6643.33SE +/- 0.01, N = 32.962.952.962.95MIN: 2.39 / MAX: 71.74MIN: 2.31 / MAX: 64.16MIN: 2.36 / MAX: 80.4MIN: 2.37 / MAX: 60.041. (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 Vehicle Bike Detection FP16 - Device: CPUabcd14002800420056007000SE +/- 17.13, N = 36280.346303.606270.576240.171. (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: CPUabcd48121620SE +/- 0.04, N = 315.2515.1915.2715.34MIN: 12.68 / MAX: 103.08MIN: 12.88 / MAX: 123.19MIN: 12.18 / MAX: 108.89MIN: 12.8 / MAX: 110.561. (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

OpenBenchmarking.orgFPS, More Is BetterOpenVINO 2022.3Model: Age Gender Recognition Retail 0013 FP16 - Device: CPUabcd20K40K60K80K100KSE +/- 450.23, N = 3110460.51111897.59112093.02112095.521. (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: CPUabcd0.090.180.270.360.45SE +/- 0.00, N = 30.40.40.40.4MIN: 0.31 / MAX: 24.44MIN: 0.33 / MAX: 23.94MIN: 0.31 / MAX: 37.77MIN: 0.32 / MAX: 28.361. (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.orgFPS, More Is BetterOpenVINO 2022.3Model: Age Gender Recognition Retail 0013 FP16-INT8 - Device: CPUabcd15K30K45K60K75KSE +/- 696.32, N = 368911.4269578.8669611.4066799.281. (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: Age Gender Recognition Retail 0013 FP16-INT8 - Device: CPUabcd0.25430.50860.76291.01721.2715SE +/- 0.00, N = 31.121.131.131.13MIN: 0.81 / MAX: 35.87MIN: 0.78 / MAX: 30.57MIN: 0.8 / MAX: 39.35MIN: 0.78 / MAX: 28.191. (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

39 Results Shown

TensorFlow:
  CPU - 16 - AlexNet
  CPU - 32 - AlexNet
  CPU - 64 - AlexNet
  CPU - 256 - AlexNet
  CPU - 512 - AlexNet
  CPU - 16 - GoogLeNet
  CPU - 16 - ResNet-50
  CPU - 32 - GoogLeNet
  CPU - 32 - ResNet-50
  CPU - 64 - GoogLeNet
  CPU - 64 - ResNet-50
  CPU - 256 - GoogLeNet
  CPU - 256 - ResNet-50
  CPU - 512 - GoogLeNet
  CPU - 512 - ResNet-50
OpenVINO:
  Face Detection FP16 - CPU:
    FPS
    ms
  Person Detection FP16 - CPU:
    FPS
    ms
  Person Detection FP32 - CPU:
    FPS
    ms
  Vehicle Detection FP16 - CPU:
    FPS
    ms
  Face Detection FP16-INT8 - CPU:
    FPS
    ms
  Vehicle Detection FP16-INT8 - CPU:
    FPS
    ms
  Weld Porosity Detection FP16 - CPU:
    FPS
    ms
  Machine Translation EN To DE FP16 - CPU:
    FPS
    ms
  Weld Porosity Detection FP16-INT8 - CPU:
    FPS
    ms
  Person Vehicle Bike Detection FP16 - CPU:
    FPS
    ms
  Age Gender Recognition Retail 0013 FP16 - CPU:
    FPS
    ms
  Age Gender Recognition Retail 0013 FP16-INT8 - CPU:
    FPS
    ms