ai

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.

HTML result view exported from: https://openbenchmarking.org/result/2306210-NE-AI780463786&grs.

aiProcessorMotherboardChipsetMemoryDiskGraphicsMonitorNetworkOSKernelDesktopDisplay ServerCompilerFile-SystemScreen Resolutionabcd2 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 12.2.0ext41920x1080OpenBenchmarking.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- Scaling Governor: intel_cpufreq performance - CPU Microcode: 0x2c0001d1Python Details- Python 3.11.2Security Details- 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

aitensorflow: CPU - 32 - GoogLeNettensorflow: CPU - 32 - AlexNettensorflow: CPU - 512 - ResNet-50tensorflow: CPU - 32 - ResNet-50tensorflow: CPU - 64 - AlexNettensorflow: CPU - 16 - AlexNettensorflow: CPU - 256 - GoogLeNetopenvino: Age Gender Recognition Retail 0013 FP16-INT8 - CPUtensorflow: CPU - 256 - AlexNettensorflow: CPU - 64 - GoogLeNettensorflow: CPU - 16 - GoogLeNettensorflow: CPU - 64 - ResNet-50tensorflow: CPU - 512 - AlexNetopenvino: Person Detection FP32 - CPUopenvino: Person Detection FP32 - CPUtensorflow: CPU - 256 - ResNet-50tensorflow: CPU - 512 - GoogLeNetopenvino: Person Detection FP16 - CPUopenvino: Person Detection FP16 - CPUopenvino: Age Gender Recognition Retail 0013 FP16 - CPUopenvino: Person Vehicle Bike Detection FP16 - CPUopenvino: Weld Porosity Detection FP16-INT8 - CPUopenvino: Person Vehicle Bike Detection FP16 - CPUopenvino: Age Gender Recognition Retail 0013 FP16-INT8 - CPUtensorflow: CPU - 16 - ResNet-50openvino: Face Detection FP16-INT8 - CPUopenvino: Vehicle Detection FP16-INT8 - CPUopenvino: Vehicle Detection FP16-INT8 - CPUopenvino: Face 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: Vehicle Detection FP16 - CPUopenvino: Vehicle Detection FP16 - CPUopenvino: Weld Porosity Detection FP16-INT8 - CPUopenvino: Age Gender Recognition Retail 0013 FP16 - CPUopenvino: Face Detection FP16 - CPUopenvino: Face Detection FP16 - CPUabcd129.13373.5472.650.86431.07240209.5368911.42585.76159.05104.3957.69685.2534.32696.1770.97232.36700.1634.12110460.516280.3431933.2315.251.1240.35294.4617.025630.29325.255.9715718.16643.4537.242922.388.192.960.4149.92159.92138.1361.2576.9647.79450.94229.08200.669578.86593.27154.89105.3959.23671.2234.35696.7769.57234.35703.8533.97111897.596303.632169.3715.191.1340.64294.87175637.81324.865.9415755.63641.2137.362926.318.182.950.4151.35158.39136.99356.6977.7750.61445.77240.69206.5369611.40609.80157.31104.2657.17666.1033.70709.0770.31237.48699.3834.20112093.026270.5732075.6915.271.1340.35293.8617.035628.20325.915.9415763.43640.3937.412920.108.192.960.4158.88151.47140.15347.677.7650.58453.77229.92206.766799.28599.68152.92101.5457.12679.8433.4715.4471.32235.21693.1434.48112095.526240.1732249.8715.341.1340.5293.1316.935661.26326.615.9415797.2641.2337.372931.838.162.950.4150.66159.12OpenBenchmarking.org

TensorFlow

Device: CPU - Batch Size: 32 - Model: GoogLeNet

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

TensorFlow

Device: CPU - Batch Size: 32 - Model: AlexNet

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

TensorFlow

Device: CPU - Batch Size: 512 - Model: ResNet-50

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

TensorFlow

Device: CPU - Batch Size: 32 - Model: ResNet-50

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

TensorFlow

Device: CPU - Batch Size: 64 - Model: AlexNet

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

TensorFlow

Device: CPU - Batch Size: 16 - Model: AlexNet

OpenBenchmarking.orgimages/sec, More Is BetterTensorFlow 2.12Device: CPU - Batch Size: 16 - Model: AlexNetabcd50100150200250SE +/- 2.42, N = 15240.00229.08240.69229.92

TensorFlow

Device: CPU - Batch Size: 256 - Model: GoogLeNet

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

OpenVINO

Model: Age Gender Recognition Retail 0013 FP16-INT8 - Device: CPU

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

TensorFlow

Device: CPU - Batch Size: 256 - Model: AlexNet

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

TensorFlow

Device: CPU - Batch Size: 64 - Model: GoogLeNet

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

TensorFlow

Device: CPU - Batch Size: 16 - Model: GoogLeNet

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

TensorFlow

Device: CPU - Batch Size: 64 - Model: ResNet-50

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

TensorFlow

Device: CPU - Batch Size: 512 - Model: AlexNet

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

OpenVINO

Model: Person Detection FP32 - Device: CPU

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

OpenVINO

Model: Person Detection FP32 - Device: CPU

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

TensorFlow

Device: CPU - Batch Size: 256 - Model: ResNet-50

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

TensorFlow

Device: CPU - Batch Size: 512 - Model: GoogLeNet

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

OpenVINO

Model: Person Detection FP16 - Device: CPU

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

OpenVINO

Model: Person Detection FP16 - Device: CPU

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

OpenVINO

Model: Age Gender Recognition Retail 0013 FP16 - Device: CPU

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

OpenVINO

Model: Person Vehicle Bike Detection FP16 - Device: CPU

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

OpenVINO

Model: Weld Porosity Detection FP16-INT8 - Device: CPU

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

OpenVINO

Model: Person Vehicle Bike Detection FP16 - Device: CPU

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

OpenVINO

Model: Age Gender Recognition Retail 0013 FP16-INT8 - Device: CPU

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

TensorFlow

Device: CPU - Batch Size: 16 - Model: ResNet-50

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

OpenVINO

Model: Face Detection FP16-INT8 - Device: CPU

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

OpenVINO

Model: Vehicle Detection FP16-INT8 - Device: CPU

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

OpenVINO

Model: Vehicle Detection FP16-INT8 - Device: CPU

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

OpenVINO

Model: Face Detection FP16-INT8 - Device: CPU

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

OpenVINO

Model: Weld Porosity Detection FP16 - Device: CPU

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

OpenVINO

Model: Weld Porosity Detection FP16 - Device: CPU

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

OpenVINO

Model: Machine Translation EN To DE FP16 - Device: CPU

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

OpenVINO

Model: Machine Translation EN To DE FP16 - Device: CPU

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

OpenVINO

Model: Vehicle Detection FP16 - Device: CPU

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

OpenVINO

Model: Vehicle Detection FP16 - Device: CPU

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

OpenVINO

Model: Weld Porosity Detection FP16-INT8 - Device: CPU

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

OpenVINO

Model: Age Gender Recognition Retail 0013 FP16 - Device: CPU

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

OpenVINO

Model: Face Detection FP16 - Device: CPU

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

OpenVINO

Model: Face Detection FP16 - Device: CPU

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

Phoronix Test Suite v10.8.5