rembrandt openvino and other new

AMD Ryzen 7 PRO 6850U testing with a LENOVO 21CM0001US (R22ET51W 1.21 BIOS) and AMD Radeon 680M 1GB on Ubuntu 22.10 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 2208318-PTS-REMBRAND95
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rembrandt openvino and other newOpenBenchmarking.orgPhoronix Test SuiteAMD Ryzen 7 PRO 6850U @ 4.77GHz (8 Cores / 16 Threads)LENOVO 21CM0001US (R22ET51W 1.21 BIOS)AMD Device 14b516GB512GB Micron MTFDKBA512TFKAMD Radeon 680M 1GB (2200/400MHz)AMD Rembrandt Radeon HD AudioQualcomm QCNFA765Ubuntu 22.106.0.0-060000rc2daily20220824-generic (x86_64)GNOME Shell 42.4X Server + Wayland4.6 Mesa 22.1.3 (LLVM 14.0.6 DRM 3.48)1.3.211GCC 11.3.0ext41920x1200ProcessorMotherboardChipsetMemoryDiskGraphicsAudioNetworkOSKernelDesktopDisplay ServerOpenGLVulkanCompilerFile-SystemScreen ResolutionRembrandt Openvino And Other New 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-11-7Xaroy/gcc-11-11.3.0/debian/tmp-nvptx/usr,amdgcn-amdhsa=/build/gcc-11-7Xaroy/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: amd-pstate schedutil (Boost: Enabled) - Platform Profile: balanced - CPU Microcode: 0xa404102 - ACPI Profile: balanced - 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

AbCResult OverviewPhoronix Test Suite100%100%100%101%Mobile Neural NetworkOpenVINO7-Zip Compression

rembrandt openvino and other newcompress-7zip: Compression Ratingcompress-7zip: Decompression Ratingmnn: nasnetmnn: mobilenetV3mnn: squeezenetv1.1mnn: resnet-v2-50mnn: SqueezeNetV1.0mnn: MobileNetV2_224mnn: mobilenet-v1-1.0mnn: inception-v3openvino: 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 - CPUAbC551255120312.1331.9243.49026.8706.7753.1113.02637.2911.462732.031.003986.390.984081.09124.8931.983.361190.38210.2819.00157.7525.3117.91223.30334.4523.84216.8618.404388.371.778512.510.92553955172712.2131.9193.50626.9236.7953.1323.01337.2061.472714.631.013955.070.994016.88127.2831.383.41175.84212.4818.80158.9925.1118.04221.62335.8123.74216.6318.424408.381.768565.580.92551475140612.0621.9203.45026.7156.6873.1013.01236.9361.472727.921.003967.680.994035.11126.2031.653.391180.58210.8418.95158.9725.1118.06221.46336.7323.68216.9118.404402.551.778563.920.92OpenBenchmarking.org

7-Zip Compression

This is a test of 7-Zip compression/decompression with its integrated benchmark feature. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgMIPS, More Is Better7-Zip Compression 22.01Test: Compression RatingAbC12K24K36K48K60KSE +/- 354.18, N = 3SE +/- 189.74, N = 3SE +/- 307.96, N = 35512555395551471. (CXX) g++ options: -lpthread -ldl -O2 -fPIC

OpenBenchmarking.orgMIPS, More Is Better7-Zip Compression 22.01Test: Decompression RatingAbC11K22K33K44K55KSE +/- 786.48, N = 3SE +/- 815.01, N = 3SE +/- 890.93, N = 35120351727514061. (CXX) g++ options: -lpthread -ldl -O2 -fPIC

Mobile Neural Network

MNN is the Mobile Neural Network as a highly efficient, lightweight deep learning framework developed by Alibaba. This MNN test profile is building the OpenMP / CPU threaded version for processor benchmarking and not any GPU-accelerated test. MNN does allow making use of AVX-512 extensions. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgms, Fewer Is BetterMobile Neural Network 2.1Model: nasnetAbC3691215SE +/- 0.03, N = 3SE +/- 0.15, N = 3SE +/- 0.02, N = 312.1312.2112.06MIN: 11.39 / MAX: 49.71MIN: 11.26 / MAX: 49.36MIN: 11.31 / MAX: 47.171. (CXX) g++ options: -std=c++11 -O3 -fvisibility=hidden -fomit-frame-pointer -fstrict-aliasing -ffunction-sections -fdata-sections -ffast-math -fno-rtti -fno-exceptions -rdynamic -pthread -ldl

OpenBenchmarking.orgms, Fewer Is BetterMobile Neural Network 2.1Model: mobilenetV3AbC0.43290.86581.29871.73162.1645SE +/- 0.004, N = 3SE +/- 0.006, N = 3SE +/- 0.007, N = 31.9241.9191.920MIN: 1.42 / MAX: 5.08MIN: 1.4 / MAX: 5.13MIN: 1.43 / MAX: 16.461. (CXX) g++ options: -std=c++11 -O3 -fvisibility=hidden -fomit-frame-pointer -fstrict-aliasing -ffunction-sections -fdata-sections -ffast-math -fno-rtti -fno-exceptions -rdynamic -pthread -ldl

OpenBenchmarking.orgms, Fewer Is BetterMobile Neural Network 2.1Model: squeezenetv1.1AbC0.78891.57782.36673.15563.9445SE +/- 0.054, N = 3SE +/- 0.018, N = 3SE +/- 0.019, N = 33.4903.5063.450MIN: 3.13 / MAX: 31.43MIN: 3.27 / MAX: 39.92MIN: 3.21 / MAX: 28.581. (CXX) g++ options: -std=c++11 -O3 -fvisibility=hidden -fomit-frame-pointer -fstrict-aliasing -ffunction-sections -fdata-sections -ffast-math -fno-rtti -fno-exceptions -rdynamic -pthread -ldl

OpenBenchmarking.orgms, Fewer Is BetterMobile Neural Network 2.1Model: resnet-v2-50AbC612182430SE +/- 0.14, N = 3SE +/- 0.03, N = 3SE +/- 0.01, N = 326.8726.9226.72MIN: 25.67 / MAX: 63.69MIN: 25.92 / MAX: 63.77MIN: 25.76 / MAX: 61.621. (CXX) g++ options: -std=c++11 -O3 -fvisibility=hidden -fomit-frame-pointer -fstrict-aliasing -ffunction-sections -fdata-sections -ffast-math -fno-rtti -fno-exceptions -rdynamic -pthread -ldl

OpenBenchmarking.orgms, Fewer Is BetterMobile Neural Network 2.1Model: SqueezeNetV1.0AbC246810SE +/- 0.058, N = 3SE +/- 0.006, N = 3SE +/- 0.029, N = 36.7756.7956.687MIN: 6.22 / MAX: 43.58MIN: 6.38 / MAX: 28.99MIN: 6.21 / MAX: 44.461. (CXX) g++ options: -std=c++11 -O3 -fvisibility=hidden -fomit-frame-pointer -fstrict-aliasing -ffunction-sections -fdata-sections -ffast-math -fno-rtti -fno-exceptions -rdynamic -pthread -ldl

OpenBenchmarking.orgms, Fewer Is BetterMobile Neural Network 2.1Model: MobileNetV2_224AbC0.70471.40942.11412.81883.5235SE +/- 0.015, N = 3SE +/- 0.008, N = 3SE +/- 0.010, N = 33.1113.1323.101MIN: 2.89 / MAX: 27.12MIN: 2.91 / MAX: 27.7MIN: 2.91 / MAX: 30.521. (CXX) g++ options: -std=c++11 -O3 -fvisibility=hidden -fomit-frame-pointer -fstrict-aliasing -ffunction-sections -fdata-sections -ffast-math -fno-rtti -fno-exceptions -rdynamic -pthread -ldl

OpenBenchmarking.orgms, Fewer Is BetterMobile Neural Network 2.1Model: mobilenet-v1-1.0AbC0.68091.36182.04272.72363.4045SE +/- 0.003, N = 3SE +/- 0.004, N = 3SE +/- 0.002, N = 33.0263.0133.012MIN: 2.78 / MAX: 34.28MIN: 2.79 / MAX: 25.08MIN: 2.82 / MAX: 24.851. (CXX) g++ options: -std=c++11 -O3 -fvisibility=hidden -fomit-frame-pointer -fstrict-aliasing -ffunction-sections -fdata-sections -ffast-math -fno-rtti -fno-exceptions -rdynamic -pthread -ldl

OpenBenchmarking.orgms, Fewer Is BetterMobile Neural Network 2.1Model: inception-v3AbC918273645SE +/- 0.27, N = 3SE +/- 0.24, N = 3SE +/- 0.18, N = 337.2937.2136.94MIN: 33.89 / MAX: 75.25MIN: 33.07 / MAX: 73MIN: 33.35 / MAX: 72.481. (CXX) g++ options: -std=c++11 -O3 -fvisibility=hidden -fomit-frame-pointer -fstrict-aliasing -ffunction-sections -fdata-sections -ffast-math -fno-rtti -fno-exceptions -rdynamic -pthread -ldl

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 2022.2.devModel: Face Detection FP16 - Device: CPUAbC0.33080.66160.99241.32321.654SE +/- 0.00, N = 3SE +/- 0.00, N = 3SE +/- 0.00, N = 31.461.471.471. (CXX) g++ options: -fPIC -fsigned-char -ffunction-sections -fdata-sections -O3 -fno-strict-overflow -fwrapv -flto -shared

OpenBenchmarking.orgms, Fewer Is BetterOpenVINO 2022.2.devModel: Face Detection FP16 - Device: CPUAbC6001200180024003000SE +/- 2.30, N = 3SE +/- 5.27, N = 3SE +/- 1.49, N = 32732.032714.632727.92MIN: 2684.4 / MAX: 2778.78MIN: 2566.77 / MAX: 2775.21MIN: 2663.42 / MAX: 2790.341. (CXX) g++ options: -fPIC -fsigned-char -ffunction-sections -fdata-sections -O3 -fno-strict-overflow -fwrapv -flto -shared

OpenBenchmarking.orgFPS, More Is BetterOpenVINO 2022.2.devModel: Person Detection FP16 - Device: CPUAbC0.22730.45460.68190.90921.1365SE +/- 0.01, N = 3SE +/- 0.00, N = 3SE +/- 0.00, N = 31.001.011.001. (CXX) g++ options: -fPIC -fsigned-char -ffunction-sections -fdata-sections -O3 -fno-strict-overflow -fwrapv -flto -shared

OpenBenchmarking.orgms, Fewer Is BetterOpenVINO 2022.2.devModel: Person Detection FP16 - Device: CPUAbC9001800270036004500SE +/- 13.80, N = 3SE +/- 7.20, N = 3SE +/- 7.56, N = 33986.393955.073967.68MIN: 3822.49 / MAX: 4120.21MIN: 3719.09 / MAX: 4022.86MIN: 3819.7 / MAX: 4043.721. (CXX) g++ options: -fPIC -fsigned-char -ffunction-sections -fdata-sections -O3 -fno-strict-overflow -fwrapv -flto -shared

OpenBenchmarking.orgFPS, More Is BetterOpenVINO 2022.2.devModel: Person Detection FP32 - Device: CPUAbC0.22280.44560.66840.89121.114SE +/- 0.01, N = 3SE +/- 0.00, N = 3SE +/- 0.00, N = 30.980.990.991. (CXX) g++ options: -fPIC -fsigned-char -ffunction-sections -fdata-sections -O3 -fno-strict-overflow -fwrapv -flto -shared

OpenBenchmarking.orgms, Fewer Is BetterOpenVINO 2022.2.devModel: Person Detection FP32 - Device: CPUAbC9001800270036004500SE +/- 19.30, N = 3SE +/- 9.52, N = 3SE +/- 5.19, N = 34081.094016.884035.11MIN: 3979.02 / MAX: 4229.09MIN: 3787.09 / MAX: 4109.09MIN: 3881.64 / MAX: 4169.881. (CXX) g++ options: -fPIC -fsigned-char -ffunction-sections -fdata-sections -O3 -fno-strict-overflow -fwrapv -flto -shared

OpenBenchmarking.orgFPS, More Is BetterOpenVINO 2022.2.devModel: Vehicle Detection FP16 - Device: CPUAbC306090120150SE +/- 1.02, N = 3SE +/- 0.40, N = 3SE +/- 0.36, N = 3124.89127.28126.201. (CXX) g++ options: -fPIC -fsigned-char -ffunction-sections -fdata-sections -O3 -fno-strict-overflow -fwrapv -flto -shared

OpenBenchmarking.orgms, Fewer Is BetterOpenVINO 2022.2.devModel: Vehicle Detection FP16 - Device: CPUAbC714212835SE +/- 0.26, N = 3SE +/- 0.10, N = 3SE +/- 0.09, N = 331.9831.3831.65MIN: 21.12 / MAX: 72MIN: 21.56 / MAX: 55.41MIN: 24.41 / MAX: 57.631. (CXX) g++ options: -fPIC -fsigned-char -ffunction-sections -fdata-sections -O3 -fno-strict-overflow -fwrapv -flto -shared

OpenBenchmarking.orgFPS, More Is BetterOpenVINO 2022.2.devModel: Face Detection FP16-INT8 - Device: CPUAbC0.7651.532.2953.063.825SE +/- 0.02, N = 3SE +/- 0.00, N = 3SE +/- 0.01, N = 33.363.403.391. (CXX) g++ options: -fPIC -fsigned-char -ffunction-sections -fdata-sections -O3 -fno-strict-overflow -fwrapv -flto -shared

OpenBenchmarking.orgms, Fewer Is BetterOpenVINO 2022.2.devModel: Face Detection FP16-INT8 - Device: CPUAbC30060090012001500SE +/- 6.11, N = 3SE +/- 0.10, N = 3SE +/- 4.14, N = 31190.381175.841180.58MIN: 1162.14 / MAX: 1245.69MIN: 1089.88 / MAX: 1210.5MIN: 1119.6 / MAX: 1225.761. (CXX) g++ options: -fPIC -fsigned-char -ffunction-sections -fdata-sections -O3 -fno-strict-overflow -fwrapv -flto -shared

OpenBenchmarking.orgFPS, More Is BetterOpenVINO 2022.2.devModel: Vehicle Detection FP16-INT8 - Device: CPUAbC50100150200250SE +/- 0.76, N = 3SE +/- 1.19, N = 3SE +/- 0.49, N = 3210.28212.48210.841. (CXX) g++ options: -fPIC -fsigned-char -ffunction-sections -fdata-sections -O3 -fno-strict-overflow -fwrapv -flto -shared

OpenBenchmarking.orgms, Fewer Is BetterOpenVINO 2022.2.devModel: Vehicle Detection FP16-INT8 - Device: CPUAbC510152025SE +/- 0.07, N = 3SE +/- 0.11, N = 3SE +/- 0.04, N = 319.0018.8018.95MIN: 14.9 / MAX: 54.02MIN: 14.71 / MAX: 39.05MIN: 14.87 / MAX: 38.721. (CXX) g++ options: -fPIC -fsigned-char -ffunction-sections -fdata-sections -O3 -fno-strict-overflow -fwrapv -flto -shared

OpenBenchmarking.orgFPS, More Is BetterOpenVINO 2022.2.devModel: Weld Porosity Detection FP16 - Device: CPUAbC4080120160200SE +/- 0.01, N = 3SE +/- 0.36, N = 3SE +/- 0.22, N = 3157.75158.99158.971. (CXX) g++ options: -fPIC -fsigned-char -ffunction-sections -fdata-sections -O3 -fno-strict-overflow -fwrapv -flto -shared

OpenBenchmarking.orgms, Fewer Is BetterOpenVINO 2022.2.devModel: Weld Porosity Detection FP16 - Device: CPUAbC612182430SE +/- 0.00, N = 3SE +/- 0.06, N = 3SE +/- 0.04, N = 325.3125.1125.11MIN: 21.33 / MAX: 40.07MIN: 21.13 / MAX: 38.32MIN: 21.37 / MAX: 60.551. (CXX) g++ options: -fPIC -fsigned-char -ffunction-sections -fdata-sections -O3 -fno-strict-overflow -fwrapv -flto -shared

OpenBenchmarking.orgFPS, More Is BetterOpenVINO 2022.2.devModel: Machine Translation EN To DE FP16 - Device: CPUAbC48121620SE +/- 0.05, N = 3SE +/- 0.03, N = 3SE +/- 0.05, N = 317.9118.0418.061. (CXX) g++ options: -fPIC -fsigned-char -ffunction-sections -fdata-sections -O3 -fno-strict-overflow -fwrapv -flto -shared

OpenBenchmarking.orgms, Fewer Is BetterOpenVINO 2022.2.devModel: Machine Translation EN To DE FP16 - Device: CPUAbC50100150200250SE +/- 0.61, N = 3SE +/- 0.39, N = 3SE +/- 0.58, N = 3223.30221.62221.46MIN: 196.56 / MAX: 244.11MIN: 201.08 / MAX: 257.32MIN: 193.98 / MAX: 253.411. (CXX) g++ options: -fPIC -fsigned-char -ffunction-sections -fdata-sections -O3 -fno-strict-overflow -fwrapv -flto -shared

OpenBenchmarking.orgFPS, More Is BetterOpenVINO 2022.2.devModel: Weld Porosity Detection FP16-INT8 - Device: CPUAbC70140210280350SE +/- 0.15, N = 3SE +/- 0.62, N = 3SE +/- 0.54, N = 3334.45335.81336.731. (CXX) g++ options: -fPIC -fsigned-char -ffunction-sections -fdata-sections -O3 -fno-strict-overflow -fwrapv -flto -shared

OpenBenchmarking.orgms, Fewer Is BetterOpenVINO 2022.2.devModel: Weld Porosity Detection FP16-INT8 - Device: CPUAbC612182430SE +/- 0.01, N = 3SE +/- 0.04, N = 3SE +/- 0.04, N = 323.8423.7423.68MIN: 19.99 / MAX: 58.25MIN: 19.99 / MAX: 48MIN: 19.67 / MAX: 58.271. (CXX) g++ options: -fPIC -fsigned-char -ffunction-sections -fdata-sections -O3 -fno-strict-overflow -fwrapv -flto -shared

OpenBenchmarking.orgFPS, More Is BetterOpenVINO 2022.2.devModel: Person Vehicle Bike Detection FP16 - Device: CPUAbC50100150200250SE +/- 1.35, N = 3SE +/- 1.90, N = 8SE +/- 2.10, N = 6216.86216.63216.911. (CXX) g++ options: -fPIC -fsigned-char -ffunction-sections -fdata-sections -O3 -fno-strict-overflow -fwrapv -flto -shared

OpenBenchmarking.orgms, Fewer Is BetterOpenVINO 2022.2.devModel: Person Vehicle Bike Detection FP16 - Device: CPUAbC510152025SE +/- 0.12, N = 3SE +/- 0.16, N = 8SE +/- 0.18, N = 618.4018.4218.40MIN: 14.61 / MAX: 47.36MIN: 14.07 / MAX: 53.4MIN: 14.74 / MAX: 39.211. (CXX) g++ options: -fPIC -fsigned-char -ffunction-sections -fdata-sections -O3 -fno-strict-overflow -fwrapv -flto -shared

OpenBenchmarking.orgFPS, More Is BetterOpenVINO 2022.2.devModel: Age Gender Recognition Retail 0013 FP16 - Device: CPUAbC9001800270036004500SE +/- 7.50, N = 3SE +/- 10.48, N = 3SE +/- 3.62, N = 34388.374408.384402.551. (CXX) g++ options: -fPIC -fsigned-char -ffunction-sections -fdata-sections -O3 -fno-strict-overflow -fwrapv -flto -shared

OpenBenchmarking.orgms, Fewer Is BetterOpenVINO 2022.2.devModel: Age Gender Recognition Retail 0013 FP16 - Device: CPUAbC0.39830.79661.19491.59321.9915SE +/- 0.00, N = 3SE +/- 0.00, N = 3SE +/- 0.00, N = 31.771.761.77MIN: 1.04 / MAX: 23.3MIN: 1.26 / MAX: 23.56MIN: 1.02 / MAX: 22.651. (CXX) g++ options: -fPIC -fsigned-char -ffunction-sections -fdata-sections -O3 -fno-strict-overflow -fwrapv -flto -shared

OpenBenchmarking.orgFPS, More Is BetterOpenVINO 2022.2.devModel: Age Gender Recognition Retail 0013 FP16-INT8 - Device: CPUAbC2K4K6K8K10KSE +/- 8.43, N = 3SE +/- 18.04, N = 3SE +/- 40.98, N = 38512.518565.588563.921. (CXX) g++ options: -fPIC -fsigned-char -ffunction-sections -fdata-sections -O3 -fno-strict-overflow -fwrapv -flto -shared

OpenBenchmarking.orgms, Fewer Is BetterOpenVINO 2022.2.devModel: Age Gender Recognition Retail 0013 FP16-INT8 - Device: CPUAbC0.2070.4140.6210.8281.035SE +/- 0.00, N = 3SE +/- 0.00, N = 3SE +/- 0.00, N = 30.920.920.92MIN: 0.56 / MAX: 35.43MIN: 0.56 / MAX: 26.74MIN: 0.66 / MAX: 25.761. (CXX) g++ options: -fPIC -fsigned-char -ffunction-sections -fdata-sections -O3 -fno-strict-overflow -fwrapv -flto -shared

34 Results Shown

7-Zip Compression:
  Compression Rating
  Decompression Rating
Mobile Neural Network:
  nasnet
  mobilenetV3
  squeezenetv1.1
  resnet-v2-50
  SqueezeNetV1.0
  MobileNetV2_224
  mobilenet-v1-1.0
  inception-v3
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