8565U New Tests

Intel Core i7-8565U testing with a Dell 0KTW76 (1.0.0 BIOS) and Intel UHD 620 3GB on Ubuntu 20.04 via the Phoronix Test Suite.

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Result
Identifier
Performance Per
Dollar
Date
Run
  Test
  Duration
Core i7 8565U
September 18 2020
  21 Hours, 4 Minutes
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8565U New TestsOpenBenchmarking.orgPhoronix Test SuiteIntel Core i7-8565U @ 4.60GHz (4 Cores / 8 Threads)Dell 0KTW76 (1.0.0 BIOS)Intel Cannon Point-LP16GBPC401 NVMe SK hynix 256GBIntel UHD 620 3GB (1150MHz)Realtek ALC3271Qualcomm Atheros QCA6174 802.11acUbuntu 20.045.4.0-45-generic (x86_64)GNOME Shell 3.36.4X Server 1.20.8modesetting 1.20.84.6 Mesa 20.0.4OpenCL 2.1GCC 9.3.0ext41920x1080ProcessorMotherboardChipsetMemoryDiskGraphicsAudioNetworkOSKernelDesktopDisplay ServerDisplay DriverOpenGLOpenCLCompilerFile-SystemScreen Resolution8565U New Tests PerformanceSystem Logs- --build=x86_64-linux-gnu --disable-vtable-verify --disable-werror --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++,gm2 --enable-libstdcxx-debug --enable-libstdcxx-time=yes --enable-multiarch --enable-multilib --enable-nls --enable-objc-gc=auto --enable-offload-targets=nvptx-none,hsa --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_pstate powersave - CPU Microcode: 0xd6- itlb_multihit: KVM: Mitigation of Split huge pages + l1tf: Not affected + mds: Mitigation of Clear buffers; SMT vulnerable + meltdown: Not affected + spec_store_bypass: Mitigation of SSB disabled via prctl and seccomp + spectre_v1: Mitigation of usercopy/swapgs barriers and __user pointer sanitization + spectre_v2: Mitigation of Full generic retpoline IBPB: conditional IBRS_FW STIBP: conditional RSB filling + srbds: Mitigation of Microcode + tsx_async_abort: Not affected

8565U New Testsincompact3d: Cylindermocassin: Dust 2D tau100.0mnn: SqueezeNetV1.0mnn: resnet-v2-50mnn: MobileNetV2_224mnn: mobilenet-v1-1.0mnn: inception-v3ncnn: CPU - squeezenet_int8ncnn: CPU - mobilenet_v3ncnn: CPU - squeezenetncnn: CPU - mnasnetncnn: CPU - blazefacencnn: CPU - googlenet_int8ncnn: CPU - vgg16_int8ncnn: CPU - resnet18_int8ncnn: CPU - alexnetncnn: CPU - resnet50_int8ncnn: CPU - mobilenetv2_yolov3kripke: Core i7 8565U1149.6559940517.17391.1238.70012.568101.33924.958.696.479.272.8276.24292.1850.5729.18164.0339.772341575OpenBenchmarking.org

Incompact3D

Incompact3d is a Fortran-MPI based, finite difference high-performance code for solving the incompressible Navier-Stokes equation and as many as you need scalar transport equations. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgSeconds, Fewer Is BetterIncompact3D 2020-09-17Input: CylinderCore i7 8565U2004006008001000SE +/- 14.70, N = 91149.661. (F9X) gfortran options: -cpp -funroll-loops -floop-optimize -fcray-pointer -fbacktrace -pthread -lmpi_usempif08 -lmpi_mpifh -lmpi

Monte Carlo Simulations of Ionised Nebulae

Mocassin is the Monte Carlo Simulations of Ionised Nebulae. MOCASSIN is a fully 3D or 2D photoionisation and dust radiative transfer code which employs a Monte Carlo approach to the transfer of radiation through media of arbitrary geometry and density distribution. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgSeconds, Fewer Is BetterMonte Carlo Simulations of Ionised Nebulae 2019-03-24Input: Dust 2D tau100.0Core i7 8565U901802703604504051. (F9X) gfortran options: -cpp -Jsource/ -ffree-line-length-0 -lm -std=legacy -O3 -O2 -pthread -lmpi_usempif08 -lmpi_mpifh -lmpi

Mobile Neural Network

MNN is the Mobile Neural Network as a highly efficient, lightweight deep learning framework developed by ALibaba. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgms, Fewer Is BetterMobile Neural Network 2020-09-17Model: SqueezeNetV1.0Core i7 8565U48121620SE +/- 0.10, N = 317.17MIN: 16.17 / MAX: 57.571. (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 2020-09-17Model: resnet-v2-50Core i7 8565U20406080100SE +/- 0.23, N = 391.12MIN: 87.37 / MAX: 130.631. (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 2020-09-17Model: MobileNetV2_224Core i7 8565U246810SE +/- 0.033, N = 38.700MIN: 8.39 / MAX: 50.291. (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 2020-09-17Model: mobilenet-v1-1.0Core i7 8565U3691215SE +/- 0.07, N = 312.57MIN: 11.8 / MAX: 48.871. (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 2020-09-17Model: inception-v3Core i7 8565U20406080100SE +/- 0.27, N = 3101.34MIN: 96.15 / MAX: 142.161. (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

NCNN

OpenBenchmarking.orgms, Fewer Is BetterNCNN 20200916Target: CPU - Model: squeezenet_int8Core i7 8565U612182430SE +/- 0.66, N = 924.95MIN: 18.59 / MAX: 45.721. (CXX) g++ options: -O3 -rdynamic -lgomp -lpthread

OpenBenchmarking.orgms, Fewer Is BetterNCNN 20200916Target: CPU - Model: mobilenet_v3Core i7 8565U246810SE +/- 0.09, N = 98.69MIN: 8.33 / MAX: 42.891. (CXX) g++ options: -O3 -rdynamic -lgomp -lpthread

OpenBenchmarking.orgms, Fewer Is BetterNCNN 20200916Target: CPU - Model: squeezenetCore i7 8565U246810SE +/- 0.03, N = 96.47MIN: 6.12 / MAX: 11.351. (CXX) g++ options: -O3 -rdynamic -lgomp -lpthread

OpenBenchmarking.orgms, Fewer Is BetterNCNN 20200916Target: CPU - Model: mnasnetCore i7 8565U3691215SE +/- 0.07, N = 99.27MIN: 8.49 / MAX: 55.141. (CXX) g++ options: -O3 -rdynamic -lgomp -lpthread

OpenBenchmarking.orgms, Fewer Is BetterNCNN 20200916Target: CPU - Model: blazefaceCore i7 8565U0.63451.2691.90352.5383.1725SE +/- 0.04, N = 92.82MIN: 2.54 / MAX: 7.681. (CXX) g++ options: -O3 -rdynamic -lgomp -lpthread

OpenBenchmarking.orgms, Fewer Is BetterNCNN 20200916Target: CPU - Model: googlenet_int8Core i7 8565U20406080100SE +/- 0.05, N = 976.24MIN: 72.78 / MAX: 92.521. (CXX) g++ options: -O3 -rdynamic -lgomp -lpthread

OpenBenchmarking.orgms, Fewer Is BetterNCNN 20200916Target: CPU - Model: vgg16_int8Core i7 8565U60120180240300SE +/- 0.44, N = 9292.18MIN: 208.38 / MAX: 323.71. (CXX) g++ options: -O3 -rdynamic -lgomp -lpthread

OpenBenchmarking.orgms, Fewer Is BetterNCNN 20200916Target: CPU - Model: resnet18_int8Core i7 8565U1122334455SE +/- 0.02, N = 950.57MIN: 48.86 / MAX: 68.421. (CXX) g++ options: -O3 -rdynamic -lgomp -lpthread

OpenBenchmarking.orgms, Fewer Is BetterNCNN 20200916Target: CPU - Model: alexnetCore i7 8565U714212835SE +/- 0.11, N = 929.18MIN: 25.62 / MAX: 46.851. (CXX) g++ options: -O3 -rdynamic -lgomp -lpthread

OpenBenchmarking.orgms, Fewer Is BetterNCNN 20200916Target: CPU - Model: resnet50_int8Core i7 8565U4080120160200SE +/- 0.06, N = 9164.03MIN: 158.64 / MAX: 201.331. (CXX) g++ options: -O3 -rdynamic -lgomp -lpthread

OpenBenchmarking.orgms, Fewer Is BetterNCNN 20200916Target: CPU - Model: mobilenetv2_yolov3Core i7 8565U918273645SE +/- 0.03, N = 939.77MIN: 38.67 / MAX: 57.171. (CXX) g++ options: -O3 -rdynamic -lgomp -lpthread

Kripke

Kripke is a simple, scalable, 3D Sn deterministic particle transport code. Its primary purpose is to research how data layout, programming paradigms and architectures effect the implementation and performance of Sn transport. Kripke is developed by LLNL. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgThroughput FoM, More Is BetterKripke 1.2.4Core i7 8565U500K1000K1500K2000K2500KSE +/- 99368.79, N = 923415751. (CXX) g++ options: -O3 -fopenmp