Core i7 1065G7 Ozapft

Intel Core i7-1065G7 testing with a Dell 06CDVY (1.0.9 BIOS) and Intel Iris Plus G7 3GB on Ubuntu 20.04 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 2009203-PTS-COREI71043
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Core i7 1065G7
September 19 2020
  14 Hours, 29 Minutes
c2
September 19 2020
  13 Hours, 25 Minutes
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September 20 2020
  14 Hours, 30 Minutes
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Core i7 1065G7 OzapftOpenBenchmarking.orgPhoronix Test Suite 10.2.2Intel Core i7-1065G7 @ 3.90GHz (4 Cores / 8 Threads)Dell 06CDVY (1.0.9 BIOS)Intel Device 34ef16GBKBG40ZPZ512G NVMe TOSHIBA 512GBIntel Iris Plus G7 3GB (1100MHz)Realtek ALC289Intel Killer Wi-Fi 6 AX1650i 160MHzUbuntu 20.045.9.0-050900rc1daily20200819-generic (x86_64) 20200818GNOME Shell 3.36.4X Server 1.20.8modesetting 1.20.84.6 Mesa 20.0.41.2.131GCC 9.3.0ext41920x1200ProcessorMotherboardChipsetMemoryDiskGraphicsAudioNetworkOSKernelDesktopDisplay ServerDisplay DriverOpenGLVulkanCompilerFile-SystemScreen ResolutionCore I7 1065G7 Ozapft BenchmarksSystem 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: 0x78- Python 3.8.2- itlb_multihit: KVM: Mitigation of VMX disabled + l1tf: Not affected + mds: Not affected + 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 Enhanced IBRS IBPB: conditional RSB filling + srbds: Not affected + tsx_async_abort: Not affected

Core i7 1065G7c2c3Result OverviewPhoronix Test Suite 10.2.2100%101%102%102%KripkeIncompact3DNCNNMonte Carlo Simulations of Ionised NebulaeGPAWLAMMPS Molecular Dynamics SimulatorMobile Neural Network

Core i7 1065G7 Ozapftkripke: ncnn: CPU - mobilenetv2_yolov3ncnn: CPU - resnet18_int8incompact3d: Cylinderncnn: CPU - alexnetncnn: CPU - mnasnetncnn: CPU - squeezenet_int8lammps: 20k Atomsncnn: CPU - mobilenet_v3mocassin: Dust 2D tau100.0ncnn: CPU - squeezenetncnn: CPU - googlenet_int8ncnn: CPU - vgg16_int8gpaw: Carbon Nanotubemnn: mobilenet-v1-1.0mnn: resnet-v2-50mnn: SqueezeNetV1.0mnn: inception-v3ncnn: CPU - blazefacelammps: Rhodopsin Proteinmnn: MobileNetV2_224ncnn: CPU - resnet50_int8Core i7 1065G7c2c31149500432.8343.551046.6059220.458.2920.422.1477.523915.7668.90236.47717.3939.41458.49512.25271.7302.402.5925.213147.821169518733.0443.691045.2990320.498.3120.562.1417.563935.7969.15235.78715.4489.40458.59212.23971.7252.402.6115.230160.001184014133.4544.091058.1643120.638.3620.592.1307.583945.8069.27236.83715.1179.42458.60512.26071.6332.402.6445.223148.33OpenBenchmarking.org

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 1065G7c2c33M6M9M12M15MSE +/- 190633.80, N = 9SE +/- 151151.38, N = 3SE +/- 181316.61, N = 91149500411695187118401411. (CXX) g++ options: -O3 -fopenmp
OpenBenchmarking.orgThroughput FoM, More Is BetterKripke 1.2.4Core i7 1065G7c2c32M4M6M8M10MMin: 11048060 / Avg: 11495004.44 / Max: 12658260Min: 11457370 / Avg: 11695186.67 / Max: 11975720Min: 11011850 / Avg: 11840141.11 / Max: 124822301. (CXX) g++ options: -O3 -fopenmp

NCNN

OpenBenchmarking.orgms, Fewer Is BetterNCNN 20200916Target: CPU - Model: mobilenetv2_yolov3Core i7 1065G7c2c3816243240SE +/- 0.06, N = 9SE +/- 0.16, N = 9SE +/- 0.21, N = 932.8333.0433.45MIN: 31.46 / MAX: 47.76MIN: 31.38 / MAX: 49.26MIN: 31.35 / MAX: 77.011. (CXX) g++ options: -O3 -rdynamic -lgomp -lpthread
OpenBenchmarking.orgms, Fewer Is BetterNCNN 20200916Target: CPU - Model: mobilenetv2_yolov3Core i7 1065G7c2c3714212835Min: 32.72 / Avg: 32.83 / Max: 33.28Min: 32.67 / Avg: 33.04 / Max: 33.9Min: 32.79 / Avg: 33.45 / Max: 34.451. (CXX) g++ options: -O3 -rdynamic -lgomp -lpthread

OpenBenchmarking.orgms, Fewer Is BetterNCNN 20200916Target: CPU - Model: resnet18_int8Core i7 1065G7c2c31020304050SE +/- 0.03, N = 9SE +/- 0.01, N = 9SE +/- 0.34, N = 943.5543.6944.09MIN: 42.21 / MAX: 59.32MIN: 42.2 / MAX: 63.01MIN: 39.63 / MAX: 445.951. (CXX) g++ options: -O3 -rdynamic -lgomp -lpthread
OpenBenchmarking.orgms, Fewer Is BetterNCNN 20200916Target: CPU - Model: resnet18_int8Core i7 1065G7c2c3918273645Min: 43.44 / Avg: 43.55 / Max: 43.7Min: 43.65 / Avg: 43.69 / Max: 43.76Min: 43.57 / Avg: 44.09 / Max: 46.761. (CXX) g++ options: -O3 -rdynamic -lgomp -lpthread

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 1065G7c2c32004006008001000SE +/- 4.62, N = 3SE +/- 7.24, N = 3SE +/- 6.05, N = 31046.611045.301058.161. (F9X) gfortran options: -cpp -funroll-loops -floop-optimize -fcray-pointer -fbacktrace -pthread -lmpi_usempif08 -lmpi_mpifh -lmpi
OpenBenchmarking.orgSeconds, Fewer Is BetterIncompact3D 2020-09-17Input: CylinderCore i7 1065G7c2c32004006008001000Min: 1040.31 / Avg: 1046.61 / Max: 1055.61Min: 1031.01 / Avg: 1045.3 / Max: 1054.5Min: 1049.34 / Avg: 1058.16 / Max: 1069.741. (F9X) gfortran options: -cpp -funroll-loops -floop-optimize -fcray-pointer -fbacktrace -pthread -lmpi_usempif08 -lmpi_mpifh -lmpi

NCNN

OpenBenchmarking.orgms, Fewer Is BetterNCNN 20200916Target: CPU - Model: alexnetCore i7 1065G7c2c3510152025SE +/- 0.05, N = 9SE +/- 0.03, N = 9SE +/- 0.06, N = 920.4520.4920.63MIN: 19.3 / MAX: 37.23MIN: 19.29 / MAX: 36.32MIN: 19.26 / MAX: 66.671. (CXX) g++ options: -O3 -rdynamic -lgomp -lpthread
OpenBenchmarking.orgms, Fewer Is BetterNCNN 20200916Target: CPU - Model: alexnetCore i7 1065G7c2c3510152025Min: 20.32 / Avg: 20.45 / Max: 20.74Min: 20.42 / Avg: 20.49 / Max: 20.75Min: 20.45 / Avg: 20.63 / Max: 20.881. (CXX) g++ options: -O3 -rdynamic -lgomp -lpthread

OpenBenchmarking.orgms, Fewer Is BetterNCNN 20200916Target: CPU - Model: mnasnetCore i7 1065G7c2c3246810SE +/- 0.01, N = 9SE +/- 0.01, N = 9SE +/- 0.01, N = 98.298.318.36MIN: 7.91 / MAX: 16.48MIN: 7.92 / MAX: 13.43MIN: 7.91 / MAX: 13.281. (CXX) g++ options: -O3 -rdynamic -lgomp -lpthread
OpenBenchmarking.orgms, Fewer Is BetterNCNN 20200916Target: CPU - Model: mnasnetCore i7 1065G7c2c33691215Min: 8.24 / Avg: 8.29 / Max: 8.33Min: 8.27 / Avg: 8.31 / Max: 8.42Min: 8.32 / Avg: 8.36 / Max: 8.441. (CXX) g++ options: -O3 -rdynamic -lgomp -lpthread

OpenBenchmarking.orgms, Fewer Is BetterNCNN 20200916Target: CPU - Model: squeezenet_int8Core i7 1065G7c2c3510152025SE +/- 0.35, N = 9SE +/- 0.37, N = 9SE +/- 0.37, N = 920.4220.5620.59MIN: 17.32 / MAX: 40.6MIN: 17.33 / MAX: 39.14MIN: 17.3 / MAX: 45.021. (CXX) g++ options: -O3 -rdynamic -lgomp -lpthread
OpenBenchmarking.orgms, Fewer Is BetterNCNN 20200916Target: CPU - Model: squeezenet_int8Core i7 1065G7c2c3510152025Min: 17.59 / Avg: 20.42 / Max: 20.88Min: 17.64 / Avg: 20.56 / Max: 20.99Min: 17.66 / Avg: 20.59 / Max: 21.011. (CXX) g++ options: -O3 -rdynamic -lgomp -lpthread

LAMMPS Molecular Dynamics Simulator

LAMMPS is a classical molecular dynamics code, and an acronym for Large-scale Atomic/Molecular Massively Parallel Simulator. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgns/day, More Is BetterLAMMPS Molecular Dynamics Simulator 24Aug2020Model: 20k AtomsCore i7 1065G7c2c30.48310.96621.44931.93242.4155SE +/- 0.003, N = 3SE +/- 0.001, N = 3SE +/- 0.003, N = 32.1472.1412.1301. (CXX) g++ options: -O3 -pthread -lm
OpenBenchmarking.orgns/day, More Is BetterLAMMPS Molecular Dynamics Simulator 24Aug2020Model: 20k AtomsCore i7 1065G7c2c3246810Min: 2.14 / Avg: 2.15 / Max: 2.15Min: 2.14 / Avg: 2.14 / Max: 2.14Min: 2.13 / Avg: 2.13 / Max: 2.141. (CXX) g++ options: -O3 -pthread -lm

NCNN

OpenBenchmarking.orgms, Fewer Is BetterNCNN 20200916Target: CPU - Model: mobilenet_v3Core i7 1065G7c2c3246810SE +/- 0.01, N = 9SE +/- 0.02, N = 9SE +/- 0.02, N = 97.527.567.58MIN: 7.02 / MAX: 25.19MIN: 7 / MAX: 20.22MIN: 7.01 / MAX: 18.211. (CXX) g++ options: -O3 -rdynamic -lgomp -lpthread
OpenBenchmarking.orgms, Fewer Is BetterNCNN 20200916Target: CPU - Model: mobilenet_v3Core i7 1065G7c2c33691215Min: 7.46 / Avg: 7.52 / Max: 7.57Min: 7.5 / Avg: 7.56 / Max: 7.73Min: 7.52 / Avg: 7.58 / Max: 7.731. (CXX) g++ options: -O3 -rdynamic -lgomp -lpthread

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 1065G7c2c390180270360450SE +/- 0.58, N = 3SE +/- 0.33, N = 33913933941. (F9X) gfortran options: -cpp -Jsource/ -ffree-line-length-0 -lm -std=legacy -O3 -O2 -pthread -lmpi_usempif08 -lmpi_mpifh -lmpi
OpenBenchmarking.orgSeconds, Fewer Is BetterMonte Carlo Simulations of Ionised Nebulae 2019-03-24Input: Dust 2D tau100.0Core i7 1065G7c2c370140210280350Min: 390 / Avg: 391 / Max: 392Min: 393 / Avg: 393.67 / Max: 3941. (F9X) gfortran options: -cpp -Jsource/ -ffree-line-length-0 -lm -std=legacy -O3 -O2 -pthread -lmpi_usempif08 -lmpi_mpifh -lmpi

NCNN

OpenBenchmarking.orgms, Fewer Is BetterNCNN 20200916Target: CPU - Model: squeezenetCore i7 1065G7c2c31.3052.613.9155.226.525SE +/- 0.01, N = 9SE +/- 0.01, N = 9SE +/- 0.02, N = 95.765.795.80MIN: 5.54 / MAX: 10.67MIN: 5.54 / MAX: 10.34MIN: 5.53 / MAX: 37.581. (CXX) g++ options: -O3 -rdynamic -lgomp -lpthread
OpenBenchmarking.orgms, Fewer Is BetterNCNN 20200916Target: CPU - Model: squeezenetCore i7 1065G7c2c3246810Min: 5.72 / Avg: 5.76 / Max: 5.78Min: 5.76 / Avg: 5.79 / Max: 5.84Min: 5.76 / Avg: 5.8 / Max: 5.941. (CXX) g++ options: -O3 -rdynamic -lgomp -lpthread

OpenBenchmarking.orgms, Fewer Is BetterNCNN 20200916Target: CPU - Model: googlenet_int8Core i7 1065G7c2c31530456075SE +/- 0.05, N = 9SE +/- 0.03, N = 9SE +/- 0.02, N = 968.9069.1569.27MIN: 65.9 / MAX: 95.74MIN: 67.96 / MAX: 86.33MIN: 67.94 / MAX: 88.571. (CXX) g++ options: -O3 -rdynamic -lgomp -lpthread
OpenBenchmarking.orgms, Fewer Is BetterNCNN 20200916Target: CPU - Model: googlenet_int8Core i7 1065G7c2c31326395265Min: 68.67 / Avg: 68.9 / Max: 69.04Min: 69.01 / Avg: 69.15 / Max: 69.24Min: 69.16 / Avg: 69.27 / Max: 69.361. (CXX) g++ options: -O3 -rdynamic -lgomp -lpthread

OpenBenchmarking.orgms, Fewer Is BetterNCNN 20200916Target: CPU - Model: vgg16_int8Core i7 1065G7c2c350100150200250SE +/- 0.11, N = 9SE +/- 0.14, N = 9SE +/- 0.13, N = 9236.47235.78236.83MIN: 227.29 / MAX: 295.39MIN: 230.92 / MAX: 256.51MIN: 227.39 / MAX: 335.991. (CXX) g++ options: -O3 -rdynamic -lgomp -lpthread
OpenBenchmarking.orgms, Fewer Is BetterNCNN 20200916Target: CPU - Model: vgg16_int8Core i7 1065G7c2c34080120160200Min: 236.04 / Avg: 236.47 / Max: 236.88Min: 235.29 / Avg: 235.78 / Max: 236.71Min: 236.31 / Avg: 236.83 / Max: 237.461. (CXX) g++ options: -O3 -rdynamic -lgomp -lpthread

GPAW

GPAW is a density-functional theory (DFT) Python code based on the projector-augmented wave (PAW) method and the atomic simulation environment (ASE). Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgSeconds, Fewer Is BetterGPAW 20.1Input: Carbon NanotubeCore i7 1065G7c2c3150300450600750SE +/- 4.56, N = 3SE +/- 1.37, N = 3SE +/- 0.29, N = 3717.39715.45715.121. (CC) gcc options: -pthread -shared -fwrapv -O2 -lxc -lblas -lmpi
OpenBenchmarking.orgSeconds, Fewer Is BetterGPAW 20.1Input: Carbon NanotubeCore i7 1065G7c2c3130260390520650Min: 711.89 / Avg: 717.39 / Max: 726.43Min: 712.83 / Avg: 715.45 / Max: 717.43Min: 714.58 / Avg: 715.12 / Max: 715.581. (CC) gcc options: -pthread -shared -fwrapv -O2 -lxc -lblas -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: mobilenet-v1-1.0Core i7 1065G7c2c33691215SE +/- 0.020, N = 3SE +/- 0.010, N = 3SE +/- 0.016, N = 39.4149.4049.424MIN: 8.88 / MAX: 33.54MIN: 8.87 / MAX: 29.15MIN: 8.82 / MAX: 37.661. (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 1065G7c2c33691215Min: 9.38 / Avg: 9.41 / Max: 9.45Min: 9.39 / Avg: 9.4 / Max: 9.42Min: 9.4 / Avg: 9.42 / Max: 9.461. (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 2020-09-17Model: resnet-v2-50Core i7 1065G7c2c31326395265SE +/- 0.33, N = 3SE +/- 0.31, N = 3SE +/- 0.26, N = 358.5058.5958.61MIN: 55.95 / MAX: 79.63MIN: 55.91 / MAX: 82.97MIN: 56.04 / MAX: 83.441. (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 1065G7c2c31224364860Min: 57.84 / Avg: 58.5 / Max: 58.89Min: 58.04 / Avg: 58.59 / Max: 59.11Min: 58.09 / Avg: 58.6 / Max: 58.881. (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: SqueezeNetV1.0Core i7 1065G7c2c33691215SE +/- 0.09, N = 3SE +/- 0.09, N = 3SE +/- 0.10, N = 312.2512.2412.26MIN: 11.69 / MAX: 35.17MIN: 11.7 / MAX: 33.18MIN: 11.74 / MAX: 35.921. (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: SqueezeNetV1.0Core i7 1065G7c2c348121620Min: 12.07 / Avg: 12.25 / Max: 12.37Min: 12.07 / Avg: 12.24 / Max: 12.37Min: 12.07 / Avg: 12.26 / Max: 12.391. (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 1065G7c2c31632486480SE +/- 0.43, N = 3SE +/- 0.41, N = 3SE +/- 0.36, N = 371.7371.7371.63MIN: 69.48 / MAX: 95.62MIN: 69.72 / MAX: 93.82MIN: 69.71 / MAX: 92.551. (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 1065G7c2c31428425670Min: 70.92 / Avg: 71.73 / Max: 72.4Min: 71.04 / Avg: 71.73 / Max: 72.46Min: 70.92 / Avg: 71.63 / Max: 72.051. (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: blazefaceCore i7 1065G7c2c30.541.081.622.162.7SE +/- 0.01, N = 9SE +/- 0.00, N = 9SE +/- 0.01, N = 92.402.402.40MIN: 2.24 / MAX: 6.82MIN: 2.21 / MAX: 6.66MIN: 2.23 / MAX: 7.091. (CXX) g++ options: -O3 -rdynamic -lgomp -lpthread
OpenBenchmarking.orgms, Fewer Is BetterNCNN 20200916Target: CPU - Model: blazefaceCore i7 1065G7c2c3246810Min: 2.36 / Avg: 2.4 / Max: 2.42Min: 2.38 / Avg: 2.4 / Max: 2.42Min: 2.37 / Avg: 2.4 / Max: 2.431. (CXX) g++ options: -O3 -rdynamic -lgomp -lpthread

LAMMPS Molecular Dynamics Simulator

LAMMPS is a classical molecular dynamics code, and an acronym for Large-scale Atomic/Molecular Massively Parallel Simulator. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgns/day, More Is BetterLAMMPS Molecular Dynamics Simulator 24Aug2020Model: Rhodopsin ProteinCore i7 1065G7c2c30.59491.18981.78472.37962.9745SE +/- 0.076, N = 15SE +/- 0.073, N = 15SE +/- 0.079, N = 152.5922.6112.6441. (CXX) g++ options: -O3 -pthread -lm
OpenBenchmarking.orgns/day, More Is BetterLAMMPS Molecular Dynamics Simulator 24Aug2020Model: Rhodopsin ProteinCore i7 1065G7c2c3246810Min: 2.21 / Avg: 2.59 / Max: 2.92Min: 2.26 / Avg: 2.61 / Max: 2.94Min: 2.31 / Avg: 2.64 / Max: 3.191. (CXX) g++ options: -O3 -pthread -lm

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: MobileNetV2_224Core i7 1065G7c2c31.17682.35363.53044.70725.884SE +/- 0.522, N = 3SE +/- 0.498, N = 3SE +/- 0.521, N = 35.2135.2305.223MIN: 3.92 / MAX: 28.66MIN: 3.93 / MAX: 29.24MIN: 3.92 / MAX: 27.351. (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 1065G7c2c3246810Min: 4.17 / Avg: 5.21 / Max: 5.76Min: 4.23 / Avg: 5.23 / Max: 5.73Min: 4.18 / Avg: 5.22 / Max: 5.751. (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: resnet50_int8Core i7 1065G7c2c34080120160200SE +/- 0.08, N = 9SE +/- 11.79, N = 9SE +/- 0.06, N = 9147.82160.00148.33MIN: 145.24 / MAX: 166.07MIN: 142.07 / MAX: 8406.08MIN: 145.05 / MAX: 177.031. (CXX) g++ options: -O3 -rdynamic -lgomp -lpthread
OpenBenchmarking.orgms, Fewer Is BetterNCNN 20200916Target: CPU - Model: resnet50_int8Core i7 1065G7c2c3306090120150Min: 147.47 / Avg: 147.82 / Max: 148.19Min: 147.99 / Avg: 160 / Max: 254.31Min: 148.12 / Avg: 148.33 / Max: 148.561. (CXX) g++ options: -O3 -rdynamic -lgomp -lpthread