jetson

ARMv8 Cortex-A57 testing with a NVIDIA Jetson Nano Developer Kit and NVIDIA TEGRA on Ubuntu 18.04 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 2012278-FI-JETSON92942
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cuda
December 25 2020
  27 Minutes
glmark2
December 27 2020
  51 Minutes
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jetson ProcessorMotherboardMemoryDiskGraphicsMonitorNetworkOSKernelDesktopDisplay ServerDisplay DriverVulkanCompilerFile-SystemScreen Resolutioncudaglmark2ARMv8 Cortex-A57 @ 1.48GHz (4 Cores)NVIDIA Jetson Nano Developer Kit4096MB16GB DG4016 + 15GB i-TFNVIDIA TEGRAASUS VN248Realtek RTL8111/8168/8411Ubuntu 18.044.9.140-tegra (aarch64)Unity 7.5.0X Server 1.19.6NVIDIA 1.0.01.2.131GCC 7.5.0 + CUDA 10.2ext41920x1080PHL 276E8V5760x2160OpenBenchmarking.orgCompiler Details- cuda: --build=aarch64-linux-gnu --disable-libquadmath --disable-libquadmath-support --disable-werror --enable-bootstrap --enable-checking=release --enable-clocale=gnu --enable-default-pie --enable-fix-cortex-a53-843419 --enable-gnu-unique-object --enable-languages=c,ada,c++,go,d,fortran,objc,obj-c++ --enable-libstdcxx-debug --enable-libstdcxx-time=yes --enable-multiarch --enable-nls --enable-plugin --enable-shared --enable-threads=posix --host=aarch64-linux-gnu --program-prefix=aarch64-linux-gnu- --target=aarch64-linux-gnu --with-default-libstdcxx-abi=new --with-gcc-major-version-only -v Processor Details- Scaling Governor: tegra-cpufreq schedutilPython Details- glmark2: Python 2.7.17 + Python 3.6.9

jetson glmark2: 800 x 600glmark2: 1024 x 768glmark2: 1280 x 1024glmark2: 1600 x 1200glmark2: 1920 x 1080glmark2: 1920 x 1200glmark2: 2560 x 1440glmark2: 3840 x 2160glmark2: 5760 x 2160cuda-mini-nbody: Flush Denormals To Zerocuda-mini-nbody: SOA Data Layoutcuda-mini-nbody: Loop Unrollingcuda-mini-nbody: Cache Blockingcuda-mini-nbody: Originalcudaglmark216606.88116425.12916419.35816572.24512249.1751533114276554949740227313095OpenBenchmarking.org

GLmark2

This is a test of Linaro's glmark2 port, currently using the X11 OpenGL 2.0 target. GLmark2 is a basic OpenGL benchmark. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgScore, More Is BetterGLmark2 2020.04Resolution: 800 x 600glmark2300600900120015001533

OpenBenchmarking.orgScore, More Is BetterGLmark2 2020.04Resolution: 1024 x 768glmark220040060080010001142

OpenBenchmarking.orgScore, More Is BetterGLmark2 2020.04Resolution: 1280 x 1024glmark2160320480640800765

OpenBenchmarking.orgScore, More Is BetterGLmark2 2020.04Resolution: 1600 x 1200glmark2120240360480600549

OpenBenchmarking.orgScore, More Is BetterGLmark2 2020.04Resolution: 1920 x 1080glmark2110220330440550497

OpenBenchmarking.orgScore, More Is BetterGLmark2 2020.04Resolution: 1920 x 1200glmark290180270360450402

OpenBenchmarking.orgScore, More Is BetterGLmark2 2020.04Resolution: 2560 x 1440glmark260120180240300273

OpenBenchmarking.orgScore, More Is BetterGLmark2 2020.04Resolution: 3840 x 2160glmark2306090120150130

OpenBenchmarking.orgScore, More Is BetterGLmark2 2020.04Resolution: 5760 x 2160glmark22040608010095

CUDA Mini-Nbody

The CUDA version of Harrism's mini-nbody tests. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.org(NBody^2)/s, More Is BetterCUDA Mini-Nbody 2015-11-10Test: Flush Denormals To Zerocuda4K8K12K16K20KSE +/- 180.88, N = 316606.88

OpenBenchmarking.org(NBody^2)/s, More Is BetterCUDA Mini-Nbody 2015-11-10Test: SOA Data Layoutcuda4K8K12K16K20KSE +/- 187.36, N = 616425.13

OpenBenchmarking.org(NBody^2)/s, More Is BetterCUDA Mini-Nbody 2015-11-10Test: Loop Unrollingcuda4K8K12K16K20KSE +/- 101.50, N = 316419.36

OpenBenchmarking.org(NBody^2)/s, More Is BetterCUDA Mini-Nbody 2015-11-10Test: Cache Blockingcuda4K8K12K16K20KSE +/- 91.84, N = 316572.25

OpenBenchmarking.org(NBody^2)/s, More Is BetterCUDA Mini-Nbody 2015-11-10Test: Originalcuda3K6K9K12K15KSE +/- 84.57, N = 312249.18