python20201120

R Pi Python Test

Compare your own system(s) to this result file with the Phoronix Test Suite by running the command: phoronix-test-suite benchmark 2011199-KH-PYTHON20240

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python20201120OpenBenchmarking.orgPhoronix Test Suite 10.2.0ARMv7 rev 3 @ 1.50GHz (4 Cores)BCM27114096MB16GB SC16Gllvmpipe (LLVM 9.0.1 128 bits)Panasonic-TVRaspbian 105.4.74-v7ls3775590-g2ae9829c3da5 (armv7l)LXDE 0.10.0X Server plymouth.ignore-serial-consolesmodesetting 1.20.43.3 Mesa 19.3.2ext41280x720ProcessorMotherboardMemoryDiskGraphicsMonitorOSKernelDesktopDisplay ServerDisplay DriverOpenGLFile-SystemScreen ResolutionPython20201120 BenchmarksSystem LogsOPC Classification- snd_bcm2835.enable_compat_alsa=0 snd_bcm2835.enable_hdmi=1 - --build=arm-linux-gnueabihf --disable-libitm --disable-libquadmath --disable-libquadmath-support --disable-sjlj-exceptions --disable-werror --enable-bootstrap --enable-checking=release --enable-clocale=gnu --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-objc-gc=auto --enable-plugin --enable-shared --enable-threads=posix --host=arm-linux-gnueabihf --program-prefix=arm-linux-gnueabihf- --target=arm-linux-gnueabihf --with-arch=armv6 --with-default-libstdcxx-abi=new --with-float=hard --with-fpu=vfp --with-gcc-major-version-only --with-target-system-zlib -v - Scaling Governor: cpufreq-dt ondemand- Python 2.7.16.

python20201120numpy: Phoronix Test Suite v5.2.1pybench: Total For Average Test Timespyperformance: gopyperformance: 2to3pyperformance: chaospyperformance: floatpyperformance: nbodypyperformance: pathlibpyperformance: raytracepyperformance: json_loadspyperformance: crypto_pyaespyperformance: regex_compilepyperformance: python_startuppyperformance: django_templatepyperformance: pickle_pure_pythonnumenta-nab: Windowed Gaussiannumenta-nab: Earthgecko Skylinepythons377559025.8052161.371.806326026061452.7714356598443.603702.82179.081933.53OpenBenchmarking.org

Numpy Benchmark

This is a test to obtain the general Numpy performance. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgScore, More Is BetterNumpy BenchmarkPhoronix Test Suite v5.2.1pythons3775590612182430SE +/- 0.05, N = 325.80

PyBench

This test profile reports the total time of the different average timed test results from PyBench. PyBench reports average test times for different functions such as BuiltinFunctionCalls and NestedForLoops, with this total result providing a rough estimate as to Python's average performance on a given system. This test profile runs PyBench each time for 20 rounds. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgMilliseconds, Fewer Is BetterPyBench 2018-02-16Total For Average Test Timespythons377559011002200330044005500SE +/- 10.40, N = 35216

PyPerformance

PyPerformance is the reference Python performance benchmark suite. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgMilliseconds, Fewer Is BetterPyPerformance 1.0.0Benchmark: gopythons37755900.30830.61660.92491.23321.5415SE +/- 0.00, N = 31.37

OpenBenchmarking.orgMilliseconds, Fewer Is BetterPyPerformance 1.0.0Benchmark: 2to3pythons37755900.4050.811.2151.622.025SE +/- 0.00, N = 31.80

OpenBenchmarking.orgMilliseconds, Fewer Is BetterPyPerformance 1.0.0Benchmark: chaospythons3775590140280420560700SE +/- 0.58, N = 3632

OpenBenchmarking.orgMilliseconds, Fewer Is BetterPyPerformance 1.0.0Benchmark: floatpythons3775590130260390520650SE +/- 1.53, N = 3602

OpenBenchmarking.orgMilliseconds, Fewer Is BetterPyPerformance 1.0.0Benchmark: nbodypythons3775590130260390520650SE +/- 0.58, N = 3606

OpenBenchmarking.orgMilliseconds, Fewer Is BetterPyPerformance 1.0.0Benchmark: pathlibpythons3775590306090120150SE +/- 0.33, N = 3145

OpenBenchmarking.orgMilliseconds, Fewer Is BetterPyPerformance 1.0.0Benchmark: raytracepythons37755900.62331.24661.86992.49323.1165SE +/- 0.00, N = 32.77

OpenBenchmarking.orgMilliseconds, Fewer Is BetterPyPerformance 1.0.0Benchmark: json_loadspythons3775590306090120150SE +/- 0.33, N = 3143

OpenBenchmarking.orgMilliseconds, Fewer Is BetterPyPerformance 1.0.0Benchmark: crypto_pyaespythons3775590120240360480600SE +/- 0.00, N = 3565

OpenBenchmarking.orgMilliseconds, Fewer Is BetterPyPerformance 1.0.0Benchmark: regex_compilepythons37755902004006008001000SE +/- 1.20, N = 3984

OpenBenchmarking.orgMilliseconds, Fewer Is BetterPyPerformance 1.0.0Benchmark: python_startuppythons37755901020304050SE +/- 0.00, N = 343.60

OpenBenchmarking.orgMilliseconds, Fewer Is BetterPyPerformance 1.0.0Benchmark: django_templatepythons377559080160240320400SE +/- 0.33, N = 3370

OpenBenchmarking.orgMilliseconds, Fewer Is BetterPyPerformance 1.0.0Benchmark: pickle_pure_pythonpythons37755900.63451.2691.90352.5383.1725SE +/- 0.01, N = 32.82

Numenta Anomaly Benchmark

Numenta Anomaly Benchmark (NAB) is a benchmark for evaluating algorithms for anomaly detection in streaming, real-time applications. It is comprised of over 50 labeled real-world and artificial timeseries data files plus a novel scoring mechanism designed for real-time applications. This test profile currently measures the time to run various detectors. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgSeconds, Fewer Is BetterNumenta Anomaly Benchmark 1.1Detector: Windowed Gaussianpythons37755904080120160200SE +/- 1.62, N = 3179.08

OpenBenchmarking.orgSeconds, Fewer Is BetterNumenta Anomaly Benchmark 1.1Detector: Earthgecko Skylinepythons3775590400800120016002000SE +/- 7.61, N = 31933.53


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