pythonTest

ARMv7 Cortex-A72 testing with a BCM2711 Raspberry Pi 4 Model B Rev 1.4 and vc4drmfb on Raspbian 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 2011200-FI-PYTHONTES63
Jump To Table - Results

Statistics

Remove Outliers Before Calculating Averages

Graph Settings

Prefer Vertical Bar Graphs

Multi-Way Comparison

Condense Multi-Option Tests Into Single Result Graphs

Table

Show Detailed System Result Table

Run Management

Result
Identifier
View Logs
Performance Per
Dollar
Date
Run
  Test
  Duration
s3597958Python
November 19 2020
  10 Hours, 5 Minutes
Only show results matching title/arguments (delimit multiple options with a comma):
Do not show results matching title/arguments (delimit multiple options with a comma):


pythonTestOpenBenchmarking.orgPhoronix Test SuiteARMv7 Cortex-A72 @ 1.50GHz (4 Cores)BCM2711 Raspberry Pi 4 Model B Rev 1.48GB2 x 31GB USB Flash Drive + 64GB SR64Gvc4drmfbASUS VA27EHERaspbian 105.4.75-s3597958+ (armv7l)LXDE 0.10.0X Server 1.20.4modesetting 1.20.42.1 Mesa 19.3.2GCC 8.3.0ext41920x1080ProcessorMotherboardMemoryDiskGraphicsMonitorOSKernelDesktopDisplay ServerDisplay DriverOpenGLCompilerFile-SystemScreen ResolutionPythonTest BenchmarksSystem Logs- 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 + Python 3.7.3

pythonTestnumpy: pybench: 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: EXPoSEnumenta-nab: Relative Entropynumenta-nab: Windowed Gaussiannumenta-nab: Earthgecko Skylinenumenta-nab: Bayesian Changepointscikit-learn: s3597958Python25.4852021.381.826356066011552.86148590167.3646.93843.211009.727341.476172.4292122.3991028.108198.112OpenBenchmarking.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 Benchmarks3597958Python612182430SE +/- 0.09, N = 325.48

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 Timess3597958Python11002200330044005500SE +/- 9.33, N = 35202

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: gos3597958Python0.31050.6210.93151.2421.5525SE +/- 0.00, N = 31.38

OpenBenchmarking.orgMilliseconds, Fewer Is BetterPyPerformance 1.0.0Benchmark: 2to3s3597958Python0.40950.8191.22851.6382.0475SE +/- 0.00, N = 31.82

OpenBenchmarking.orgMilliseconds, Fewer Is BetterPyPerformance 1.0.0Benchmark: chaoss3597958Python140280420560700635

OpenBenchmarking.orgMilliseconds, Fewer Is BetterPyPerformance 1.0.0Benchmark: floats3597958Python130260390520650606

OpenBenchmarking.orgMilliseconds, Fewer Is BetterPyPerformance 1.0.0Benchmark: nbodys3597958Python130260390520650SE +/- 0.67, N = 3601

OpenBenchmarking.orgMilliseconds, Fewer Is BetterPyPerformance 1.0.0Benchmark: pathlibs3597958Python306090120150SE +/- 2.32, N = 4155

OpenBenchmarking.orgMilliseconds, Fewer Is BetterPyPerformance 1.0.0Benchmark: raytraces3597958Python0.64351.2871.93052.5743.2175SE +/- 0.02, N = 32.86

OpenBenchmarking.orgMilliseconds, Fewer Is BetterPyPerformance 1.0.0Benchmark: json_loadss3597958Python306090120150SE +/- 0.88, N = 3148

OpenBenchmarking.orgMilliseconds, Fewer Is BetterPyPerformance 1.0.0Benchmark: crypto_pyaess3597958Python130260390520650SE +/- 4.97, N = 12590

OpenBenchmarking.orgMilliseconds, Fewer Is BetterPyPerformance 1.0.0Benchmark: regex_compiles3597958Python4080120160200SE +/- 112.14, N = 12167.36

OpenBenchmarking.orgMilliseconds, Fewer Is BetterPyPerformance 1.0.0Benchmark: python_startups3597958Python1122334455SE +/- 0.27, N = 346.9

OpenBenchmarking.orgMilliseconds, Fewer Is BetterPyPerformance 1.0.0Benchmark: django_templates3597958Python80160240320400SE +/- 6.11, N = 3384

OpenBenchmarking.orgMilliseconds, Fewer Is BetterPyPerformance 1.0.0Benchmark: pickle_pure_pythons3597958Python0.72231.44462.16692.88923.6115SE +/- 0.01, N = 33.21

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: EXPoSEs3597958Python2004006008001000SE +/- 17.15, N = 91009.73

OpenBenchmarking.orgSeconds, Fewer Is BetterNumenta Anomaly Benchmark 1.1Detector: Relative Entropys3597958Python70140210280350SE +/- 0.96, N = 3341.48

OpenBenchmarking.orgSeconds, Fewer Is BetterNumenta Anomaly Benchmark 1.1Detector: Windowed Gaussians3597958Python4080120160200SE +/- 0.51, N = 3172.43

OpenBenchmarking.orgSeconds, Fewer Is BetterNumenta Anomaly Benchmark 1.1Detector: Earthgecko Skylines3597958Python5001000150020002500SE +/- 1.80, N = 32122.40

OpenBenchmarking.orgSeconds, Fewer Is BetterNumenta Anomaly Benchmark 1.1Detector: Bayesian Changepoints3597958Python2004006008001000SE +/- 0.57, N = 31028.11

Scikit-Learn

Scikit-learn is a Python module for machine learning Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgSeconds, Fewer Is BetterScikit-Learn 0.22.1s3597958Python4080120160200SE +/- 0.54, N = 3198.11