python-test-suite

Running pts/numpy-1.2.1, pts/cython-bench-1.0.0, pts/pybench-1.1.3, pts/pyperformance-1.0.2, pts/numenta-nab-1.1.0, pts/mlpack-1.0.2, pts/scikit-learn-1.1.0 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 2011180-KH-PYTHONTES39
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python-test-suiteProcessorMotherboardMemoryDiskGraphicsOSKernelDesktopDisplay ServerDisplay DriverOpenGLFile-SystemScreen Resolutionfirst-runsecond-run-no-fanARMv7 rev 3 @ 1.50GHz (4 Cores)BCM27114096MB31GB SD32Gllvmpipe (LLVM 9.0.1 128 bits)Raspbian 105.4.72-v7l+ (armv7l)LXDE 0.10.0X Server plymouth.ignore-serial-consolesmodesetting 1.20.43.3 Mesa 19.3.2ext41200x800AMD Radeon R7 M3705.4.77-v7l-s3588366+ (armv7l)1.41440x900OpenBenchmarking.orgKernel Details- first-run: snd_bcm2835.enable_compat_alsa=0 snd_bcm2835.enable_hdmi=1 snd_bcm2835.enable_headphones=1 Compiler Details- --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 Processor Details- Scaling Governor: cpufreq-dt ondemandSystem Details- Python 2.7.16.

python-test-suitenumpy: 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 Skylinefirst-runsecond-run-no-fan25.8252261.371.806376025961452.7614256698343.803672.82156.561866.6026.1852811.371.796325985981442.7714256998043.573652.82250.722962.19OpenBenchmarking.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 v5.2.1first-runsecond-run-no-fan612182430SE +/- 0.05, N = 3SE +/- 0.06, N = 325.8226.18
OpenBenchmarking.orgScore, More Is BetterNumpy BenchmarkPhoronix Test Suite v5.2.1first-runsecond-run-no-fan612182430Min: 25.75 / Avg: 25.82 / Max: 25.93Min: 26.07 / Avg: 26.18 / Max: 26.29

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 Timesfirst-runsecond-run-no-fan11002200330044005500SE +/- 6.39, N = 3SE +/- 9.70, N = 352265281
OpenBenchmarking.orgMilliseconds, Fewer Is BetterPyBench 2018-02-16Total For Average Test Timesfirst-runsecond-run-no-fan9001800270036004500Min: 5216 / Avg: 5226.33 / Max: 5238Min: 5263 / Avg: 5281.33 / Max: 5296

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: gofirst-runsecond-run-no-fan0.30830.61660.92491.23321.5415SE +/- 0.00, N = 3SE +/- 0.00, N = 31.371.37
OpenBenchmarking.orgMilliseconds, Fewer Is BetterPyPerformance 1.0.0Benchmark: gofirst-runsecond-run-no-fan246810Min: 1.37 / Avg: 1.37 / Max: 1.37Min: 1.37 / Avg: 1.37 / Max: 1.37

OpenBenchmarking.orgMilliseconds, Fewer Is BetterPyPerformance 1.0.0Benchmark: 2to3first-runsecond-run-no-fan0.4050.811.2151.622.025SE +/- 0.00, N = 3SE +/- 0.00, N = 31.801.79
OpenBenchmarking.orgMilliseconds, Fewer Is BetterPyPerformance 1.0.0Benchmark: 2to3first-runsecond-run-no-fan246810Min: 1.8 / Avg: 1.8 / Max: 1.8Min: 1.79 / Avg: 1.79 / Max: 1.79

OpenBenchmarking.orgMilliseconds, Fewer Is BetterPyPerformance 1.0.0Benchmark: chaosfirst-runsecond-run-no-fan140280420560700SE +/- 0.88, N = 3SE +/- 0.58, N = 3637632
OpenBenchmarking.orgMilliseconds, Fewer Is BetterPyPerformance 1.0.0Benchmark: chaosfirst-runsecond-run-no-fan110220330440550Min: 635 / Avg: 636.67 / Max: 638Min: 631 / Avg: 632 / Max: 633

OpenBenchmarking.orgMilliseconds, Fewer Is BetterPyPerformance 1.0.0Benchmark: floatfirst-runsecond-run-no-fan130260390520650SE +/- 0.33, N = 3SE +/- 0.33, N = 3602598
OpenBenchmarking.orgMilliseconds, Fewer Is BetterPyPerformance 1.0.0Benchmark: floatfirst-runsecond-run-no-fan110220330440550Min: 602 / Avg: 602.33 / Max: 603Min: 598 / Avg: 598.33 / Max: 599

OpenBenchmarking.orgMilliseconds, Fewer Is BetterPyPerformance 1.0.0Benchmark: nbodyfirst-runsecond-run-no-fan130260390520650SE +/- 1.20, N = 3SE +/- 0.33, N = 3596598
OpenBenchmarking.orgMilliseconds, Fewer Is BetterPyPerformance 1.0.0Benchmark: nbodyfirst-runsecond-run-no-fan110220330440550Min: 594 / Avg: 596.33 / Max: 598Min: 598 / Avg: 598.33 / Max: 599

OpenBenchmarking.orgMilliseconds, Fewer Is BetterPyPerformance 1.0.0Benchmark: pathlibfirst-runsecond-run-no-fan306090120150SE +/- 0.00, N = 3SE +/- 0.33, N = 3145144
OpenBenchmarking.orgMilliseconds, Fewer Is BetterPyPerformance 1.0.0Benchmark: pathlibfirst-runsecond-run-no-fan306090120150Min: 145 / Avg: 145 / Max: 145Min: 144 / Avg: 144.33 / Max: 145

OpenBenchmarking.orgMilliseconds, Fewer Is BetterPyPerformance 1.0.0Benchmark: raytracefirst-runsecond-run-no-fan0.62331.24661.86992.49323.1165SE +/- 0.00, N = 3SE +/- 0.00, N = 32.762.77
OpenBenchmarking.orgMilliseconds, Fewer Is BetterPyPerformance 1.0.0Benchmark: raytracefirst-runsecond-run-no-fan246810Min: 2.76 / Avg: 2.76 / Max: 2.77Min: 2.77 / Avg: 2.77 / Max: 2.77

OpenBenchmarking.orgMilliseconds, Fewer Is BetterPyPerformance 1.0.0Benchmark: json_loadsfirst-runsecond-run-no-fan306090120150SE +/- 0.33, N = 3SE +/- 0.00, N = 3142142
OpenBenchmarking.orgMilliseconds, Fewer Is BetterPyPerformance 1.0.0Benchmark: json_loadsfirst-runsecond-run-no-fan306090120150Min: 142 / Avg: 142.33 / Max: 143Min: 142 / Avg: 142 / Max: 142

OpenBenchmarking.orgMilliseconds, Fewer Is BetterPyPerformance 1.0.0Benchmark: crypto_pyaesfirst-runsecond-run-no-fan120240360480600SE +/- 0.33, N = 3SE +/- 0.33, N = 3566569
OpenBenchmarking.orgMilliseconds, Fewer Is BetterPyPerformance 1.0.0Benchmark: crypto_pyaesfirst-runsecond-run-no-fan100200300400500Min: 565 / Avg: 565.67 / Max: 566Min: 568 / Avg: 568.67 / Max: 569

OpenBenchmarking.orgMilliseconds, Fewer Is BetterPyPerformance 1.0.0Benchmark: regex_compilefirst-runsecond-run-no-fan2004006008001000SE +/- 1.20, N = 3SE +/- 1.53, N = 3983980
OpenBenchmarking.orgMilliseconds, Fewer Is BetterPyPerformance 1.0.0Benchmark: regex_compilefirst-runsecond-run-no-fan2004006008001000Min: 981 / Avg: 983.33 / Max: 985Min: 978 / Avg: 980 / Max: 983

OpenBenchmarking.orgMilliseconds, Fewer Is BetterPyPerformance 1.0.0Benchmark: python_startupfirst-runsecond-run-no-fan1020304050SE +/- 0.06, N = 3SE +/- 0.03, N = 343.8043.57
OpenBenchmarking.orgMilliseconds, Fewer Is BetterPyPerformance 1.0.0Benchmark: python_startupfirst-runsecond-run-no-fan918273645Min: 43.7 / Avg: 43.8 / Max: 43.9Min: 43.5 / Avg: 43.57 / Max: 43.6

OpenBenchmarking.orgMilliseconds, Fewer Is BetterPyPerformance 1.0.0Benchmark: django_templatefirst-runsecond-run-no-fan80160240320400SE +/- 0.00, N = 3SE +/- 0.00, N = 3367365
OpenBenchmarking.orgMilliseconds, Fewer Is BetterPyPerformance 1.0.0Benchmark: django_templatefirst-runsecond-run-no-fan70140210280350Min: 367 / Avg: 367 / Max: 367Min: 365 / Avg: 365 / Max: 365

OpenBenchmarking.orgMilliseconds, Fewer Is BetterPyPerformance 1.0.0Benchmark: pickle_pure_pythonfirst-runsecond-run-no-fan0.63451.2691.90352.5383.1725SE +/- 0.00, N = 3SE +/- 0.01, N = 32.822.82
OpenBenchmarking.orgMilliseconds, Fewer Is BetterPyPerformance 1.0.0Benchmark: pickle_pure_pythonfirst-runsecond-run-no-fan246810Min: 2.81 / Avg: 2.82 / Max: 2.82Min: 2.81 / Avg: 2.82 / Max: 2.83

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 Gaussianfirst-runsecond-run-no-fan50100150200250SE +/- 0.41, N = 3SE +/- 6.85, N = 6156.56250.72
OpenBenchmarking.orgSeconds, Fewer Is BetterNumenta Anomaly Benchmark 1.1Detector: Windowed Gaussianfirst-runsecond-run-no-fan50100150200250Min: 155.9 / Avg: 156.56 / Max: 157.32Min: 219.45 / Avg: 250.72 / Max: 265.1

OpenBenchmarking.orgSeconds, Fewer Is BetterNumenta Anomaly Benchmark 1.1Detector: Earthgecko Skylinefirst-runsecond-run-no-fan6001200180024003000SE +/- 10.31, N = 3SE +/- 36.34, N = 31866.602962.19
OpenBenchmarking.orgSeconds, Fewer Is BetterNumenta Anomaly Benchmark 1.1Detector: Earthgecko Skylinefirst-runsecond-run-no-fan5001000150020002500Min: 1851.57 / Avg: 1866.6 / Max: 1886.33Min: 2901.57 / Avg: 2962.19 / Max: 3027.21

17 Results Shown

Numpy Benchmark
PyBench
PyPerformance:
  go
  2to3
  chaos
  float
  nbody
  pathlib
  raytrace
  json_loads
  crypto_pyaes
  regex_compile
  python_startup
  django_template
  pickle_pure_python
Numenta Anomaly Benchmark:
  Windowed Gaussian
  Earthgecko Skyline