Python Clear Linux Performance

Intel Core i9-7980XE testing with a ASUS PRIME X299-A (1602 BIOS) and NVIDIA NV120 12GB on Clear Linux OS 27760 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 1902133-SP-PYTHONCLE64
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CPU Massive 4 Tests
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Identifier
Performance Per
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Date
Run
  Test
  Duration
Clear Linux Python 3.7.2
February 13 2019
  41 Minutes
Python 3.7.2 Release Build
February 13 2019
  7 Minutes
PyPy 7.0 Python 3.5
February 13 2019
 
Intel Distribution for Python 2019.2
February 13 2019
  43 Minutes
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  23 Minutes

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Python Clear Linux PerformanceOpenBenchmarking.orgPhoronix Test SuiteIntel Core i9-7980XE @ 4.20GHz (18 Cores / 36 Threads)ASUS PRIME X299-A (1602 BIOS)Intel Sky Lake-E DMI3 Registers16384MBSamsung SSD 970 EVO 500GBNVIDIA NV120 12GBRealtek ALC1220ASUS PB278Intel I219-VClear Linux OS 277604.20.7-694.native (x86_64)GNOME Shell 3.30.2X Server 1.20.3nouveau 1.0.164.3 Mesa 19.1.0-develGCC 8.2.1 20190212 + Clang 7.0.1 + LLVM 7.0.1ext42560x1440ProcessorMotherboardChipsetMemoryDiskGraphicsAudioMonitorNetworkOSKernelDesktopDisplay ServerDisplay DriverOpenGLCompilerFile-SystemScreen ResolutionPython Clear Linux Performance BenchmarksSystem Logs- CFFLAGS=-g-O3-feliminate-unused-debug-types-pipe-Wall-Wp-D_FORTIFY_SOURCE=2-fexceptions-fstack-protector--param=ssp-buffer-size=32-Wl--copy-dt-needed-entries-m64-fasynchronous-unwind-tables-Wp-D_REENTRANT-ftree-loop-distribute-patterns-Wl-z-Wl now-Wl-z-Wl relro-malign-data=abi-fno-semantic-interposition-ftree-vectorize-ftree-loop-vectorize-Wl-sort-common-Wl--enable-new-dtags FFLAGS=-g-O3-feliminate-unused-debug-types-pipe-Wall-Wp-D_FORTIFY_SOURCE=2-fexceptions-fstack-protector--param=ssp-buffer-size=32-Wl--copy-dt-needed-entries-m64-fasynchronous-unwind-tables-Wp-D_REENTRANT-ftree-loop-distribute-patterns-Wl-z-Wl relro-malign-data=abi-fno-semantic-interposition-ftree-vectorize-ftree-loop-vectorize-Wl--enable-new-dtags CXXFLAGS=-g-O3-feliminate-unused-debug-types-pipe-Wall-Wp-D_FORTIFY_SOURCE=2-fexceptions-fstack-protector--param=ssp-buffer-size=32-Wformat-Wformat-security-Wl--copy-dt-needed-entries-m64-fasynchronous-unwind-tables-Wp-D_REENTRANT-ftree-loop-distribute-patterns-Wl-z-Wl relro-fno-semantic-interposition-ffat-lto-objects-fno-signed-zeros-fno-trapping-math-fassociative-math-Wl-sort-common-Wl--enable-new-dtags-mtune=skylake-fvisibility-inlines-hidden-Wl--enable-new-dtags MESA_GLSL_CACHE_DISABLE=0 CFLAGS=-g-O3-feliminate-unused-debug-types-pipe-Wall-Wp-D_FORTIFY_SOURCE=2-fexceptions-fstack-protector--param=ssp-buffer-size=32-Wformat-Wformat-security-Wl--copy-dt-needed-entries-m64-fasynchronous-unwind-tables-Wp-D_REENTRANT-ftree-loop-distribute-patterns-Wl-z-Wl relro-fno-semantic-interposition-ffat-lto-objects-fno-signed-zeros-fno-trapping-math-fassociative-math-Wl-sort-common-Wl--enable-new-dtags-mtune=skylake THEANO_FLAGS=floatX=float32 openmp=true gcc.cxxflags="-ftree-vectorize-mavx" - Scaling Governor: intel_pstate performance- Clear Linux Python 3.7.2: EXA- Clear Linux Python 3.7.2: Python 3.7.2- Python 3.7.2 Release Build: Python 3.7.2- PyPy 7.0 Python 3.5: /home/phoronix/Downloads/pypy3.5-v7.0.0-linux64/bin/python: error while loading shared libraries: libtinfo.so.5: cannot open shared object file: No such file or directory + /home/phoronix/Downloads/pypy3.5-v7.0.0-linux64/bin/python3: error while loading shared libraries: libtinfo.so.5: cannot open shared object file: No such file or directory - Intel Distribution for Python 2019.2: Python 3.6.8 :: Intel- KPTI + __user pointer sanitization + Full generic retpoline IBPB: conditional IBRS_FW STIBP: conditional RSB filling + SSB disabled via prctl and seccomp + PTE Inversion; VMX: conditional cache flushes SMT vulnerable

Python Clear Linux Performancenumpy: cython-bench: tensorflow: Cifar10pybench: Total For Average Test Timesscikit-learn: Clear Linux Python 3.7.2Python 3.7.2 Release BuildPyPy 7.0 Python 3.5Intel Distribution for Python 2019.2458870021.8229.629007.6125.91997468526292.60131410.88OpenBenchmarking.org

Numpy Benchmark

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

OpenBenchmarking.orgNanoseconds, Fewer Is BetterNumpy BenchmarkClear Linux Python 3.7.2Intel Distribution for Python 2019.21000K2000K3000K4000K5000K45887004685262

Cython benchmark

Stress benchmark tests to measure time consumed by cython code Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgSeconds, Fewer Is BetterCython benchmark 0.27Clear Linux Python 3.7.2Python 3.7.2 Release BuildIntel Distribution for Python 2019.220406080100SE +/- 0.05, N = 3SE +/- 0.67, N = 12SE +/- 0.41, N = 321.8225.9192.60
OpenBenchmarking.orgSeconds, Fewer Is BetterCython benchmark 0.27Clear Linux Python 3.7.2Python 3.7.2 Release BuildIntel Distribution for Python 2019.220406080100Min: 21.73 / Avg: 21.82 / Max: 21.89Min: 23.96 / Avg: 25.91 / Max: 28.9Min: 91.92 / Avg: 92.6 / Max: 93.34

Tensorflow

This is a benchmark of the Tensorflow deep learning framework using the CIFAR10 data set. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgSeconds, Fewer Is BetterTensorflow 2017-02-03Build: Cifar10Clear Linux Python 3.7.2714212835SE +/- 0.02, N = 329.62

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 TimesClear Linux Python 3.7.2Python 3.7.2 Release BuildIntel Distribution for Python 2019.230060090012001500SE +/- 2.33, N = 3SE +/- 3.18, N = 3SE +/- 0.88, N = 39009971314
OpenBenchmarking.orgMilliseconds, Fewer Is BetterPyBench 2018-02-16Total For Average Test TimesClear Linux Python 3.7.2Python 3.7.2 Release BuildIntel Distribution for Python 2019.22004006008001000Min: 895 / Avg: 899.67 / Max: 902Min: 991 / Avg: 997.33 / Max: 1001Min: 1312 / Avg: 1313.67 / Max: 1315

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 0.17.1Clear Linux Python 3.7.2Intel Distribution for Python 2019.23691215SE +/- 0.02, N = 3SE +/- 0.03, N = 37.6110.88
OpenBenchmarking.orgSeconds, Fewer Is BetterScikit-Learn 0.17.1Clear Linux Python 3.7.2Intel Distribution for Python 2019.23691215Min: 7.58 / Avg: 7.61 / Max: 7.64Min: 10.82 / Avg: 10.88 / Max: 10.92