AMD Ryzen 9 5900X python Benchmarks - Python 3 vs. Pyston 2.1

AMD Ryzen 9 5900X Python benchmarks by Michael Larabel.

HTML result view exported from: https://openbenchmarking.org/result/2101246-HA-PYTHON59078&sor&grt.

AMD Ryzen 9 5900X python Benchmarks - Python 3 vs. Pyston 2.1ProcessorMotherboardChipsetMemoryDiskGraphicsAudioMonitorNetworkOSKernelDesktopDisplay ServerDisplay DriverOpenGLVulkanCompilerFile-SystemScreen ResolutionPython 3.8.6Python 3.9.1Pyston 2.1.0AMD Ryzen 9 5900X 12-Core @ 3.70GHz (12 Cores / 24 Threads)ASUS ROG CROSSHAIR VIII HERO (3202 BIOS)AMD Starship/Matisse16GB1000GB Samsung SSD 980 PRO 1TBSapphire AMD Radeon RX 5600 OEM/5600 XT / 5700/5700 6GB (1780/875MHz)AMD Navi 10 HDMI AudioASUS VP28URealtek RTL8125 2.5GbE + Intel I211Ubuntu 20.105.8.0-38-generic (x86_64)GNOME Shell 3.38.1X Server 1.20.9modesetting 1.20.94.6 Mesa 20.2.1 (LLVM 11.0.0)1.2.131GCC 10.2.0ext43840x2160OpenBenchmarking.orgKernel Details- Transparent Huge Pages: madviseProcessor Details- Scaling Governor: acpi-cpufreq ondemand (Boost: Enabled) - CPU Microcode: 0xa201009Python Details- Python 3.8.6: Python 3.8.6- Python 3.9.1: Python 3.9.1 + Python 3.8.6- Pyston 2.1.0: Python 3.8.2 (heads/rel2.1:da378ef Jan 12 2021 15:46:12)[Pyston 2.1.0 GCC 9.3.0]Security Details- itlb_multihit: Not affected + l1tf: Not affected + mds: Not affected + meltdown: Not affected + spec_store_bypass: Mitigation of SSB disabled via prctl and seccomp + spectre_v1: Mitigation of usercopy/swapgs barriers and __user pointer sanitization + spectre_v2: Mitigation of Full AMD retpoline IBPB: conditional IBRS_FW STIBP: always-on RSB filling + srbds: Not affected + tsx_async_abort: Not affected

AMD Ryzen 9 5900X python Benchmarks - Python 3 vs. Pyston 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_pythonPython 3.8.6Python 3.9.1Pyston 2.1.072718823581.481.388.912.734717.477.01236.1834.731772218723480.981.288.812.734817.477.11236.1934.631546411417538.648.341.011.019817.951.166.26.3924.2198OpenBenchmarking.org

PyBench

Total For Average Test Times

OpenBenchmarking.orgMilliseconds, Fewer Is BetterPyBench 2018-02-16Total For Average Test TimesPyston 2.1.0Python 3.9.1Python 3.8.6160320480640800SE +/- 1.20, N = 3SE +/- 6.89, N = 3SE +/- 10.07, N = 3464722727

PyPerformance

Benchmark: go

OpenBenchmarking.orgMilliseconds, Fewer Is BetterPyPerformance 1.0.0Benchmark: goPyston 2.1.0Python 3.9.1Python 3.8.64080120160200SE +/- 0.33, N = 3114187188

PyPerformance

Benchmark: 2to3

OpenBenchmarking.orgMilliseconds, Fewer Is BetterPyPerformance 1.0.0Benchmark: 2to3Pyston 2.1.0Python 3.9.1Python 3.8.650100150200250SE +/- 0.58, N = 3175234235

PyPerformance

Benchmark: chaos

OpenBenchmarking.orgMilliseconds, Fewer Is BetterPyPerformance 1.0.0Benchmark: chaosPyston 2.1.0Python 3.9.1Python 3.8.620406080100SE +/- 0.07, N = 3SE +/- 0.09, N = 3SE +/- 0.25, N = 338.680.981.4

PyPerformance

Benchmark: float

OpenBenchmarking.orgMilliseconds, Fewer Is BetterPyPerformance 1.0.0Benchmark: floatPyston 2.1.0Python 3.9.1Python 3.8.620406080100SE +/- 0.03, N = 3SE +/- 0.13, N = 3SE +/- 0.09, N = 348.381.281.3

PyPerformance

Benchmark: nbody

OpenBenchmarking.orgMilliseconds, Fewer Is BetterPyPerformance 1.0.0Benchmark: nbodyPyston 2.1.0Python 3.9.1Python 3.8.620406080100SE +/- 0.12, N = 3SE +/- 0.32, N = 3SE +/- 0.21, N = 341.088.888.9

PyPerformance

Benchmark: pathlib

OpenBenchmarking.orgMilliseconds, Fewer Is BetterPyPerformance 1.0.0Benchmark: pathlibPyston 2.1.0Python 3.8.6Python 3.9.13691215SE +/- 0.03, N = 3SE +/- 0.00, N = 3SE +/- 0.00, N = 311.012.712.7

PyPerformance

Benchmark: raytrace

OpenBenchmarking.orgMilliseconds, Fewer Is BetterPyPerformance 1.0.0Benchmark: raytracePyston 2.1.0Python 3.8.6Python 3.9.180160240320400SE +/- 0.58, N = 3198347348

PyPerformance

Benchmark: json_loads

OpenBenchmarking.orgMilliseconds, Fewer Is BetterPyPerformance 1.0.0Benchmark: json_loadsPython 3.8.6Python 3.9.1Pyston 2.1.048121620SE +/- 0.03, N = 3SE +/- 0.03, N = 3SE +/- 0.00, N = 317.417.417.9

PyPerformance

Benchmark: crypto_pyaes

OpenBenchmarking.orgMilliseconds, Fewer Is BetterPyPerformance 1.0.0Benchmark: crypto_pyaesPyston 2.1.0Python 3.8.6Python 3.9.120406080100SE +/- 0.06, N = 3SE +/- 0.07, N = 3SE +/- 0.15, N = 351.177.077.1

PyPerformance

Benchmark: regex_compile

OpenBenchmarking.orgMilliseconds, Fewer Is BetterPyPerformance 1.0.0Benchmark: regex_compilePyston 2.1.0Python 3.8.6Python 3.9.1306090120150SE +/- 0.10, N = 3SE +/- 0.33, N = 3SE +/- 0.33, N = 366.2123.0123.0

PyPerformance

Benchmark: python_startup

OpenBenchmarking.orgMilliseconds, Fewer Is BetterPyPerformance 1.0.0Benchmark: python_startupPython 3.8.6Python 3.9.1Pyston 2.1.0246810SE +/- 0.01, N = 3SE +/- 0.01, N = 3SE +/- 0.01, N = 36.186.196.39

PyPerformance

Benchmark: django_template

OpenBenchmarking.orgMilliseconds, Fewer Is BetterPyPerformance 1.0.0Benchmark: django_templatePyston 2.1.0Python 3.9.1Python 3.8.6816243240SE +/- 0.00, N = 3SE +/- 0.00, N = 3SE +/- 0.00, N = 324.234.634.7

PyPerformance

Benchmark: pickle_pure_python

OpenBenchmarking.orgMilliseconds, Fewer Is BetterPyPerformance 1.0.0Benchmark: pickle_pure_pythonPyston 2.1.0Python 3.9.1Python 3.8.670140210280350SE +/- 0.88, N = 3SE +/- 0.88, N = 3198315317


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