python-z-1

AMD Ryzen 5 3400G testing with a LENOVO 3706 (O4DKT35A BIOS) and AMD Picasso 2GB on Ubuntu 20.04 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 2107283-IB-PYTHONZ1154
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Result
Identifier
Performance Per
Dollar
Date
Run
  Test
  Duration
AMD Ryzen 5 3400G
July 28 2021
  1 Hour, 38 Minutes
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python-z-1OpenBenchmarking.orgPhoronix Test SuiteAMD Ryzen 5 3400G @ 3.70GHz (4 Cores / 8 Threads)LENOVO 3706 (O4DKT35A BIOS)AMD Raven/Raven214GB500GB Western Digital WD5000LPVX-8AMD Picasso 2GB (1400/1333MHz)AMD Raven/Raven2/FenghuangDP2VGA V226Realtek RTL8111/8168/8411 + Realtek RTL8821CE 802.11ac PCIeUbuntu 20.045.4.0-80-generic (x86_64)GNOME Shell 3.36.9X Server 1.20.9GCC 9.3.0ext41024x768ProcessorMotherboardChipsetMemoryDiskGraphicsAudioMonitorNetworkOSKernelDesktopDisplay ServerCompilerFile-SystemScreen ResolutionPython-z-1 BenchmarksSystem Logs- Transparent Huge Pages: madvise- --build=x86_64-linux-gnu --disable-vtable-verify --disable-werror --enable-checking=release --enable-clocale=gnu --enable-default-pie --enable-gnu-unique-object --enable-languages=c,ada,c++,go,brig,d,fortran,objc,obj-c++,gm2 --enable-libstdcxx-debug --enable-libstdcxx-time=yes --enable-multiarch --enable-multilib --enable-nls --enable-objc-gc=auto --enable-offload-targets=nvptx-none=/build/gcc-9-HskZEa/gcc-9-9.3.0/debian/tmp-nvptx/usr,hsa --enable-plugin --enable-shared --enable-threads=posix --host=x86_64-linux-gnu --program-prefix=x86_64-linux-gnu- --target=x86_64-linux-gnu --with-abi=m64 --with-arch-32=i686 --with-default-libstdcxx-abi=new --with-gcc-major-version-only --with-multilib-list=m32,m64,mx32 --with-target-system-zlib=auto --with-tune=generic --without-cuda-driver -v - Scaling Governor: acpi-cpufreq ondemand (Boost: Enabled) - CPU Microcode: 0x8108102 - Python 3.8.10- 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 STIBP: disabled RSB filling + srbds: Not affected + tsx_async_abort: Not affected

python-z-1numpy: cython-bench: N-Queenspybench: 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 Changepointmlpack: scikit_svmmlpack: scikit_linearridgeregressionscikit-learn: AMD Ryzen 5 3400G273.8524.931107029540813512314520.560028.912719516.270.3607147.88349.43625.631317.91084.76021.45194.16110.739OpenBenchmarking.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 BenchmarkAMD Ryzen 5 3400G60120180240300SE +/- 0.77, N = 3273.85

Cython Benchmark

Cython provides a superset of Python that is geared to deliver C-like levels of performance. This test profile makes use of Cython's bundled benchmark tests and runs an N-Queens sample test as a simple benchmark to the system's Cython performance. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgSeconds, Fewer Is BetterCython Benchmark 0.29.21Test: N-QueensAMD Ryzen 5 3400G612182430SE +/- 0.24, N = 324.93

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 TimesAMD Ryzen 5 3400G20040060080010001070

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: goAMD Ryzen 5 3400G60120180240300295

OpenBenchmarking.orgMilliseconds, Fewer Is BetterPyPerformance 1.0.0Benchmark: 2to3AMD Ryzen 5 3400G90180270360450408

OpenBenchmarking.orgMilliseconds, Fewer Is BetterPyPerformance 1.0.0Benchmark: chaosAMD Ryzen 5 3400G306090120150135

OpenBenchmarking.orgMilliseconds, Fewer Is BetterPyPerformance 1.0.0Benchmark: floatAMD Ryzen 5 3400G306090120150123

OpenBenchmarking.orgMilliseconds, Fewer Is BetterPyPerformance 1.0.0Benchmark: nbodyAMD Ryzen 5 3400G306090120150145

OpenBenchmarking.orgMilliseconds, Fewer Is BetterPyPerformance 1.0.0Benchmark: pathlibAMD Ryzen 5 3400G510152025SE +/- 0.06, N = 320.5

OpenBenchmarking.orgMilliseconds, Fewer Is BetterPyPerformance 1.0.0Benchmark: raytraceAMD Ryzen 5 3400G130260390520650SE +/- 1.86, N = 3600

OpenBenchmarking.orgMilliseconds, Fewer Is BetterPyPerformance 1.0.0Benchmark: json_loadsAMD Ryzen 5 3400G714212835SE +/- 0.09, N = 328.9

OpenBenchmarking.orgMilliseconds, Fewer Is BetterPyPerformance 1.0.0Benchmark: crypto_pyaesAMD Ryzen 5 3400G306090120150127

OpenBenchmarking.orgMilliseconds, Fewer Is BetterPyPerformance 1.0.0Benchmark: regex_compileAMD Ryzen 5 3400G4080120160200195

OpenBenchmarking.orgMilliseconds, Fewer Is BetterPyPerformance 1.0.0Benchmark: python_startupAMD Ryzen 5 3400G48121620SE +/- 0.07, N = 316.2

OpenBenchmarking.orgMilliseconds, Fewer Is BetterPyPerformance 1.0.0Benchmark: django_templateAMD Ryzen 5 3400G1632486480SE +/- 0.06, N = 370.3

OpenBenchmarking.orgMilliseconds, Fewer Is BetterPyPerformance 1.0.0Benchmark: pickle_pure_pythonAMD Ryzen 5 3400G130260390520650SE +/- 1.15, N = 3607

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: EXPoSEAMD Ryzen 5 3400G306090120150SE +/- 0.89, N = 3147.88

OpenBenchmarking.orgSeconds, Fewer Is BetterNumenta Anomaly Benchmark 1.1Detector: Relative EntropyAMD Ryzen 5 3400G1122334455SE +/- 0.44, N = 349.44

OpenBenchmarking.orgSeconds, Fewer Is BetterNumenta Anomaly Benchmark 1.1Detector: Windowed GaussianAMD Ryzen 5 3400G612182430SE +/- 0.01, N = 325.63

OpenBenchmarking.orgSeconds, Fewer Is BetterNumenta Anomaly Benchmark 1.1Detector: Earthgecko SkylineAMD Ryzen 5 3400G70140210280350SE +/- 1.13, N = 3317.91

OpenBenchmarking.orgSeconds, Fewer Is BetterNumenta Anomaly Benchmark 1.1Detector: Bayesian ChangepointAMD Ryzen 5 3400G20406080100SE +/- 0.16, N = 384.76

Mlpack Benchmark

Mlpack benchmark scripts for machine learning libraries Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgSeconds, Fewer Is BetterMlpack BenchmarkBenchmark: scikit_svmAMD Ryzen 5 3400G510152025SE +/- 0.15, N = 321.45

OpenBenchmarking.orgSeconds, Fewer Is BetterMlpack BenchmarkBenchmark: scikit_linearridgeregressionAMD Ryzen 5 3400G4080120160200SE +/- 1.39, N = 3194.16

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 0.22.1AMD Ryzen 5 3400G20406080100SE +/- 0.07, N = 3110.74