#PARALLEL PROCESSING OPERATING SYSTEM DOWNLOAD CODE#
Cython also helps removing the GIL to parallelize code.
Thus, it allows converting Cython code to C code and compile it as a C python library that can be imported as a real python package.
It says to be 30% faster than CPython by just replacing CPython by Pyston version without updating your code.Ĭython - Cython is a language which adds C types declaration to Python language.
After having been stopped in 2017 new version is back again since Python 3.8.8.
Pyston - Pyston is a faster CPython implementation using C optimisation and DynASM Just In Time compiler
It is meant to efficiently compile scientific programs, and takes advantage of multi-cores and SIMD instruction units.
It takes a Python module annotated with a few interface description and turns it into a native Python module with the same interface, but (hopefully) faster.
Pythran - Pythran is an ahead of time compiler for a subset of the Python language, with a focus on scientific computing.
Numba can use vectorized instructions (SIMD - Single Instruction Multiple Data) like SSE/AVX.
Numba - Numba is an open source JIT compiler that translates a subset of Python and NumPy code into fast machine code.
For version 0.6 of Nuitka and Python 2.7 speedup was 312% !.
Nuitka translates Python into a C program that then is linked against libpython to execute exactly like CPython.
You feed Nuitka your Python app, it does a lot of clever things, and spits out an executable or extension module.
Nuitka - As the authors say: Nuitka is a Python compiler written in Python ! Some Python libraries allow compiling Python functions at run time, this is called Just In Time (JIT) compilation. This page seeks to provide references to the different libraries and solutions available. Parallel Processing and Multiprocessing in PythonĪ number of Python-related libraries exist for the programming of solutions either employing multiple CPUs or multicore CPUs in a symmetric multiprocessing (SMP) or shared memory environment, or potentially huge numbers of computers in a cluster or grid environment.