Performance Comparison of Python Translators for a Multi-threaded CPU-bound Application
Abstract
Currently, Python is one of the most widely used languages in various application areas. However, it has limitations when it comes to optimizing and parallelizing applications due to the nature of its official CPython interpreter, especially for CPU-bound applications. To solve this problem, several alternative translators have emerged, each with a different approach and its own cost-performance ratio. Due to the absence of comparative studies, we have carried out a performance comparison of these translators using N-Body as a case study (a well-known problem with high computational demand). The results obtained show that CPython and PyPy presented poor performance due to their limitations when it comes to parallelizing algorithms; while Numba and Cython achieved significantly higher performance, proving to be viable options to speed up numerical algorithms.
Keywords
Cite
@article{arxiv.2203.08263,
title = {Performance Comparison of Python Translators for a Multi-threaded CPU-bound Application},
author = {Andrés Milla and Enzo Rucci},
journal= {arXiv preprint arXiv:2203.08263},
year = {2022}
}
Comments
In: Pesado, P., Gil, G. (eds). Computer Science - CACIC 2021. Springer Communications in Computer and Information Science, vol 1584