arrow
Return

Playdoh: A lightweight Python library for distributed computing and optimisation

delete2013-09-01
delete12
PRE
AI
C
Cyrille Rossant *
B
Bertrand Fontaine
D
Dan F. M. Goodman
DOI:10.1016/j.jocs.2011.06.002delete
deleteOriginal
deleteOriginal request for help
deleteShare
deleteSave
Abstract

Abstract

En 中文
Parallel computing is now an essential paradigm for high performance scientific computing. Most existing hardware and software solutions are expensive or difficult to use. We developed Playdoh, a Python library for distributing computations across the free computing units available in a small network of multicore computers. Playdoh supports independent and loosely coupled parallel problems such as global optimisations, Monte Carlo simulations and numerical integration of partial differential equations. It is designed to be lightweight and easy to use and should be of interest to scientists wanting to turn their lab computers into a small cluster at no cost. (C) 2011 Elsevier B.V. All rights reserved.
Keywords:
Python
Parallel computing
Distributed computing
Optimisation
High performance computing
AI Summary

AI Summary

Key information extracted from the uploaded paper, including a brief overview, abstract, background, key highlights, visual analysis, and future outlook.

Journal

Nature Computational Science cover
Nature Computational Science
IF:
18.3
Papers:
3.1K
Citations:
4.0K

Organization

U
Universite Paris Cite
Scholars:
8.9W
Papers: 6.3W
Citations: 604