Parallel distributed computing using Python']Python

被引:327
|
作者
Dalcin, Lisandro D. [1 ]
Paz, Rodrigo R. [1 ]
Kler, Pablo A. [1 ]
Cosimo, Alejandro [1 ]
机构
[1] Univ Nacl Litoral UNL, Consejo Nacl Invest Cient & Tecn CONICET, Ctr Int Metodos Computac Ingn CIMEC, Inst Desarrollo Tecnol Ind Quim INTEC, Santa Fe, Argentina
关键词
!text type='Python']Python[!/text; MPI; PETSc; FREE-FLOW ELECTROPHORESIS; SIMULATION;
D O I
10.1016/j.advwatres.2011.04.013
中图分类号
TV21 [水资源调查与水利规划];
学科分类号
081501 ;
摘要
This work presents two software components aimed to relieve the costs of accessing high-performance parallel computing resources within a Python programming environment: MPI for Python and PETSc for Python. MPI for Python is a general-purpose Python package that provides bindings for the Message Passing Interface (MPI) standard using any back-end MPI implementation. Its facilities allow parallel Python programs to easily exploit multiple processors using the message passing paradigm. PETSc for Python provides access to the Portable, Extensible Toolkit for Scientific Computation (PETSc) libraries. Its facilities allow sequential and parallel Python applications to exploit state of the art algorithms and data structures readily available in PETSc for the solution of large-scale problems in science and engineering. MPI for Python and PETSc for Python are fully integrated to PETSc-FEM, an MPI and PETSc based parallel, multiphysics, finite elements code developed at CIMEC laboratory. This software infrastructure supports research activities related to simulation of fluid flows with applications ranging from the design of microfluidic devices for biochemical analysis to modeling of large-scale stream/aquifer interactions. (C) 2011 Elsevier Ltd. All rights reserved.
引用
收藏
页码:1124 / 1139
页数:16
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