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
相关论文
共 50 条
  • [1] Modules to teach parallel and distributed computing using MPI for Python']Python and Disco
    Ortiz-Ubarri, Jose
    Arce-Nazario, Rafael
    Orozco, Edusmildo
    [J]. 2016 IEEE 30TH INTERNATIONAL PARALLEL AND DISTRIBUTED PROCESSING SYMPOSIUM WORKSHOPS (IPDPSW), 2016, : 958 - 962
  • [2] Teaching Parallel Computing and Dependence Analysis with Python']Python
    Watkinson, Neftali
    Shivam, Aniket
    Nicolau, Alexandru
    Veidenbaum, Alexander V.
    [J]. 2019 IEEE INTERNATIONAL PARALLEL AND DISTRIBUTED PROCESSING SYMPOSIUM WORKSHOPS (IPDPSW), 2019, : 320 - 325
  • [3] A scalable interactive parallel computing environment for python']python
    Raghunathan, Sudarshan
    [J]. COMPUTING AND INFORMATICS, 2008, 27 (02) : 249 - 259
  • [4] A Parallel Block Predictor-Corrector Method by Python']Python-Based Distributed Computing
    Yu, Kun-Ming
    Lee, Ming-Gong
    [J]. INFORMATION TECHNOLOGY APPLICATIONS IN INDUSTRY, PTS 1-4, 2013, 263-266 : 1315 - +
  • [5] Parallel Computing Model Based on Python']Python in Quantitative Analysis
    Li, Qiutong
    Yang, Yuechen
    Kang, Xiaona
    [J]. 2ND INTERNATIONAL CONFERENCE ON APPLIED MATHEMATICS, MODELLING, AND INTELLIGENT COMPUTING (CAMMIC 2022), 2022, 12259
  • [6] PyMW: a Python']Python Module for Parallel Master Worker Computing
    Heien, E. M.
    Kornafeld, A.
    Takata, Y.
    Hagihara, K.
    [J]. PROCEEDINGS OF THE FIRST INTERNATIONAL CONFERENCE ON PARALLEL, DISTRIBUTED AND GRID COMPUTING FOR ENGINEERING, 2009, (90): : 203 - +
  • [7] Automatic Parallelization of Python']Python Programs for Distributed Heterogeneous Computing
    Shirako, Jun
    Hayashi, Akihiro
    Paul, Sri Raj
    Tumanov, Alexey
    Sarkar, Vivek
    [J]. EURO-PAR 2022: PARALLEL PROCESSING, 2022, 13440 : 350 - 366
  • [8] Playdoh: A lightweight Python']Python library for distributed computing and optimisation
    Rossant, Cyrille
    Fontaine, Bertrand
    Goodman, Dan F. M.
    [J]. JOURNAL OF COMPUTATIONAL SCIENCE, 2013, 4 (05) : 352 - 359
  • [9] On parallel software engineering education using python']python
    Marowka, Ami
    [J]. EDUCATION AND INFORMATION TECHNOLOGIES, 2018, 23 (01) : 357 - 372
  • [10] Using BSP and python']python to simplify parallel programming
    Hinsen, K
    Langtangen, HP
    Skavhaug, O
    Odegård, A
    [J]. FUTURE GENERATION COMPUTER SYSTEMS-THE INTERNATIONAL JOURNAL OF GRID COMPUTING THEORY METHODS AND APPLICATIONS, 2006, 22 (1-2): : 123 - 157