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  • 标题:Parallel Fem Application Development In Python.
  • 本地全文:下载
  • 作者:Lisandro D. Dalcín ; Rodrigo R. Paz ; Andrés A. Anca
  • 期刊名称:Mecánica Computacional
  • 印刷版ISSN:2591-3522
  • 出版年度:2006
  • 页码:1823-1838
  • 语种:English
  • 出版社:CIMEC-INTEC-CONICET-UNL
  • 摘要:Python is a modern but mature, easy to learn, powerful programming language. It has efficient high-level data structures and a simple but effective approach to object-oriented programming. Python codes are quickly developed, easily debugged and maintained, and can achieve a high degree of integration with other libraries written in compiled languages. Those characteristics make Python an ideal candidate for writing the higher-level parts of large-scale scientific applications and driving simulations in parallel architectures like clusters of PC’s or SMP’s. In this work, we present some parallel finite element simulations driven in a cluster of PC’s using the Python programming language. Our previously developed MPI, PETSc and ParMETIS packages are used together to deploy a model parallel FEM framework, integrating an important subset of OOFELIE toolkit, a sequential C++ code for FEM simulation and development. Our main concern is in showing the advantages of using high-level scripting languages for the high-level part of that kind of codes, where parallelization introduces some extra complexities.
  • 其他摘要:Python is a modern but mature, easy to learn, powerful programming language. It has efficient high-level data structures and a simple but effective approach to object-oriented programming. Python codes are quickly developed, easily debugged and maintained, and can achieve a high degree of integration with other libraries written in compiled languages. Those characteristics make Python an ideal candidate for writing the higher-level parts of large-scale scientific applications and driving simulations in parallel architectures like clusters of PC’s or SMP’s. In this work, we present some parallel finite element simulations driven in a cluster of PC’s using the Python programming language. Our previously developed MPI, PETSc and ParMETIS packages are used together to deploy a model parallel FEM framework, integrating an important subset of OOFELIE toolkit, a sequential C++ code for FEM simulation and development. Our main concern is in showing the advantages of using high-level scripting languages for the high-level part of that kind of codes, where parallelization introduces some extra complexities.
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