High-level abstractions for message-passing parallel programming

Fan Chan, Jiannong Cao, Yudong Sun

Research output: Journal article publicationJournal articleAcademic researchpeer-review

19 Citations (Scopus)

Abstract

Large-scale scientific and engineering computation problems are usually complex and consequently the development of parallel programs for solving these problems is a difficult task. In this paper, we describe the graph-oriented programming (GOP) model and environment for building and evaluating parallel applications. The GOP model provides higher level abstractions for message-passing parallel programming and the software environment offers tools which can ease programmers for parallelizing, writing, and deploying scientific and engineering computing applications. We discuss the motivations and various issues in developing the model and the software environment, present the design of the system architecture and the components, and describe the evaluation of the environment implemented on top of MPI with a sample parallel scientific application program. With the support of the high-level abstractions provided by the proposed GOP environment, programming of parallel applications on various parallel architectures can be greatly simplified.
Original languageEnglish
Pages (from-to)1589-1621
Number of pages33
JournalParallel Computing
Volume29
Issue number11-12 SPEC.ISS.
DOIs
Publication statusPublished - 1 Nov 2003

Keywords

  • Cluster computing
  • Graph-oriented computing
  • Programming environments

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Software
  • Hardware and Architecture
  • Computer Networks and Communications
  • Computer Graphics and Computer-Aided Design
  • Artificial Intelligence

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