Run-time and compiler support for programming in adaptive parallel environments

Guy Edjlali, Gagan Agrawal, Alan Sussman, Jim Humphries, Joel Saltz

Research output: Contribution to journalArticlepeer-review

15 Scopus citations

Abstract

For better utilization of computing resources, it is important to consider parallel programming environments in which the number of available processors varies at run-time. In this article, we discuss run-time support for data-parallel programming in such an adaptive environment. Executing programs in an adaptive environment requires redistributing data when the number of processors changes, and also requires determining new loop bounds and communication patterns for the new set of processors. We have developed a run-time library to provide this support. We discuss how the run-time library can be used by compilers of high-performance Fortran (HPF)-like languages to generate code for an adaptive environment. We present performance results for a Navier-Stokes solver and a multigrid template run on a network of workstations and an IBM SP-2. Our experiments show that if the number of processors is not varied frequently, the cost of data redistribution is not significant compared to the time required for the actual computation. Overall, our work establishes the feasibility of compiling HPF for a network of nondedicated workstations, which are likely to be an important resource for parallel programming in the future.

Original languageEnglish (US)
Pages (from-to)215-227
Number of pages13
JournalScientific Programming
Volume6
Issue number2
DOIs
StatePublished - 1997
Externally publishedYes

ASJC Scopus subject areas

  • Software
  • Computer Science Applications

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