Segmented alignment: An enhanced model to align data parallel programs of HPF

Gwan Hwan Hwang, Cheng Wei Chen, Jenq Kuen Lee, Roy Dz-Ching Ju

Research output: Contribution to journalArticle

Abstract

In this paper, we propose a new automatic data alignment model called segmented alignment. The conventional data alignment model, such as that used in High-Performance Fortran (HPF), aligns arrays with the whole index domain. The principle of our proposed segmented alignment is to allow alignment relations within delimited index domains. We first provide motivating examples to illustrate how code fragments of HPF with EOSHIFT or CSHIFT operations, or produced by synthesis operations can benefit from our enhanced alignment scheme. Second, we show that this new model can be implemented in HPF-like languages by adding WHEN and IN constructs to them. In addition, we show that the new proposed schemes for WHEN and IN constructs can be emulated using standard HPF syntax. Finally, we address issues related to automatic data alignment for the new proposed model, and present an algorithm to automatically align programs using our segmented alignment scheme. Since the optimal algorithm to do this is NP-hard. a practical heuristic is also given. Our experiments were performed on a DEC Alpha Farm with HPF environments. Our experiments confirm our theory that our proposed alignment scheme can significantly enhance not only the performance of HPF code fragments with EOSHIFT or CSHIFT operations, but also that of codes produced by synthesis operations.

Original languageEnglish
Pages (from-to)17-41
Number of pages25
JournalJournal of Supercomputing
Volume25
Issue number1
DOIs
Publication statusPublished - 2003 May 1

Keywords

  • Automatic array alignment
  • Compiler optimization
  • Distributed-memory machines
  • HPF compilers
  • Parallelizing compiler
  • Segmented alignment

ASJC Scopus subject areas

  • Software
  • Theoretical Computer Science
  • Information Systems
  • Hardware and Architecture

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