Algorithmic concept recognition support for automatic parallelization: A case study on loop optimization and parallelization

Beniamino D.I. Di Martino

Research output: Contribution to journalArticle

5 Citations (Scopus)

Abstract

Automated algorithmic concept recognition within sequential code can support compilation techniques for program parallelization by allowing the introduction of heuristics and extensive pruning of the search space associated with the code transformation selections, thus enabling application of more aggressive transformations. This paper shows, through a case study, how automatic recognition of algorithmic patterns can enable automatic selection of suitable sequences of loop transformations for the implementing code, selection of suitable data and work distributions, and provision for communication optimizations.
Original languageEnglish
Pages (from-to)191 - 203
Number of pages13
JournalJournal of Information Science and Engineering
Volume14
Issue number1
Publication statusPublished - Mar 1998
Externally publishedYes

    Fingerprint

All Science Journal Classification (ASJC) codes

  • Software
  • Human-Computer Interaction
  • Hardware and Architecture
  • Library and Information Sciences
  • Computational Theory and Mathematics

Cite this