Run-time parallelization optimization techniques

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

In this paper we first present several compiler techniques to reduce the overhead of run-time parallelization. We show how to use sta- tic control flow information to reduce the number of memory references that need to be traced at run-time. Then we introduce several methods designed specifically for the parallelization of sparse applications. We detail some heuristics on how to speculate on the type and data structu- res used by the original code and thus reduce the memory requirements for tracing the sparse access patterns without performing any additional work. Optimization techniques for the sparse reduction parallelization and speculative loop distribution conclude the paper.

Original languageEnglish (US)
Title of host publicationLanguages and Compilers for Parallel Computing - 12th International Workshop, LCPC 1999, Proceedings
EditorsLarry Carter, Jeanne Ferrante
PublisherSpringer-Verlag
Pages481-484
Number of pages4
ISBN (Print)9783540678588
StatePublished - Jan 1 2000
Externally publishedYes
Event12th International Workshop on Languages and Compilers for Parallel Computing, LCPC 1999 - La Jolla, United States
Duration: Aug 4 1999Aug 6 1999

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume1863
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Other

Other12th International Workshop on Languages and Compilers for Parallel Computing, LCPC 1999
CountryUnited States
CityLa Jolla
Period8/4/998/6/99

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

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  • Cite this

    Yu, H., & Rauchwerger, L. (2000). Run-time parallelization optimization techniques. In L. Carter, & J. Ferrante (Eds.), Languages and Compilers for Parallel Computing - 12th International Workshop, LCPC 1999, Proceedings (pp. 481-484). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 1863). Springer-Verlag.