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Identifying parallelism in programs with cyclic graphs

  • National Taiwan Ocean University

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

6 Scopus citations

Abstract

Dependence analysis algorithms have been proposed to identify parallelism in programs with tree-like data structures. However, they can not analyze the dependence of statements if recursive data structures of programs are cyclic. This paper presents a technique to identify parallelism in programs with cyclic graphs. The technique consists of three steps: (1) Traversal patterns that loops or recursive procedures traverse graphs are identified, and the statements that construct the links of traversal patterns are located by definition-use chains of recursive data structures; (2) Shape analysis is performed to estimate possible shapes of traversal patterns; (3) Dependence analysis is performed to identify parallelism using the result of shape analysis. This approach can identify parallelism in programs with cyclic data structures due to the facts that many programs follow acyclic structures (i.e. traversal patterns) to access all nodes on the cyclic data structures. Once the traversal patterns are isolated from the overall data structures, dependence analysis can be applied to identify parallelism.

Original languageEnglish
Title of host publicationProceedings - 2000 International Conference on Parallel Processing, ICPP 2000
EditorsDavid J. Lilja
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages201-208
Number of pages8
ISBN (Electronic)0769507689
DOIs
StatePublished - 2000
EventInternational Conference on Parallel Processing, ICPP 2000 - Toronto, Canada
Duration: Aug 21 2000Aug 24 2000

Publication series

NameProceedings of the International Conference on Parallel Processing
Volume2000-January
ISSN (Print)0190-3918

Conference

ConferenceInternational Conference on Parallel Processing, ICPP 2000
Country/TerritoryCanada
CityToronto
Period08/21/0008/24/00

Keywords

  • Algorithm design and analysis
  • Data analysis
  • Data structures
  • Pattern analysis
  • Performance analysis
  • Recursive estimation
  • Shape
  • State estimation
  • Tree data structures
  • Tree graphs

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