• DocumentCode
    2523209
  • Title

    Identifying parallelism in programs with cyclic graphs

  • Author

    Hwang, Yuan-Shin ; Saltz, Joel

  • Author_Institution
    Dept. of Comput. Sci., Nat. Taiwan Ocean Univ., Keelung, Taiwan
  • fYear
    2000
  • fDate
    2000
  • Firstpage
    201
  • Lastpage
    208
  • 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
  • Keywords
    parallel programming; tree data structures; cyclic data structures; cyclic graphs; definition-use chains; dependence analysis; dependence analysis algorithms; parallelism; recursive data structures; shape analysis; traversal patterns; tree-like data structures; Algorithm design and analysis; Data analysis; Data structures; Pattern analysis; Performance analysis; Recursive estimation; Shape; State estimation; Tree data structures; Tree graphs;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Parallel Processing, 2000. Proceedings. 2000 International Conference on
  • Conference_Location
    Toronto, Ont.
  • ISSN
    0190-3918
  • Print_ISBN
    0-7695-0768-9
  • Type

    conf

  • DOI
    10.1109/ICPP.2000.876120
  • Filename
    876120