Identifying parallelism in programs with cyclic graphs

  • Authors:

  • Yuan-Shin Hwang;Joel H. Saltz

  • Affiliations:

  • Department of Computer Science, National Taiwan Ocean University, Keelung 20224, Taiwan;Department of Biomedical Informatics, The Ohio State University, Columbus, OH

  • Venue:
  • Journal of Parallel and Distributed Computing
  • Year:
  • 2003

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Abstract

Dependence analysis algorithms have been proposed to identify parallelism in programs with tree-like data structures. However, they cannot 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 will be located by definition-use chains of recursive data structures; (2) traversal-pattern-sensitive 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.