Data dependence analysis on multi-dimensional array references

  • Authors:

  • Zhiyuan Li;Pen-Chung Yew;Chuag-Qi Zhu

  • Affiliations:

  • Center for Supercomputing Research and Development, University of Illinois at Urbana-Champaign, 305 Talbot, 104 S. Wright St., Urbanba, IL;Center for Supercomputing Research and Development, University of Illinois at Urbana-Champaign, 305 Talbot, 104 S. Wright St., Urbanba, IL;Center for Supercomputing Research and Development, University of Illinois at Urbana-Champaign, 305 Talbot, 104 S. Wright St., Urbanba, IL

  • Venue:
  • ICS '89 Proceedings of the 3rd international conference on Supercomputing
  • Year:
  • 1989

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Abstract

An efficient and precise data dependence analysis is the key to the success of a parallelizing compiler because it is required in almost all phases of the parallelism detection and enhancement in such compilers. However, existing test algorithms are quite weak in analyzing multi-dimensional array references, which are usually where the parallelism is in most programs.In this paper, a new algorithm, called &lgr;-test, is presented for an efficient and accurate data dependence analysis on multi-dimensional array references. It achieves high efficiency and high accuracy at the same time, which is in general not allowed in previous algorithms. This algorithm has been implemented in Parafrase [Wolf82]. Some experimental results are also presented to show its effectiveness.