An Accumulative Parallel Skeleton for All

  • Authors:
  • Zhenjiang Hu;Hideya Iwasaki;Masato Takeichi

  • Affiliations:
  • -;-;-

  • Venue:
  • ESOP '02 Proceedings of the 11th European Symposium on Programming Languages and Systems
  • Year:
  • 2002

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Abstract

Parallel skeletons intend to encourage programmers to build a parallel program from ready-made components for which efficient implementations are known to exist, making the parallelization process simpler. However, it is neither easy to develop efficient parallel programs using skeletons nor to use skeletons to manipulate irregular data, and moreover there lacks a systematic way to optimize skeletal parallel programs. To remedy this situation, we propose a novel parallel skeleton, called accumulate, which not only efficiently describes data dependency in computation but also exhibits nice algebraic properties for manipulation. We show that this skeleton significantly eases skeletal parallel programming in practice, efficiently manipulating both regular and irregular data, and systematically optimizing skeletal parallel programs.