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Domain-Specific Optimization Strategy for Skeleton Programs

  • Kento Emoto
  • Kiminori Matsuzaki
  • Zhenjiang Hu
  • Masato Takeichi
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4641)

Abstract

Skeletal parallel programming enables us to develop parallel programs easily by composing ready-made components called skeletons. However, a simply-composed skeleton program often lacks efficiency due to overheads of intermediate data structures and communications. Many studies have focused on optimizations by fusing successive skeletons to eliminate the overheads. Existing fusion transformations, however, are too general to achieve adequate efficiency for some classes of problems. Thus, a specific fusion optimization is needed for a specific class. In this paper, we propose a strategy for domain-specific optimization of skeleton programs. In this strategy, one starts with a normal form that abstracts the programs of interest, then develops fusion rules that transform a skeleton program into the normal form, and finally makes efficient parallel implementation of the normal form. We illustrate the strategy with a case study: optimization of skeleton programs involving neighbor elements, which is often seen in scientific computations.

Keywords

Normal Form Parallel Implementation Fusion Rule Input List Fusion Optimization 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2007

Authors and Affiliations

  • Kento Emoto
    • 1
  • Kiminori Matsuzaki
    • 1
  • Zhenjiang Hu
    • 1
  • Masato Takeichi
    • 1
  1. 1.Graduate School of Information Science and Technology, University of Tokyo 

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