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Macro Tree Transformations of Linear Size Increase Achieve Cost-Optimal Parallelism

  • Akimasa Morihata
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7078)

Abstract

This paper studies parallel evaluation of tree transformations, in particular accumulative ones. Accumulation is a ubiquitous programming pattern. However, since accumulation usually imposes restrictions on evaluation orders, accumulative tree transformations appear to be unsuitable for parallel evaluation. We propose a parallel evaluation method for a large class of tree-to-tree recursive functions, which may contain accumulations, higher-order terms, and function compositions. Our parallel evaluation method achieves optimal parallel speedup if the transformation is of linear size increase, namely, the size of each output is linearly bounded by the size of the corresponding input. Our result is based on the theory of macro tree transducers and that of parallel tree contractions. The main contribution is to reveal a good collaboration between them.

Keywords

Recursive Function Recursive Call Input Tree Tree Automaton Parallel Evaluation 
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 2011

Authors and Affiliations

  • Akimasa Morihata
    • 1
  1. 1.Research Institute of Electrical CommunicationTohoku UniversityJapan

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