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Asian Symposium on Programming Languages and Systems

APLAS 2011: Programming Languages and Systems pp 204–219Cite as

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

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Part of the book series: Lecture Notes in Computer Science ((LNPSE,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.

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Authors and Affiliations

  1. Research Institute of Electrical Communication, Tohoku University, Japan

    Akimasa Morihata

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  1. Akimasa Morihata
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Editors and Affiliations

  1. Department of Computer Science, University of Oxford, Parks Road, OX1 3QD, Oxford, UK

    Hongseok Yang

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Morihata, A. (2011). Macro Tree Transformations of Linear Size Increase Achieve Cost-Optimal Parallelism. In: Yang, H. (eds) Programming Languages and Systems. APLAS 2011. Lecture Notes in Computer Science, vol 7078. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-25318-8_17

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  • DOI: https://doi.org/10.1007/978-3-642-25318-8_17

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-25317-1

  • Online ISBN: 978-3-642-25318-8

  • eBook Packages: Computer ScienceComputer Science (R0)

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