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Functional parallel algorithms

Published:27 September 2010Publication History
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Abstract

Functional programming presents several important advantages in the design, analysis and implementation of parallel algorithms:

  • It discourages iteration and encourages decomposition.

  • It supports persistence and hence easy speculation.

  • It encourages higher-order aggregate operations.

  • It is well suited for defining cost models tied to the programming language rather than the machine.

  • Implementations can avoid false sharing.

  • Implementations can use cheaper weak consistency models.

  • And most importantly, it supports safe deterministic parallelism.

In fact functional programming supports a level of abstraction in which parallel algorithms are often as easy to design and analyze as sequential algorithms. The recent widespread advent of parallel machines therefore presents a great opportunity for functional programming languages. However, any changes will require significant education at all levels and involvement of the functional programming community.

In this talk I will discuss an approach to designing and analyzing parallel algorithms in a strict functional and fully deterministic setting. Key ideas include a cost model defined in term of analyzing work and span, the use of divide-and-conquer and contraction, the need for arrays (immutable) to achieve asymptotic efficiency, and the power of (deterministic) randomized algorithms. These are all ideas I believe can be taught at any level.

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icfp-weds-0900-blelloch.mov

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      • Published in

        cover image ACM SIGPLAN Notices
        ACM SIGPLAN Notices  Volume 45, Issue 9
        ICFP '10
        September 2010
        382 pages
        ISSN:0362-1340
        EISSN:1558-1160
        DOI:10.1145/1932681
        Issue’s Table of Contents
        • cover image ACM Conferences
          ICFP '10: Proceedings of the 15th ACM SIGPLAN international conference on Functional programming
          September 2010
          398 pages
          ISBN:9781605587943
          DOI:10.1145/1863543

        Copyright © 2010 Copyright is held by the author/owner(s)

        Publisher

        Association for Computing Machinery

        New York, NY, United States

        Publication History

        • Published: 27 September 2010

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