Skip to content

Research at St Andrews

In search of a map: using program slicing to discover potential parallelism in recursive functions

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Recursion schemes, such as the well-known map, can be used as loci of potential parallelism, where schemes are replaced with an equivalent parallel implementation. This paper formalises a novel technique, using program slicing, that automatically and statically identifies computations in recursive functions that can be lifted out of the function and then potentially performed in parallel. We define a new program slicing algorithm, build a prototype implementation, and demonstrate its use on 12 Haskell examples, including benchmarks from the NoFib suite and functions from the standard Haskell Prelude. In all cases, we obtain the expected results in terms of finding potential parallelism. Moreover, we have tested our prototype against synthetic benchmarks, and found that our prototype has quadratic time complexity. For the NoFib benchmark examples we demonstrate that relative parallel speedups can be obtained (up to 32.93x the sequential performance on 56 hyperthreaded cores).
Close

Details

Original languageEnglish
Title of host publicationProceedings of the 6th ACM SIGPLAN International Workshop on Functional High-Performance Computing (FHPC 2017)
Place of PublicationNew York
PublisherACM
Pages30-41
ISBN (Electronic)9781450351812
DOIs
StatePublished - 7 Sep 2017
EventFHPC 2017 Workshop on Functional High-Performance Computing - Oxford, United Kingdom
Duration: 7 Sep 20177 Sep 2017
https://icfp17.sigplan.org/track/FHPC-2017-papers

Workshop

WorkshopFHPC 2017 Workshop on Functional High-Performance Computing
Abbreviated titleFHPC
CountryUnited Kingdom
CityOxford
Period7/09/177/09/17
Internet address

    Research areas

  • Program slicing, Recursion schemes, Patten discovery, Parallelism

Discover related content
Find related publications, people, projects and more using interactive charts.

View graph of relations

Related by author

  1. Extending the ‘Open-Closed Principle’ to automated algorithm configuration

    Swan, J., Adriænsen, S., Barwell, A. D., Hammond, K. & White, D. 17 Dec 2018 In : Evolutionary Computation.

    Research output: Contribution to journalArticle

  2. The Missing Link! A new skeleton for evolutionary multi-agent systems in Erlang

    Stypka, J., Turek, W., Byrski, A., Kisiel-Dorohinicki, M., Barwell, A. D., Brown, C. M., Hammond, K. & Janjic, V. Feb 2018 In : International Journal of Parallel Programming. 46, 1, p. 4-22 19 p.

    Research output: Contribution to journalArticle

  3. Towards semi-automatic data-type translation for parallelism in Erlang

    Barwell, A. D., Brown, C. M., Castro, D. & Hammond, K. 23 Sep 2016 Proceedings of the 15th International Workshop on Erlang. New York: ACM, p. 60-61

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

ID: 257273951