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Conference Papers Year : 2017

Implementing Algorithmic Skeletons with Bulk Synchronous Parallel ML

Abstract

Skeletal parallelism offers a good trade-off between programming productivity and execution efficiency. In this style of parallelism, an application is a composition of algorithmic skeletons. An algorithmic skeleton captures a pattern of parallel algorithm on a distributed data structure, and is also often associated with a sequential algorithm on a sequential data structure that is the counterpart of the parallel data structure. The algorithmic skeleton approach has been inspired by functional programming. It is therefore very natural to embed algorithmic skeletons in a functional programming language. In this paper we present a new algorithmic skeleton library for the statically typed functional language OCaml, and illustrate its use on some applications. This functional skeletal parallel programming library is implemented using the Bulk Synchronous Parallel ML parallel programming library for OCaml.
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Dates and versions

hal-02317099 , version 1 (15-10-2019)

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Frédéric Loulergue. Implementing Algorithmic Skeletons with Bulk Synchronous Parallel ML. 2017 18th International Conference on Parallel and Distributed Computing, Applications and Technologies (PDCAT), Dec 2017, Taipei, Taiwan. pp.461-468, ⟨10.1109/PDCAT.2017.00079⟩. ⟨hal-02317099⟩
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