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Appears in Collections:Computing Science and Mathematics Conference Papers and Proceedings
Author(s): Archibald, Blair
Maier, Patrick
Stewart, Rob
Trinder, Phil
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Title: YewPar: Skeletons for Exact Combinatorial Search
Citation: Archibald B, Maier P, Stewart R & Trinder P (2020) YewPar: Skeletons for Exact Combinatorial Search. In: PPoPP '20: Proceedings of the 25th Symposium on Principles and Practice of Parallel Programming. Principles and Practice of Parallel Programming 2020 (PPoPP 2020), San Diego, 22.02.2020-26.02.2020. New York: ACM.
Issue Date: 22-Feb-2020
Conference Name: Principles and Practice of Parallel Programming 2020 (PPoPP 2020)
Conference Dates: 2020-02-22 - 2020-02-26
Conference Location: San Diego
Abstract: Combinatorial search is central to many applications, yet the huge irregular search trees and the need to respect search heuristics make it hard to parallelise. We aim to improve the reuse of intricate parallel search implementations by providing the first general purpose scalable parallel framework for exact combinatorial search, YewPar. We make the following contributions. (1) We present a novel formal model of parallel backtracking search, covering enumeration, decision, and optimisation search. (2) We introduce Lazy Node Generators as a uniform API for search tree generation. (3) We present the design and implementation of 12 widely applicable algorithmic skeletons for tree search on shared and distributed memory architectures. (4) Uniquely in the field we demonstrate how a wide range of parallel search applications can easily be constructed by composing Lazy Node Generators and the search skeletons. (5) We report a systematic performance analysis of all 12 YewPar skeletons on standard instances of 7 search applications, investigating skeleton overheads, and scalability up to 255 workers on 17 distributed locations.
Status: AM - Accepted Manuscript
Rights: This item has been embargoed for a period. During the embargo please use the Request a Copy feature at the foot of the Repository record to request a copy directly from the author. You can only request a copy if you wish to use this work for your own research or private study. © 2020 Association for Computing Machinery. This is the author’s version of the work. It is posted here for your personal use. Not for redistribution. The definitive Version of Record was published in 25th ACM SIGPLAN Symposium on Principles and Practice of Parallel Programming (PPoPP ’20), February 22–26, 2020, San Diego, CA, USA,
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