2009INFORMS journal on computingRequires access

Transparent Parallelization of Constraint Programming

Laurent Michel, Andrew See, Pascal Van Hentenryck

Open publisher page 41 citations

Abstract

The availability of commodity multicore and multiprocessor machines and the inherent parallelism in constraint programming search offer significant opportunities for constraint programming. These opportunities also present a fundamental challenge: how to exploit parallelism transparently to speed up constraint programs. This paper shows how to parallelize constraint programs transparently without changes to the sequential code. The main technical idea consists of automatically lifting a sequential exploration strategy into its parallel counterpart, allowing workers to share and steal subproblems. Experimental results show that the parallel implementation may produce significant speedups on multicore machines.

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What this paper is about

The availability of commodity multicore and multiprocessor machines and the inherent parallelism in constraint programming search offer significant opportunities for constraint programming. These opportunities also present a fundamental challenge: how to exploit parallelism transparently to speed up constraint programs. This paper shows how to parallelize constraint programs transparently without changes to the sequential code. The main technical idea consists of automatically lifting a sequential exploration strategy into its parallel counterpart, allowing workers to share and steal subproblems. Experimental results show that the parallel implementation may produce significant speedups on multicore machines.

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OpenAlex reports 41 citations for this work. Citation counts describe recorded attention and do not establish research quality.

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Available abstract

The availability of commodity multicore and multiprocessor machines and the inherent parallelism in constraint programming search offer significant opportunities for constraint programming. These opportunities also present a fundamental challenge: how to exploit parallelism transparently to speed up constraint programs. This paper shows how to parallelize constraint programs transparently without changes to the sequential code. The main technical idea consists of automatically lifting a sequential exploration strategy into its parallel counterpart, allowing workers to share and steal subproblems. Experimental results show that the parallel implementation may produce significant speedups on multicore machines.

Key concepts: Computer science, Constraint programming, Parallel computing, Constraint (computer-aided design), Parallelism (grammar), Multiprocessing, Multi-core processor, Constraint satisfaction

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