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Communication Dans Un Congrès Année : 2014

A GPU Implementation of Parallel Constraint-Based Local Search

Résumé

In this paper we study the performance of constraint-based local search solvers on a GPU. The massively parallel architecture of the GPU makes it possible to explore parallelism at two different levels inside the local search algorithm. First, by executing multiple copies of the algorithm in a multiwalk manner and, second, by evaluating large neighborhoods in parallel in a single-walk manner. Experiments on three wellknown problem benchmarks indicate that the current GPU implementation is up to 17 times faster than a well-tuned sequential algorithm implemented on a desktop computer.
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hal-04416685 , version 1 (25-01-2024)

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Alejandro Arbelaez, Philippe Codognet. A GPU Implementation of Parallel Constraint-Based Local Search. 2014 22nd Euromicro International Conference on Parallel, Distributed and Network-Based Processing (PDP), Feb 2014, Torino, France. pp.648-655, ⟨10.1109/PDP.2014.28⟩. ⟨hal-04416685⟩
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