Abstract
The availability of commodity multiprocessors offers significant opportunities for addressing the increasing computational requirements of optimization applications. To leverage these potential benefits, it is important however to make parallel processing easily accessible to a wide audience of optimization programmers. This paper addresses this challenge by proposing parallel programming abstractions that keep the distance between sequential and parallel local search algorithms as small as possible. The abstractions, that include parallel loops, interruptions, and thread pools, are compositional and cleanly separate the optimization program and the parallel instructions. They have been evaluated experimentally on a variety of applications, including facility location and coloring, for which they provide significant speedups.
Keywords
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Aiex, R., Binato, S., Resende, M.: Parallel GRASP with Path-Relinking for Jobshop Scheduling. Parallel Computing 29(4), 393–430 (2003)
Chandra, R., Dagum, L., Kohr, D., Maydan, D., McDonald, J., Menon, R.: Parallel Programming in OpenMP. Morgan Kaufmann, San Francisco (2000) ISBN:1558606718
Clocksin, W.F., Alshawi, H.: A Method for Efficiently Executing Horn Clause Programs Using Multiple Processors. New Generation Computing 5, 361–376 (1988)
Dagum, L., Menon, R.: Openmp: An industry-standard api for shared-memory programming. IEEE Computational Science and Engineering 5, 46–55 (1998)
Dell’Amico, M., Trubian, M.: Applying Tabu Search to the Job-Shop Scheduling Problem. Annals of Operations Research 41, 231–252 (1993)
Dorne, R., Hao, J.K.: Meta-heuristics: Advances and Trends in Local Search Paradigms for Optimization. In: Tabu Search for Graph Coloring, T-Colorings and Set T-Colorings, pp. 77–92. Kluwer Academic Publishers, Dordrecht (1998)
Michel, L., Van Hentenryck, P.: A Constraint-Based Architecture for Local Search. In: OOPSLA 2002, Seattle, November 2002, pp. 101–110 (2002)
Michel, L., Van Hentenryck, P.: A Decomposition-Based Implementation of Search Strategies. ACM Transactions on Computational Logic 5(2) (2004)
Perron, L.: Search Procedures and Parallelism in Constraint Programming. In: Jaffar, J. (ed.) CP 1999. LNCS, vol. 1713, pp. 346–361. Springer, Heidelberg (1999)
Van Hentenryck, P., Michel, L.: Control Abstractions for Local Search. In: Rossi, F. (ed.) CP 2003. LNCS, vol. 2833, pp. 65–80. Springer, Heidelberg (2003)
Van Hentenryck, P., Michel, L.: Constraint-Based Local Search. The MIT Press, Cambridge (2005)
Van Hentenryck, P., Michel, L.: Nondeterministic Control for Hybrid Search. In: Barták, R., Milano, M. (eds.) CPAIOR 2005. LNCS, vol. 3524, pp. 380–395. Springer, Heidelberg (2005)
Van Hentenryck, P., Michel, L., Liu, L.: Constraint-Based Combinators for Local Search. In: Wallace, M. (ed.) CP 2004. LNCS, vol. 3258, pp. 47–61. Springer, Heidelberg (2004)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2005 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Michel, L., Van Hentenryck, P. (2005). Parallel Local Search in Comet. In: van Beek, P. (eds) Principles and Practice of Constraint Programming - CP 2005. CP 2005. Lecture Notes in Computer Science, vol 3709. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11564751_33
Download citation
DOI: https://doi.org/10.1007/11564751_33
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-29238-8
Online ISBN: 978-3-540-32050-0
eBook Packages: Computer ScienceComputer Science (R0)