Abstract : Constraint satisfaction and combinatorial optimization problems , even when modeled with efficient metaheurisics such as local search remain computationally very intensive. Solvers stand to benefit significantly from execution on parallel systems, which are increasingly available. The architectural diversity and complexity of the latter means that these systems pose ever greater challenges in order to be effectively used, both from the point of view of the modeling effort and from that of the degree of coverage of the available computing resources. In this article we discuss impositions and design issues for a framework to make efficient use of various parallel architectures.
Type de document :
Communication dans un congrès
Workshop on Parallel Methods for Search & Optimization (ParSearchOpt14), Jul 2014, Vienna, Austria
https://hal-paris1.archives-ouvertes.fr/hal-01195526
Contributeur : Danny Munera
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Soumis le : lundi 7 septembre 2015 - 21:03:43
Dernière modification le : mercredi 9 septembre 2015 - 01:04:16
Document(s) archivé(s) le : mercredi 26 avril 2017 - 15:40:00
Salvador Abreu, Danny Munera, Daniel Diaz. Towards a Parallel Hierarchical Adaptive Solver Tool. Workshop on Parallel Methods for Search & Optimization (ParSearchOpt14), Jul 2014, Vienna, Austria. 〈hal-01195526〉
