Towards a Parallel Hierarchical Adaptive Solver Tool

dc.contributor.authorAbreu, Salvador
dc.contributor.authorMunera, Danny
dc.contributor.authorDiaz, Daniel
dc.date.accessioned2016-03-10T11:11:41Z
dc.date.available2016-03-10T11:11:41Z
dc.date.issued2014-07
dc.description.abstractConstraint 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 ...por
dc.identifier.authoremailsalvador.abreu@acm.org
dc.identifier.authoremailnd
dc.identifier.authoremailnd
dc.identifier.citationSalvador 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>por
dc.identifier.scientificarea283por
dc.identifier.urihttps://hal-paris1.archives-ouvertes.fr/hal-01195526/
dc.identifier.urihttp://hdl.handle.net/10174/17897
dc.language.isoengpor
dc.peerreviewedyespor
dc.publisherT.U. Wienpor
dc.rightsopenAccesspor
dc.titleTowards a Parallel Hierarchical Adaptive Solver Toolpor
dc.typearticlepor

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