Towards a Parallel Hierarchical Adaptive Solver Tool

Salvador Abreu (1) , Danny Munera (2) , Daniel Diaz (2)

1 Universidade de Évora
2 CRI - Centre de Recherche en Informatique de Paris 1

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.

Domains: Distributed, Parallel, and Cluster Computing [cs.DC]

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⟩