Decomposition techniques for parallel resolution of constraint satisfaction problems in shared memory: a comparative study

Authors:
Zineb Habbas;Michael Krajecki;Daniel Singer
Affiliations:
Universite Paul Verlaine de Metz, LITA, EA 3097, Ile du Saulcy, F 57 045 Metz Cedex, France.;CReSTIC, EA 3804, Universite de Reims Champagne-Ardenne, Moulin de la Housse, BP 1039, F51687 Reims Cedex 2, France.;Universite Paul Verlaine de Metz, LITA, EA 3097, Ile du Saulcy, F 57 045 Metz Cedex, France
Venue:
International Journal of Computational Science and Engineering
Year:
2005

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Abstract

This paper provides both a formal and an empirical study of decomposition techniques for parallel resolution of Constraint Satisfaction Problems (CSP) in shared memory. The main contribution of this study is to bring together decomposition techniques with Backtrack search to solve CSP on parallel architectures in shared memory. Another contribution is to demonstrate how to obtain good scalability up to hundreds of processors in shared memory for CSP resolution and more generally for Irregular Applications.