2010 | OriginalPaper | Buchkapitel
Diversification and Intensification in Parallel SAT Solving
verfasst von : Long Guo, Youssef Hamadi, Said Jabbour, Lakhdar Sais
Erschienen in: Principles and Practice of Constraint Programming – CP 2010
Verlag: Springer Berlin Heidelberg
Aktivieren Sie unsere intelligente Suche, um passende Fachinhalte oder Patente zu finden.
Wählen Sie Textabschnitte aus um mit Künstlicher Intelligenz passenden Patente zu finden. powered by
Markieren Sie Textabschnitte, um KI-gestützt weitere passende Inhalte zu finden. powered by
In this paper, we explore the two well-known principles of diversification and intensification in portfolio-based parallel SAT solving. These dual concepts play an important role in several search algorithms including local search, and appear to be a key point in modern parallel SAT solvers. To study their tradeoff, we define two roles for the computational units. Some of them classified as
Masters
perform an original search strategy, ensuring diversification. The remaining units, classified as
Slaves
are there to intensify their master’s strategy. Several important questions have to be answered. The first one is what information should be given to a slave in order to intensify a given search effort? The second one is, how often, a subordinated unit has to receive such information? Finally, the question of finding the number of subordinated units and their connections with the search efforts has to be answered. Our results lead to an original intensification strategy which outperforms the best parallel SAT solver ManySAT, and solves some open SAT instances.