Parallel QBF Solving with Advanced Knowledge Sharing

Authors:
Matthew Lewis;Tobias Schubert;Bernd Becker;Paolo Marin;Massimo Narizzano;Enrico Giunchiglia
Affiliations:
(Correspd.) University of Freiburg, Freiburg, Germany. surname@informatik.uni-freiburg.de;University of Freiburg, Freiburg, Germany. surname@informatik.uni-freiburg.de;University of Freiburg, Freiburg, Germany. surname@informatik.uni-freiburg.de;University of Genova, Genova, Italy. name.surname@unige.it;University of Genova, Genova, Italy. name.surname@unige.it;University of Genova, Genova, Italy. name.surname@unige.it
Venue:
Fundamenta Informaticae - RCRA 2009 Experimental Evaluation of Algorithms for Solving Problems with Combinatorial Explosion
Year:
2011

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Abstract

In this paper we present the parallel QBF Solver PaQuBE. This new solver leverages the additional computational power that can be exploited from modern computer architectures, from pervasive multi-core boxes to clusters and grids, to solve more relevant instances faster than previous generation solvers. Furthermore, PaQuBE's progressive MPI based parallel framework is the first to support advanced knowledge sharing in which solution cubes as well as conflict clauses can be exchanged between solvers. Knowledge sharing plays a critical role in the performance of PaQuBE. However, due to the overhead associated with sending and receiving MPI messages, and the restricted communication/network bandwidth available between solvers, it is essential to optimize not only what information is shared, but the way in which it is shared. In this context, we compare multiple conflict clause and solution cube sharing strategies, and finally show that an adaptive method provides the best overall results.