Collaborative Approach for Multi-Threaded SAT Solving

The last decade progresses have led the Satisfiability Problem (sat) to be a great and competitive practical approach to solve a wide range of industrial and academic problems. Thanks to these progresses, the size and difficulty of the sat instances has grown significantly. Among the recent solvers,...

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Bibliographic Details
Published in:International journal of parallel programming Vol. 37; no. 3; pp. 324 - 342
Main Authors: Vander-Swalmen, Pascal, Dequen, Gilles, Krajecki, Michaël
Format: Journal Article
Language:English
Published: Boston Boston : Springer US 01.06.2009
Springer US
Springer Nature B.V
Springer Verlag
Subjects:
Algorithms
Artificial Intelligence
Boolean
Collaboration
Combinatorics
Computer programming
Computer Science
Distributed, Parallel, and Cluster Computing
Open source software
Optimization
Parallel processing
Processor Architectures
Software Engineering/Programming and Operating Systems
Studies
Theory of Computation
Parallel combinatorial optimization
MP
Satisfiability
O
ISSN:0885-7458, 1573-7640
Online Access:Get full text
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Summary:The last decade progresses have led the Satisfiability Problem (sat) to be a great and competitive practical approach to solve a wide range of industrial and academic problems. Thanks to these progresses, the size and difficulty of the sat instances has grown significantly. Among the recent solvers, a few are parallel and most of them use the message passing paradigm. In a previous work by Vander-Swalmen et al. (IWOMP, 146-157, 2008), we presented a fine grain parallel sat solver designed for shared memory using OpenMP and named mtss, for Multi Threaded Sat Solver. mtss extends the “guiding path” notion and uses a collaborative approach where a rich thread is in charge of the search-tree evaluation and where a set of poor threads yield logical or heuristics information to simplify the rich task. In this paper, we extend the poor thread abilities of mtss and present extensive comparative results on random 3-sat problems. These new experimentations show that fine grained techniques associated to poor tasks within the framework of mtss can achieve very interesting speedup on multi-core processors.
Bibliography:http://dx.doi.org/10.1007/s10766-009-0097-6
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ISSN:0885-7458
1573-7640
DOI:10.1007/s10766-009-0097-6