DocumentCode :
2824431
Title :
Toward Easy Parallel SAT Solving
Author :
Dequen, Gilles ; Vander-Swalmen, Pascal ; Krajecki, Michaël
Author_Institution :
Lab. d´´Inf. de Paris 6, Univ. de Picardie Jules Verne, Paris, TX, USA
fYear :
2009
fDate :
2-4 Nov. 2009
Firstpage :
425
Lastpage :
432
Abstract :
In spite of its computational complexity, the satisfiability problem is a great and competitive approach to solve a wide range of problems. This leads to have a strong demand for high-performance sat-solving tools in industry. Over the years, many different approaches and optimizations have been developed to tackle the problem more efficiently while being unaware of the actual trend in processor development which is from single-core to multi-core CPUs. This paper presents a shared memory parallel solving framework which is able to statically exploit the existing sequential and parallel solvers or preprocessors. This new framework facilitates the future parallel sat solving implementation approaches. It also briefly describes the associated lemma exchange policy. Some examples and experimentations with and without lemma exchange strategies using march, kcnfs and minisat are presented. Finally it shows the relevance of the scheme providing super linear speedups on some satisfiable and unsatisfiable formulas.
Keywords :
computability; computational complexity; multi-threading; program processors; computational complexity; easy parallel SAT solving; kcnfs; lemma exchange policy; march; minisat; parallel solvers; satisfiability problem; sequential preprocessors; shared memory parallel solving framework; Artificial intelligence; Collaborative work; Computational complexity; Cryptography; Data preprocessing; Logic design; Memory architecture; Multicore processing; NP-complete problem; Very large scale integration; Blackbox; Parallel Solving; Satisfiability Problem;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Tools with Artificial Intelligence, 2009. ICTAI '09. 21st International Conference on
Conference_Location :
Newark, NJ
ISSN :
1082-3409
Print_ISBN :
978-1-4244-5619-2
Electronic_ISBN :
1082-3409
Type :
conf
DOI :
10.1109/ICTAI.2009.63
Filename :
5363778
Link To Document :
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