Arrow Research search
Back to IJCAI

IJCAI 2009

Conference Paper Constraints, Satisfiability, and Search Artificial Intelligence

Abstract

Conflict driven clause learning, one of the most important component of modern SAT solvers, is also recognized as very important in parallel SAT solving. Indeed, it allows clause sharing between multiple processing units working on related (sub- )problems. However, without limitation, sharing clauses might lead to an exponential blow up in communication or to the sharing of irrelevant clauses. This paper, proposes two innovative policies to dynamically adjust the size of shared clauses between any pair of processing units. The first approach controls the overall number of exchanged clauses whereas the second additionally exploits the relevance quality of shared clauses. Experimental results show important improvements of the state-of the-art parallel SAT solver.

Authors

Keywords

No keywords are indexed for this paper.

Context

Venue
International Joint Conference on Artificial Intelligence
Archive span
1969-2025
Indexed papers
14525
Paper id
217503191700946168
v2026.09.13