PSATO: a distributed propositional prover and its application to quasigroup problems
Journal of Symbolic Computation - Special issue on parallel symbolic computation
GRASP—a new search algorithm for satisfiability
Proceedings of the 1996 IEEE/ACM international conference on Computer-aided design
A machine program for theorem-proving
Communications of the ACM
Chaff: engineering an efficient SAT solver
Proceedings of the 38th annual Design Automation Conference
The complexity of theorem-proving procedures
STOC '71 Proceedings of the third annual ACM symposium on Theory of computing
Alembic: an efficient algorithm for CNF preprocessing
Proceedings of the 44th annual Design Automation Conference
Vivifying Propositional Clausal Formulae
Proceedings of the 2008 conference on ECAI 2008: 18th European Conference on Artificial Intelligence
SAT '09 Proceedings of the 12th International Conference on Theory and Applications of Satisfiability Testing
A new clause learning scheme for efficient unsatisfiability proofs
AAAI'08 Proceedings of the 23rd national conference on Artificial intelligence - Volume 3
Towards understanding and harnessing the potential of clause learning
Journal of Artificial Intelligence Research
SATzilla: portfolio-based algorithm selection for SAT
Journal of Artificial Intelligence Research
Predicting learnt clauses quality in modern SAT solvers
IJCAI'09 Proceedings of the 21st international jont conference on Artifical intelligence
A lightweight component caching scheme for satisfiability solvers
SAT'07 Proceedings of the 10th international conference on Theory and applications of satisfiability testing
Generalized conflict-clause strengthening for satisfiability solvers
SAT'11 Proceedings of the 14th international conference on Theory and application of satisfiability testing
Effective preprocessing in SAT through variable and clause elimination
SAT'05 Proceedings of the 8th international conference on Theory and Applications of Satisfiability Testing
Partitioning Search Spaces of a Randomized Search
Fundamenta Informaticae - RCRA 2009 Experimental Evaluation of Algorithms for Solving Problems with Combinatorial Explosion
Revisiting clause exchange in parallel SAT solving
SAT'12 Proceedings of the 15th international conference on Theory and Applications of Satisfiability Testing
Designing scalable parallel SAT solvers
SAT'12 Proceedings of the 15th international conference on Theory and Applications of Satisfiability Testing
IJCAR'12 Proceedings of the 6th international joint conference on Automated Reasoning
Refining restarts strategies for SAT and UNSAT
CP'12 Proceedings of the 18th international conference on Principles and Practice of Constraint Programming
Parallel SAT solver selection and scheduling
CP'12 Proceedings of the 18th international conference on Principles and Practice of Constraint Programming
Cube and conquer: guiding CDCL SAT solvers by lookaheads
HVC'11 Proceedings of the 7th international Haifa Verification conference on Hardware and Software: verification and testing
Asynchronous multi-core incremental SAT solving
TACAS'13 Proceedings of the 19th international conference on Tools and Algorithms for the Construction and Analysis of Systems
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This work presents a novel strategy for improving SAT solver performance by using concurrency. Rather than aiming to parallelize search, we use concurrency to aid a conventional CDCL search procedure. More concretely, our work extends a conventional CDCL SAT solver with a second computation thread, which is solely used to strengthen the clauses learned by the solver. This provides a simple and natural way to exploit the availability of multi-core hardware. We have employed our technique to extend two well established solvers, MiniSAT and Glucose. Despite its conceptual simplicity the technique yields a significant improvement of those solvers' performances, in particular for unsatisfiable benchmarks. For such benchmarks an extensive empirical evaluation revealed a remarkably consistent reduction of the wall clock time required to determine unsatisfiability, as well as an ability to solve more benchmarks in the same CPU time. The proposed technique can be applied in combination with existing parallel SAT solving techniques, including both portfolio and search space splitting approaches. The approach presented here can thus be seen as orthogonal to those existing techniques.