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
Boosting combinatorial search through randomization
AAAI '98/IAAI '98 Proceedings of the fifteenth national/tenth conference on Artificial intelligence/Innovative applications of artificial intelligence
A machine program for theorem-proving
Communications of the ACM
Chaff: engineering an efficient SAT solver
Proceedings of the 38th annual Design Automation Conference
Evaluating general purpose automated theorem proving systems
Artificial Intelligence
Heavy-Tailed Phenomena in Satisfiability and Constraint Satisfaction Problems
Journal of Automated Reasoning
Efficient conflict driven learning in a boolean satisfiability solver
Proceedings of the 2001 IEEE/ACM international conference on Computer-aided design
Improving Backtrack Search for SAT by Means of Redundancy
ISMIS '99 Proceedings of the 11th International Symposium on Foundations of Intelligent Systems
Eighteenth national conference on Artificial intelligence
A Parallelization Scheme Based on Work Stealing for a Class of SAT Solvers
Journal of Automated Reasoning
ASP-DAC '07 Proceedings of the 2007 Asia and South Pacific Design Automation Conference
Handbook of Satisfiability: Volume 185 Frontiers in Artificial Intelligence and Applications
Handbook of Satisfiability: Volume 185 Frontiers in Artificial Intelligence and Applications
Width-Based Restart Policies for Clause-Learning Satisfiability Solvers
SAT '09 Proceedings of the 12th International Conference on Theory and Applications of Satisfiability Testing
c-sat: A Parallel SAT Solver for Clusters
SAT '09 Proceedings of the 12th International Conference on Theory and Applications of Satisfiability Testing
SATzilla: portfolio-based algorithm selection for SAT
Journal of Artificial Intelligence Research
Control-based clause sharing in parallel SAT solving
IJCAI'09 Proceedings of the 21st international jont conference on Artifical intelligence
A generalized framework for conflict analysis
SAT'08 Proceedings of the 11th international conference on Theory and applications of satisfiability testing
Adaptive restart strategies for conflict driven SAT solvers
SAT'08 Proceedings of the 11th international conference on Theory and applications of satisfiability testing
An overview of parallel SAT solving
Constraints
Parallel search for maximum satisfiability
AI Communications - 18th RCRA International Workshop on “Experimental evaluation of algorithms for solving problems with combinatorial explosion”
Designing scalable parallel SAT solvers
SAT'12 Proceedings of the 15th international conference on Theory and Applications of Satisfiability Testing
Intensification search in modern SAT solvers
SAT'12 Proceedings of the 15th international conference on Theory and Applications of Satisfiability Testing
A hybrid paradigm for adaptive parallel search
CP'12 Proceedings of the 18th international conference on Principles and Practice of Constraint Programming
Counter implication restart for parallel SAT solvers
LION'12 Proceedings of the 6th international conference on Learning and Intelligent Optimization
Thread-based multi-engine model checking for multicore platforms
ACM Transactions on Design Automation of Electronic Systems (TODAES)
Soundness of inprocessing in clause sharing SAT solvers
SAT'13 Proceedings of the 16th international conference on Theory and Applications of Satisfiability Testing
| Hi-index | 0.00 |
In this paper, we explore the two well-known principles of diversification and intensification in portfolio-based parallel SAT solving. These dual concepts play an important role in several search algorithms including local search, and appear to be a key point in modern parallel SAT solvers. To study their trade-off, we define two roles for the computational units. Some of them classified as Masters perform an original search strategy, ensuring diversification. The remaining units, classified as Slaves are there to intensify their master's strategy. Several important questions have to be answered. The first one is what information should be given to a slave in order to intensify a given search effort? The second one is, how often, a subordinated unit has to receive such information? Finally, the question of finding the number of subordinated units and their connections with the search efforts has to be answered. Our results lead to an original intensification strategy which outperforms the best parallel SAT solver ManySAT, and solves some open SAT instances.