Optimal speedup of Las Vegas algorithms
Information Processing Letters
PSATO: a distributed propositional prover and its application to quasigroup problems
Journal of Symbolic Computation - Special issue on parallel symbolic computation
Artificial Intelligence - special issue on computational tradeoffs under bounded resources
Heavy-Tailed Phenomena in Satisfiability and Constraint Satisfaction Problems
Journal of Automated Reasoning
Optimal Parallelization of Las Vegas Algorithms
STACS '94 Proceedings of the 11th Annual Symposium on Theoretical Aspects of Computer Science
Restart Policies with Dependence among Runs: A Dynamic Programming Approach
CP '02 Proceedings of the 8th International Conference on Principles and Practice of Constraint Programming
Eighteenth national conference on Artificial intelligence
GridSAT: A Chaff-based Distributed SAT Solver for the Grid
Proceedings of the 2003 ACM/IEEE conference on Supercomputing
A Parallelization Scheme Based on Work Stealing for a Class of SAT Solvers
Journal of Automated Reasoning
ZetaSAT - Boolean SATisfiability solving on Desktop Grids
CCGRID '05 Proceedings of the Fifth IEEE International Symposium on Cluster Computing and the Grid (CCGrid'05) - Volume 2 - Volume 02
A competitive and cooperative approach to propositional satisfiability
Discrete Applied Mathematics - Special issue: Discrete algorithms and optimization, in honor of professor Toshihide Ibaraki at his retirement from Kyoto University
On Portfolios for Backtracking Search in the Presence of Deadlines
ICTAI '07 Proceedings of the 19th IEEE International Conference on Tools with Artificial Intelligence - Volume 01
Using the Grid for Enhancing the Performance of a Medical Image Search Engine
CBMS '08 Proceedings of the 2008 21st IEEE International Symposium on Computer-Based Medical Systems
Restart schedules for ensembles of problem instances
AAAI'07 Proceedings of the 22nd national conference on Artificial intelligence - Volume 2
IJCAI'99 Proceedings of the 16th international joint conference on Artificial intelligence - Volume 2
The effect of restarts on the efficiency of clause learning
IJCAI'07 Proceedings of the 20th international joint conference on Artifical intelligence
On universal restart strategies for backtracking search
CP'07 Proceedings of the 13th international conference on Principles and practice of constraint programming
A distribution method for solving SAT in grids
SAT'06 Proceedings of the 9th international conference on Theory and Applications of Satisfiability Testing
Incorporating Learning in Grid-Based Randomized SAT Solving
AIMSA '08 Proceedings of the 13th international conference on Artificial Intelligence: Methodology, Systems, and Applications
Partitioning Search Spaces of a Randomized Search
AI*IA '09: Proceedings of the XIth International Conference of the Italian Association for Artificial Intelligence Reggio Emilia on Emergent Perspectives in Artificial Intelligence
Partitioning SAT instances for distributed solving
LPAR'10 Proceedings of the 17th international conference on Logic for programming, artificial intelligence, and reasoning
Partitioning Search Spaces of a Randomized Search
Fundamenta Informaticae - RCRA 2009 Experimental Evaluation of Algorithms for Solving Problems with Combinatorial Explosion
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Grid computing offers a promising approach to solving challenging computational problems in an environment consisting of a large number of easily accessible resources. In this paper we develop strategies for solving collections of hard instances of the propositional satisfiability problem (SAT) with a randomized SAT solver run in a Grid. We study alternative strategies by using a simulation framework which is composed of (i) a grid model capturing the communication and management delays, and (ii) run-time distributions of a randomized solver, obtained by running a state-of-the-art SAT solver on a collection of hard instances. The results are experimentally validated in a production level Grid. When solving a single hard SAT instance, the results show that in practice only a relatively small amount of parallelism can be efficiently used; the speedup obtained by increasing parallelism thereafter is negligible. This observation leads to a novel strategy of using grid to solve collections of hard instances. Instead of solving instances one-by-one, the strategy aims at decreasing the overall solution time by applying an alternating distribution schedule.