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We present the latest instantiation of GridSAT [1], a distributed and complete satisfiability solver that is explicitly designed to aggregate Grid resources for application performance. GridSAT was previously shown to outperform the state-of-the-art sequential solvers. In this work, we explore the unprecedented solving power GridSAT enables through algorithmic and implementation innovations. We describe the implementation techniques that allow GridSAT to leverage a variety of high-end batch-scheduled resources, clusters, interactive workstations, and personal computing resources through autonomous scheduling, checkpoint scheduling, and work migration. These innovations have allowed GridSAT to solve a set of 'hard' and previously

SUMMARYWe present a Grid portal problem (which is accessible through http://orca.cs.ucsb.edu/sat portal) for solving Boolean satisfiability. The portal provides a simple and public interface to a sophisticated and complex Grid application-GridSAT-running on a large set of distributed computational resources hosted in different large-scale national computing centers (i.e. the national cyberinfrastructure circa 2005). In this paper we describe the design goals of the portal and how it has influenced some of the application features. We also describe how the adaptive and self-tuning features of Grid applications (written from first principles) make the portal simpler and easier to implement.

We present GridSAT, a parallel and complete satisfiability solver designed to solve non-trivial SAT problem instances using a large number of widely distributed and heterogeneous resources.The GridSAT parallel algorithm uses intelligent backtracking, distributed and carefully scheduled sharing of learned clauses, and clause reduction. Our implementation focuses on dynamic resource acquisition and release to optimize application execution. We show how the large number of computational resources that are available from a Grid can be managed effectively for the application by an automatic scheduler and effective implementation. GridSAT execution speed is compared against the best sequential solver as rated by the SAT2002 competition using a wide variety of problem instances. The results show that GridSAT delivers speed-up for all but one of the test problem instances that are of significant size. In addition, we describe how GridSAT has solved previously unsolved satisfiability problems and the domain science contribution these results make.