Improving SAT Solver Efficiency Using a Multi-Core Approach

Many practical problems in multiple fields can be converted to a SAT problem, or a sequence of SAT problems, such that their solution immediately implies a solution to the original problem. Despite the enormous progress achieved over the last decade in the development of SAT solvers, there is strong demand for higher algorithm efficiency to solve harder and larger problems. The widespread availability of multi-core, shared memory parallel environments provides an opportunity for such improvements. In this paper we present our results on improving the effectiveness of standard SAT solvers on such architectures, through a portfolio approach. Multiple instances of the same basic solver using different heuristic strategies, for search-space exploration and problem analysis, share information and cooperate towards the solution of a given problem. Results from the application of our methodology to known problems from SAT competitions show relevant improvements over the state of the art and yield the promise of further advances.