Parallel SAT simplification on GPU architectures

Abstract

The growing scale of applications encoded to Boolean Satisfiability (SAT) problems imposes the need for accelerating SAT simplifications or preprocessing. Parallel SAT preprocessing has been an open challenge for many years. Therefore, we propose novel parallel algorithms for variable and subsumption elimination targeting Graphics Processing Units (GPUs). Benchmarks show that the algorithms achieve an acceleration of 66 × over a state-of-the-art SAT simplifier (SatELite). Regarding SAT solving, we have conducted a thorough evaluation, combining both our GPU algorithms and SatELite with MiniSat to solve the simplified problems. In addition, we have studied the impact of the algorithms on the solvability of problems with Lingeling. We conclude that our algorithms have a considerable impact on the solvability of SAT problems.