Computer algorithms, Graphics processing units, Boolean algebra
NVIDIA’s Compute Unified Device Architecture (CUDA) is a relatively-recent development that allows to realize very fast algorithms for several Constraint Satisfaction and Computer Aided Design tasks. In this paper we present an approach to use Graphics Processing Units (GPU) and CUDA for solving Unate Covering Problem, a practical problem related to SAT. In particular we present a CUDA-enabled Petrick Function Minimizer. We compare the performance of a pipeline-processor (CPU) and a parallel processor (GPU) implementation of the matrix-multiplication method for solving unate covering problems.
Paul, Eric, Bernd Steinbach, and Marek Perkowski. "Application of CUDA in the Boolean Domain for the Unate Covering Problem." Boolean Problems, Proceedings of the 9th International Workshops on Boolean Problems. 2010.