Adapted parallel quine-McCluskey algorithm using GPGPU

This paper deals with parallelization of the Quine-McCluskey algorithm. This algorithm is a method used for minimization of boolean functions. The algorithm has a limitation when dealing with more than four variables. The problem computed by this algorithm is NP-hard and run-time of the algorithm grows exponentially with the number of variables. It is possible to adapt the Quine-McCluskey algorithm for running on a parallel computing system. The graphics processing units (GPUs) brings acceleration of computing process. This solution differs from the previous solution in the use of bit fields. Parallelization of the algorithm is implemented through Compute Unified Device Architecture (CUDA).