An Efficient Algorithm for Parallel Computation of Rough Entropy Using CUDA

Continuously improving computation efficiency of rough entropy is very meaningful, because it is helpful to apply rough sets to some fields with high performance requirement. Recently, Graphics Processing Unit (GPU) has gained a lot of attention from scientific communities for its applicability in high performance computing. This paper proposes an efficient algorithm which is based on sorting technique to accelerate the computation of rough entropy using CUDA. The proposed algorithm is compared with a sorting-based serial algorithm. Experimental results prove the effectiveness of the proposed algorithm.