Multiple core processors are present on most of the modern computers. For getting greatest benefits of computational power from the core architecture on existing algorithms, we need an advanced design and software. We assert the parallelization of the rough k-means clustering algorithm. In k-means algorithm for clustering by rough set, every cluster is to be formed regarding with the two approximations, lower and upper approximation. For making rough kmeans clustering be fine parallelized, we employ parallel mechanism on rough K-means. Therefore, the implementation can be eminently parallel and fault and defect tolerant. The experimental results flaunt bountiful speeduprate of asserted parallel rough k-means clustering method as compared to basic rough k-means algorithm methodology. © 2016, International Journal of Pharmacy and Technology. All rights reserved.