The discernibility matrix is one of the most important approaches to computing positive region, reduct, core and value reduct in rough sets. The subject of this paper is to develop a parallel approach of it, called “tree expression”. Its computational complexity for positive region and reduct is O(m ² × n) instead of O(m × n ²) in discernibility-matrix-based approach, and is not over O(n ²) for other concepts in rough sets, where m and n are the numbers of attributes and objects respectively in a given dataset (also called an “information system” in rough sets). This approach suits information systems with n ≫ m and containing over one million objects.