The invention discloses an attribute reduction method for an information system based on MPI parallel solving. The attribute reduction method comprises the following steps: firstly, reading the data of the information system, pretreating numerical values, and carrying out data discretization; then, horizontally dividing the information system into p sample data subsets, assigning to n nodes through communication, calculating the equivalence class of the data subsets in parallel, and integrating the result of each node to obtain m equivalence class division information subsystems of the whole information system; then, assigning the m information subsystems to the n nodes, carrying out parallel attribute core computing until all the information subsystems are processed, then merging the results of the nodes to obtain the attribute core of the whole information system; and finally, carrying out parallel solving attribute reduction, and merging the attribute reduction results of the nodes to obtain the attribute reduction of the whole information system. A rough set attribute reduction method is combined with MPI parallel computing, so that parallel solving can be carried out by using differentiation matrix solving attribute reduction calculation, and the algorithmic efficiency is improved.