Abstract
This paper introduces a novel parallel matrices multiplication algorithm (SMPMM) implies dividing the problem of matrices multiplication into smaller independent tasks where each processor in the parallel environment executes one single task a time, once done, the processor receives another task to process it. As opposed to previous algorithms, like Cannon, Fox, PUMMA, SUMMA, DIMMA and HSUMMA algorithms, where the decomposition is carried out on the data, i.e. the multiplied matrices are decomposed into small blocks, where each processor multiplies some blocks and sends the result to neighbor processors; SMPMM does include any data decomposing. In addition, SMPMM contradicts with previous algorithms where there is no data exchange and no communication among processors on in the parallel environment. One more important advantage is SMPMM multiplies non-square matrices in parallel, which is not available by any previous parallel matrices multiplication algorithms.