PERFORMANCE COMPARISON OF ROW PER SLAVE AND ROWS SET PER SLAVE METHOD IN PVM BASED PARALLEL MATRIX MULTIPLICATION

Sampath S, Nanjesh B R, Bharat Bhushan Sagar, C K Subbaraya

Abstract: Parallel computing operates on the principle that large problems can often be divided into smaller ones, which are then solved concurrently to save time by taking advantage of non-local resources and overcoming memory constraints. Multiplication of larger matrices requires a lot of computation time. This paper deals with the two methods for handling Parallel Matrix Multiplication. First is, dividing the rows of one of the input matrices into set of rows based on the number of slaves and assigning one rows set for each slave for computation. Second method is, assigning one row of one of the input matrices at a time for each slave starting from first row to first slave and second row to second slave and so on and loop backs to the first slave when last slave assignment is finished and repeated until all rows are finished assigning. These two methods are implemented using Parallel Virtual Machine and the computation is performed for different sizes of matrices over the different number of nodes. The results show that the row per slave method gives the optimal computation time in PVM based parallel matrix multiplication

Keywords: Parallel Execution, Cluster Computing, MPI (Message Passing Interface), PVM (Parallel Virtual Machine) RAM (Random Access Memory).

DOI: https://doi.org/10.15623/ijret.2013.0212043