The master–slave paradigm on heterogeneous systems: A dynamic programming approach for the optimal mapping

We study the master–slave paradigm over heterogeneous systems. According to an analytical model, we develop a dynamic programming algorithm that allows to solve the optimal mapping for such paradigm. Our proposal considers heterogeneity due both to computation and also to communication. The optimization strategy used allows to obtain the set of processors for an optimal computation. The computational results show that considering heterogeneity also on the communication increases the performance of the parallel algorithm.