In this paper we present a new data partitioning algorithm
to improve the performance of parallel matrix multiplication of dense
square matrices on heterogeneous clusters. Existing algorithms either use
single speed performance models which are too simplistic or they do not
attempt to minimise the total volume of communication. The Functional
performance model (FPM) is more realistic then single speed models be-
cause it integrates many important features of heterogeneous processors
such as the processor heterogeneity, the heterogeneity of memory struc-
