Efficient execution of scientific computation on geographically distributed clusters

To achieve data intensive computation, the joining of geographically distributed heterogeneous clusters of workstations through the Internet call be an inexpensive approach. To obtain effective collaboration in such a collection of clusters, overcoming processors and networks heterogeneity, a system architecture was defined. This architecture and a model able to predict application performance and to help its design is described. The matrix multiplication algorithm is used as a benchmark and experiments are conducted over two geographically distributed heterogeneous clusters, one in Brazil and the other in Spain. The model obtained over 90% prediction accuracy in the experiments.