Sparse equation systems in heterogeneous clusters of computers

This paper presents a parallelization strategy in heterogeneous clusters of the Gauss-Seidel's method applied for the solution of sparse equation systems. From the point of view of the numerical solution for matrices of coefficients with low density of non null-elements, the standard lines of thought are followed, that is, only non-null elements are stored and iterative solution-search methods are used. Two basic guidelines are defined for the parallel algorithm: one-dimensional data distribution and broadcast messages for all data communications. One-dimensional data distribution eases the processing workload balance on heterogeneous clusters. The use of broadcast messages for every data communication is directly oriented to optimize performance on the the most common cluster interconnection: Ethernet. Experimental results obtained in a local network of heterogeneous computers are presented.