A Jacobi-based algorithm for computing symmetric eigenvalues and eigenvectors in a two-dimensional mesh

The paper proposes an algorithm for computing symmetric eigenvalues and eigenvectors that uses a one-sided Jacobi approach and is targeted to a multicomputer in which nodes can be arranged as a two-dimensional mesh with an arbitrary number of rows and columns. The algorithm is analysed through simple analytical models of execution time, which show that an adequate choice of the mesh configuration (number of rows and columns) can improve performance significantly, with respect to a one-dimensional configuration, which is the most frequently considered scenario in current proposals. This improvement is especially noticeable in large systems.