A concurrent object-oriented approach to the Eigenproblem treatment in shared memory multicore environments

Abstract

This work presents an object-oriented approach to the concurrent computation of eigenvalues and eigenvectors in real symmetric and Hermitian matrices on present memory shared multicore systems. This can be considered the lower level step in a general framework for dealing with large size eigenproblems, where the matrices are factorized to a small enough size. The results show that the proposed parallelization achieves a good speedup in actual systems with up to four cores. Also, it is observed that the limiting performance factor is the number of threads rather than the size of the matrix. We also find that a reasonable upper limit for a "small" dense matrix to be treated in actual processors is in the interval 10000-30000. © 2011 Springer-Verlag.