Hardware architectures for eigenvalue computation of real symmetric matrices

Computation of eigenvalues is essential in many applications in the fields of science and engineering. When the application of interest requires the computation of eigenvalues of high throughput or real-time performance, a hardware implementation of an eigenvalue computation block is often employed. The problem of eigenvalue computation of real symmetric matrices is focused upon. For the general case of a symmetric matrix eigenvalue problem, the approximate Jacobi method is proposed, where for the special case of a 3times3 symmetric matrix, an algebraic-based method is introduced. The proposed methods are compared with various other approaches reported in the literature. Results obtained by mapping the above architectures on a field programmable gate array device illustrate the advantages of the proposed methods over the existing ones.