A New Efficient Parallelization Strategy for the QR Algorithm

Abstract The efficient solution of the matrix eigenvalue problem is of great importance for quantum mechanical calculations. For the determination of all eigenvalues and all eigenvectors of a non-sparse matrix, we have investigated the widely-used QR algorithm. In this paper we present a new efficient parallelization for loosely-coupled multiprocessing systems, based upon cyclic reductions.