A one-sided Jacobi hyperbolic singular value decomposition (HSVD) algorithm, using a
massively parallel graphics processing unit (GPU), is developed. The algorithm also serves …

In this paper, we propose a novel preconditioned solver for generalized Hermitian
eigenvalue problems. More specifically, we address the case of a definite matrix pencil A− λ …

The paper studies the global convergence of the block Jacobi me\-thod for symmetric
matrices. Given a symmetric matrix $ A $ of order $ n $, the method generates a sequence of …

The paper describes how to modify the two-sided Hari–Zimmermann algorithm for
computation of the generalized eigenvalues of a matrix pair (A, B), where B is positive …

The paper considers convergence, accuracy and efficiency of a block J-Jacobi method. The
method is a proper BLAS 3 generalization of the known method of Veselić for computing the …

The paper derives and investigates the Jacobi methods for the generalized eigenvalue
problem A x= λ B x, where A is a symmetric and B is a symmetric positive definite matrix. The …

The paper considers the convergence of the complex block Jacobi diagonalization methods
under the large set of the generalized serial pivot strategies. The global convergence of the …

We present a hierarchically blocked one-sided Jacobi algorithm for the singular value
decomposition (SVD), targeting both single and multiple graphics processing units (GPUs) …

We provide sufficient conditions for the general sequential block Jacobi-type method to
converge to the diagonal form for cyclic pivot strategies which are weakly equivalent to the …

The paper describes several efficient parallel implementations of the one-sided hyperbolic
Jacobi-type algorithm for computing eigenvalues and eigenvectors of Hermitian matrices. By …