We propose a distributed-memory parallel algorithm for computing some of the algebraically
smallest eigenvalues (and corresponding eigenvectors) of a large, sparse, real symmetric …

This paper proposes a parallel domain decomposition Rayleigh--Ritz projection scheme to
compute a selected number of eigenvalues (and, optionally, associated eigenvectors) of …

We consider automatic performance tuning of dense symmetric eigenvalue problems using
ATMathCoreLib, which is a library to assist automatic tuning. We deal with two problems …

Complex moment-based eigensolvers have been well studied for solving interior eigenvalue
problems because of their high parallel efficiency. Recently, as a time-efficient complex …

An a posteriori verification method is proposed for the generalized real-symmetric
eigenvalue problem and is applied to densely clustered eigenvalue problems in large-scale …

We propose a verified computation method for eigenvalues in a region and the
corresponding eigenvectors of generalized Hermitian eigenvalue problems. The proposed …

We propose a verified computation method for partial eigenvalues of a Hermitian
generalized eigenproblem. The block Sakurai–Sugiura Hankel method, a contour integral …

A performance prediction method for massively parallel computation is proposed. The
method is based on performance modeling and Bayesian inference to predict elapsed time …

abstract We propose a verified computation method for eigenvalues in a region and the
corresponding eigenvectors of generalized Hermitian eigenvalue problems. The proposed …

Large sparse matrices arise in many applications in science and engineering, where the
solution of a linear system or an eigenvalue problem is needed. While direct methods are …