Following the initial release of LAPACK and the emerging importance of distributed memory
computing, work began on adapting LAPACK to distributed-memory architectures. Since …

The FEniCS Project set out in 2003 with an idea to automate the solution of mathematical
models based on differential equations. Initially, the FEniCS Project consisted of two …

Eigenvalue problems are ubiquitous in engineering and science. This book presents a
unified theoretical development of the two most important classes of algorithms for solving …

This paper presents a small-bulge multishift variation of the multishift QR algorithm that
avoids the phenomenon of shift blurring, which retards convergence and limits the number …

The calculation of eigenvalues of a matrix is required by many algorithms. Specifically, it is
the key technique in subspace-based direction of arrival (DOA) estimation algorithms, eg …

Model reduction is an area of fundamental importance in many modeling and control
applications. In this paper we analyze the use of parallel computing in model reduction …

Fifty years after the invention of the QR algorithm by John Francis and Vera Kublanovskaya
we reconstruct the ideas and the influences that led to its genesis from the originators' own …

The BR algorithm is a novel and efficient method to find all eigenvalues of upper
Hessenberg matrices and has never been applied to eigenanalysis for power system small …

Many eigenvalue problems are most naturally viewed as product eigenvalue problems. The
eigenvalues of a matrix A are wanted, but A is not given explicitly. Instead it is presented as …

In this thesis, we have investigated numerical methods for the solution of general and
structured eigenvalue problems. Moreover, we have presented software implementing these …