High Performance Algorithms for Structured Matrix Problems (Advances in the Theory of Computation and Computational Math)

The main aim of this volume is to summarize the state of the art in the area of high performance solutions of structured linear systems as well as the area of structured eigenvalue and singular-value problems. The volume highlights research directions perceived to be the most important for computing the structured problems. The topics covered range from parallel solvers for sparse or banded linear systems to parallel computation of eigenvalues and singular values of tridiagonal and bidiagonal matrices. In addition, the volume contains articles on specialized solution techniques for dense Toeplitz and Hankel matrices. The papers also discuss implementation issues on numerous parallel architectures such as vector computers, shared and distributed memory multiprocessors, and clusters of workstations.