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Describes a selection of important parallel algorithms for matrix
computations. Reviews the current status and provides an overall
perspective of parallel algorithms for solving problems arising in
the major areas of numerical linear algebra, including (1) direct
solution of dense, structured, or sparse linear systems, (2) dense
or structured least squares computations, (3) dense or structured
eigenvaluen and singular value computations, and (4) rapid elliptic
solvers. The book emphasizes computational primitives whose
efficient execution on parallel and vector computers is essential
to obtain high performance algorithms. Consists of two
comprehensive survey papers on important parallel algorithms for
solving problems arising in the major areas of numerical linear
algebra - direct solution of linear systems, least squares
computations, eigenvalue and singular value computations, and rapid
elliptic solvers, plus an extensive up-to-date bibliography (2,000
items) on related research.
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