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9780898714289 Academic Inspection Copy

Numerical Linear Algebra for High-Performance Computers

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This updated version of "Solving Linear Systems on Vector and Shared Memory Computers" (SIAM, 1990) discusses major elements of the new advanced-architecture computers and recent developments in the solution of systems of linear equations and eigenvalue algorithms for dense and sparse matrices that are designed to exploit these elements. It updates material on high-performance computers from the previous book, expands on sparse direct and iterative methods for systems of equations, and covers large sparse eigenvalue problems.
About the Authors Preface Introduction Chapter 1: High Performance Computing Chapter 2: Overview of Current High-Performance Computers Chapter 3: Implementation Details and Overhead Chapter 4: Performance: Analysis, Modeling, and Measurements Chapter 5: Building Blocks in Linear Algebra Chapter 6: Direct Solution of Sparse Linear Systems Chapter 7: Krylov Subspaces: Projection Chapter 8: Iterative Methods for Linear Systems Chapter 9: Preconditioning and Parallel Preconditioning Chapter 10: Linear Eigenvalue Problems Ax=?x Chapter 11: The Generalized Eigenproblem Appendix A: Acquiring Mathematical Software Appendix B: Glossary Appendix C: Level 1, 2, and 3 BLAS Quick Reference Appendix D: Operation Counts for Various BLAS and Decompositions Bibliography Index.
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