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Numerical Linear Algebra on High-Performance Computers

Numerical Linear Algebra on High-Performance Computers

£48.99

Part of Software, Environments and Tools

  • Date Published: November 1998
  • availability: This item is not supplied by Cambridge University Press in your region. Please contact Soc for Industrial & Applied Mathematics for availability.
  • format: Paperback
  • isbn: 9780898714289

£ 48.99
Paperback

This item is not supplied by Cambridge University Press in your region. Please contact Soc for Industrial & Applied Mathematics for availability.
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About the Authors
  • This book presents a unified treatment of recently developed techniques and current understanding about solving systems of linear equations and large scale eigenvalue problems on high-performance computers. It provides a rapid introduction to the world of vector and parallel processing for these linear algebra applications. Topics include major elements of advanced-architecture computers and their performance, recent algorithmic development, and software for direct solution of dense matrix problems, direct solution of sparse systems of equations, iterative solution of sparse systems of equations, and solution of large sparse eigenvalue problems. This book supercedes the SIAM publication Solving Linear Systems on Vector and Shared Memory Computers, which appeared in 1990. The new book includes a considerable amount of new material in addition to incorporating a substantial revision of existing text.

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    Product details

    • Date Published: November 1998
    • format: Paperback
    • isbn: 9780898714289
    • length: 360 pages
    • dimensions: 255 x 175 x 18 mm
    • weight: 0.6kg
    • availability: This item is not supplied by Cambridge University Press in your region. Please contact Soc for Industrial & Applied Mathematics for availability.
  • Table of Contents

    About the authors
    Preface
    Introduction
    1. High performance computing
    2. Overview of current high-performance computers
    3. Implementation details and overhead
    4. Performance: analysis, modeling, and measurements
    5. Building blocks in linear algebra
    6. Direct solution of sparse linear systems
    7. Krylov subspaces: projection
    8. Iterative methods for linear systems
    9. Preconditioning and parallel preconditioning
    10. Linear Eigenvalue problems Ax=lx
    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.

  • Authors

    Jack J. Dongarra

    Iain S. Duff

    Danny C. Sorensen

    Hank A. van der Vorst

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