LAPACK Users' Guide
Seiten
1999
|
Third Edition
Society for Industrial & Applied Mathematics,U.S. (Verlag)
978-0-89871-447-0 (ISBN)
Society for Industrial & Applied Mathematics,U.S. (Verlag)
978-0-89871-447-0 (ISBN)
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LAPACK is a library of numerical linear algebra subroutines designed for high performance on workstations, vector computers, and shared memory multiprocessors. Release 3.0 of LAPACK introduces new routines and extends the functionality of existing routines. Each Users' Guide comes with a ""Quick Reference Guide"" card.
LAPACK is a library of numerical linear algebra subroutines designed for high performance on workstations, vector computers, and shared memory multiprocessors. Release 3.0 of LAPACK introduces new routines and extends the functionality of existing routines. The most significant new routines and functions include: a faster singular value decomposition computed by divide-and-conquer; faster routines for solving rank-deficient least squares problems: using QR with column pivoting; using the SVD based on divide-and-conquer; new routines for the generalized symmetric eigenproblem: faster routines based on divide-and-conquer; routines based on bisection/inverse iteration, for computing part of the spectrum; faster routine for the symmetric eigen problem using “relatively robust eigenvector algorithm”; new simple and expert drivers for the generalized nonsymmetric eigenproblem, including error bounds; solver for generalized Sylvester equation, used in computational routines
Each Users' Guide comes with a "Quick Reference Guide" card.
LAPACK is a library of numerical linear algebra subroutines designed for high performance on workstations, vector computers, and shared memory multiprocessors. Release 3.0 of LAPACK introduces new routines and extends the functionality of existing routines. The most significant new routines and functions include: a faster singular value decomposition computed by divide-and-conquer; faster routines for solving rank-deficient least squares problems: using QR with column pivoting; using the SVD based on divide-and-conquer; new routines for the generalized symmetric eigenproblem: faster routines based on divide-and-conquer; routines based on bisection/inverse iteration, for computing part of the spectrum; faster routine for the symmetric eigen problem using “relatively robust eigenvector algorithm”; new simple and expert drivers for the generalized nonsymmetric eigenproblem, including error bounds; solver for generalized Sylvester equation, used in computational routines
Each Users' Guide comes with a "Quick Reference Guide" card.
Preface to the Third Edition
Preface to the Second Edition
Part 1: Guide. Chapter 1: Essentials
Chapter 2: Contents of LAPACK
Chapter 3: Performance of LAPACK
Chapter 4: Accuracy and Stability
Chapter 5: Documentation and Software Conventions
Chapter 6: Installing LAPACK Routines
Chapter 7: Troubleshooting
Appendix A: Index of Driver and Computational Routines
Appendix B: Index of Auxiliary Routines
Appendix C: Quick Reference Guide to the BLAS
Appendix D: Converting from LINPACK or EISPACK
Appendix E: LAPACK Working Notes
Part 2: Specifications of Routines. Bibliography
Index by Keyword
Index by Routine Name.
| Erscheint lt. Verlag | 30.11.1999 |
|---|---|
| Reihe/Serie | Software Environments and Tools |
| Verlagsort | New York |
| Sprache | englisch |
| Maße | 151 x 228 mm |
| Gewicht | 995 g |
| Themenwelt | Mathematik / Informatik ► Mathematik ► Algebra |
| Mathematik / Informatik ► Mathematik ► Computerprogramme / Computeralgebra | |
| ISBN-10 | 0-89871-447-8 / 0898714478 |
| ISBN-13 | 978-0-89871-447-0 / 9780898714470 |
| Zustand | Neuware |
| Informationen gemäß Produktsicherheitsverordnung (GPSR) | |
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