9780898714470-0898714478-LAPACK Users' Guide (Software, Environments and Tools, Series Number 9)

LAPACK Users' Guide (Software, Environments and Tools, Series Number 9)

ISBN-13: 9780898714470
ISBN-10: 0898714478
Edition: 3
Author: E. Anderson, Z. Bai, C. Bischof, S. Blackford, J. Demmel, J. Dongarra, J. Du Croz, A. Greenbaum, S. Hammarling, A. McKenney, D. Sorensen
Publication date: 1987
Publisher: Society for Industrial and Applied Mathematics
Format: Paperback 429 pages
Category: Software
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Book details

ISBN-13: 9780898714470
ISBN-10: 0898714478
Edition: 3
Author: E. Anderson, Z. Bai, C. Bischof, S. Blackford, J. Demmel, J. Dongarra, J. Du Croz, A. Greenbaum, S. Hammarling, A. McKenney, D. Sorensen
Publication date: 1987
Publisher: Society for Industrial and Applied Mathematics
Format: Paperback 429 pages
Category: Software

Summary

LAPACK Users' Guide (Software, Environments and Tools, Series Number 9) (ISBN-13: 9780898714470 and ISBN-10: 0898714478), written by authors E. Anderson, Z. Bai, C. Bischof, S. Blackford, J. Demmel, J. Dongarra, J. Du Croz, A. Greenbaum, S. Hammarling, A. McKenney, D. Sorensen, was published by Society for Industrial and Applied Mathematics in 1987. With an overall rating of 4.2 stars, it's a notable title among other Software books. You can easily purchase or rent LAPACK Users' Guide (Software, Environments and Tools, Series Number 9) (Paperback) from BooksRun, along with many other new and used Software books and textbooks. And, if you're looking to sell your copy, our current buyback offer is $0.3.

Description

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: 1. a faster singular value decomposition computed by divide-and-conquer 2. faster routines for solving rank-deficient least squares problems: Using QR with column pivoting using the SVD based on divide-and-conquer 3. 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 4. faster routine for the symmetric eigenproblem using "relatively robust eigenvector algorithm" 5. new simple and expert drivers for the generalized nonsymmetric eigenproblem, including error bounds 6. solver for generalized Sylvester equation, used in 5 7.computational routines used in 5 Each Users' Guide comes with a 'Quick Reference Guide' card.

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