LAPACK Users' Guide

C. Bischof, E. Anderson, Z. Bai, S. Blackford, J. Demmel

ISBN 10: 0898714478 / ISBN 13: 9780898714470

Published by Society for Industrial and Applied Mathematics,U.S., US, 1999

About this Item

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.

Seller Inventory # LU-9780898714470

Bibliographic Details

• Title: LAPACK Users' Guide
• Publisher: Society for Industrial and Applied Mathematics,U.S., US
• Publication Date: 1999
• Language: English
• ISBN 10: 0898714478
• ISBN 13: 9780898714470
• Binding: Paperback
• Edition: Third Edition.
• Condition: New
• Dimensions: 20.32W x 2.54H x 27.31D centimeters 20.32 centimeters width by 2.54 centimeters height by 27.31 centimeters depth
• Weight: 296 grams

About this title

Synopsis

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.