LAPACK95 is a Fortran 95 interface to the Fortran 77 LAPACK library. It is relevant for anyone who writes in the Fortran 95 language and needs reliable software for basic numerical linear algebra. It improves upon the original user-interface to the LAPACK package, taking advantage of the considerable simplifications that Fortran 95 allows. LAPACK95 Users' Guide provides an introduction to the design of the LAPACK95 package, a detailed description of its contents, reference manuals for the leading comments of the routines, and example programs.
LAPACK (Linear Algebra PACKage) 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
LAPACK (Linear Algebra PACKage) 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
Title LAPACK95 Users' Guide
Author(s) Vincent A. Barker, L. Susan Blackford, Jack J. Dongarra, Jeremy Du Croz, Sven Hammarling, Minka Marinova, Jerzy Wasniewski, Plamen Yalamov
Publisher: Society for Industrial and Applied Mathematics; 1st edition (December 13, 2001)
Hardcover 258 pages
Language: English
ISBN-10: 0898715040
ISBN-13: 978-0898715040
eBook: http://www.netlib.org/lapack95/lug95/
Author(s) Vincent A. Barker, L. Susan Blackford, Jack J. Dongarra, Jeremy Du Croz, Sven Hammarling, Minka Marinova, Jerzy Wasniewski, Plamen Yalamov
Publisher: Society for Industrial and Applied Mathematics; 1st edition (December 13, 2001)
Hardcover 258 pages
Language: English
ISBN-10: 0898715040
ISBN-13: 978-0898715040
eBook: http://www.netlib.org/lapack95/lug95/
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