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...
LAPACK is a library of numerical linear algebra subroutines designed for high performance on workstations, vector computers, and shared memory multipr...
Organizes the many available methods for the numerical solution of eigenvalue problems. The first of the eleven chapters provide the top level of a decision tree for classifying eigenvalue problems, and summarize the mathematical principals of projection o
Organizes the many available methods for the numerical solution of eigenvalue problems. The first of the eleven chapters provide the top level of a de...
