Contents

Generalized Symmetric Definite Eigenvalue Problems: LAPACK Driver Routines

This
topic
describes LAPACK driver routines used for solving generalized symmetric definite eigenproblems. See also computational routines that can be called to solve these problems. Table
"Driver Routines for Solving Generalized Symmetric Definite Eigenproblems"
lists all such driver routines.
Driver Routines for Solving Generalized Symmetric Definite Eigenproblems
Routine Name
Operation performed
Computes all eigenvalues and, optionally, eigenvectors of a real / complex generalized symmetric /Hermitian positive-definite eigenproblem.
Computes all eigenvalues and, optionally, eigenvectors of a real / complex generalized symmetric /Hermitian positive-definite eigenproblem. If eigenvectors are desired, it uses a divide and conquer method.
Computes selected eigenvalues and, optionally, eigenvectors of a real / complex generalized symmetric /Hermitian positive-definite eigenproblem.
Computes all eigenvalues and, optionally, eigenvectors of a real / complex generalized symmetric /Hermitian positive-definite eigenproblem with matrices in packed storage.
Computes all eigenvalues and, optionally, eigenvectors of a real / complex generalized symmetric /Hermitian positive-definite eigenproblem with matrices in packed storage. If eigenvectors are desired, it uses a divide and conquer method.
Computes selected eigenvalues and, optionally, eigenvectors of a real / complex generalized symmetric /Hermitian positive-definite eigenproblem with matrices in packed storage.
Computes all eigenvalues and, optionally, eigenvectors of a real / complex generalized symmetric /Hermitian positive-definite eigenproblem with banded matrices.
Computes all eigenvalues and, optionally, eigenvectors of a real / complex generalized symmetric /Hermitian positive-definite eigenproblem with banded matrices. If eigenvectors are desired, it uses a divide and conquer method.
Computes selected eigenvalues and, optionally, eigenvectors of a real / complex generalized symmetric /Hermitian positive-definite eigenproblem with banded matrices.
1

Product and Performance Information

1

Intel's compilers may or may not optimize to the same degree for non-Intel microprocessors for optimizations that are not unique to Intel microprocessors. These optimizations include SSE2, SSE3, and SSSE3 instruction sets and other optimizations. Intel does not guarantee the availability, functionality, or effectiveness of any optimization on microprocessors not manufactured by Intel. Microprocessor-dependent optimizations in this product are intended for use with Intel microprocessors. Certain optimizations not specific to Intel microarchitecture are reserverd for Intel microprocessors. Please refer to the applicable product User and Reference Guides for more information regarding the specific instruction sets covered by this notice.

Notice revision #20110804