Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
4640029 | Journal of Computational and Applied Mathematics | 2010 | 10 Pages |
Abstract
The shift-and-invert method is very efficient in eigenvalue computations, in particular when interior eigenvalues are sought. This method involves solving linear systems of the form (A−σI)z=b(A−σI)z=b. The shift σσ is variable, hence when a direct method is used to solve the linear system, the LU factorization of (A−σI)(A−σI) needs to be computed for every shift change. We present two strategies that reduce the number of floating point operations performed in the LU factorization when the shift changes. Both methods perform first a preprocessing step that aims at eliminating parts of the matrix that are not affected by the diagonal change. This leads to about 43% and 50% flops savings respectively for the dense matrices.
Related Topics
Physical Sciences and Engineering
Mathematics
Applied Mathematics
Authors
Laura Grigori, Desire Nuentsa Wakam, Hua Xiang,