Hello,

I use LAPACK to find only the largest absolute eigenvalue of matrix? If there is no single largest value, then the one that is equal largest. I only need the largest and I was hoping to save time by not finding the others.

Thanks.

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Hello,

I use LAPACK to find only the largest absolute eigenvalue of matrix? If there is no single largest value, then the one that is equal largest. I only need the largest and I was hoping to save time by not finding the others.

Thanks.

I use LAPACK to find only the largest absolute eigenvalue of matrix? If there is no single largest value, then the one that is equal largest. I only need the largest and I was hoping to save time by not finding the others.

Thanks.

- powerr
**Posts:**2**Joined:**Mon Nov 07, 2011 12:39 am

Hi,

1) For real symmetric (or complex Hermitian) eigenvalue problem, you can use xSYEVX (or xHEEVX) or xSYEVR (or xHEEVR) to compute only a few of the eigenvalues.

(So in particular for the largest one.) The cost of the algorithm will still be O(n^3) but this should be significantly faster than computing the whole spectrum.

2) For real nonsymetric (or complex nonHermitian) eigenvalue problem, LAPACK xGEEV subroutines compute all the eigenvalues.

3) Using software package based on iterative methods will reduce very likely the cost to O(n^2). (See for example ARPACK, BLOPEX, PRIMME.)

1) For real symmetric (or complex Hermitian) eigenvalue problem, you can use xSYEVX (or xHEEVX) or xSYEVR (or xHEEVR) to compute only a few of the eigenvalues.

(So in particular for the largest one.) The cost of the algorithm will still be O(n^3) but this should be significantly faster than computing the whole spectrum.

2) For real nonsymetric (or complex nonHermitian) eigenvalue problem, LAPACK xGEEV subroutines compute all the eigenvalues.

3) Using software package based on iterative methods will reduce very likely the cost to O(n^2). (See for example ARPACK, BLOPEX, PRIMME.)

- admin
- Site Admin
**Posts:**486**Joined:**Wed Dec 08, 2004 7:07 pm

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