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### LOBPCG method for Eigen Value Computation.

Posted: Sun Oct 18, 2015 7:20 am
Hi,

I am new to MAGMA. I want to find the top K(K is a very small number) eigen vectors of a sparse symmetric matrix whose dimension is more than 30000. In addition, the matrix in consideration is positive semi definite. However, I am not able to understand the arguments that needs to be passed to the magma_slobpcg function for the magma_s_solver_par and the magma_s_preconditioner structures. I wanted to know the parameters that I have to set as a minimum requirement. Also, what parameters that i could enable to perform the calculations faster?

Nithish

### Re: LOBPCG method for Eigen Value Computation.

Posted: Sun Oct 18, 2015 9:06 am
Dear Nithish,

for a plain LOBPCG, use ./testing_dsolver --solver 8 --ev k /path/to/the/matrix

If you want to use a preconditioner (faster solver convergence in many cases) type

./testing_dsolver --solver 8 --ev k --precond x /path/to/the/matrix

where x = 1 is Jacobi, x = 2 is ILU.

Let me know whether this helps!

Thanks, Hartwig

### Re: LOBPCG method for Eigen Value Computation.

Posted: Sun Oct 18, 2015 6:59 pm
Hi Hartwig,

Thanks for the reply. I tried the use the solver using the method suggested by you and it helped me to find the eigenvalues correctly. However instead of providing the k-largest eigen values, it provides me with K-smallest ones. Is there a setting for the algorithm which calculates the largest eigen values?

With regards,
Nithish

### Re: LOBPCG method for Eigen Value Computation.

Posted: Mon Oct 19, 2015 1:07 pm
Nithish,
We haven't provided explicitly an option for that but if you compute the eigenvalues for -A, and multiply the result by -1 at the end, you will get the set of the largest eigenvalues for A.
Best regards,
Stan

### Re: LOBPCG method for Eigen Value Computation.

Posted: Fri Oct 23, 2015 8:25 pm
Thanks for the info, Stan