SVD runs very slow and sometimes doesn't return for matrices which cannot converge

Hi Guys

I have been struggling with the MKL SVD computation recently. So I really appreciate if anyone can help out.

Basically I am using MKL SVD to calculate the first two eigenvectors for a matrix. I use the LAPACK_dgesvd method in the MKL to do the job. It runs fairly fast for matrix which can converge. But for those who can't converge, MKL SVD runs extremely slow and sometimes it never return. I am not sure what is going on behind the scene. Maybe MKL just tries exhaustively when the matrix can't converge?

My questions is:

1. If there is any method which can just compute two eigenvectors rather than all of them?

2. if there is a way to set the max iteration for SVD computation or timeout when matrix cannot converge.

thank you very much in advance.