Which MKL routines to use to efficiently diagonalize large, sparse, and hermitian/symmetric matrices?

I am trying to diagonalize a large sparse and hermitian matrix, but I can probably afford to make it real symmetric. This matrix is large, it can be 10^6 x 10^6. But I am only interested in a few of its lowest eigenvalues, probably just around 50 of them. I heard that several ways to do this is to use Lanczos or conjugate-gradient method. Are there routines in MKL I can use to employ one or both of the aforementioned methods?