Inconsistency finding Eigenvalues for sparse matrices with MKL

Hi,

I am trying to calculate the smallest real eigenvalues of a general problem A*V = B*V*D with sparse matrices using MKL and I have been having four problems when comparing to MATLAB:

1. I am always missing at least one of the smallest eigenvalues in MKL in comparison to MATLAB.

For example

2. Using the same matrix most of the eigenvalues I do get are almost Identical between MATLAB and MKL, but which of the eigenvalues I am missing is somewhat random.

Same System, different results

3. The smallest eigenvalue tend to be a several orders of magnitudes different between MATLAB and MKL (in some unfrequent cases not only the first)

MATLAB both Graphs: -0.000200            

MKL first graph:          380057.918617          

MKL second graph:     364053.320270

4. For some sparse matrices describing a very similar system with similar sparcity but different non-zero values I get no eigenvalues on MKL but several hundreds on MATLAB

I attached all data needed to reproduce my results in two Zips docs

Could somebody help me understand what I might be doing wrong or what alternative could I use to solve the problem

Thanks a lot

Andrés Delgado