Different engineering models such as physic simulations or information retrieval rely on modelling and solving large-scale sparse eigenvalue problems, such as fluid simulation or document retrieval. SLEPc (http://slepc.upv.es) is a software library for the solution of this kind of algebraic problems on distributed computers. We can use this with Python through slepc4py to provide solutions to these computationally expensive problems, using parallelization with different schemes. In this poster we introduce slepc4py (https://bitbucket.org/slepc/slepc4py), a python wrapper for SLEPc, along with the problem of determining the nuclear reactor’s stability, a problem that is modeled as obtaining the eigenvalues of certain matrices that are large and sparse. We introduce the techniques that are implemented in SLEPc for solving a problem with these characteristics.