This paper presents the work carried out by the authors to apply Intel MKL PARDISO (a parallel sparse matrix solver) to the load flow solution algorithms of MATPOWER and OpenDSS. The goal is to explore the potential execution time reduction obtained when working with large power systems and multi-core installations. Test systems of different sizes were solved in order to observe the time reduction as function of the system size and the number of cores used in the parallel execution. Results show that except for the Full Newton-Raphson (NR) algorithm, one should not expect a reduction in execution times when using a parallel routine. The use of a parallel sparse matrix solver is only justified when the sparse matrix must be recalculated at every step of the solution process or the systems under study are much larger than those analyzed here. This paper also presents how a parallel computing solution can be implemented in different applications by using available high-performance parallel libraries.