  Nowadays, several industrial applications are being ported to parallel
architectures. In fact, these platforms allow acquire more performance for
system modelling and simulation. In the electric machines area, there are many
problems which need speed-up on their solution. This paper examines the
parallelism of sparse matrix solver on the graphics processors. More
specifically, we implement the conjugate gradient technique with input matrix
stored in CSR, and Symmetric CSR and CSC formats. This method is one of the
most efficient iterative methods available for solving the finite-element basis
functions of Maxwell's equations. The GPU (Graphics Processing Unit), which is
used for its implementation, provides mechanisms to parallel the algorithm.
Thus, it increases significantly the computation speed in relation to serial
code on CPU based systems.
