Recently iterative algorithms based on the optimization of the Rayleigh quotient have been developed, and CG scheme for the optimization of the Rayleigh quotient has been proven a very attractive and promising technique for large sparse eigenproblems for interior eigenvalues. A x = \delta B x (1) The given matrices A, and B are assumed to be large and sparse, and symmetric and B is further assumed to be positive definite. Also, the method is very amenable to parallel computations. A proper choice of the preconditioner significantly improves the convergence of the CG scheme. We compare the parallel preconditioners for the computation of the interior eigenvalues of a symmetric matrix by CG-type method. The considered preconditioners are ILU(0) in the natural order, ILU(0) in the multi-coloring order, and Multi-Color Block SSOR(Symmetric Succesive OverRelaxation). Our results were implemented on the CRAY-T3E with 128 nodes, assuming B = I. The MPI (Message Passing Interface) library was adopted for the interprocessor communications. The test matrices are up to 512x512 in dimensions and were created from the discretizations of the elliptic PDE. All things considered the MC-BSSOR seems to be most robust preconditioner.