The solution of the large, nonsymmetric, sparse linear system resulting from the discretization of the Boltzmann transport equation can be computationally intensive, even when innovative coarse mesh finite difference (CMFD) acceleration methods are applied on a high-performance computer. The research reported here describes the development and implementation of an innovative hybrid Reduced Symmetric Successive Over-Relaxation (RSOR) and Incomplete Lower Upper (ILU) (RSILU) preconditioner for the preconditioned Generalized Minimal RESidual (GMRES) solution of the three-dimensional, whole-core, pin-resolved transport calculation of a nuclear reactor core. The preconditioner was designed specifically to improve parallel computing capability and minimize the computational burden for solution of the CMFD method on a high-end computing platform. The hybrid RSILU preconditioner is applied to the preconditioned GMRES method without multicolor reordering by utilizing the ILU preconditioner for internal elements on each processor and the RSOR preconditioner for boundary elements that would require interprocessor communication. The construction of the RSILU preconditioner requires only that the diagonal elements be modified, factorized, and stored, which is identical to serial ILU. The computational cost of RSILU is minimized since the factorized diagonal block requires minimal data preparation time for interprocessor communication and exchanges information only once in parallel computation. This paper reports first the serial performance of RSOR, and numerical results show that the new proposed RSOR is an effective preconditioner even for serial computing applications. The parallel performance of RSILU is then assessed and compared to conventional multicolor ILU preconditioners. The results show that RSILU provides comparable convergence rates to the Standard Incomplete Lower Upper (SILU) preconditioners, but it is easier to implement since it does not require multicolor ordering. Although the required iterations of RSILU preconditioned GMRES increase as the number of processors increases, only slightly more iterations are required than the SILU preconditioner for a practical nuclear reactor application. The number of iterations required by the RSILU preconditioner increases only slightly and significantly less than the increased number of iterations required when using conventional Block-Jacobi Incomplete Lower Upper or Symmetric Successive Over-Relaxation preconditioners. Overall, the RSILU is shown to be an efficient and practical preconditioner for the GMRES method for improving the parallel computing performance for large-scale applications.