The linear system solver plays a key role in scientific computing. This paper evaluates the performances of PETSc (Portable, Extensible Toolkit for Scientific Computation) and HIPS (Portable, Extensible Toolkit for Scientific Computation) solving a singular matrix arising from a bucking problem from UF matrix collection. We employ preconditioned (Level-based ILU) iterative methods (GMRES) for PETSc while HIPS adopts the Schur complement method, named iterative or hybrid mode. Moreover, HIPS proposed HID (Hierarchical interface decomposition) to improve the parallel efficiency. We hope to transfer these results into industrial applications.