This paper describes a domain-based multilevel block ILU preconditioner (BILUTM) for solving general sparse linear systems. This preconditioner combines a high accuracy incomplete LU factorization with an algebraic multilevel recursive reduction. Thus, in the first level the matrix is permuted into a block form using (block) independent set ordering and an ILUT factorization for the reordered matrix is performed. The reduced system is the approximate Schur complement associated with the partitioning, and it is obtained implicitly as a by-product of the partial ILUT factorization with respect to the complement of the independent set. The incomplete factorization process is repeated with the reduced systems recursively. The last reduced system is factored approximately using ILUT again. The successive reduced systems are not stored. This implementation is efficient in controlling the fill-in elements during the multilevel block ILU factorization, especially when large size blocks are used in domain decomposition-type implementations. Numerical experiments are used to show the robustness and efficiency of the proposed technique for solving some difficult problems.
- Incomplete LU factorization
- Krylov subspace methods
- Multielimination ILU factorization
- Multilevel ILU preconditioner