DAS-ILU: A Distributed Asynchronous Parallel ILU Factorization Based on Domain Decomposition

This paper presents DAS-ILU, a Distributed Asynchronous parallel Incomplete LU factorization method based on domain decomposition. DAS-ILU partitions the computational domain into independently processed interior nodes and asynchronously updated separator nodes, thereby reducing cross-processor dependencies and halving the separator size compared to conventional methods. To further improve performance, it employs optimized data exchange patterns to minimize communication overhead and extends support to block-structured sparse matrices via exact block inversions. Comprehensive evaluations on a range of problem types—including structural mechanics, computational fluid dynamics, and reservoir simulation demonstrate the superior performance of DAS-ILU. Compared to state-of-the-art ILU implementations, DAS-ILU achieves solve time speedups of up to 2.07 × over Chow-Patel’s fine-grained parallel ILU and up to 4.11 × over HYPRE’s ILU. Moreover, DAS-ILU exhibits strong robustness when applied to challenging nonsymmetric and indefinite systems.