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DAS-ILU: A Distributed Asynchronous Parallel ILU Factorization Based on Domain Decomposition
DescriptionThis 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 $2.07\times$ over Chow-Patel's fine-grained parallel ILU and up to $4.11\times$ over HYPRE's ILU. Moreover, DAS-ILU exhibits strong robustness when applied to challenging non-symmetric and indefinite systems.