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An Efficient ILU Preconditioning for Highly Sparse Matrices Constructed using the FDFD Method

机译:使用FDFD方法构造的高稀疏矩阵的高效ILU预处理

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摘要

Finding a good preconditioner to solve a given sparse linear system is often considered a difficult but important task. One of the simplest ways of defining a preconditioner is to perform an incomplete LU decomposition (ILU) of the original matrix. The ILU factorization is considered to be an easy and inexpensive preconditioner to use. However, it fails to provide a solution of a sparse linear system generated from general three-dimensional problems with three unknowns. In this paper, a modified ILU preconditioner is proposed to provide an efficient preconditioner for highly sparse matrices, especially for matrices constructed using the finite-difference frequency-domain (FDFD) method for three-dimensional applications. It has been proven that the proposed ILU preconditioner provides a valid solution when the classical ILU preconditioner fails. The efficiency of the proposed ILU preconditioner is also demonstrated by the small memory requirements relative to traditional ILU preconditioners.
机译:寻找一个好的预处理器来解决一个给定的稀疏线性系统通常被认为是困难而重要的任务。定义前置条件的最简单方法之一是对原始矩阵执行不完整的LU分解(ILU)。 ILU分解被认为是一种易于使用且便宜的预处理器。但是,它不能提供由三个未知数的一般三维问题生成的稀疏线性系统的解决方案。本文提出了一种改进的ILU预调节器,为高稀疏矩阵提供了一种有效的预调节器,尤其是对于使用有限差分频域(FDFD)方法构建的三维应用矩阵。已经证明,当经典的ILU预处理器失败时,提出的ILU预处理器提供了有效的解决方案。相对于传统ILU预调节器,较小的内存需求也证明了所提出的ILU预调节器的效率。

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