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Parallel two level block ILU preconditioning techniques for solving large sparse linear systems

机译:并行两级块ILU预处理技术,用于求解大型稀疏线性系统

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We discuss issues related to domain decomposition and multilevel preconditioning techniques which are often employed for solving large sparse linear systems in parallel computations. We implement a parallel preconditioner for solving general sparse linear systems based on a two level block ILU factorization strategy. We give some new data structures and strategies to construct a local coefficient matrix and a local Schur complement matrix on each processor. The preconditioner constructed is fast and robust for solving certain large sparse matrices. Numerical experiments show that our domain based two level block ILU preconditioned are more robust and more efficient than some published ILU preconditioners based on Schur complement techniques for parallel sparse matrix solutions.
机译:我们讨论与域分解和多级预处理技术有关的问题,这些问题通常用于解决并行计算中的大型稀疏线性系统。我们基于两级块ILU分解策略实现了并行预处理器,用于求解一般的稀疏线性系统。我们给出了一些新的数据结构和策略,以便在每个处理器上构造局部系数矩阵和局部Schur补码矩阵。构造的预处理器快速而健壮,可以解决某些大型稀疏矩阵。数值实验表明,我们的基于域的两级块ILU预处理比基于Schur互补技术的已发布ILU预处理器对并行稀疏矩阵解决方案的鲁棒性和效率更高。

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