New trends in algebraic preconditioning

B. Carpentieri
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Abstract

In this chapter, we discuss trends and problems in the design of preconditioned Krylov methods for large-scale problems, particularly when they are formulated with surface integral equations such that dense and large matrices arise. We cover various numerical linear algebra aspects, such as the choice of iterative methods, characteristics and performances of fast integral-equation solvers for the required matrix-vector products, and the design of algebraic preconditioners based on multilevel incomplete LU factorization, sparse approximate inverses, inner-outer methods, and spectral approaches, particularly when they are combined with fast solvers. As shown via examples, the developed numerical linear algebra tools can enable efficient solutions of large electromagnetic problems on moderate number of cores and processors.
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代数预处理的新趋势
在本章中,我们讨论了大规模问题的预条件Krylov方法设计的趋势和问题,特别是当它们用表面积分方程表示时,这样就会出现密集和大矩阵。我们涵盖了各种数值线性代数方面,例如迭代方法的选择,所需矩阵-向量乘积的快速积分方程求解器的特征和性能,以及基于多级不完全LU分解,稀疏近似逆,内外方法和谱方法的代数前置条件的设计,特别是当它们与快速求解器相结合时。通过实例表明,所开发的数值线性代数工具可以在中等数量的内核和处理器上有效地解决大型电磁问题。
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Back Matter New trends in geometric modeling and discretization for integral equations New trends in algebraic preconditioning New trends in uncertainty quantification for large-scale electromagnetic analysis: from tensor product cubature rules to spectral quantic tensor-train approximation New trends in frequency-domain volume integral equations
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