Assessing the Performance of Mixed-Precision ILU(0)-Preconditioned Multiple-Precision Real and Complex Krylov Subspace Methods
Numerical Analysis
2025-07-10 v1 Numerical Analysis
Abstract
Krylov subspace methods are linear solvers based on matrix-vector multiplications and vector operations. While easily parallelizable, they are sensitive to rounding errors and may experience convergence issues. ILU(0), an incomplete LU factorization with zero fill-in, is a well-known preconditioning technique that enhances convergence for sparse matrices. In this paper, we implement a double-precision and multiple-precision ILU(0) preconditioner, compatible with product-type Krylov subspace methods, and evaluate its performance.
Keywords
Cite
@article{arxiv.2504.14498,
title = {Assessing the Performance of Mixed-Precision ILU(0)-Preconditioned Multiple-Precision Real and Complex Krylov Subspace Methods},
author = {Tomonori Kouya},
journal= {arXiv preprint arXiv:2504.14498},
year = {2025}
}