Structure of the preconditioned system in various preconditioned conjugate gradient squared algorithms

DOI10.1016/j.rinam.2019.100008zbMath1452.65061arXiv1603.00176OpenAlexW3100257776MaRDI QIDQ2211057

Shoji Itoh, Masaaki Sugihara

Publication date: 10 November 2020

Published in: Results in Applied Mathematics (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/1603.00176

zbMATH Keywords

preconditioned conjugate gradient squared methodpreconditioned Krylov subspace methodcongruence of preconditioning conversion

Mathematics Subject Classification ID

Iterative numerical methods for linear systems (65F10) Preconditioners for iterative methods (65F08)

Related Items (2)

Changing over stopping criterion for stable solving nonsymmetric linear equations by preconditioned conjugate gradient squared method ⋮ Improvement of preconditioned bi-Lanczos-type algorithms with residual norm minimization for the stable solution of systems of linear equations

Uses Software

• SparseMatrix
• Lis

Cites Work

• The university of Florida sparse matrix collection
• CGS, A Fast Lanczos-Type Solver for Nonsymmetric Linear systems
• Bi-CGSTAB: A Fast and Smoothly Converging Variant of Bi-CG for the Solution of Nonsymmetric Linear Systems
• GPBi-CG: Generalized Product-type Methods Based on Bi-CG for Solving Nonsymmetric Linear Systems
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