A class of parallel decomposition-type relaxation methods for large sparse systems of linear equations
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Publication:1809086
DOI10.1016/S0024-3795(98)10093-9zbMath0939.65045OpenAlexW2063717873MaRDI QIDQ1809086
Publication date: 10 July 2000
Published in: Linear Algebra and its Applications (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1016/s0024-3795(98)10093-9
convergenceparallel computationsuccessive overrelaxationlarge sparse systemsaccelerated overrelaxationdecomposition-type relaxation methods
Computational methods for sparse matrices (65F50) Iterative numerical methods for linear systems (65F10) Parallel numerical computation (65Y05)
Related Items (9)
Max norm estimation for the inverse of block matrices ⋮ Some convergence conditions for a class of parallel decomposition-type linear relaxation methods ⋮ New subclasses of block \(H\)-matrices with applications to parallel decomposition-type relaxation methods ⋮ The block preconditioned \textit{LSQR} and \textit{GL}-\textit{LSQR} algorithms for the block partitioned matrices ⋮ Fast Solvers for Systems of Linear Equations with Block-Band Matrices ⋮ Some results on preconditioned mixed-type splitting iterative method ⋮ An inexact parallel splitting augmented Lagrangian method for large system of linear equations ⋮ Some properties of the block matrices in the parallel decomposition-type relaxation methods ⋮ Convergence properties of preconditioned Hermitian and skew-Hermitian splitting methods for non-Hermitian positive semidefinite matrices
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