Problems of parallel solution of large systems of linear algebraic equations

DOI10.1007/s10958-016-2945-4zbMath1347.65064OpenAlexW2467772279MaRDI QIDQ308680

V. P. Il'in

Publication date: 6 September 2016

Published in: Journal of Mathematical Sciences (New York) (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/s10958-016-2945-4

zbMATH Keywords

convergenceiterationpreconditioningsparse matricesparallel algorithmsKrylov subspace methodalgebraic domain decompositionmultiprocessor computer system

Mathematics Subject Classification ID

Multigrid methods; domain decomposition for boundary value problems involving PDEs (65N55) Iterative numerical methods for linear systems (65F10) Parallel numerical computation (65Y05) Numerical algorithms for specific classes of architectures (65Y10) Preconditioners for iterative methods (65F08)

Related Items (1)

Iterative preconditioned methods in Krylov spaces: trends of the 21st century

Uses Software

• Algorithm 913
• KRYLOV

Cites Work

• Rational Krylov sequence methods for eigenvalue computation
• Parallel approaches and technologies of domain decomposition methods
• Eigenvalue bounds and inequalities using vector aggregation of matrices
• Semi-conjugate direction methods for real positive definite systems
• Robust domain decomposition preconditioners for abstract symmetric positive definite bilinear forms
• The Optimized Schwarz Method with a Coarse Grid Correction
• Flexible and multi-shift induced dimension reduction algorithms for solving large sparse linear systems
• Algorithm 913
• On the semi-conjugate direction methods with dynamic preconditioning
• Variational Iterative Methods for Nonsymmetric Systems of Linear Equations
• Analysis of the Rational Krylov Subspace and ADI Methods for Solving the Lyapunov Equation
• Additive Schwarz with Variable Weights
• Breaking the Curse of Dimensionality, Or How to Use SVD in Many Dimensions
• An Introduction to Domain Decomposition Methods
• Hierarchische Matrizen
• Deflated and Augmented Krylov Subspace Techniques
• A Rank–One Reduction Formula and Its Applications to Matrix Factorizations
• A Multipreconditioned Conjugate Gradient Algorithm
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