Parallel block ILUT/ILDLT preconditioning for sparse eigenproblems and sparse linear systems

DOI<635::AID-NLA216>3.0.CO;2-B 10.1002/1099-1506(200010/12)7:7/8<635::AID-NLA216>3.0.CO;2-BzbMath1051.65049OpenAlexW2087283353MaRDI QIDQ4814502

Achim Basermann

Publication date: 7 September 2004

Full work available at URL: https://doi.org/10.1002/1099-1506(200010/12)7:7/8<635::aid-nla216>3.0.co;2-b

zbMATH Keywords

parallel computingsparse linear systemsJacobi-Davidson methodincomplete block \(LU\) preconditioning methods with thresholdsparse eigenproblems

Mathematics Subject Classification ID

Numerical computation of eigenvalues and eigenvectors of matrices (65F15) Numerical computation of matrix norms, conditioning, scaling (65F35) Parallel numerical computation (65Y05) Complexity and performance of numerical algorithms (65Y20)

Related Items (2)

ParILUT---A New Parallel Threshold ILU Factorization ⋮ A geometric theory for preconditioned inverse iteration. III: A short and sharp convergence estimate for generalized eigenvalue problems

Uses Software

• SPARSKIT

Cites Work

• Modification of the Liu-Davidson method for obtaining one or simultaneously several eigensolutions of a large real-symmetric matrix
• QMR: A quasi-minimal residual method for non-Hermitian linear systems
• Preconditioned CG methods for sparse matrices on massively parallel machines
• Bi-CGSTAB: A Fast and Smoothly Converging Variant of Bi-CG for the Solution of Nonsymmetric Linear Systems
• The parallel computation of the smallest eigenpair of an acoustic problem with damping
• A Jacobi–Davidson Iteration Method for Linear Eigenvalue Problems
• A Transpose-Free Quasi-Minimal Residual Algorithm for Non-Hermitian Linear Systems
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