A Shifted Block Lanczos Algorithm for Solving Sparse Symmetric Generalized Eigenproblems
SIAM Journal on Matrix Analysis and Applications
Iterative methods for solving linear systems
Iterative methods for solving linear systems
Analysis of Projection Methods for Solving Linear Systems with Multiple Right-Hand Sides
SIAM Journal on Scientific Computing
Galerkin Projection Methods for Solving Multiple Linear Systems
SIAM Journal on Scientific Computing
A Deflated Version of the Conjugate Gradient Algorithm
SIAM Journal on Scientific Computing
SIAM Journal on Scientific Computing
The Solution of Parametrized Symmetric Linear Systems
SIAM Journal on Matrix Analysis and Applications
An Automated Multilevel Substructuring Method for Eigenspace Computation in Linear Elastodynamics
SIAM Journal on Scientific Computing
A Comparative Study of Iterative Solvers Exploiting Spectral Information for SPD Systems
SIAM Journal on Scientific Computing
Recycling Subspace Information for Diffuse Optical Tomography
SIAM Journal on Scientific Computing
Recycling Krylov Subspaces for Sequences of Linear Systems
SIAM Journal on Scientific Computing
Use of near-breakdowns in the block Arnoldi method for solving large Sylvester equations
Applied Numerical Mathematics
Efficient linear circuit analysis by Pade approximation via the Lanczos process
IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems
Spectral Methods for Parameterized Matrix Equations
SIAM Journal on Matrix Analysis and Applications
A Posteriori Error Analysis of Parameterized Linear Systems Using Spectral Methods
SIAM Journal on Matrix Analysis and Applications
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The solution of linear systems with a parameter is an important problem in engineering applications, including structural dynamics, acoustics, and electronic circuit simulations, and in related model order reduction methods such as Padé via Lanczos. In this paper, we present a Lanczos-based method for solving parameterized symmetric linear systems with multiple right-hand sides. We show that for this class of applications, a simple deflation method can be used.