scholarly journals Comparison of Algebraic Multigrid Preconditioners for Solving Helmholtz Equations

2012 ◽  
Vol 2012 ◽  
pp. 1-12 ◽  
Author(s):  
Dandan Chen ◽  
Ting-Zhu Huang ◽  
Liang Li
Keyword(s):  
Krylov Subspace ◽  
Spectral Estimation ◽  
Solution Process ◽  
Krylov Subspace Methods ◽  
Good Choice ◽  
Algebraic Multigrid ◽  
Subspace Methods ◽  
Helmholtz Equations ◽  
Smoothed Aggregation ◽  
Aggregation Technique

An algebraic multigrid (AMG) with aggregation technique to coarsen is applied to construct a better preconditioner for solving Helmholtz equations in this paper. The solution process consists of constructing the preconditioner by AMG and solving the preconditioned Helmholtz problems by Krylov subspace methods. In the setup process of AMG, we employ the double pairwise aggregation (DPA) scheme firstly proposed by Y. Notay (2006) as the coarsening method. We compare it with the smoothed aggregation algebraic multigrid and meanwhile show shifted Laplacian preconditioners. According to numerical results, we find that DPA algorithm is a good choice in AMG for Helmholtz equations in reducing time and memory. Spectral estimation of system preconditioned by the three methods and the influence of second-order and fourth-order accurate discretizations on the three techniques are also considered.

scholarly journals Krylov subspace methods for estimating operator-vector multiplications in Hilbert spaces

2021 ◽  
Author(s):  
Yuka Hashimoto ◽  
Takashi Nodera
Keyword(s):  
Krylov Subspace ◽  
Time Series Data ◽  
Linear Equations ◽  
Transfer Operator ◽  
Krylov Subspace Methods ◽  
Krylov Subspace Method ◽  
Linear Operators ◽  
Series Data ◽  
Subspace Method ◽  
Subspace Methods

AbstractThe Krylov subspace method has been investigated and refined for approximating the behaviors of finite or infinite dimensional linear operators. It has been used for approximating eigenvalues, solutions of linear equations, and operator functions acting on vectors. Recently, for time-series data analysis, much attention is being paid to the Krylov subspace method as a viable method for estimating the multiplications of a vector by an unknown linear operator referred to as a transfer operator. In this paper, we investigate a convergence analysis for Krylov subspace methods for estimating operator-vector multiplications.

POWER GRIDS ANALYSIS IN COMPRESSED KRYLOV-SUBSPACE METHODS

2008 ◽  
Vol 17 (03) ◽  
pp. 439-446
Author(s):  
HAOHANG SU ◽  
YIMEN ZHANG ◽  
YUMING ZHANG ◽  
JINCAI MAN
Keyword(s):  
Present Method ◽  
Large Scale ◽  
Krylov Subspace ◽  
Power Grid ◽  
Excellent Result ◽  
Krylov Subspace Methods ◽  
Power Grids ◽  
Improved Method ◽  
Subspace Methods ◽  
Transient Simulations

An improved method is proposed based on compressed and Krylov-subspace iterative approaches to perform efficient static and transient simulations for large-scale power grid circuits. It is implemented with CG and BiCGStab algorithms and an excellent result has been obtained. Extensive experimental results on large-scale power grid circuits show that the present method is over 200 times faster than SPICE3 and around 10–20 times faster than ICCG method in transient simulations. Furthermore, the presented algorithm saves the memory usage over 95% of SPICE3 and 75% of ICCG method, respectively while the accuracy is not compromised.

On tensor tubal-Krylov subspace methods

2021 ◽  
pp. 1-24
Author(s):  
Alaa El Ichi ◽  
Khalide Jbilou ◽  
Rachid Sadaka
Keyword(s):  
Krylov Subspace ◽  
Krylov Subspace Methods ◽  
Subspace Methods
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