88 research outputs found
Model Integration and Coupling in A Hydroinformatics System
Source: ICHE Conference Archive - https://mdi-de.baw.de/icheArchiv
A simple and efficient segregated smoother for the discrete Stokes equations
We consider the multigrid solution of the generalized Stokes equations with a segre- gated (i.e., equationwise) Gauss–Seidel smoother based on a Uzawa-type iteration. We analyze the smoother in the framework of local Fourier analysis, and obtain an analytic bound on the smoothing factor showing uniform performance for a family of Stokes problems. These results are confirmed by the numerical computation of the two-grid convergence factor for different types of grids and dis- cretizations. Numerical results also show that the actual convergence of the W-cycle is approximately the same as that obtained by a Vanka smoother, despite this latter smoother being significantly more costly per iteration step
How fast the Laplace equation was solved in 1995
On the occasion of the third centenary of the appointment of Johann Bernoulli at the University of Groningen, a number of linear systems solvers for some Laplace-like equations have been compared during a one-day workshop. CPU times of several advanced solvers measured on the same computer (an HP-755 workstation) are presented, which makes it possible to draw clear conclusions about the performance of these solvers
Fast interior point solution of quadratic programming problems arising from PDE-constrained optimization
Interior point methods provide an attractive class of approaches for solving linear, quadratic and nonlinear programming problems, due to their excellent efficiency and wide applicability. In this paper, we consider PDE-constrained optimization problems with bound constraints on the state and control variables, and their representation on the discrete level as quadratic programming problems. To tackle complex problems and achieve high accuracy in the solution, one is required to solve matrix systems of huge scale resulting from Newton iteration, and hence fast and robust methods for these systems are required. We present preconditioned iterative techniques for solving a number of these problems using Krylov subspace methods, considering in what circumstances one may predict rapid convergence of the solvers in theory, as well as the solutions observed from practical computations
On Block Triangular Preconditioners for the Interior Point Solution of PDE-Constrained Optimization Problems
We consider the numerical solution of saddle point systems of equations resulting from the discretization of PDE-constrained optimization problems, with additional bound constraints on the state and control variables, using an interior point method. In particular, we derive a Bramble-Pasciak Conjugate Gradient method and a tailored block triangular preconditioner which may be applied within it. Crucial to the usage of the preconditioner are carefully chosen approximations of the (1,1)-block and Schur complement of the saddle point system. To apply the inverse of the Schur complement approximation, which is computationally the most expensive part of the preconditioner, one may then utilize methods such as multigrid or domain decomposition to handle individual sub-blocks of the matrix system
On Convergence of the Inexact Rayleigh Quotient Iteration with the Lanczos Method Used for Solving Linear Systems
For the Hermitian inexact Rayleigh quotient iteration (RQI), the author has
established new local general convergence results, independent of iterative
solvers for inner linear systems. The theory shows that the method locally
converges quadratically under a new condition, called the uniform positiveness
condition. In this paper we first consider the local convergence of the inexact
RQI with the unpreconditioned Lanczos method for the linear systems. Some
attractive properties are derived for the residuals, whose norms are
's, of the linear systems obtained by the Lanczos method. Based on
them and the new general convergence results, we make a refined analysis and
establish new local convergence results. It is proved that the inexact RQI with
Lanczos converges quadratically provided that with a
constant . The method is guaranteed to converge linearly provided
that is bounded by a small multiple of the reciprocal of the
residual norm of the current approximate eigenpair. The results are
fundamentally different from the existing convergence results that always
require , and they have a strong impact on effective
implementations of the method. We extend the new theory to the inexact RQI with
a tuned preconditioned Lanczos for the linear systems. Based on the new theory,
we can design practical criteria to control to achieve quadratic
convergence and implement the method more effectively than ever before.
Numerical experiments confirm our theory.Comment: 20 pages, 8 figures. arXiv admin note: text overlap with
arXiv:0906.223
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