Preconditioned GMRES Research Articles

On the performance of various adaptive preconditioned GMRES strategies

This paper compares the performance on linear systems of equations of three similar adaptive accelerating strategies for restarted GMRES. The underlying idea is to adaptively use spectral information gathered from the Arnoldi process. The first strategy retains approximations to some eigenvectors from the previous restart and adds them to the Krylov subspace. The second strategy also uses approximated eigenvectors to define a preconditioner at each restart. This paper designs a third new strategy which combines elements of both previous approaches. Numerical results show that this new method is both more efficient and more robust. © 1998 John Wiley & Sons, Ltd.

On the performance of various adaptive preconditioned GMRES strategies

This paper compares the performance on linear systems of equations of three similar adaptive accelerating strategies for restarted GMRES. The underlying idea is to adaptively use spectral information gathered from the Arnoldi process. The first strategy retains approximations to some eigenvectors from the previous restart and adds them to the Krylov subspace. The second strategy also uses approximated eigenvectors to define a preconditioner at each restart. This paper designs a third new strategy which combines elements of both previous approaches. Numerical results show that this new method is both more efficient and more robust. © 1998 John Wiley & Sons, Ltd.

An Evaluation of Parallel Multigrid as a Solver and a Preconditioner for Singularly Perturbed Problems

In this paper we try to achieve h-independent convergence with preconditioned GMRES ([Y. Saad and M. H. Schultz, SIAM J. Sci. Comput., 7 (1986), pp. 856--869]) and BiCGSTAB ([H. A. Van der Vorst, SIAM J. Sci. Comput., 13 (1992), pp. 63--644]) for two-dimensional (2D) singularly perturbed equations. Three recently developed multigrid methods are adopted as a preconditioner. They are also used as solution methods in order to compare the performance of the methods as solvers and as preconditioners. Two of the multigrid methods differ only in the transfer operators. One uses standard matrix-dependent prolongation operators from [J. E. Dendy Jr., J. Comput. Phys., 48 (1982), pp. 366--386], [W. Hackbusch, Multi-grid Methods and Applications, Springer, Berlin, 1985]. The second uses "upwind" prolongation operators, developed in [P. M. de Zeeuw, J. Comput.\ Appl.\ Math., 33 (1990), pp. 1--27]. Both employ the Galerkin coarse grid approximation and an alternating zebra line Gauss--Seidel smoother. The third method is based on the block LU decomposition of a matrix and on an approximate Schur complement. This multigrid variant is presented in [A. Reusken, A Multigrid Method Based on Incomplete Gaussian Elimination, University of Eindhoven, the Netherlands, 1995]. All three multigrid algorithms are algebraic methods. The eigenvalue spectra of the three multigrid iteration matrices are analyzed for the equations solved in order to understand the convergence of the three algorithms. Furthermore, the construction of the search directions for the multigrid preconditioned GMRES solvers is investigated by the calculation and solution of the minimal residual polynomials. For Poisson and convection-diffusion problems all solution methods are investigated and evaluated for finite volume discretizations on fine grids. The methods have been parallelized with a grid partitioning technique and are compared on an MIMD machine.

A preconditioned GMRES method

In this paper, we show the convergence of GMRES method for nonsymmetric problems preconditioned with a multigrid method based on the original operator. This is simpler and more natural to implement than using a preconditioner based on the principal part, as suggested by Cai and Xu.

A comparison of segregated and coupled methods for the solution of the incompressible Navier-Stokes equations

Three different solution methods for the finite-volume discretized incompressible Navier-Stokes equations have been tested: segregated approaches, built around coupling methods such as SIMPLE, SIMPLER and PISO plus a line Gauss-Seidel linear solver; coupled methods, incorporating a penalty formulation to eliminate zero diagonal elements in the coefficient matrices, plus preconditioned GMRES as a linear solver;- and a FAS-full multigrid algorithm accelerating a classical segregated method based upon SIMPLE and the line Gauss-Seidel solver. Results demonstrate that the coupled method compares favourably to the segregated technique at small grid sizes but becomes too expensive for large problems. The FAS-full multigrid algorithm outperforms the other two methods when large numbers of nodes are employed in the simulation.

Parallel solution of large‐scale differential‐algebraic systems

AbstractDASPK solves large‐scale systems of differential‐algebraic equations. It is based on the integration method in DASSL, but instead of a direct method for the associated linear systems which arise at each time step, the preconditioned GMRES iteration is applied in combination with an inexact Newton method. Two parallel versions of DASPK have been developed: DASPKF90, a Fortran 90 data parallel implementation, and DASPKMP, a message‐passing implementation written in Fortran 77 with extended BLAS. The parallel versions have been implemented for the Thinking Machines Corporation (TMC) CM‐5, a massively parallel multiprocessor, keeping the user interface relatively simple while allowing for portability to other massively parallel architectures. The codes have been demonstrated on several large‐scale test problems, including three‐dimensional formulations of the heat equation, the Cahn‐Hilliard equation and a multi‐species reaction‐diffusion problem. The formulations are described, including detail on preconditioning the Krylov iteration, timing results and performance analysis.