GMRES is a popular iterative method for the solution of linear system of equations with an unsymmetric square matrix. Range restricted GMRES (RRGMRES) is one GMRES version proposed by Calvetti et al in 2000. In this paper, a weighted implementation for RRGMRES is proposed. Numerical results prove this weighted RRGMRES is better than RRGMRES.

Though computational techniques for two-dimensional viscoelastic free surface flows are well developed, three-dimensional flows continue to present significant computational challenges. Fully coupled free surface flow models lead to nonlinear systems whose steady states can be found via Newton’s method. Each Newton iteration requires the solution of a large, sparse linear system, for which memo...

The GMRES and Arnoldi algorithms, which reduce to the CR and Lanczos algorithms in the symmetric case, both minimize p(A)b over polynomials p of degree n. The difference is that p is normalized at z 0 for GMRES and at z x for Arnoldi. Analogous "ideal GMRES" and "ideal Arnoldi" problems are obtained if one removes b from the discussion and minimizes p(/l)II instead. Investigation of these true ...

Multigrid algorithms are developed for systems arising from high-order discontinuous Galerkin discretizations of the compressible Navier-Stokes equations on unstructured meshes. The algorithms are based on coupling both pand h-multigrid (ph-multigrid) methods which are used in non-linear or linear forms, and either directly as solvers or as preconditioners to a Newton-Krylov method. The perform...

An implicit finite-element flow solver based on the Galerkin finite-element method is employed to study unsteady laminar flow past single and multiple objects. A fast dynamic remeshing technique is used to control the distribution of the mesh nodes during the unsteady simulation, thus minimizing (or even eliminating) the need for adding artificial dissipation terms. The quad-dominant mesh gener...

We have developed a parallel algorithm for radial basis function (rbf) interpolation that exhibits O(N) complexity, requires O(N) storage, and scales excellently up to a thousand processes. The algorithm uses a gmres iterative solver with a restricted additive Schwarz method (rasm) as a preconditioner and a fast matrix-vector algorithm. Previous fast rbf methods—achieving at most O(N logN) comp...

Inversion of sparse matrices with standard direct solve schemes is robust, but computationally expensive. Iterative solvers, on the other hand, demonstrate better scalability, but need to be used with an appropriate preconditioner (e.g., ILU, AMG, Gauss-Seidel, etc.) for proper convergence. The choice of an effective preconditioner is highly problem dependent. We propose a novel fully algebraic...

The solution of large scale Sylvester matrix equation plays an important role in control and large scientific computations. A popular approach is to use the global GMRES algorithm. In this work, we first consider the global GMRES algorithm with weighting strategy, and propose some new schemes based on residual to update the weighting matrix. Due to the growth of memory requirements and computat...

When solving a linear algebraic system Ax = b with GMRES, the relative residual norm at each step is bounded from above by the so-called ideal GMRES approximation. This worstcase bound is sharp (i.e. it is attainable by the relative GMRES residual norm) in case of a normal matrix A, but it need not characterize the worst-case GMRES behavior if A is nonnormal. Characterizing the tightness of thi...