Multigrid Theory Research Articles

A cascaded FAS-UNet+ framework with iterative optimization strategy for segmentation of organs at risk.

Segmentation of organs at risks (OARs) in the thorax plays a critical role in radiation therapy for lung and esophageal cancer. Although automatic segmentation of OARs has been extensively studied, it remains challenging due to the varying sizes and shapes of organs, as well as the low contrast between the target and background. This paper proposes a cascaded FAS-UNet+ framework, which integrates convolutional neural networks and nonlinear multi-grid theory to solve a modified Mumford-shah model for segmenting OARs. This framework is equipped with an enhanced iteration block, a coarse-to-fine multiscale architecture, an iterative optimization strategy, and a model ensemble technique. The enhanced iteration block aims to extract multiscale features, while the cascade module is used to refine coarse segmentation predictions. The iterative optimization strategy improves the network parameters to avoid unfavorable local minima. An efficient data augmentation method is also developed to train the network, which significantly improves its performance. During the prediction stage, a weighted ensemble technique combines predictions from multiple models to refine the final segmentation. The proposed cascaded FAS-UNet+ framework was evaluated on the SegTHOR dataset, and the results demonstrate significant improvements in Dice score and Hausdorff Distance (HD). The Dice scores were 95.22%, 95.68%, and HD values were 0.1024, and 0.1194 for the segmentations of the aorta and heart in the official unlabeled dataset, respectively. Our code and trained models are available at https://github.com/zhuhui100/C-FASUNet-plus .

Hp-Multigrid Preconditioner for a Divergence-Conforming HDG Scheme for the Incompressible Flow Problems

In this study, we present an hp-multigrid preconditioner for a divergence-conforming HDG scheme for the generalized Stokes and the Navier–Stokes equations using an augmented Lagrangian formulation. Our method relies on conforming simplicial meshes in two- and three-dimensions. The hp-multigrid algorithm is a multiplicative auxiliary space preconditioner that employs the lowest-order space as the auxiliary space, and we develop a geometric multigrid method as the auxiliary space solver. For the generalized Stokes problem, the crucial ingredient of the geometric multigrid method is the equivalence between the condensed lowest-order divergence-conforming HDG scheme and a Crouzeix–Raviart discretization with a pressure-robust treatment as introduced in Linke and Merdon (Comput Methods Appl Mech Engrg 311:304–326, 2022), which allows for the direct application of geometric multigrid theory on the Crouzeix–Raviart discretization. The numerical experiments demonstrate the robustness of the proposed hp-multigrid preconditioner with respect to mesh size and augmented Lagrangian parameter, with iteration counts insensitivity to polynomial order increase. Inspired by the works by Benzi and Olshanskii (SIAM J Sci Comput 28:2095–2113, 2006) and Farrell et al. (SIAM J Sci Comput 41:A3073–A3096, 2019), we further test the proposed preconditioner on the divergence-conforming HDG scheme for the Navier–Stokes equations. Numerical experiments show a mild increase in the iteration counts of the preconditioned GMRes solver with the rise in Reynolds number up to 103\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$10^3$$\\end{document}.

Optimal Geometric Multigrid Preconditioners for HDG-P0 Schemes for the reaction-diffusion equation and the Generalized Stokes equations

We present the lowest-order hybridizable discontinuous Galerkin schemes with numerical integration (quadrature), denoted as HDG-P0 for the reaction-diffusion equation and the generalized Stokes equations on conforming simplicial meshes in two- and three-dimensions. Here by lowest order, we mean that the (hybrid) finite element space for the global HDG facet degrees of freedom (DOFs) is the space of piecewise constants on the mesh skeleton. A discontinuous piecewise linear space is used for the approximation of the local primal unknowns. We give the optimal a priori error analysis of the proposed HDG-P0 schemes, which hasn’t appeared in the literature yet for HDG discretizations as far as numerical integration is concerned. Moreover, we propose optimal geometric multigrid preconditioners for the statically condensed HDG-P0 linear systems on conforming simplicial meshes. In both cases, we first establish the equivalence of the statically condensed HDG system with a (slightly modified) nonconforming Crouzeix–Raviart (CR) discretization, where the global (piecewise-constant) HDG finite element space on the mesh skeleton has a natural one-to-one correspondence to the nonconforming CR (piecewise-linear) finite element space that live on the whole mesh. This equivalence then allows us to use the well-established nonconforming geometry multigrid theory to precondition the condensed HDG system. Numerical results in two- and three-dimensions are presented to verify our theoretical findings.

On an effective multigrid solver for solving a class of variational problems with application to image segmentation

ABSTRACT In this paper we reformulate a class of non-linear variational models for global and selective image segmentation and obtain convergent multigrid solutions. In contrast, non-linear multigrid schemes do not converge for these problems with strong non-linearity and non-smoothness (jumps). Our new approach is to reformulate the non-linear models, using splitting techniques, to generate linear models in a higher dimension which are easier to solve and amenable to the linear multigrid framework. Although splitting techniques are well studied in isolation, direct application of a splitting idea is not sufficient and it is the combination of two splitting approaches and linear multigrid theory approaches which results in a highly effective multigrid algorithm. Numerical results demonstrate the fast convergence of the new multigrid methods.

A note on terminology in multigrid methods

AbstractWe compare terminology used in the literature on multigrid methods for compressible computational fluid dynamics to that used in linear multigrid theory. Several popular iterative and direct smoothers are presented side‐by‐side using the same terminology. We argue for greater analysis of these methods in order to place them into a more rigorous framework and to identify the most promising candidates for future development. (© 2016 Wiley‐VCH Verlag GmbH & Co. KGaA, Weinheim)

Multigrid methods for isogeometric discretization

We present (geometric) multigrid methods for isogeometric discretization of scalar second order elliptic problems. The smoothing property of the relaxation method, and the approximation property of the intergrid transfer operators are analyzed. These properties, when used in the framework of classical multigrid theory, imply uniform convergence of two-grid and multigrid methods. Supporting numerical results are provided for the smoothing property, the approximation property, convergence factor and iterations count for V-, W- and F-cycles, and the linear dependence of V-cycle convergence on the smoothing steps. For two dimensions, numerical results include the problems with variable coefficients, simple multi-patch geometry, a quarter annulus, and the dependence of convergence behavior on refinement levels ℓ, whereas for three dimensions, only the constant coefficient problem in a unit cube is considered. The numerical results are complete up to polynomial order p=4, and for C0 and Cp-1 smoothness.

An Alternative Coarse Space for Irregular Subdomains and an Overlapping Schwarz Algorithm for Scalar Elliptic Problems in the Plane

In earlier work on domain decomposition methods for elliptic problems in the plane, an assumption that each subdomain is triangular or a union of a few coarse triangles has often been made. This is similar to what is required in geometric multigrid theory and is unrealistic if the subdomains are produced by a mesh partitioner. In an earlier paper, coauthored with Axel Klawonn, the authors introduced a coarse subspace for an overlapping Schwarz method with one degree of freedom for each subdomain vertex and one for each subdomain edge. A condition number bound proportional to $(1+\log(H/h))^2(1+H/\delta)$ was established assuming only that the subdomains are John domains; here $H/\delta$ measures the relative overlap between neighboring subdomains and $H/h$ the maximum number of elements across individual subdomains. We were also able to relate the rate of convergence to a parameter in an isoperimetric inequality for the subdomains into which the domain of the problem has been partitioned. In this paper, the dimension of the coarse subspace is decreased by using only one degree of freedom for each subdomain vertex; if all subdomains have three edges, this leads to a reduction of the dimension of the coarse subspace by approximately a factor four. In addition, the condition number bound is shown to be proportional to $(1+\log(H/h))(1+H/\delta)$ under a quite mild assumption on the relative length of adjacent subdomain edges. In this study, the subdomains are assumed to be uniform in the sense of Peter Jones. As in our earlier work, the results are insensitive to arbitrary large jumps in the coefficients of the elliptic problem across the interface between the subdomains. Numerical results are presented which confirm the theory and demonstrate the usefulness of the algorithm for a variety of mesh decompositions and distributions of material properties. It is also shown that the new algorithm often converges faster than the older one in spite of the fact that the dimension of the coarse space has been decreased considerably.

Multigrid Smoothers for Ultraparallel Computing

This paper investigates the properties of smoothers in the context of algebraic multigrid (AMG) running on parallel computers with potentially millions of processors. The development of multigrid smoothers in this case is challenging, because some of the best relaxation schemes, such as the Gauss-Seidel (GS) algorithm, are inherently sequential. Based on the sharp two-grid multigrid theory from [R. D. Falgout and P. S. Vassilevski, SIAM J. Numer. Anal., 42 (2004), pp. 1669-1693] and [R. D. Falgout, P. S. Vassilevski, and L. T. Zikatanov, Numer. Linear Algebra Appl., 12 (2005), pp. 471-494] we characterize the smoothing properties of a number of practical candidates for parallel smoothers, including several $C$-$F$, polynomial, and hybrid schemes. We show, in particular, that the popular hybrid GS algorithm has multigrid smoothing properties which are independent of the number of processors in many practical applications, provided that the problem size per processor is large enough. This is encouraging news for the scalability of AMG on ultraparallel computers. We also introduce the more robust $\ell_1$ smoothers, which are always convergent and have already proven essential for the parallel solution of some electromagnetic problems [T. Kolev and P. Vassilevski, J. Comput. Math., 27 (2009), pp. 604-623].

Algebraic multigrid methods for Laplacians of graphs

Classical algebraic multigrid theory relies on the fact that the system matrix is positive definite. We extend this theory to cover the positive semidefinite case as well, by formulating semiconvergence results for these singular systems. For the class of irreducible diagonal dominant singular M-matrices we show that the requirements of the developed theory hold and that the coarse level systems are still of the same class, if the C / F -splitting is good enough. An important example for matrices that are irreducible diagonal dominant M-matrices are Laplacians of graphs. Recent shape optimizing methods for graph partitioning require to solve singular linear systems involving these Laplacians. We present convergence results as well as experimental results for numerous graphs arising from finite element discretizations with up to 10 6 vertices.

An efficient multigrid method for the simulation of high-resolution elastic solids

We present a multigrid framework for the simulation of high-resolution elastic deformable models, designed to facilitate scalability on shared memory multiprocessors. We incorporate several state-of-the-art techniques from multigrid theory, while adapting them to the specific requirements of graphics and animation applications, such as the ability to handle elaborate geometry and complex boundary conditions. Our method supports simulation of linear elasticity and corotational linear elasticity. The efficiency of our solver is practically independent of material parameters, even for near-incompressible materials. We achieve simulation rates as high as 6 frames per second for test models with 256K vertices on an 8-core SMP, and 1.6 frames per second for a 2M vertex object on a 16-core SMP.

Multigrid Methods for a Stabilized Reissner–Mindlin Plate Formulation

We consider a stabilized finite element formulation for the Reissner–Mindlin plate bending model. The method uses standard basis functions for the deflection and the rotation vector. We apply a standard multigrid algorithm to obtain a preconditioner. We prove that the condition number of the preconditioned system is uniformly bounded with respect to the mesh size and the thickness parameter. In order to apply the abstract multigrid theory, we introduce new interpolation norms and prove error estimates in them. Numerical results confirm the analysis.

The convergence of V-cycle multigrid algorithms for axisymmetric Laplace and Maxwell equations

We investigate some simple finite element discretizations for the axisymmetric Laplace equation and the azimuthal component of the axisymmetric Maxwell equations as well as multigrid algorithms for these discretizations. Our analysis is targeted at simple model problems and our main result is that the standard V-cycle with point smoothing converges at a rate independent of the number of unknowns. This is contrary to suggestions in the existing literature that line relaxations and semicoarsening are needed in multigrid algorithms to overcome difficulties caused by the singularities in the axisymmetric Maxwell problems. Our multigrid analysis proceeds by applying the well known regularity based multigrid theory. In order to apply this theory, we prove regularity results for the axisymmetric Laplace and Maxwell equations in certain weighted Sobolev spaces. These, together with some new finite element error estimates in certain weighted Sobolev norms, are the main ingredients of our analysis.

A Multigrid Method for the Mortar-Type Morley Element Approximation of a Plate Bending Problem

In this paper, a multigrid algorithm is presented for the mortar element method for the Morley nonconforming plate element. Based on the multigrid theory developed by Bramble, Pasciak, and Xu in [Math. Comp., 56 (1991), pp. 1--34], we prove that the W-cycle multigrid method is optimal, i.e., the convergence rate is independent of the mesh size and mesh level. Moreover, a variable V-cycle multigrid preconditioner is constructed, which results in a preconditioned system with a uniformly bounded condition number.

Multigrid Computation of Axisymmetric Electromagnetic Fields

The focus of this paper is on boundary value problems for Maxwell's equations that feature cylindrical symmetry both of the domain Ω⊂R 3 and the data. Thus, by resorting to cylindrical coordinates, a reduction to two dimensions is possible. However, cylindrical coordinates introduce a potentially malicious singularity at the axis rendering the variational problems degenerate. As a consequence, the analysis of multigrid solvers along the lines of variational multigrid theory confronts severe difficulties. Line relaxation in radial direction and semicoarsening can successfully reign in the degeneracy. In addition, the lack of H 1-ellipticity of the double-curl operator entails using special hybrid smoothing procedures. All these techniques combined yield a fast multigrid solver. The theoretical investigation of the method relies on blending generalized Fourier techniques and modern variational multigrid theory. We first determine invariant subspaces of the multigrid iteration operator and analyze the smoothers therein. Under certain assumptions on the material parameters we manage to show uniform convergence of a symmetric V-cycle.

Toward large scale F.E. computation of hot forging process using iterative solvers, parallel computation and multigrid algorithms

AbstractThe industrial simulation code Forge3® is devoted to three‐dimensional metal forming applications. This finite element software is based on an implicit approach. It is able to carry out the large deformations of viscoplastic incompressible materials with unilateral contact conditions. The finite element discretization is based on a stable mixed velocity–pressure formulation and tetrahedral unstructured meshes. Central to the Newton iterations dealing with the non‐linearities, a preconditioned conjugate residual method (PCR) is used. The parallel version of the code uses an SPMD programming model and several results on complex applications have been published. In order to reduce the CPU time computation, a new solver has been developed which is based on multigrid theory. A detailed presentation of the different elements of the method is given: the geometrical approach based on embedded meshes, the direct resolution of the velocity–pressure system, the use of PCR method as an original smoother and for solving the coarse problem, the full multigrid method and the required preconditioning by an incomplete Cholesky factorization for problems with complex contact conditions. By considering different forging cases, the theoretical properties of the multigrid method are numerically verified, optimizations of the solver are presented and finally, the results obtained on several industrial problems are given, showing the efficiency of the new solver that provides speed‐up larger than 5. Copyright © 2001 John Wiley & Sons, Ltd.

Algebraic Multigrid Based on Element Interpolation (AMGe)

We introduce AMGe, an algebraic multigrid method for solving the discrete equations that arise in Ritz-type finite element methods for partial differential equations. Assuming access to the element stiffness matrices, we have that AMGe is based on the use of two local measures, which are derived from global measures that appear in existing multigrid theory. These new measures are used to determine local representations of algebraically "smooth" error components that provide the basis for constructing effective interpolation and, hence, the coarsening process for AMG. Here, we focus on the interpolation process; choice of the coarse "grids" based on these measures is the subject of current research. We develop a theoretical foundation for AMGe and present numerical results that demonstrate the efficacy of the method.

Multilevel methods for mixed finite elements in three dimensions

In this paper we consider second order scalar elliptic boundary value problems posed over three–dimensional domains and their discretization by means of mixed Raviart–Thomas finite elements [18]. This leads to saddle point problems featuring a discrete flux vector field as additional unknown. Following Ewing and Wang [26], the proposed solution procedure is based on splitting the flux into divergence free components and a remainder. It leads to a variational problem involving solenoidal Raviart–Thomas vector fields. A fast iterative solution method for this problem is presented. It exploits the representation of divergence free vector fields as ${\bf curl}$ s of the ${\bf H}({\bf curl})$ –conforming finite element functions introduced by Nedelec [43]. We show that a nodal multilevel splitting of these finite element spaces gives rise to an optimal preconditioner for the solenoidal variational problem: Duality techniques in quotient spaces and modern algebraic multigrid theory [50, 10, 31] are the main tools for the proof.

V-Cycle Multigrid for Cell-Centered Finite Differences

We introduce and analyze a V-cycle multigrid algorithm for cell-centered finite difference methods applied to second-order elliptic boundary value problems. Unlike conventional cell-centered multigrid algorithms that use the natural injection operator for prolongation, we use a new prolongation operator whose energy norm we prove is bounded by 1 in the constant coefficient case and 1+Ch in the nonconstant case. We are thus able to use general finite element multigrid theory to conclude that the V-cycle either converges well or serves as a reasonably good preconditioner, respectively. While our theory does not establish optimal performance, our numerical experiments do show that the resulting algorithm converges much faster than the conventional schemes. In fact, these results show that the energy norm convergence factor is small and remains bounded uniformly in the finest mesh size, while that of the conventional algorithm grows.

ON THE OPTIMALITY OF SOME FAC AND AFAC METHODS FOR ELLIPTIC FINITE ELEMENT PROBLEMS

We consider some solution methods for large sparse linear systems of equations which arise from second-order elliptic finite element problems defined on composite meshes. Historically these methods were called FAC and AFAC methods. Optimal bounds of the condition number for certain AFAC iterative operator are established by proving a strengthened Cauchy-Schwarz inequality using an interpolation theorem for Hilbert scales. This work completes earlier work by Dryja and Widlund. We also apply an extension theorem for finite element functions to get a weaker bound under some more general assumptions. The optimality of the FAC methods, with exact solvers or spectrally equivalent inexact solvers being used, is also proved by using similar techniques and some ideas from multigrid theory..

ON THE OPTIMALITY OF SOME FAC AND AFAC METHODS FOR ELLIPTIC FINITE ELEMENT PROBLEMS

We consider some solution methods for large sparse linear systems of equations which arise from second-order elliptic finite element problems defined on composite meshes. Historically these methods were called FAC and AFAC methods. Optimal bounds of the condition number for certain AFAC iterative operator are established by proving a strengthened Cauchy-Schwarz inequality using an interpolation theorem for Hilbert scales. This work completes earlier work by Dryja and Widlund. We also apply an extension theorem for finite element functions to get a weaker bound under some more general assumptions. The optimality of the FAC methods, with exact solvers or spectrally equivalent inexact solvers being used, is also proved by using similar techniques and some ideas from multigrid theory..