Preface 1. Background in linear algebra 2. Discretization of partial differential equations 3. Sparse matrices 4. Basic iterative methods 5. Projection methods 6. Krylov subspace methods Part I 7. Krylov subspace methods Part II 8. Methods related to the normal equations 9. Preconditioned iterations 10. Preconditioning techniques 11. Parallel implementations 12. Parallel preconditioners 13. Multigrid methods 14. Domain decomposition methods Bibliography Index.

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Iterative Methods for Sparse Linear Systems

In this book, which focuses on the use of iterative methods for solving large sparse systems of linear equations, templates are introduced to meet the needs of both the traditional user and the high-performance specialist Templates, a description of a general algorithm rather than the executable object or source code more commonly found in a conventional software library, offer whatever degree of customization the user may desire

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Templates for the Solution of Linear Systems: Building Blocks for Iterative Methods

Preface How to Get the Software Part I. Linear Equations. 1. Basic Concepts and Stationary Iterative Methods 2. Conjugate Gradient Iteration 3. GMRES Iteration Part II. Nonlinear Equations. 4. Basic Concepts and Fixed Point Iteration 5. Newton's Method 6. Inexact Newton Methods 7. Broyden's Method 8. Global Convergence Bibliography Index.

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Iterative Methods for Linear and Nonlinear Equations

Large linear systems of saddle point type arise in a wide variety of applications throughout computational science and engineering. Due to their indefiniteness and often poor spectral properties, such linear systems represent a significant challenge for solver developers. In recent years there has been a surge of interest in saddle point problems, and numerous solution techniques have been proposed for this type of system. The aim of this paper is to present and discuss a large selection of solution methods for linear systems in saddle point form, with an emphasis on iterative methods for large and sparse problems.

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Numerical solution of saddle point problems

The package REGULARIZATION TOOLS consists of 54 Matlab routines for analysis and solution of discrete ill-posed problems, i.e., systems of linear equations whose coefficient matrix has the properties that its condition number is very large, and its singular values decay gradually to zero. Such problems typically arise in connection with discretization of Fredholm integral equations of the first kind, and similar ill-posed problems. Some form of regularization is always required in order to compute a stabilized solution to discrete ill-posed problems. The purpose of REGULARIZATION TOOLS is to provide the user with easy-to-use routines, based on numerical robust and efficient algorithms, for doing experiments with regularization of discrete ill-posed problems. By means of this package, the user can experiment with different regularization strategies, compare them, and draw conclusions from these experiments that would otherwise require a major programming effert. For discrete ill-posed problems, which are indeed difficult to treat numerically, such an approach is certainly superior to a single black-box routine. This paper describes the underlying theory gives an overview of the package; a complete manual is also available.

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REGULARIZATION TOOLS: A Matlab package for analysis and solution of discrete ill-posed problems

We characterize the class $CG(s)$ of matrices A for which the linear system $A{\bf x} = {\bf b}$ can be solved by an s-term conjugate gradient method. We show that, except for a few anomalies, the class $CG(s)$ consists of matrices A for which conjugate gradient methods are already known. These matrices are the Hermitian matrices, $A^ * = A$, and the matrices of the form $Ae^{i\theta} (dI + B)$, with $B^ * = - B$.

Necessary and Sufficient Conditions for the Existence of a Conjugate Gradient Method

The authors give a new upper bound for the diameter $D(G)$ of a graph $G$ in terms of the eigenvalue of the Laplacian of $G$. The bound is
$$ D(G)\leqq \lfloor\fract{cosh^{-1}(n-1)}{cosh^{-1}\frac{\lambda_n + \lambda_2}{\lambda_n - \lambda_2}}\rfloor +1, $$
where $0\leq \lambda_2 \leq \cdots \leq \lambda_n$ are the eigenvalues of the Laplacian of $G$ and where $\lfloor \rfloor$ is the floor function.

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An Upper Bound on the Diameter of a Graph from Eigenvalues Associated with its Laplacian

Cayley graph techniques are introduced for the problem of constructing networks having the maximum possible number of nodes, among networks that satisfy prescribed bounds on the parameters maximum node degree and broadcast diameter. The broadcast diameter of a network is the maximum time required for a message originating at a node of the network to be relayed to all other nodes, under the restriction that in a single time step any node can communicate with only one neighboring node. For many parameter values these algebraic methods yield the largest known constructions, improving on previous graph-theoretic approaches. It has previously been shown that hypercubes are optimal for degree $k$ and broadcast diameter $k$. A construction employing dihedral groups is shown to be optimal for degree $k$ and broadcast diameter $k+1$.

Algebraic constructions of efficient broadcast networks

On the theory of equivalent operators and application to the numerical solution of uniformly elliptic partial differential equations

We address the degree-diameter problem for Cayley graphs of Abelian groups (Abelian graphs), both directed and undirected. The problem turns out to be closely related to the problem of finding efficient lattice coverings of Euclidean space by shapes such as octahedra and tetrahedra; we exploit this relationship in both directions. In particular, we find the largest Abelian graphs with 2 generators (dimensions) and a given diameter. (The results for 2 generators are not new; they are given in the literature of distributed loop networks.) We find an undirected Abelian graph with 3 generators and a given diameter which we conjecture to be as large as possible; for the directed case, we obtain partial results, which lead to unusual lattice coverings of 3-space. We discuss the asymptotic behavior of the problem for large numbers of generators. The graphs obtained here are substantially better than traditional toroidal meshes, but, in the simpler undirected cases, retain certain desirable features such as good routing algorithms, easy constructibility, and the ability to host mesh-connected numerical algorithms without any increase in communication times.

Vance Faber

Papers

Necessary and Sufficient Conditions for the Existence of a Conjugate Gradient Method

An Upper Bound on the Diameter of a Graph from Eigenvalues Associated with its Laplacian

Algebraic constructions of efficient broadcast networks

On the theory of equivalent operators and application to the numerical solution of uniformly elliptic partial differential equations

The degree-diameter problem for several varieties of Cayley graphs, I: the Abelian case