This book deals with numerical methods for solving large sparse linear systems of equations, particularly those arising from the discretization of partial differential equations. It covers both direct and iterative methods. Direct methods which are considered are variants of Gaussian elimination and fast solvers for separable partial differential equations in rectangular domains. The book reviews the classical iterative methods like Jacobi, Gauss-Seidel and alternating directions algorithms. A particular emphasis is put on the conjugate gradient as well as conjugate gradient -like methods for non symmetric problems. Most efficient preconditioners used to speed up convergence are studied. A chapter is devoted to the multigrid method and the book ends with domain decomposition algorithms that are well suited for solving linear systems on parallel computers.
This book will be of interest to students and practitioners in the fields of computer science and applied mathematics.
Computer Solution of Large Sparse Positive Definite Systems
Mathematics of Computing -- General.
For more general Bi - CGSTAB ( C ) schemes see [ 174 , 177 ] . xo is an initial guess , ro = b – Axo Choose ro , for example ro = r po = 1 , u = 0 , a = 0 , W2 = 1 for i = 0 , 2 , 4 , 6 , .... Po = -02P0 even Bi - CG step : Pi = ( ro ...
[122] R. W. Freund and H. Zha. Simplifications of the nonsymmetric Lanczos process and a new algorithm for ... P. R. Graves-Morris and A. Salam. Avoiding breakdown in Van der Vorst's method. Numer. Algorithms, 21:205–223, 1999.
Although the origins of parallel computing go back to the last century, it was only in the 1970s that parallel and vector computers became available to the scientific community.
The book includes CSparse, a concise downloadable sparse matrix package that illustrates the algorithms and theorems presented in the book and equips readers with the tools necessary to understand larger and more complex software packages ...
This book provides an overview of the use of iterative methods for solving sparse linear systems, identifying future research directions in the mainstream of modern scientific computing with an eye to contributions of the past, present, and ...
This is a crucial part of the program and we owe her a great deal of thanks.
[ 116 ] C. Lanczos , Chebyshev polynomials in the solution of large - scale linear systems , Toronto Symposium on Computing ... [ 127 ] G. Meurant , Computer Solution of Large Linear Systems , North - Holland , Amsterdam , 1999 .