Schwarz Splitting and Template Operators.

Abstract

Schwarz alternating method is an old mathematical technique dating from 1869. It was commonly believed that SAM was a useful tool for theoretical analysis but not a very practical approach for computations. The earlier experiences showed that SAM converged slowly. In this thesis, SAM is reexamined and generalized. The governing factors of convergence of SAM are explored through the analysis for the model problem. Based on this knowledge, many acceleration schemes can be combined with SAM to yield a new type of iterative method for large sparse matrix problems. In particular, when these techniques are applied to the solution of the model problem, an optimal complexity can be achieved. Some generalizations of SAM, namely Schwarz splittings (SS), are presented here. For many important applications, such as performing parallel computations in a non-shared memory environment, using composite grids and also applying fast solvers in an irregular region, (SS)s are found to be useful techniques. In order to identify the types of problems for which (SS)s are most suitable, a new structure for the linear operators called template operators has been developed. Some decay results for the elements of the inverses of sparse operators are given. These results provide a theoretical basis for determining when these SS techniques can be used successfully.

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Document Details

Document Type
Technical Report
Publication Date
Jul 01, 1987
Accession Number
ADA187956

Entities

People

  • Wei-pai Tang

Organizations

  • Stanford University

Tags

Communities of Interest

  • C4I
  • Energy and Power Technologies
  • Materials and Manufacturing Processes

DTIC Thesaurus Topics

  • Band Structures
  • Boundary Value Problems
  • Computational Fluid Dynamics
  • Computational Science
  • Computer Science
  • Difference Equations
  • Differential Equations
  • Equations
  • Linear Algebra
  • Parallel Computing
  • Parallel Processing
  • Partial Differential Equations
  • Poisson Equation
  • Three Dimensional
  • Two Dimensional
  • Vector Spaces

Readers

  • Computational Fluid Dynamics (CFD)
  • Linear Algebra
  • Systems Analysis and Design