Adaptive Acceleration of SSOR for Solving Large Linear Systems.

Abstract

Symmetric successive overrelaxation (SSOR) for solving large, sparse systems of linear equations involves the estimation of a parameter omega. An adaptive procedure is outlined for improving the estimates for omega and the spectral radius S(Sigma omega) of the iteration matrix Sigma omega. These estimates are then used in the SSOR method with Chebyshev acceleration. The objective is to achieve convergence in only a few more iterations than would be required if the best possible values of omega and S(Sigma omega) were used from the outset. The method is applied to obtain finite difference solutions of a number of generalized Dirichlet problems. In certain cases, the number of iterations required using the adaptive precedure increases like h to the minus 1/2 power, where h is the mesh size. (Author)

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Document Details

Document Type
Technical Report
Publication Date
Mar 01, 1979
Accession Number
ADA069133

Entities

People

  • Vitalius Benokraitis

Organizations

  • Ballistic Research Laboratory

Tags

Communities of Interest

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

DTIC Thesaurus Topics

  • Algebra
  • Algorithms
  • Boundaries
  • Boundary Value Problems
  • Chebyshev Polynomials
  • Computer Science
  • Convergence
  • Difference Equations
  • Differential Equations
  • Eigenvectors
  • Equations
  • Linear Systems
  • Mathematics
  • New York
  • Numerical Analysis
  • Partial Differential Equations
  • Polynomials

Fields of Study

  • Mathematics
  • Physics

Readers

  • Approximation Theory.
  • Finite Element Method (FEM) for solving Partial Differential Equations (PDEs)