Optimisation Algorithms for Highly Parallel Computer Architectures. The Performance of the Truncated Newton, Conjugate Gradient Algorithm in FORTRAN and ADA.

Abstract

This project is concerned with the optimisation of objective functions F(x) in a large dimensional space R to the n power on highly parallel computers. It has been established that the truncated Newton method introduced by Dembo & Steihang is an efficient method for solving large optimisation algorithms on a sequential machine, Dixon & Price. The truncated Newton method consists of two main steps: 1) the calculation of the function value F(x),, gradient vector g(x) and Hessian matrix H(x) at a sequence of points x to the (k) power. 2) solving the set of linear equations H(x) d = - g(x) approximately for the search direction d.

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Document Details

Document Type
Technical Report
Publication Date
Mar 01, 1988
Accession Number
ADA193940

Entities

People

  • L. C. Dixon
  • Z. A. Maany

Tags

Communities of Interest

  • Energy and Power Technologies

DTIC Thesaurus Topics

  • Accuracy
  • Algorithms
  • Arithmetic
  • Automatic
  • Band Structures
  • Computational Fluid Dynamics
  • Computer Architecture
  • Computer Programming
  • Computers
  • Energy Bands
  • Equations
  • Iterations
  • Linear Programming
  • Optimization
  • Simplex Method
  • Sparse Matrix
  • Test Sets

Readers

  • Operations Research

Technology Areas

  • Space