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

This project is concerned with the optimisation of objective functions Fx 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 Fx,, gradient vector gx and Hessian matrix Hx at a sequence of points x to the k power. 2 solving the set of linear equations Hx d - gx approximately for the search direction d.