Non-linear Optimization on a Parallel Intel i860 RISC Based Architecture

Abstract

A description of a parallel implementation of the Genetic Algorithm for non-linear optimization is presented. The system is implemented with four Intel i860 RISC processors using INMOS transputers for communications. The performance is compared to the Cray Y-MP, Cray J916, an SGI Power Challenge L R8000 75 MHZ workstation, an SGI Challenge L R4400 100 MHZ work-station, an SGI Indy SC R4400 200 MHZ workstation, and both parastation and Paramid parallel I860 machines, each with one to four participating I860s. Comparisons were made for neural network optimization of a limited dependent variable problem and a chaotic time series. A complex rational expectations model was also estimated. The I860 based machines were able to achieve performances comparable to the supercomputers.