Distributed artificial neural network architectures

Abstract

The computational cost of training artificial neural network (ANN) algorithms limits the use of large systems capable of processing complex problems. Implementing ANNs on a parallel or distributed platform to improve performance is therefore desirable. This work illustrates a method to predict and evaluate the performance of distributed ANN algorithms by… (More)
DOI: 10.1109/HPCS.2005.24

20 Figures and Tables

Topics

  • Presentations referencing similar topics