A development environment for multilayer neural network applications mapped onto DSPs with multiprocessing capabilities

Authors:
Eugenio S. Cáner;José M. Seixas;Rodrigo C. Torres
Affiliations:
COPPE/EE/Federal University of Rio de Janeiro, Rio de Janeiro, Brazil;COPPE/EE/Federal University of Rio de Janeiro, Rio de Janeiro, Brazil;COPPE/EE/Federal University of Rio de Janeiro, Rio de Janeiro, Brazil
Venue:
VECPAR'02 Proceedings of the 5th international conference on High performance computing for computational science
Year:
2002

Citing 4
Cited 0

Using and designing massively parallel computers for artificial neural networks

Journal of Parallel and Distributed Computing - Special issue on neural computing on massively parallel processing
Parallel and distributed computing handbook

Parallel and distributed computing handbook
Artificial Neural Systems: Foundations, Paradigms, Applications, and Implementations

Artificial Neural Systems: Foundations, Paradigms, Applications, and Implementations
Neural Networks: A Comprehensive Foundation (3rd Edition)

Neural Networks: A Comprehensive Foundation (3rd Edition)

Quantified Score

Hi-index	0.00

Visualization

Abstract

This paper concerns the development of artificial neural network applications in digital signal processors (DSPs) with multiprocessing capabilities. For defining an efficient partition of processing tasks within target DSP boards, a user-friendly development environment evaluates different parallelism approaches for the network design according to specific device features. The development environment supports two different levels of experience (novice, expert) on both parallel system and neural network designs, enabling novice users to access system resources easily and shorten design cycle time. Pre-processing methods based on topological mapping and principal component analysis are also supported by the system, so that compact and efficient neural network system designs can be implemented.