Power scalable implementation of artificial neural networks

S. S. Modi, P. R. Wilson, A. D. Brown

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Citation (Scopus)

Abstract

As the use of Artificial Neural Network(ANN) in mobile embedded devices gets more pervasive, power consumption of ANN hardware is becoming a major limiting factor. Although considerable research efforts are now directed towards low-power implementations of ANN, the issue of dynamic power scalability of the implemented design has been largely overlooked. In this paper, we discuss the motivation and basic principles for implementing power scaling in ANN Hardware. With the help of a simple example, we demonstrate how power scaling can be achieved with dynamic pruning techniques.
Original languageEnglish
Title of host publication12th IEEE International Conference on Electronics, Circuits and Systems (ICECS), 2005
PublisherIEEE
Pages1-4
ISBN (Print)9789972611001
DOIs
Publication statusPublished - 2005
Event12th IEEE International Conference on Electronics, Circuits and Systems (ICECS), 2005 - Gammarth, Tunisia
Duration: 11 Dec 200514 Dec 2005

Conference

Conference12th IEEE International Conference on Electronics, Circuits and Systems (ICECS), 2005
CountryTunisia
CityGammarth
Period11/12/0514/12/05

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