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 language | English |
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Title of host publication | 12th IEEE International Conference on Electronics, Circuits and Systems (ICECS), 2005 |
Publisher | IEEE |
Pages | 1-4 |
ISBN (Print) | 9789972611001 |
DOIs | |
Publication status | Published - 2005 |
Event | 12th IEEE International Conference on Electronics, Circuits and Systems (ICECS), 2005 - Gammarth, Tunisia Duration: 11 Dec 2005 → 14 Dec 2005 |
Conference
Conference | 12th IEEE International Conference on Electronics, Circuits and Systems (ICECS), 2005 |
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Country/Territory | Tunisia |
City | Gammarth |
Period | 11/12/05 → 14/12/05 |