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Expansible & Reconfigurable Neuro Informatics Engine : ERNIE  

김영주 (인하대학교 정보통신공학과)
동성수 (인하대학교 정보통신공학과)
이종호 (용인송담대학 디지털전자정보과)
Publication Information
Journal of the Institute of Electronics Engineers of Korea CI / v.40, no.6, 2003 , pp. 56-68 More about this Journal
Abstract
Difficult problems In implementing digital neural network hardware are the extension of synapses and the programmability for relocating neurons. In this paper, the structure of a new hardware is proposed for solving these problems. Our structure based on traditional SIMD can be dynamically and easily reconfigured connections of network without synthesizing and mapping original design for each use. Using additional modular processing unit the numbers of neurons find synapses increase. To show the extensibility of our structure, various models of neural networks : multi-layer perceptrons and Kohonen network are formed and tested. The performance comparison with software simulation shows its superiority in the aspects of performance and flexibility.
Keywords
Neural network; Digital hardware; SIMD; Modular structure;
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