A compact Multi-Chip-Module Implementation of a Multi-Precision Neural Network Classifier

Amine Bermak Dominique Martinez 1
1 CORTEX - Neuromimetic intelligence
INRIA Lorraine, LORIA - Laboratoire Lorrain de Recherche en Informatique et ses Applications
Abstract : This paper describes a novel Multi-Chip Module (MCM) digital implementation of a reconfigurable multi-precision neural network classifier. The design is based on a scalable systolic architecture with a user defined topology and arithmetic precision of the neural network. Indeed, the MCM integrates 64/32/16 neurons with a corresponding accuracy of 4/8/16-bits. A prototype has been designed and successfully tested in CMOS 0.7 $\mu$m technology.
Mots-clés : réseaux de neurones neural networks vlsi
Type de document :
Communication dans un congrès
IEEE International Symposium on Circuits and Systems - ISCAS'2001, May 2001, Sydney, Australia, 3, pp.249-252, 2001
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https://hal.inria.fr/inria-00108072
Contributeur : Publications Loria <>
Soumis le : jeudi 19 octobre 2006 - 15:40:46
Dernière modification le : jeudi 11 janvier 2018 - 06:19:48

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  • HAL Id : inria-00108072, version 1

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INRIA | LORIA | UNIV-LORRAINE

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Amine Bermak, Dominique Martinez. A compact Multi-Chip-Module Implementation of a Multi-Precision Neural Network Classifier. IEEE International Symposium on Circuits and Systems - ISCAS'2001, May 2001, Sydney, Australia, 3, pp.249-252, 2001. 〈inria-00108072〉

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