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Communication Dans Un Congrès Année : 2020

Distributed Clique-Based Neural Networks for Data Fusion at the Edge

Résumé

Distributed smart sensors are more and more used in applications such as biomedical or domestic monitoring. However, each sensor broadcasts data wirelessly to the others or to an aggregator, which leads to energy-hungry sensors not ensuring data privacy. To tackle both challenges, this work proposes to distribute a part of a clique-based neural network in each sensor. This scheme allows standardizing data at the sensor level, ensuring privacy if the data is intercepted. Besides, a lower number of bits is transmitted, thus limiting the communication overhead. The circuit implementation is possible with the use of single-cluster iterative clique-based circuits. To this end, a hardware circuit has been fabricated and performs a classification using 115fJ per synaptic event per neuron in 83ns.
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Dates et versions

hal-03377032 , version 1 (13-10-2021)

Identifiants

Citer

Benoit Larras, Antoine Frappé. Distributed Clique-Based Neural Networks for Data Fusion at the Edge. 2020 2nd IEEE International Conference on Artificial Intelligence Circuits and Systems (AICAS), Aug 2020, Genova, Italy. pp.55-58, ⟨10.1109/AICAS48895.2020.9073801⟩. ⟨hal-03377032⟩
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