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Communication Dans Un Congrès Année : 2021

Exploration of Ultra Low Power Architectures for Machine Learning at the Edge

Theo Soriano
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David Novo
Pascal Benoit

Résumé

In the field of IoT, sensor nodes have received considerable attention from both academia and industry. These small low power devices are designed to embed very simple applications, they can perform some processing, gather sensory data and communicate with other nodes in the network. However, recent advances in machine learning have made it possible to consider the implementation of smart applications in such constrained systems. In this work, we defined a basic parametric model and designed a generic microcontroller architecture to evaluate the energy profile of such applications in low-power sensor nodes.
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Dates et versions

hal-03596094 , version 1 (03-03-2022)

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  • HAL Id : hal-03596094 , version 1

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Theo Soriano, David Novo, Pascal Benoit. Exploration of Ultra Low Power Architectures for Machine Learning at the Edge. 15ème Colloque National du GDR SoC², Jun 2021, Rennes, France. ⟨hal-03596094⟩
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