Deployment Pipeline from Rockpool to Xylo for Edge Computing

Peng Zhou, Dylan R. Muir
12/15/2024
cs.NEcs.AI

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Abstract

Deploying Spiking Neural Networks (SNNs) on the Xylo neuromorphic chip via the Rockpool framework represents a significant advancement in achieving ultra-low-power consumption and high computational efficiency for edge applications. This paper details a novel deployment pipeline, emphasizing the integration of Rockpool's capabilities with Xylo's architecture, and evaluates the system's performance in terms of energy efficiency and accuracy. The unique advantages of the Xylo chip, including its digital spiking architecture and event-driven processing model, are highlighted to demonstrate its suitability for real-time, power-sensitive applications.

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Cite this paper

@article{zhou2024deployment,
  title  = {Deployment Pipeline from Rockpool to Xylo for Edge Computing},
  author = {Peng Zhou and Dylan R. Muir},
  year   = {2024},
  eprint = {2412.11047},
  archivePrefix = {arXiv},
  url    = {http://arxiv.org/abs/2412.11047v1}
}

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