Deployment Pipeline from Rockpool to Xylo for Edge Computing

December 15, 2024 ยท Declared Dead ยท ๐Ÿ› arXiv.org

๐Ÿ‘ป CAUSE OF DEATH: Ghosted
No code link whatsoever

"No code URL or promise found in abstract"

Evidence collected by the PWNC Scanner

Authors Peng Zhou, Dylan R. Muir arXiv ID 2412.11047 Category cs.NE: Neural & Evolutionary Cross-listed cs.AI Citations 0 Venue arXiv.org Last Checked 4 months ago
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.
Community shame:
Not yet rated
Community Contributions

Found the code? Know the venue? Think something is wrong? Let us know!

๐Ÿ“œ Similar Papers

In the same crypt โ€” Neural & Evolutionary

๐Ÿ”ฎ ๐Ÿ”ฎ The Ethereal

LSTM: A Search Space Odyssey

Klaus Greff, Rupesh Kumar Srivastava, ... (+3 more)

cs.NE ๐Ÿ› IEEE TNNLS ๐Ÿ“š 6.0K cites 11 years ago

Died the same way โ€” ๐Ÿ‘ป Ghosted