SENECA: building a fully digital neuromorphic processor, design trade-offs and challenges

SENECA: building a fully digital neuromorphic processor, design trade-offs and challenges

Neuromorphic processors aim to emulate the biological principles of the brain to achieve high efficiency with low power consumption. However, the lack of flexibility in most neuromorphic architecture designs results in significant performance loss and inefficient memory usage when mapping various ne...

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Detalhes bibliográficos
Principais autores: Guangzhi Tang, Kanishkan Vadivel, Yingfu Xu, Refik Bilgic, Kevin Shidqi, Paul Detterer, Stefano Traferro, Mario Konijnenburg, Manolis Sifalakis, Gert-Jan van Schaik, Amirreza Yousefzadeh
Formato: Artigo
Idioma:English
Publicado em: Frontiers Media S.A. 2023-06-01
coleção:Frontiers in Neuroscience
Assuntos:
event-based neuromorphic processor
spiking neural network
architectural exploration
bio-inspired processing
SENECA
AI accelerator
Acesso em linha:https://www.frontiersin.org/articles/10.3389/fnins.2023.1187252/full

Internet

https://www.frontiersin.org/articles/10.3389/fnins.2023.1187252/full

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