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A study on supporting spiking neural network models based on multiple neuromorphic processors

Authors
Hong B.Cho J.Kim B.Min H.Hong J.Lee K.M.
Issue Date
Sep-2019
Publisher
Association for Computing Machinery, Inc
Keywords
Neuromorphic computing; Neuromorphic porcessor; Spiking neural networks
Citation
Proceedings of the 2019 Research in Adaptive and Convergent Systems, RACS 2019, pp.131 - 132
Journal Title
Proceedings of the 2019 Research in Adaptive and Convergent Systems, RACS 2019
Start Page
131
End Page
132
URI
http://scholarworks.bwise.kr/ssu/handle/2018.sw.ssu/35492
DOI
10.1145/3338840.3355692
ISSN
0000-0000
Abstract
Neuromorphic computing or neuromorphic engineering is an engineering discipline that attempts to simulate human brain function by creating circuits that mimic the shape of neurons. In the field of neuromorphic computing, neuromorphic processors are used. There are many types of neuromorphic processors, and there are neuromorphic processors implemented based on FPGAS. Neuromorphic processors use an artificial intelligence model called a spiking neural network. Each neuromorphic processor has different characteristics. For example, the spiking neural network model supported by each supported neuromorphic processor may be different. In this paper, we propose a service architecture named NAAL (Neuromorphic Architecture Abstract Layer) that enables the use of spiking neural networks by virtualizing various neuromorphic processors with different characteristics. © 2019 Association for Computing Machinery.
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