File(s) not publicly available
An efficient SpiNNaker implementation of the Neural Engineering Framework
conference contribution
posted on 2023-06-09, 07:05 authored by Andrew Mundy, James KnightJames Knight, Terrence C Stewart, Steve FurberBy building and simulating neural systems we hope to understand how the brain may work and use this knowledge to build neural and cognitive systems to tackle engineering problems. The Neural Engineering Framework (NEF) is a hypothesis about how such systems may be constructed and has recently been used to build the world's first functional brain model, Spaun. However, while the NEF simplifies the design of neural networks, simulating them using standard computer hardware is still computationally expensive - often running far slower than biological real-time and scaling very poorly: problems the SpiNNaker neuromorphic simulator was designed to solve. In this paper we (1) argue that employing the same model of computation used for simulating general purpose spiking neural networks on SpiNNaker for NEF models results in suboptimal use of the architecture, and (2) provide and evaluate an alternative simulation scheme which overcomes the memory and compute challenges posed by the NEF. This proposed method uses factored weight matrices to reduce memory usage by around 90% and, in some cases, simulate 2000 neurons on a processing core - double the SpiNNaker architectural target.
History
Publication status
- Published
Journal
Proceedings of the 2015 International Joint Conference on Neural Networks (IJCNN); Killarney, Ireland; 12-17 July 2015ISSN
2161-4393Publisher
Institute of Electrical and Electronics EngineersExternal DOI
Page range
1-8Book title
2015 International Joint Conference on Neural Networks (IJCNN)ISBN
9781479919611Department affiliated with
- Informatics Publications
Research groups affiliated with
- Centre for Computational Neuroscience and Robotics Publications
- Sussex Neuroscience Publications
Full text available
- No
Peer reviewed?
- Yes
Legacy Posted Date
2017-07-18Usage metrics
Categories
No categories selectedKeywords
Licence
Exports
RefWorks
BibTeX
Ref. manager
Endnote
DataCite
NLM
DC