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Author Krichmar, Jeffrey L ♦ Coussy, Philippe ♦ Dutt, Nikil
Source ACM Digital Library
Content type Text
Publisher Association for Computing Machinery (ACM)
File Format PDF
Copyright Year ©2015
Language English
Subject Domain (in DDC) Computer science, information & general works ♦ Data processing & computer science
Subject Keyword GPU computing ♦ Spiking neural networks ♦ Large-scale brain models ♦ Neuromorphic engineering ♦ Simulation tools
Abstract Neuromorphic engineering is a fast growing field with great potential in both understanding the function of the brain, and constructing practical artifacts that build upon this understanding. For these novel chips and hardware to be useful, hardware compatible applications and simulation tools are needed. We argue that the neural circuit approach, in which networks of neuronal elements model brain circuitry are constructed, allows the development of practical applications and the exploration of brain function. At this level of abstraction, networks of $10^{5}$ neurons or larger can be efficiently simulated, but still preserve the neuronal and synaptic dynamics that appear to be important for brain function. Because the neural circuit level supports spiking neural networks and the prevalent Addressable Event Representation (AER) communication scheme, it fits well with many existing neuromorphic hardware and simulation tools. To show how this approach can be applied, we present case studies of spiking neural networks in vision and recognition tasks based on one instantiation of a simulation environment. However, there are now many hardware options, simulation environments, and applications in this emerging field. These approaches and other considerations are discussed.
ISSN 15504832
Age Range 18 to 22 years ♦ above 22 year
Educational Use Research
Education Level UG and PG
Learning Resource Type Article
Publisher Date 2015-04-01
Publisher Place New York
e-ISSN 15504840
Journal ACM Journal on Emerging Technologies in Computing Systems (JETC)
Volume Number 11
Issue Number 4
Page Count 18
Starting Page 1
Ending Page 18

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Source: ACM Digital Library