Opportunities for neuromorphic computing algorithms and applications

Neuromorphic computing technologies will be important for the future of computing, but much of the work in neuromorphic computing has focused on hardware development. Here, we review recent results in neuromorphic computing algorithms and applications. We highlight characteristics of neuromorphic co...

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Bibliographic Details
Published in:Nature Computational Science Vol. 2; no. 1; pp. 10 - 19
Main Authors: Schuman, Catherine D., Kulkarni, Shruti R., Parsa, Maryam, Mitchell, J. Parker, Date, Prasanna, Kay, Bill
Format: Journal Article
Language:English
Published: New York Nature Publishing Group US 01.01.2022
Nature Publishing Group
Springer Nature
Subjects:
639/705/1042
639/705/117
Algorithms
Artificial intelligence
Brain research
Computer Science
Computers
Energy consumption
MATHEMATICS AND COMPUTING
Memory
Neural networks
Neuromorphic computing
Neurons
Perspective
Semiconductors
ISSN:2662-8457, 2662-8457
Online Access:Get full text
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Summary:Neuromorphic computing technologies will be important for the future of computing, but much of the work in neuromorphic computing has focused on hardware development. Here, we review recent results in neuromorphic computing algorithms and applications. We highlight characteristics of neuromorphic computing technologies that make them attractive for the future of computing and we discuss opportunities for future development of algorithms and applications on these systems. There is still a wide variety of challenges that restrict the rapid growth of neuromorphic algorithmic and application development. Addressing these challenges is essential for the research community to be able to effectively use neuromorphic computers in the future.
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USDOE Office of Science (SC), Advanced Scientific Computing Research (ASCR)
AC05-00OR22725; SC0022566
ISSN:2662-8457
2662-8457
DOI:10.1038/s43588-021-00184-y