Advancing Neuromorphic Computing With Loihi: A Survey of Results and Outlook

Deep artificial neural networks apply principles of the brain's information processing that led to breakthroughs in machine learning spanning many problem domains. Neuromorphic computing aims to take this a step further to chips more directly inspired by the form and function of biological neur...

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Veröffentlicht in:	Proceedings of the IEEE Jg. 109; H. 5; S. 911 - 934
Hauptverfasser:	Davies, Mike, Wild, Andreas, Orchard, Garrick, Sandamirskaya, Yulia, Guerra, Gabriel A. Fonseca, Joshi, Prasad, Plank, Philipp, Risbud, Sumedh R.
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	New York IEEE 01.05.2021 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Schlagworte:	Adaptive control Artificial neural networks Biological neural networks Brain Brain modeling Brain research Chip formation Computation Computational modeling Computer architecture Data processing Deep learning Domains Machine learning Microprocessors neural network hardware Neural networks Neuromorphic computing Neuromorphic engineering neuromorphics Neurons Optimization Spikes
ISSN:	0018-9219, 1558-2256
Online-Zugang:	Volltext
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