Neuromorphic computing using non-volatile memory

Dense crossbar arrays of non-volatile memory (NVM) devices represent one possible path for implementing massively-parallel and highly energy-efficient neuromorphic computing systems. We first review recent advances in the application of NVM devices to three computing paradigms: spiking neural networ...

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Bibliographic Details
Published in:	Advances in physics: X Vol. 2; no. 1; pp. 89 - 124
Main Authors:	Burr, Geoffrey W., Shelby, Robert M., Sebastian, Abu, Kim, Sangbum, Kim, Seyoung, Sidler, Severin, Virwani, Kumar, Ishii, Masatoshi, Narayanan, Pritish, Fumarola, Alessandro, Sanches, Lucas L., Boybat, Irem, Le Gallo, Manuel, Moon, Kibong, Woo, Jiyoo, Hwang, Hyunsang, Leblebici, Yusuf
Format:	Journal Article
Language:	English
Published:	Abingdon Taylor & Francis 01-01-2017 Taylor & Francis Ltd Taylor & Francis Group
Subjects:	Algorithms Arrays Artificial neural networks Back propagation Computation Linearity Machine learning Mathematical analysis Matrix algebra Matrix methods Memory devices Multiplication Neural networks Neuromorphic computing non-volatile memory NVM-based neurons NVM-based synapses Power management Random access memory Resistance spike-timing-dependent-plasticity spiking neural networks vector-matrix multiplication
Online Access:	Get full text
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