Spin-Transfer Torque Magnetic neuron for low power neuromorphic computing

Abhronil Sengupta, Kaushik Roy

Research output: Chapter in Book/Report/Conference proceedingConference contribution

19 Scopus citations

Abstract

Neuromorphic computing attempts to emulate the remarkable efficiency of the human brain in vision, perception and cognition related tasks. Nanoscale devices that offer a direct mapping to the underlying neural computations have emerged as a promising candidate for such neuromorphic architectures. In this paper, a Magnetic Tunneling Junction (MTJ) has been proposed to perform the thresholding operation of a biological neuron. A crossbar array consisting of programmable resistive synapses generates an excitatory / inhibitory charge current input to the neuron. The magnetization of the free layer of the MTJ is manipulated by Spin-Transfer Torque generated by the net synaptic current. Algorithm, device and circuit co-simulation framework suggest the possibility of ∼ 1.63 - 1.79x power savings in comparison to a 45nm digital CMOS implementation.

Original languageEnglish (US)
Title of host publication2015 International Joint Conference on Neural Networks, IJCNN 2015
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781479919604, 9781479919604, 9781479919604, 9781479919604
DOIs
StatePublished - Sep 28 2015
EventInternational Joint Conference on Neural Networks, IJCNN 2015 - Killarney, Ireland
Duration: Jul 12 2015Jul 17 2015

Publication series

NameProceedings of the International Joint Conference on Neural Networks
Volume2015-September

Conference

ConferenceInternational Joint Conference on Neural Networks, IJCNN 2015
Country/TerritoryIreland
CityKillarney
Period7/12/157/17/15

All Science Journal Classification (ASJC) codes

  • Software
  • Artificial Intelligence

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