An electronic synapse device based on metal oxide resistive switching memory for neuromorphic computation

Shimeng Yu; Yi Wu; Rakesh Jeyasingh; Duygu Kuzum; H. S.Philip Wong

doi:10.1109/TED.2011.2147791

An electronic synapse device based on metal oxide resistive switching memory for neuromorphic computation

Shimeng Yu, Yi Wu, Rakesh Jeyasingh, Duygu Kuzum, H. S.Philip Wong

Research output: Contribution to journal › Article › peer-review

648 Scopus citations

Abstract

The multilevel capability of metal oxide resistive switching memory was explored for the potential use as a single-element electronic synapse device. TiN/HfO_x/AlO}_x/Pt resistive switching cells were fabricated. Multilevel resistance states were obtained by varying the programming voltage amplitudes during the pulse cycling. The cell conductance could be continuously increased or decreased from cycle to cycle, and about 10⁵ endurance cycles were obtained. Nominal energy consumption per operation is in the subpicojoule range with a maximum measured value of 6 pJ. This low energy consumption is attractive for the large-scale hardware implementation of neuromorphic computing and brain simulation. The property of gradual resistance change by pulse amplitudes was exploited to demonstrate the spike-timing-dependent plasticity learning rule, suggesting that metal oxide memory can potentially be used as an electronic synapse device for the emerging neuromorphic computation system.

Original language	English (US)
Article number	5872020
Pages (from-to)	2729-2737
Number of pages	9
Journal	IEEE Transactions on Electron Devices
Volume	58
Issue number	8
DOIs	https://doi.org/10.1109/TED.2011.2147791
State	Published - Aug 2011
Externally published	Yes

Keywords

Bio-inspired system
neuromorphic computation
resistive switching memory
spike-timing-dependent plasticity (STDP)
synapse

ASJC Scopus subject areas

Electronic, Optical and Magnetic Materials
Electrical and Electronic Engineering

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10.1109/TED.2011.2147791

Cite this

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title = "An electronic synapse device based on metal oxide resistive switching memory for neuromorphic computation",

abstract = "The multilevel capability of metal oxide resistive switching memory was explored for the potential use as a single-element electronic synapse device. TiN/HfOx/AlO}x/Pt resistive switching cells were fabricated. Multilevel resistance states were obtained by varying the programming voltage amplitudes during the pulse cycling. The cell conductance could be continuously increased or decreased from cycle to cycle, and about 105 endurance cycles were obtained. Nominal energy consumption per operation is in the subpicojoule range with a maximum measured value of 6 pJ. This low energy consumption is attractive for the large-scale hardware implementation of neuromorphic computing and brain simulation. The property of gradual resistance change by pulse amplitudes was exploited to demonstrate the spike-timing-dependent plasticity learning rule, suggesting that metal oxide memory can potentially be used as an electronic synapse device for the emerging neuromorphic computation system.",

keywords = "Bio-inspired system, neuromorphic computation, resistive switching memory, spike-timing-dependent plasticity (STDP), synapse",

author = "Shimeng Yu and Yi Wu and Rakesh Jeyasingh and Duygu Kuzum and Wong, {H. S.Philip}",

note = "Funding Information: Manuscript received March 1, 2011; revised April 13, 2011; accepted April 17, 2011. Date of publication June 9, 2011; date of current version July 22, 2011. This work was supported in part by DARPA SyNAPSE (DSO Program Manager T. Hylton), by the National Science Foundation (NSF) under NSF ECCS 0950305, by the Nanoelectronics Research Initiative of the Semiconductor Research Corporation through the NSF/NRI Supplement to the NSF NSEC Center for Probing the Nanoscale, and by the member companies of the Stanford Non-Volatile Memory Technology Research Initiative. The work of S. Yu was supported by the Stanford Graduate Fellowship. The work of Y. Wu was supported by a fellowship from the O. G. Villard Engineering Fund at Stanford. The review of this paper was arranged by Editor H. Shang.",

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AU - Wong, H. S.Philip

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An electronic synapse device based on metal oxide resistive switching memory for neuromorphic computation

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