In-Memory Computing Primitive for Sensor Data Fusion in 28 nm HKMG FeFET Technology

K. Ni, B. Grisafe, W. Chakraborty, A. K. Saha, S. Dutta, M. Jerry, J. A. Smith, Sumeet Kumar Gupta, S. Datta

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

1 Citation (Scopus)

Abstract

In this work, we exploit the spatio-temporal switching dynamics of ferroelectric polarization to realize an energy-efficient, and massively-parallel in-memory computational primitive for at-node sensor data fusion and analytics based on an industrial 28nm HKMG FeFET technology [1]. We demonstrate: (i) the spatio-temporal dynamics of polarization switching in HfO 2 -based ferroelectrics under the stimuli of sub-coercive voltage pulses using experiments and phase-field modeling; (ii) an inherent rectifying conductance accumulation characteristic in FeFET with a large dynamic range of G/G > 100 in the case of 3.0V, 50ns gate pulses; (iii) transition to more abrupt accumulation characteristics due to single/few domain polarization switching in scaled FeFET (34nm L G ); and (iv) successful detection of physiological anomalies from realworld multi-modal sensor data streams.

Original languageEnglish (US)
Title of host publication2018 IEEE International Electron Devices Meeting, IEDM 2018
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages16.1.1-16.1.4
ISBN (Electronic)9781728119878
DOIs
StatePublished - Jan 16 2019
Event64th Annual IEEE International Electron Devices Meeting, IEDM 2018 - San Francisco, United States
Duration: Dec 1 2018Dec 5 2018

Publication series

NameTechnical Digest - International Electron Devices Meeting, IEDM
Volume2018-December
ISSN (Print)0163-1918

Conference

Conference64th Annual IEEE International Electron Devices Meeting, IEDM 2018
CountryUnited States
CitySan Francisco
Period12/1/1812/5/18

Fingerprint

Sensor data fusion
multisensor fusion
Polarization
Data storage equipment
Ferroelectric materials
sensors
polarization
pulses
stimuli
dynamic range
anomalies
Sensors
Electric potential
electric potential
Experiments
energy

All Science Journal Classification (ASJC) codes

  • Electronic, Optical and Magnetic Materials
  • Condensed Matter Physics
  • Electrical and Electronic Engineering
  • Materials Chemistry

Cite this

Ni, K., Grisafe, B., Chakraborty, W., Saha, A. K., Dutta, S., Jerry, M., ... Datta, S. (2019). In-Memory Computing Primitive for Sensor Data Fusion in 28 nm HKMG FeFET Technology. In 2018 IEEE International Electron Devices Meeting, IEDM 2018 (pp. 16.1.1-16.1.4). [8614527] (Technical Digest - International Electron Devices Meeting, IEDM; Vol. 2018-December). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/IEDM.2018.8614527
Ni, K. ; Grisafe, B. ; Chakraborty, W. ; Saha, A. K. ; Dutta, S. ; Jerry, M. ; Smith, J. A. ; Gupta, Sumeet Kumar ; Datta, S. / In-Memory Computing Primitive for Sensor Data Fusion in 28 nm HKMG FeFET Technology. 2018 IEEE International Electron Devices Meeting, IEDM 2018. Institute of Electrical and Electronics Engineers Inc., 2019. pp. 16.1.1-16.1.4 (Technical Digest - International Electron Devices Meeting, IEDM).
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abstract = "In this work, we exploit the spatio-temporal switching dynamics of ferroelectric polarization to realize an energy-efficient, and massively-parallel in-memory computational primitive for at-node sensor data fusion and analytics based on an industrial 28nm HKMG FeFET technology [1]. We demonstrate: (i) the spatio-temporal dynamics of polarization switching in HfO 2 -based ferroelectrics under the stimuli of sub-coercive voltage pulses using experiments and phase-field modeling; (ii) an inherent rectifying conductance accumulation characteristic in FeFET with a large dynamic range of G/G > 100 in the case of 3.0V, 50ns gate pulses; (iii) transition to more abrupt accumulation characteristics due to single/few domain polarization switching in scaled FeFET (34nm L G ); and (iv) successful detection of physiological anomalies from realworld multi-modal sensor data streams.",
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Ni, K, Grisafe, B, Chakraborty, W, Saha, AK, Dutta, S, Jerry, M, Smith, JA, Gupta, SK & Datta, S 2019, In-Memory Computing Primitive for Sensor Data Fusion in 28 nm HKMG FeFET Technology. in 2018 IEEE International Electron Devices Meeting, IEDM 2018., 8614527, Technical Digest - International Electron Devices Meeting, IEDM, vol. 2018-December, Institute of Electrical and Electronics Engineers Inc., pp. 16.1.1-16.1.4, 64th Annual IEEE International Electron Devices Meeting, IEDM 2018, San Francisco, United States, 12/1/18. https://doi.org/10.1109/IEDM.2018.8614527

In-Memory Computing Primitive for Sensor Data Fusion in 28 nm HKMG FeFET Technology. / Ni, K.; Grisafe, B.; Chakraborty, W.; Saha, A. K.; Dutta, S.; Jerry, M.; Smith, J. A.; Gupta, Sumeet Kumar; Datta, S.

2018 IEEE International Electron Devices Meeting, IEDM 2018. Institute of Electrical and Electronics Engineers Inc., 2019. p. 16.1.1-16.1.4 8614527 (Technical Digest - International Electron Devices Meeting, IEDM; Vol. 2018-December).

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

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Ni K, Grisafe B, Chakraborty W, Saha AK, Dutta S, Jerry M et al. In-Memory Computing Primitive for Sensor Data Fusion in 28 nm HKMG FeFET Technology. In 2018 IEEE International Electron Devices Meeting, IEDM 2018. Institute of Electrical and Electronics Engineers Inc. 2019. p. 16.1.1-16.1.4. 8614527. (Technical Digest - International Electron Devices Meeting, IEDM). https://doi.org/10.1109/IEDM.2018.8614527