Binarized Neural Network with Stochastic Memristors

Olga Krestinskaya, Otaniyoz Otaniyozov, Alex Pappachen James

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

Abstract

This paper proposes the analog hardware implementation of Binarized Neural Network (BNN). Most of the existing hardware implementations of neural networks do not consider the memristor variability issue and its effect on the overall system performance. In this work, we investigate the variability in memristive devices in crossbar dot product computation and leakage currents in the proposed BNN, and show how it effects the overall system performance.

Original languageEnglish
Title of host publicationProceedings 2019 IEEE International Conference on Artificial Intelligence Circuits and Systems, AICAS 2019
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages274-275
Number of pages2
ISBN (Electronic)9781538678848
DOIs
Publication statusPublished - Mar 1 2019
Event1st IEEE International Conference on Artificial Intelligence Circuits and Systems, AICAS 2019 - Hsinchu, Taiwan
Duration: Mar 18 2019Mar 20 2019

Publication series

NameProceedings 2019 IEEE International Conference on Artificial Intelligence Circuits and Systems, AICAS 2019

Conference

Conference1st IEEE International Conference on Artificial Intelligence Circuits and Systems, AICAS 2019
CountryTaiwan
CityHsinchu
Period3/18/193/20/19

Fingerprint

Memristors
Neural networks
Hardware
Leakage currents

Keywords

  • Analog Circuits
  • BNN
  • Memristor Variability
  • Memristors

ASJC Scopus subject areas

  • Artificial Intelligence
  • Hardware and Architecture
  • Electrical and Electronic Engineering

Cite this

Krestinskaya, O., Otaniyozov, O., & James, A. P. (2019). Binarized Neural Network with Stochastic Memristors. In Proceedings 2019 IEEE International Conference on Artificial Intelligence Circuits and Systems, AICAS 2019 (pp. 274-275). [8771565] (Proceedings 2019 IEEE International Conference on Artificial Intelligence Circuits and Systems, AICAS 2019). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/AICAS.2019.8771565

Binarized Neural Network with Stochastic Memristors. / Krestinskaya, Olga; Otaniyozov, Otaniyoz; James, Alex Pappachen.

Proceedings 2019 IEEE International Conference on Artificial Intelligence Circuits and Systems, AICAS 2019. Institute of Electrical and Electronics Engineers Inc., 2019. p. 274-275 8771565 (Proceedings 2019 IEEE International Conference on Artificial Intelligence Circuits and Systems, AICAS 2019).

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

Krestinskaya, O, Otaniyozov, O & James, AP 2019, Binarized Neural Network with Stochastic Memristors. in Proceedings 2019 IEEE International Conference on Artificial Intelligence Circuits and Systems, AICAS 2019., 8771565, Proceedings 2019 IEEE International Conference on Artificial Intelligence Circuits and Systems, AICAS 2019, Institute of Electrical and Electronics Engineers Inc., pp. 274-275, 1st IEEE International Conference on Artificial Intelligence Circuits and Systems, AICAS 2019, Hsinchu, Taiwan, 3/18/19. https://doi.org/10.1109/AICAS.2019.8771565
Krestinskaya O, Otaniyozov O, James AP. Binarized Neural Network with Stochastic Memristors. In Proceedings 2019 IEEE International Conference on Artificial Intelligence Circuits and Systems, AICAS 2019. Institute of Electrical and Electronics Engineers Inc. 2019. p. 274-275. 8771565. (Proceedings 2019 IEEE International Conference on Artificial Intelligence Circuits and Systems, AICAS 2019). https://doi.org/10.1109/AICAS.2019.8771565
Krestinskaya, Olga ; Otaniyozov, Otaniyoz ; James, Alex Pappachen. / Binarized Neural Network with Stochastic Memristors. Proceedings 2019 IEEE International Conference on Artificial Intelligence Circuits and Systems, AICAS 2019. Institute of Electrical and Electronics Engineers Inc., 2019. pp. 274-275 (Proceedings 2019 IEEE International Conference on Artificial Intelligence Circuits and Systems, AICAS 2019).
@inproceedings{e4ce131a51134d359f50eb4d0fd054df,
title = "Binarized Neural Network with Stochastic Memristors",
abstract = "This paper proposes the analog hardware implementation of Binarized Neural Network (BNN). Most of the existing hardware implementations of neural networks do not consider the memristor variability issue and its effect on the overall system performance. In this work, we investigate the variability in memristive devices in crossbar dot product computation and leakage currents in the proposed BNN, and show how it effects the overall system performance.",
keywords = "Analog Circuits, BNN, Memristor Variability, Memristors",
author = "Olga Krestinskaya and Otaniyoz Otaniyozov and James, {Alex Pappachen}",
year = "2019",
month = "3",
day = "1",
doi = "10.1109/AICAS.2019.8771565",
language = "English",
series = "Proceedings 2019 IEEE International Conference on Artificial Intelligence Circuits and Systems, AICAS 2019",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "274--275",
booktitle = "Proceedings 2019 IEEE International Conference on Artificial Intelligence Circuits and Systems, AICAS 2019",
address = "United States",

}

TY - GEN

T1 - Binarized Neural Network with Stochastic Memristors

AU - Krestinskaya, Olga

AU - Otaniyozov, Otaniyoz

AU - James, Alex Pappachen

PY - 2019/3/1

Y1 - 2019/3/1

N2 - This paper proposes the analog hardware implementation of Binarized Neural Network (BNN). Most of the existing hardware implementations of neural networks do not consider the memristor variability issue and its effect on the overall system performance. In this work, we investigate the variability in memristive devices in crossbar dot product computation and leakage currents in the proposed BNN, and show how it effects the overall system performance.

AB - This paper proposes the analog hardware implementation of Binarized Neural Network (BNN). Most of the existing hardware implementations of neural networks do not consider the memristor variability issue and its effect on the overall system performance. In this work, we investigate the variability in memristive devices in crossbar dot product computation and leakage currents in the proposed BNN, and show how it effects the overall system performance.

KW - Analog Circuits

KW - BNN

KW - Memristor Variability

KW - Memristors

UR - http://www.scopus.com/inward/record.url?scp=85070467306&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=85070467306&partnerID=8YFLogxK

U2 - 10.1109/AICAS.2019.8771565

DO - 10.1109/AICAS.2019.8771565

M3 - Conference contribution

T3 - Proceedings 2019 IEEE International Conference on Artificial Intelligence Circuits and Systems, AICAS 2019

SP - 274

EP - 275

BT - Proceedings 2019 IEEE International Conference on Artificial Intelligence Circuits and Systems, AICAS 2019

PB - Institute of Electrical and Electronics Engineers Inc.

ER -