Neurophysics-inspired parallel architecture with resistive crosspoint array for dictionary learning

Deepak Kadetotad, Zihan Xu, Abinash Mohanty, Pai Yu Chen, Binbin Lin, Jieping Ye, Sarma Vrudhula, Shimeng Yu, Yu Cao, Jae-sun Seo

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

9 Citations (Scopus)

Abstract

This paper proposes a parallel architecture with resistive crosspoint array. The design of its two essential operations, Read and Write, is inspired by the biophysical behavior of a neural system, such as integrate-and-fire and time-dependent synaptic plasticity. The proposed hardware consists of an array with resistive random access memory (RRAM) and CMOS peripheral circuits, which perform matrix product and dictionary update in a fully parallel fashion, at the speed that is independent of the matrix dimension. The entire system is implemented in 65nm CMOS technology with RRAM to realize high-speed unsupervised dictionary learning. As compared to state-of-the-art software approach, it achieves more than 3000X speedup, enabling real-time feature extraction on a single chip.

Original languageEnglish (US)
Title of host publicationIEEE 2014 Biomedical Circuits and Systems Conference, BioCAS 2014 - Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages536-539
Number of pages4
ISBN (Print)9781479923465
DOIs
StatePublished - Dec 9 2014
Event10th IEEE Biomedical Circuits and Systems Conference, BioCAS 2014 - Lausanne, Switzerland
Duration: Oct 22 2014Oct 24 2014

Other

Other10th IEEE Biomedical Circuits and Systems Conference, BioCAS 2014
CountrySwitzerland
CityLausanne
Period10/22/1410/24/14

Fingerprint

Parallel architectures
Glossaries
Data storage equipment
Computer peripheral equipment
Plasticity
Feature extraction
Fires
Hardware
Networks (circuits)

ASJC Scopus subject areas

  • Hardware and Architecture
  • Biomedical Engineering

Cite this

Kadetotad, D., Xu, Z., Mohanty, A., Chen, P. Y., Lin, B., Ye, J., ... Seo, J. (2014). Neurophysics-inspired parallel architecture with resistive crosspoint array for dictionary learning. In IEEE 2014 Biomedical Circuits and Systems Conference, BioCAS 2014 - Proceedings (pp. 536-539). [6981781] Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/BioCAS.2014.6981781

Neurophysics-inspired parallel architecture with resistive crosspoint array for dictionary learning. / Kadetotad, Deepak; Xu, Zihan; Mohanty, Abinash; Chen, Pai Yu; Lin, Binbin; Ye, Jieping; Vrudhula, Sarma; Yu, Shimeng; Cao, Yu; Seo, Jae-sun.

IEEE 2014 Biomedical Circuits and Systems Conference, BioCAS 2014 - Proceedings. Institute of Electrical and Electronics Engineers Inc., 2014. p. 536-539 6981781.

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

Kadetotad, D, Xu, Z, Mohanty, A, Chen, PY, Lin, B, Ye, J, Vrudhula, S, Yu, S, Cao, Y & Seo, J 2014, Neurophysics-inspired parallel architecture with resistive crosspoint array for dictionary learning. in IEEE 2014 Biomedical Circuits and Systems Conference, BioCAS 2014 - Proceedings., 6981781, Institute of Electrical and Electronics Engineers Inc., pp. 536-539, 10th IEEE Biomedical Circuits and Systems Conference, BioCAS 2014, Lausanne, Switzerland, 10/22/14. https://doi.org/10.1109/BioCAS.2014.6981781
Kadetotad D, Xu Z, Mohanty A, Chen PY, Lin B, Ye J et al. Neurophysics-inspired parallel architecture with resistive crosspoint array for dictionary learning. In IEEE 2014 Biomedical Circuits and Systems Conference, BioCAS 2014 - Proceedings. Institute of Electrical and Electronics Engineers Inc. 2014. p. 536-539. 6981781 https://doi.org/10.1109/BioCAS.2014.6981781
Kadetotad, Deepak ; Xu, Zihan ; Mohanty, Abinash ; Chen, Pai Yu ; Lin, Binbin ; Ye, Jieping ; Vrudhula, Sarma ; Yu, Shimeng ; Cao, Yu ; Seo, Jae-sun. / Neurophysics-inspired parallel architecture with resistive crosspoint array for dictionary learning. IEEE 2014 Biomedical Circuits and Systems Conference, BioCAS 2014 - Proceedings. Institute of Electrical and Electronics Engineers Inc., 2014. pp. 536-539
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