Co-design of DNN model optimization for binary ReRAM array in-memory processing

Yue Guan, Takashi Ohsawa

研究成果: Conference contribution

3 被引用数 (Scopus)

抄録

In this work, a novel design of ReRAM neuromorphic system is proposed to process deep neural network (DNN) fully in array efficiently. A binary neural network model is constructed and optimized on MNIST dataset. The obtained model is simulated to be processed with the proposed ReRAM array. Co-design between hardware and network model optimization in software is analyzed to achieve feasible hardware design and generalizable model. Deployed with such co-design model, ReRAM array processes DNN with high robustness against fabrication fluctuation.

本文言語English
ホスト出版物のタイトル2019 IEEE 11th International Memory Workshop, IMW 2019
出版社Institute of Electrical and Electronics Engineers Inc.
ISBN(電子版)9781728109817
DOI
出版ステータスPublished - 2019 5
イベント11th IEEE International Memory Workshop, IMW 2019 - Montterey, United States
継続期間: 2019 5 122019 5 15

出版物シリーズ

名前2019 IEEE 11th International Memory Workshop, IMW 2019

Conference

Conference11th IEEE International Memory Workshop, IMW 2019
CountryUnited States
CityMontterey
Period19/5/1219/5/15

ASJC Scopus subject areas

  • Hardware and Architecture
  • Electrical and Electronic Engineering

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