Memristive Monte Carlo DropConnect crossbar array enabled by device and algorithm co-design-Reference-Cited by-同舟云学术

Memristive Monte Carlo DropConnect crossbar array enabled by device and algorithm co-design

Published:2024 Issue:17 Volume:11 Page:4094-4103
ISSN:2051-6347
Container-title:Materials Horizons
language:en
Short-container-title:Mater. Horiz.

Author:

Kim Do Hoon¹^ORCID,Cheong Woon Hyung²^ORCID,Song Hanchan¹,Jeon Jae Bum¹,Kim Geunyoung¹,Kim Kyung Min¹^ORCID

Affiliation:

1. Department of Materials Science and Engineering, Korea Advanced Institute of Science and Technology (KAIST), Daejeon 34141, Republic of Korea

2. Applied Science Research Institute, Korea Advanced Institute of Science and Technology (KAIST), Daejeon 34141, Republic of Korea

Abstract

A one-selector-one-memristor crossbar array was developed, capable of driving Monte Carlo DropConnect network. This could be achieved through a hardware and algorithm co-design approach, involving mutual improvement of them.

Funder

National NanoFab Center

National Research Foundation of Korea

Korea Advanced Institute of Science and Technology

Publisher

Royal Society of Chemistry (RSC)

Link

http://pubs.rsc.org/en/content/articlepdf/2024/MH/D3MH02049E

Reference43 articles.

1. Integration and Co-design of Memristive Devices and Algorithms for Artificial Intelligence

2. Opportunities for neuromorphic computing algorithms and applications

3. Training and operation of an integrated neuromorphic network based on metal-oxide memristors

4. Memristor‐Based Analog Computation and Neural Network Classification with a Dot Product Engine

5. Memristive crossbar arrays for brain-inspired computing

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