A 64 Kb Reconfigurable Full-Precision Digital ReRAM-Based Compute-In-Memory for Artificial Intelligence Applications-Reference-Cited by-同舟云学术

A 64 Kb Reconfigurable Full-Precision Digital ReRAM-Based Compute-In-Memory for Artificial Intelligence Applications

Published:2022-08 Issue:8 Volume:69 Page:3284-3296
ISSN:1549-8328
Container-title:IEEE Transactions on Circuits and Systems I: Regular Papers
language:
Short-container-title:IEEE Trans. Circuits Syst. I

Author:

Sharma Vishal¹^ORCID,Kim Hyunjoon¹^ORCID,Kim Tony Tae-Hyoung¹^ORCID

Affiliation:

1. School of Electrical and Electronic Engineering, Nanyang Technological University, Singapore

Funder

RIE2020 Agency for Science, Technology and Research (ASTAR) Advanced Manufacturing and Engineering (AME) Industry Alignment Fund–Industry Collaboration Project

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Electrical and Electronic Engineering,Hardware and Architecture

Link

http://xplorestaging.ieee.org/ielx7/8919/9841618/09763886.pdf?arnumber=9763886

Reference35 articles.

1. ReRAM Device and Circuit Co-Design Challenges in Nano-scale CMOS Technology

2. Reconfigurable 2T2R ReRAM Architecture for Versatile Data Storage and Computing In-Memory

3. IMAC: In-Memory Multi-Bit Multiplication and ACcumulation in 6T SRAM Array

4. A Multi-Functional In-Memory Inference Processor Using a Standard 6T SRAM Array

5. A ReRAM-Based Computing-in-Memory Convolutional-Macro With Customized 2T2R Bit-Cell for AIoT Chip IP Applications

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