A Software-Circuit-Device Co-Optimization Framework for Neuromorphic Inference Circuits-Reference-Cited by-同舟云学术

A Software-Circuit-Device Co-Optimization Framework for Neuromorphic Inference Circuits

Published:2022 Issue: Volume:10 Page:41078-41086
ISSN:2169-3536
Container-title:IEEE Access
language:
Short-container-title:IEEE Access

Author:

Quibuyen Paul¹^ORCID,Jiao Tom¹^ORCID,Wong Hiu Yung¹^ORCID

Affiliation:

1. Electrical Engineering Department, San José State University, San Jose, CA, USA

Funder

San José State University College of Engineering Small Group Project Team Fund

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

General Engineering,General Materials Science,General Computer Science,Electrical and Electronic Engineering

Link

http://xplorestaging.ieee.org/ielx7/6287639/9668973/09758702.pdf?arnumber=9758702

Reference40 articles.

1. Study of ReRAM neuromorphic circuit performance using DTCO simulation framework;nguyen,2021

2. Efficient implementation of multi-channel convolution in monolithic 3D ReRAM crossbar;ko;arXiv 2004 00243,2020

3. Optimizing Weight Mapping and Data Flow for Convolutional Neural Networks on RRAM Based Processing-In-Memory Architecture

4. 2022 IEEE 4th international conference on artificial intelligence circuits and systems (AICAS);quibuyen;Proc IEEE 4th Int Conf Artif Intell Circuits Syst (AICAS),2022

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3. Effect of ReRAM Neuromorphic Circuit Array Variation and Fault on Inference Accuracy;2022 IEEE 4th International Conference on Artificial Intelligence Circuits and Systems (AICAS);2022-06-13