Parasitic-Aware Modeling and Neural Network Training Scheme for Energy-Efficient Processing-in-Memory With Resistive Crossbar Array
Author:
Affiliation:
1. School of Electrical and Electronic Engineering, Nanyang Technological University, Singapore
2. A*STAR, Institute of Microelectronics (IME), Singapore
Funder
Agency for Science, Technology and Research (A*STAR), Singapore, under the Nanosystems at the Edge Program
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Subject
Electrical and Electronic Engineering
Link
http://xplorestaging.ieee.org/ielx7/5503868/9794907/09766328.pdf?arnumber=9766328
Reference33 articles.
1. Modeling and Analysis of Passive Switching Crossbar Arrays
2. A fully integrated reprogrammable memristor–CMOS system for efficient multiply–accumulate operations
3. Parasitic-Aware Modelling for Neural Networks Implemented with Memristor Crossbar Array
4. Enabling Neuromorphic Computing: BEOL Integration of CMOS RRAM Chip and Programmable Performance
5. Fully hardware-implemented memristor convolutional neural network
Cited by 8 articles. 订阅此论文施引文献 订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献
1. Memory Switching versus Threshold Memory Switching: Finding a Promising Synaptic Device for Brain-Inspired Artificial Learning Systems;ACS Applied Engineering Materials;2024-07-24
2. A Calibratable Model for Fast Energy Estimation of MVM Operations on RRAM Crossbars;2024 IEEE 6th International Conference on AI Circuits and Systems (AICAS);2024-04-22
3. Compact Modeling and Mitigation of Parasitics in Crosspoint Accelerators of Neural Networks;IEEE Transactions on Electron Devices;2024-03
4. Binary‐Stochasticity‐Enabled Highly Efficient Neuromorphic Deep Learning Achieves Better‐than‐Software Accuracy;Advanced Intelligent Systems;2023-11-12
5. ECG Classification using Binary CNN on RRAM Crossbar with Nonidealities-Aware Training, Readout Compensation and CWT Preprocessing;2023 IEEE Biomedical Circuits and Systems Conference (BioCAS);2023-10-19
1.学者识别学者识别
2.学术分析学术分析
3.人才评估人才评估
"同舟云学术"是以全球学者为主线，采集、加工和组织学术论文而形成的新型学术文献查询和分析系统，可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容，当前同舟云学术共收录了国内外主流学术期刊6万余种，收集的期刊论文及会议论文总量共计约1.5亿篇，并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询！咨询电话：010-8811{复制后删除}0370
www.globalauthorid.com
TOP
Copyright © 2019-2024 北京同舟云网络信息技术有限公司 京公网安备11010802033243号 京ICP备18003416号-3