AnalogNAS: A Neural Network Design Framework for Accurate Inference with Analog In-Memory Computing-Reference-Cited by-同舟云学术

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AnalogNAS: A Neural Network Design Framework for Accurate Inference with Analog In-Memory Computing

Published:2023-07 Issue: Volume: Page:
ISSN:
Container-title:2023 IEEE International Conference on Edge Computing and Communications (EDGE)
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Author:

Benmeziane Hadjer¹,Lammie Corey²,Boybat Irem²,Rasch Malte³,Le Gallo Manuel²,Tsai Hsinyu⁴,Muralidhar Ramachandran³,Niar Smail¹,Hamza Ouarnoughi¹,Narayanan Vijay³,Sebastian Abu²,El Maghraoui Kaoutar³

Affiliation:

1. Univ. Polytechnique Hauts-de-France,CNRS, UMR 8201 - LAMIH,Valenciennes,France,F-59313

2. IBM Research Europe,Rüschlikon,Switzerland,8803

3. IBM T. J. Watson Research Center,Yorktown Heights,NY,USA,10598

4. IBM Research Almaden,San Jose,CA,USA

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10234182/10234229/10234291.pdf?arnumber=10234291

Reference46 articles.

1. Memory devices and applications for in-memory computing

2. Accurate deep neural network inference using computational phase-change memory

3. MemTorch: An Open-source Simulation Framework for Memristive Deep Learning Systems

4. Temperature sensitivity of analog in-memory computing using phase-change memory

5. Mobilenets: Efficient convolutional neural networks for mobile vision applications;Howard;CoRR,2017

Cited by 1 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. Neural architecture search for in-memory computing-based deep learning accelerators;Nature Reviews Electrical Engineering;2024-05-20

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