DeepCAM: A Fully CAM-based Inference Accelerator with Variable Hash Lengths for Energy-efficient Deep Neural Networks-Reference-Cited by-同舟云学术

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DeepCAM: A Fully CAM-based Inference Accelerator with Variable Hash Lengths for Energy-efficient Deep Neural Networks

Published:2023-04 Issue: Volume: Page:
ISSN:
Container-title:2023 Design, Automation & Test in Europe Conference & Exhibition (DATE)
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Author:

Nguyen Duy-Thanh¹,Bhattacharjee Abhiroop¹,Moitra Abhishek¹,Panda Priyadarshini¹

Affiliation:

1. Yale University,Department of Electrical Engineering,USA

Funder

National Science Foundation

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10136870/10136706/10137068.pdf?arnumber=10137068

Reference27 articles.

1. Imagenet classification with deep convolutional neural networks;krizhevsky;NIPS,2012

2. Hardware-software co-design of an in-memory transformer network accelerator;laguna;FRONTIERS,2022

3. In-memory computing based accelerator for trans-former networks for long sequences;laguna;DATE,2021

4. The future of ferroelectric field-effect transistor technology

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. Full-Stack Optimization for CAM-Only DNN Inference;2024 Design, Automation & Test in Europe Conference & Exhibition (DATE);2024-03-25

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