Learning the Error Features of Approximate Multipliers for Neural Network Applications-Reference-Cited by-同舟云学术

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Learning the Error Features of Approximate Multipliers for Neural Network Applications

Published:2024 Issue: Volume: Page:1-14
ISSN:0018-9340
Container-title:IEEE Transactions on Computers
language:
Short-container-title:IEEE Trans. Comput.

Author:

Mo Hai¹,Wu Yong¹,Jiang Honglan²,Ma Zining¹,Lombardi Fabrizio³,Han Jie⁴,Liu Leibo¹

Affiliation:

1. School of Integrated Circuits, Tsinghua University, Beijing, China

2. Department of Micro-Nano Electronic, Shanghai Jiao Tong University, Shanghai, China

3. Department of Electrical and Computer Engineering, Northeastern University, Boston, USA

4. Department of Electrical and Computer Engineering, University of Alberta, Edmonton, AB, Canada

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Computational Theory and Mathematics,Hardware and Architecture,Theoretical Computer Science,Software

Link

http://xplorestaging.ieee.org/ielx7/12/4358213/10372208.pdf?arnumber=10372208

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. Energy-Efficient Neural Network Acceleration Using Most Significant Bit-Guided Approximate Multiplier;Electronics;2024-08-01

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