Special Session: On the Reliability of Conventional and Quantum Neural Network Hardware-Reference-Cited by-同舟云学术

Special Session: On the Reliability of Conventional and Quantum Neural Network Hardware

Published:2022-04-25 Issue: Volume: Page:
ISSN:
Container-title:2022 IEEE 40th VLSI Test Symposium (VTS)
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Author:

Sadi Mehdi¹,He Yi²,Li Yanjing²,Alam Mahabubul³,Kundu Satwik³,Ghosh Swaroop³,Bahrami Javad⁴,Karimi Naghmeh⁴

Affiliation:

1. Auburn University,Dept. of Electrical & Computer Engineering,Auburn,AL,USA

2. University of Chicago,Department of Computer Science,Chicago,IL,USA

3. The Pennsylvania State University,Dept. of Electrical & Computer Engineering,University Park,PA,USA

4. University of Maryland Baltimore County (UMBC),Dept. of Electrical & Computer Engineering,Baltimore,MD,USA

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/9793839/9794139/09794194.pdf?arnumber=9794194

Reference68 articles.

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3. Special Session: Reliability Analysis for AI/ML Hardware

4. Understanding Error Propagation in Deep Learning Neural Network (DNN) Accelerators and Applications;g l;Proceedings of the International Conference for High Performance Computing Networking Storage and Analysis ser SC ‘17,2017

5. Design of Reliable SoCs With BIST Hardware and Machine Learning

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