A 3D Implementation of Convolutional Neural Network for Fast Inference-Reference-Cited by-同舟云学术

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A 3D Implementation of Convolutional Neural Network for Fast Inference

Published:2023-05-21 Issue: Volume: Page:
ISSN:
Container-title:2023 IEEE International Symposium on Circuits and Systems (ISCAS)
language:
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Author:

Miniskar Narasinga Rao¹,Vanna-Iampikul Pruek²,Young Aaron¹,Lim Sung Kyu²,Liu Frank¹,Yoo Jieun³,Mills Corrinne³,Tran Nhan⁴,Fahim Farah⁴,Vetter Jeffrey S¹

Affiliation:

1. Oak Ridge National Laboratory,Computer Science and Mathematic Division,Oak Ridge,USA

2. Georgia Institute of Technology,Department of Electrical and Computer Engineering,Atlanta,USA

3. University of Illinois Chicago,Department of Physics,Chicago,USA

4. Fermi National Accelerator Laboratory,Scientific Computing Division,Chicago,USA

Funder

US Department of Energy

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10181241/10181318/10181622.pdf?arnumber=10181622

Reference21 articles.

1. Accelerating deep convolutional neural networks using specialized hardware;ovtcharov;Microsoft Research Whitepaper,2015

2. PatDNN: Achieving Real-Time DNN Execution on Mobile Devices with Pattern-based Weight Pruning

3. Logic Monolithic 3D ICs

4. Pseudo-3D Approaches for Commercial-Grade RTL-to-GDS Tool Flow Targeting Monolithic 3D ICs

5. Direct Cu to Cu Bonding and Alternative Bonding Techniques in 3D Packaging

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