A Convolutional Neural Network Inference Accelerator Design using Algorithmic Noise-Tolerance Technology-Reference-Cited by-同舟云学术

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A Convolutional Neural Network Inference Accelerator Design using Algorithmic Noise-Tolerance Technology

Published:2023-12-18 Issue: Volume: Page:154-159
ISSN:
Container-title:2023 IEEE 16th International Symposium on Embedded Multicore/Many-core Systems-on-Chip (MCSoC)
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Author:

Yang Shih-Yi¹,Wey I-Chyn²,Hsu Huan-Ke¹,Teo T. Hui³

Affiliation:

1. Nano-Electronic Engineering and Design Singapore University of Technology and Design,Singapore,Singapore

2. Chang Gung University,Department of Electrical Engineering,Taoyuan,Taiwan

3. Engineering Product Development Singapore University of Technology and Design,Singapore,Singapore

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10387741/10387791/10387826.pdf?arnumber=10387826

Reference37 articles.

1. Energy-efficient signal processing via algorithmic noise-tolerance

2. Reliable low-power digital signal processing via reduced precision redundancy

3. Energy-efficient motion estimation using error-tolerance

4. CNN Inference Using a Preprocessing Precision Controller and Approximate Multipliers With Various Precisions

5. AirNN: A Featherweight Framework for Dynamic Input-Dependent Approximation of CNNs

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