RMLIM: A Runtime Machine Learning based Identification Model for Approximate Computing on Data Flow Graphs-Reference-Cited by-同舟云学术

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RMLIM: A Runtime Machine Learning based Identification Model for Approximate Computing on Data Flow Graphs

Published:2021 Issue: Volume: Page:1-1
ISSN:2377-3782
Container-title:IEEE Transactions on Sustainable Computing
language:
Short-container-title:IEEE Trans. Sustain. Comput.

Author:

Wang Ye¹,Dong Jian²,Liu Yanxin³,Wang Chunpei⁴,Qu Gang⁵

Affiliation:

1. School of Computer Science and Technology, Harbin Institute of Technology, 47822 Harbin, Heilongjiang, China, 150001 (e-mail: yewang@hit.edu.cn)

2. School of Computer Science and Technology, Harbin Institute of Technology, 47822 Harbin, Heilongjiang, China, (e-mail: dan@hit.edu.cn)

3. Harbin Institute of Technology, 47822 Harbin, Heilongjiang, China, (e-mail: yanxineric@gmail.com)

4. Harbin Institute of Technology, 47822 Harbin, Heilongjiang, China, (e-mail: wchunpei@gmail.com)

5. ECE and ISR, Univ. of Maryland, college park, Maryland, United States, 20742 (e-mail: gangqu@umd.edu)

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Computational Theory and Mathematics,Control and Optimization,Hardware and Architecture,Renewable Energy, Sustainability and the Environment,Software

Link

http://xplorestaging.ieee.org/ielx7/7274860/7742329/09409646.pdf?arnumber=9409646

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