AnaCoNGA: Analytical HW-CNN Co-Design Using Nested Genetic Algorithms-Reference-Cited by-同舟云学术

AnaCoNGA: Analytical HW-CNN Co-Design Using Nested Genetic Algorithms

Published:2022-03-14 Issue: Volume: Page:
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Container-title:2022 Design, Automation & Test in Europe Conference & Exhibition (DATE)
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Author:

Fasfous Nael¹,Vemparala Manoj Rohit²,Frickenstein Alexander²,Valpreda Emanuele³,Salihu Driton¹,Hufer Julian⁴,Singh Anmol²,Nagaraja Naveen-Shankar²,Voegel Hans-Joerg²,Vu Doan Nguyen Anh¹,Martina Maurizio³,Becker Juergen⁴,Stechele Walter¹

Affiliation:

1. Technical University of Munich,Department of Electrical and Computer Engineering,Germany

2. Autonomous Driving, BMW Group,Germany

3. Politecnico di Torino,Department of Electronics and Telecommunications,Italy

4. Karlsruhe Institute of Technology,Department of Electrical Engineering and Information Technology,Germany

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/9774496/9774497/09774574.pdf?arnumber=9774574

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5. HW-FlowQ: A Multi-Abstraction Level HW-CNN Co-design Quantization Methodology

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