Flatfish: A Reinforcement Learning Approach for Application-Aware Address Mapping-Reference-Cited by-同舟云学术

Flatfish: A Reinforcement Learning Approach for Application-Aware Address Mapping

Published:2022-11 Issue:11 Volume:41 Page:4758-4770
ISSN:0278-0070
Container-title:IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems
language:
Short-container-title:IEEE Trans. Comput.-Aided Des. Integr. Circuits Syst.

Author:

Li Xingchen¹^ORCID,Yuan Zhihang¹,Guan Yijin²,Sun Guangyu¹,Zhang Tao³,Wei Rongshan⁴^ORCID,Niu Dimin²

Affiliation:

1. Center for Energy-Efficient Computing and Applications, Peking University, Beijing, China

2. Computing Technology Laboratory, Alibaba DAMO Academy, Hangzhou, China

3. Alibaba Group, T-Head Semiconductor Co., Ltd., Hangzhou, China

4. College of Physics and Information Engineering, Fuzhou University, Fuzhou, China

Funder

National Key Research and Development Program of China

National Natural Science Foundation of China

Beijing Academy of Artificial Intelligence

China National Postdoctoral Program for Innovative Talents

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Electrical and Electronic Engineering,Computer Graphics and Computer-Aided Design,Software

Link

Reference46 articles.

3. Trust region policy optimization;schulman;Proc Int Conf Mach Learn,2015

4. Policy gradient methods for reinforcement learning with function approximation;sutton;Advances in neural information processing systems,2000