TESLA: Thermally Safe, Load-Aware, and Energy-Efficient Cooling Control System for Data Centers-Reference-Cited by-同舟云学术

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TESLA: Thermally Safe, Load-Aware, and Energy-Efficient Cooling Control System for Data Centers

Published:2024-08-12 Issue: Volume:2959 Page:939-949
ISSN:
Container-title:Proceedings of the 53rd International Conference on Parallel Processing
language:
Short-container-title:

Author:

Geng Hanfei¹^ORCID,Sun Yi¹^ORCID,Li Yuanzhe²^ORCID,Leng Jichao²^ORCID,Zhu Xiangyu²^ORCID,Zhan Xianyuan³^ORCID,Li Yuanchun³^ORCID,Zhao Feng²^ORCID,Liu Yunxin³^ORCID

Affiliation:

1. Institute for AI Industry Research (AIR), Tsinghua University, China and Department of Electronic Engineering, Tsinghua University, China

2. Institute for AI Industry Research (AIR), Tsinghua University, China

3. Institute for AI Industry Research (AIR), Tsinghua University, China and Shanghai Artificial Intelligence Laboratory, China

Funder

National Natural Science Foundation of China

Intel Corporation

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3673038.3673144

Reference49 articles.

1. Theory and applications of HVAC control systems – A review of model predictive control (MPC)

2. ASHARE. 2024. The American Society of Heating, Refrigerating and Air-Conditioning Engineers. (Jan 2024). https://www.ashrae.org

3. Maximilian Balandat Brian Karrer Daniel R. Jiang Samuel Daulton Benjamin Letham Andrew Gordon Wilson and Eytan Bakshy. 2020. BoTorch: A Framework for Efficient Monte-Carlo Bayesian Optimization. In Advances in Neural Information Processing Systems 33.

4. Toward Model-Assisted Safe Reinforcement Learning for Data Center Cooling Control: A Lyapunov-based Approach

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