Affiliations: [a] State Grid Zhejiang Electric Power Co., Ltd. Hangzhou Power Supply Company, Hangzhou, China
| [b] Hangzhou Keencool Intelligent Technology Co., Ltd. Hangzhou, China
Correspondence:
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Corresponding author. Yibo Lai, State Grid Zhejiang Electric Power Co., Ltd. Hangzhou Power Supply Company, Hangzhou, 310009, China. E-mail: [email protected].
Abstract: Aiming at the problems of low convective heat transfer coefficient and high energy consumption in the air-cooled data center of immersed liquid cooling, an improved deep learning algorithm is proposed for the data center system of immersed liquid cooling equipment room. By improving the design of the immersed liquid cooling system, heat exchange is carried out between the immersed liquid cooling system and heating components such as the central processing unit of the server. The insulation coolant and cooling water achieve server heat dissipation through energy exchange, achieving data management of the immersed liquid cooling room. The proposed algorithm improves data management efficiency while ensuring computational accuracy by conducting in-depth training and learning on the obtained immersed liquid cooling data, thus achieving the management of data in the immersed liquid cooling room. Through experiments, it has been proven that the immersed liquid cooling system in this study has high data management efficiency and low error, and can maintain server memory heat below 37 ° C, with a research accuracy of up to 92%.
Keywords: Immersive liquid cooling, liquid cooling heat exchanger, deep learning, non relaxation hash algorithm, data management system
