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算力-电力-热力协同视角下数据中心高密机柜全栈联动研究

Yongzhen WangKuo SongKai HanHao LuoJiayu LinTe HanYiming WeiZixian Li

2024Scientia Sinica TechnologicaComputer Science被引 1开放获取

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摘要

<p indent="0mm">The continuous development of intelligent computing is driving the high density of computing power, leading to rapid growth in power consumption and heat dissipation density of data center (DC) cabinets. Currently, most of the energy-saving control methods for DCs are still limited to the optimization of a single chain of the upper computing equipment or the lower heat dissipation equipment, and the global optimization potential of temperature flexible control on cabinet computing and electric power consumption has not been deeply explored. Therefore, based on global optimization and dynamic scheduling, this paper proposes the concept of full-stack linkage of high-density DCs under the coordination of computing, electric, and thermal powers. Considering as examples the server power consumption and efficiency model, two-phase liquid cooling technology, and dynamic control technology involved in full-stack linkage, the related research status is analyzed, and the model construction and solution method for full-stack linkage of DCs under temperature flexible control are discussed. Accordingly, the coupling influence mechanism of operating temperature on computing, electric, and thermal powers is analyzed, and the research trend of full-stack linkage of DCs based on model-guided feedback correction is discussed.

引用本文(GB/T 7714)

Yongzhen Wang, Kuo Song, Kai Han, 等. 算力-电力-热力协同视角下数据中心高密机柜全栈联动研究[J]. Scientia Sinica Technologica, 2024.

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DOI:https://doi.org/10.1360/sst-2024-0170

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