数据中心效率更高的环境温度和优化的冷却控制

N. Ahuja, C. Rego, S. Ahuja, Matt Warner, Akhil Docca
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引用次数: 21

摘要

服务器技术的进步导致购置服务器设备的成本呈下降趋势,而数据中心的规模经济显著降低了劳动力成本。这使得能源成本成为优化的下一个目标。能源成本是由IT设备、为设备提供不间断电力的开关设备以及IT设备的冷却驱动的。在典型的数据中心中,总功耗的近40%用于冷却。此外,冷却效率是决定数据中心寿命的首要因素。行业中的一个新兴趋势是将数据中心的运行转移到更高的环境温度,一些运营商希望将送风温度设置到40°C,同时提高冷却系统的效率。该研究将表明,通过优化冷却控制,可以通过优化数据中心冷却预算来降低数据中心级别的总拥有成本,同时确保在环境温度升高的情况下没有性能损失。本文描述了一种平台辅助热管理方法,该方法使用新的传感器提供服务器气流和服务器出口温度,以改善数据中心冷却解决方案的控制。这些数据还被用作计算流体动力学(CFD)模型的输入,用于对未来变化情景进行准确的预测分析和优化,从而提高数据中心的效率并降低功耗。该研究的一个关键组成部分将是使用计算流体动力学CFD分析来优化数据中心冷却系统。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Data center efficiency with higher ambient temperatures and optimized cooling control
Advances in server technology have resulted in the cost of acquiring server equipment trending down, while economies of scale in data centers have significantly reduced the cost of labor. This leaves the cost of the energy as the next target for optimization. Energy costs are driven by operating the IT equipment, the switchgear that provides uninterrupted power to the equipment, and in cooling the IT equipment. In a typical datacenter, almost 40% of the total power consumption is spent on cooling. In addition, cooling effectiveness is a first order factor in determining the lifespan of the data center. One of the emerging trends in the industry is to move datacenter operations to higher ambient temperatures with some Operators wanting to set supply air temperatures as high as 40°C while improving cooling system efficiency. This study will show that with optimized cooling control one could reduce the total cost of ownership at the datacenter level by optimizing the datacenter cooling budget while ensuring no performance loss at increased ambient temperature conditions. This paper describes a platform-assisted thermal management approach that uses new sensors providing server airflow and server outlet temperature to improve control of the data centers cooling solution. This data is also used as input to a computational fluid dynamics (CFD) model for accurate predictive analysis and optimization of future change scenarios, thus increasing the data center efficiency and reducing power consumption. A key component of the study will be the use of computational fluid dynamics CFD analysis for optimizing the data center cooling system.
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