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Evaluating the cooling and computing energy demand of a datacentre with optimal server provisioning

机译:通过最佳服务器配置评估数据中心的冷却和计算能源需求

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As cloud computing continues to gain significance across fields, the energy consumption of datacentres creates new challenges in the design and operation of computer systems, with cooling remaining a key part of the total energy expenditure. We investigate the implications of increasing the room temperature setpoint in datacentres to save energy. For this, we develop a holistic model for the energy consumption of the server room that depends on user workload and service level agreement constraints, and that considers both cooling and computing energy dissipation. The model is applicable to a steady-state analysis of the system and brings insight into the impact of the most relevant parameters that affect the net energy consumption, such as the outside temperature, room temperature setpoint, and user demand. We analyse both static and dynamic server provisioning cases. In the latter case, a global power management scheme determines the optimal number of servers required to handle the incoming user demand to fulfil a target service level objective. Finally, we consider the extra energy needed to maintain service continuity under the expected higher server mortality rate due to warmer operational temperatures. Energy and temperature measurements acquired from a server machine running scientific benchmark programs allow to realistically fix model parameters for the study and to obtain pragmatic conclusions.
机译:随着云计算在各个领域的重要性不断提高,数据中心的能耗在计算机系统的设计和运行中提出了新的挑战,而散热仍然是总能耗的关键部分。我们研究了在数据中心内提高室温设定值以节省能源的含义。为此,我们针对服务器机房的能耗开发了一个整体模型,该模型取决于用户的工作量和服务水平协议约束,并同时考虑制冷和计算能耗。该模型适用于系统的稳态分析,并深入了解影响净能耗的最相关参数的影响,例如外部温度,室温设置点和用户需求。我们分析静态和动态服务器供应情况。在后一种情况下,全局电源管理方案确定处理传入用户需求以实现目标服务水平目标所需的最佳服务器数量。最后,我们考虑到由于运行温度升高而在预期的更高服务器死亡率下保持服务连续性所需的额外能量。从运行科学基准程序的服务器机器获取的能量和温度测量值可以实际确定用于研究的模型参数并获得务实的结论。

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