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A Comparative Study of the Effectiveness of CPU Consolidation Versus Dynamic Voltage and Frequency Scaling in a Virtualized Multicore Server

机译:虚拟多核服务器中CPU整合与动态电压和频率缩放的有效性比较研究

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Companies operating large datacenters are focusing on how to reduce the electrical energy costs of operating datacenters. A common way of cost reduction is to perform a dynamic voltage and frequency scaling (DVFS), thereby matching the CPU's performance and power level to incoming workloads. Another power saving technique is CPU consolidation, which uses the minimum number of CPUs necessary to meet the service request demands and turns OFF the remaining unused CPUs. DVFS has been already extensively studied and verified its effectiveness. On the other hand, it is necessary to study more about the effectiveness of CPU consolidation. Key questions that must be answered are how effectively the CPU consolidation improves the energy efficiency and how to maximize the improvement. These questions are addressed in this paper. After understanding modern power management techniques and developing an appropriate power model, this paper provides an extensive set of hardware-based experimental results and makes suggestions about how to maximize energy efficiency improvement through CPU consolidation. In addition, this paper also presents new online CPU consolidation algorithms, which reduce the energy-delay product up to 13% compared with the Linux default DVFS algorithm.
机译:运营大型数据中心的公司正在关注如何降低运营数据中心的电能成本。降低成本的常用方法是执行动态电压和频率缩放(DVFS),从而使CPU的性能和功率水平与传入的工作负载相匹配。另一项省电技术是CPU整合,它使用满足服务请求需求所需的最少CPU数量,并关闭其余未使用的CPU。 DVFS已被广泛研究并验证了其有效性。另一方面,有必要进一步研究CPU整合的有效性。必须回答的关键问题是CPU整合如何有效地提高能源效率以及如何最大程度地提高效率。这些问题在本文中得到解决。在了解了现代电源管理技术并开发了合适​​的电源模型之后,本文提供了一组基于硬件的广泛实验结果,并提出了有关如何通过CPU整合最大程度地提高能源效率的建议。此外,本文还介绍了新的在线CPU整合算法,与Linux默认DVFS算法相比,该算法可将能耗产品减少多达13%。

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