Exploiting CPU Voltage Margins to Increase the Profit of Cloud Infrastructure Providers

Christos Kalogirou, Panos K. Koutsovasilis, C. Antonopoulos, Nikolaos Bellas, S. Lalis, S. Venugopal, Christian Pinto
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引用次数: 6

Abstract

Energy efficiency is a major concern for cloud computing, with CPUs accounting a significant fraction of datacenter nodes power consumption. CPU manufacturers introduce voltage margins to guarantee correct operation. However, these are unnecessarily wide for real-world execution scenarios, and translate to increased power consumption. In this paper, we investigate how such margins can be exploited by infrastructure operators, by selectively undervolting nodes, at the controlled risk of inducing failures and activating service-level agreement (SLA) violation penalties. We model the problem in a formal way, capturing the most important aspects that drive VM management and system configuration decisions. Then, we introduce XM-VFS policy that reduces infrastructure operator costs by reducing voltage margins, and compare it with the state-of-the-art which employs dynamic voltage-frequency scaling (DVFS) and workload consolidation. We perform simulations to quantify the cost reduction, considering the energy consumption and potential SLA violations. Our results show significant gains, up to 17.35% and 16.32% for the energy and cost reduction respectively. In our simulations, we use realistic assumptions for voltage margins, energy consumption and performance degradation of applications due to frequency scaling, based on the characterization of commercial Intel-and ARM-based machines. Our model and scheduling policy are generic and scalable.
利用CPU电压余量增加云基础设施提供商的利润
能源效率是云计算的主要关注点,cpu占数据中心节点功耗的很大一部分。CPU制造商引入电压余量以保证正确操作。然而,对于实际的执行场景来说,这些宽度是不必要的,并且会导致功耗的增加。在本文中,我们研究了基础设施运营商如何在可控的诱导故障和激活服务水平协议(SLA)违规处罚的风险下,通过选择性地降低节点电压来利用这些边际。我们以正式的方式对问题建模,捕获驱动VM管理和系统配置决策的最重要方面。然后,我们引入XM-VFS策略,通过降低电压余量来降低基础设施运营商的成本,并将其与采用动态电压频率缩放(DVFS)和工作负载整合的最新技术进行比较。考虑到能源消耗和潜在的SLA违反,我们执行模拟来量化成本降低。我们的结果显示了显著的收益,能源和成本分别降低了17.35%和16.32%。在我们的模拟中,我们基于商用英特尔和arm机器的特征,对电压裕度、能量消耗和由于频率缩放而导致的应用程序性能下降使用了现实的假设。我们的模型和调度策略是通用的和可扩展的。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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