另类:能量不像其他指标

Vaastav Anand, Zhiqiang Xie, Matheus Stolet, Roberta De Viti, Thomas Davidson, Reyhaneh Karimipour, Safya Alzayat, Jonathan Mace
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引用次数: 6

摘要

数据中心的能源需求正在快速增长。提高数据中心效率的现有技术主要集中在硬件上。然而,如果不使应用程序具有能源意识,则可以实现的能源效率的提高是有限的。为了克服这一限制,最近的工作建议使运行在数据中心的软件具有能源意识。要做到这一点,我们必须能够在软件层面上以不同的粒度跟踪能源消耗——(i)过程层面;(ii)应用水平;(iii)端到端请求级别。目前,现有的软件能量跟踪技术主要集中在过程或应用级别的能量跟踪;只有少数技术在端到端请求级别跟踪能量。但是,不跟踪端到端请求级别的能源可能导致错误的软件优化,并导致能源效率的降低。为了在端到端请求级别上跟踪能源,我们可以利用端到端跟踪技术来实现其他指标,比如分布式跟踪。然而,我们假定能量不能仅仅作为另一种度量标准来对待,我们不能不加修改地使用现有的框架。在本文中,我们讨论了能量与其他指标的不同之处,并描述了一个能量跟踪工作流,该工作流利用这些差异和跟踪技术来跟踪端到端请求的能耗。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
The Odd One Out: Energy is Not Like Other Metrics
Energy requirements for datacenters are growing at a fast pace. Existing techniques for making datacenters efficient focus on hardware. However, the gain in energy efficiency that can be achieved without making the applications energy-aware is limited. To overcome this limitation, recent work has proposed making the software running in datacenters energy aware. To do so, we must be able to track energy consumption at various granularities at the software level - (i) process level; (ii) application level; (iii) end-to-end request level. Currently, existing software energy-tracking techniques primarily focus on tracking energy at the process or application level; only a few techniques track energy at an end-to-end request level. However, not tracking energy at an end-to-end request level can lead to false software optimizations and cause a decrease in energy efficiency. To track energy at an end-to-end request level, we can leverage end-to-end tracking techniques for other metrics such as distributed tracing. However, we posit that energy cannot be treated as just another metric and that we cannot use existing frameworks without modifications. In this paper, we discuss how energy is different from other metrics and describe an energy-tracking workflow that leverages these differences and tracing techniques in order to track energy consumption of end-to-end requests.
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