A Validation of DRAM RAPL Power Measurements

Spencer Desrochers, Chad Paradis, Vincent M. Weaver
{"title":"A Validation of DRAM RAPL Power Measurements","authors":"Spencer Desrochers, Chad Paradis, Vincent M. Weaver","doi":"10.1145/2989081.2989088","DOIUrl":null,"url":null,"abstract":"Recent Intel processors support the Running Average Power Level (RAPL) interface, which among other things provides estimated energy measurements for the CPUs, integrated GPU, and DRAM. These measurements are easily accessible by the user, and can be gathered by a wide variety of tools, including the Linux perf_event interface. This allows unprecedented easy access to energy information when designing and optimizing energy-aware code. While greatly useful, on most systems these RAPL measurements are estimated values, generated on the fly by an on-chip energy model. The values are not documented well, and the results (especially the DRAM results) have undergone only limited validation. We validate the DRAM RAPL results on both desktop and server Haswell machines, with multiple types of DDR3 and DDR4 memory. We instrument the hardware to gather actual power measurements and compare them to the RAPL values returned via Linux perf_event. We describe the many challenges encountered when instrumenting systems for detailed power measurement. We find that the RAPL results match overall energy and power trends, usually by a constant power offset. The results match best when the DRAM is being heavily utilized, but do not match as well in cases where the system is idle, or when an integrated GPU is using the memory. We also verify that Haswell server machines produce more accurate results, as they include actual power measurements gathered through the integrated voltage regulator.","PeriodicalId":283512,"journal":{"name":"Proceedings of the Second International Symposium on Memory Systems","volume":"20 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2016-10-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"87","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the Second International Symposium on Memory Systems","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/2989081.2989088","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 87

Abstract

Recent Intel processors support the Running Average Power Level (RAPL) interface, which among other things provides estimated energy measurements for the CPUs, integrated GPU, and DRAM. These measurements are easily accessible by the user, and can be gathered by a wide variety of tools, including the Linux perf_event interface. This allows unprecedented easy access to energy information when designing and optimizing energy-aware code. While greatly useful, on most systems these RAPL measurements are estimated values, generated on the fly by an on-chip energy model. The values are not documented well, and the results (especially the DRAM results) have undergone only limited validation. We validate the DRAM RAPL results on both desktop and server Haswell machines, with multiple types of DDR3 and DDR4 memory. We instrument the hardware to gather actual power measurements and compare them to the RAPL values returned via Linux perf_event. We describe the many challenges encountered when instrumenting systems for detailed power measurement. We find that the RAPL results match overall energy and power trends, usually by a constant power offset. The results match best when the DRAM is being heavily utilized, but do not match as well in cases where the system is idle, or when an integrated GPU is using the memory. We also verify that Haswell server machines produce more accurate results, as they include actual power measurements gathered through the integrated voltage regulator.
DRAM RAPL功率测量的验证
最近的英特尔处理器支持运行平均功率水平(RAPL)接口,该接口提供了cpu、集成GPU和DRAM的估计能量测量。用户可以很容易地访问这些测量值,并且可以通过各种工具(包括Linux perf_event接口)收集这些测量值。在设计和优化能源感知代码时,这使得前所未有的容易访问能源信息。虽然非常有用,但在大多数系统中,这些RAPL测量值都是估计值,由芯片上的能量模型动态生成。这些值没有很好地记录下来,结果(尤其是DRAM结果)只经过了有限的验证。我们在桌面和服务器Haswell机器上验证了DRAM RAPL结果,使用多种类型的DDR3和DDR4内存。我们测量硬件以收集实际的功率测量值,并将它们与通过Linux perf_event返回的RAPL值进行比较。我们描述了在进行详细功率测量的仪器系统时遇到的许多挑战。我们发现,RAPL结果与总体能量和功率趋势相匹配,通常是通过恒定的功率偏移。当DRAM被大量使用时,结果是最匹配的,但在系统空闲或集成GPU使用内存的情况下,结果就不匹配了。我们还验证了Haswell服务器机器产生更准确的结果,因为它们包括通过集成电压调节器收集的实际功率测量。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信