A Survey on Run-time Power Monitors at the Edge

被引:2
|
作者
Zoni, Davide [1 ]
Galimberti, Andrea [1 ]
Fornaciari, William [1 ]
机构
[1] Politecn Milan, Dipartimento Elett Informaz & Bioingn DEIB, Piazza Leonardo,32, I-20133 Milan, Italy
关键词
Run-time power modeling; run-time power monitoring; run-time power management; edge computing; CPU; GPU; hardware acceleration; regression models; machine learning; performance events; switching activity; benchmark; CONSUMPTION ESTIMATION; PERFORMANCE; PROCESSOR; ACCURATE; DESIGN; MODELS; SUITE; CORE; COST;
D O I
10.1145/3593044
中图分类号
TP301 [理论、方法];
学科分类号
081202 ;
摘要
Effectively managing energy and power consumption is crucial to the success of the design of any computing system, helping mitigate the efficiency obstacles given by the downsizing of the systems while also being a valuable step towards achieving green and sustainable computing. The quality of energy and power management is strongly affected by the prompt availability of reliable and accurate information regarding the power consumption for the different parts composing the target monitored system. At the same time, effective energy and power management are even more critical within the field of devices at the edge, which exponentially proliferated within the past decade with the digital revolution brought by the Internet of things. This manuscript aims to provide a comprehensive conceptual framework to classify the different approaches to implementing run-time power monitors for edge devices that appeared in literature, leading the reader toward the solutions that best fit their application needs and the requirements and constraints of their target computing platforms. Run-time power monitors at the edge are analyzed according to both the power modeling and monitoring implementation aspects, identifying specific quality metrics for both in order to create a consistent and detailed taxonomy that encompasses the vast existing literature and provides a sound reference to the interested reader.
引用
收藏
页数:33
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