Application Power Signature Analysis

IPDPS Workshops(2014)

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摘要
The high-performance computing (HPC) community has been greatly concerned about energy efficiency. To address this concern, it is essential to understand and characterize the electrical loads of HPC applications. In this work, we study whether HPC applications can be distinguished by their power-consumption patterns using quantitative measures in an automatic manner. Using a collection of 88 power traces from 4 different systems, we find that basic statistical measures do a surprisingly good job of summarizing applications' distinctive power behavior. Moreover, this study opens up a new area of research in power-aware HPC that has a multitude of potential applications.
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关键词
distinctive power behavior,parallel processing,power-aware hpc,power aware computing,application power signature analysis,statistical analysis,power-consumption patterns,high-performance computing community,statistical measures,high performance computing,power signature,power traces,clustering,high performance computing, power signature, clustering,benchmark testing,data collection,histograms,feature extraction
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