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AxPUE: Application Level Metrics for Power Usage Effectiveness in Data Centers

Authors :
Zhou, Runlin
Shi, Yingjie
Zhu, Chunge
Liu, Fan
Publication Year :
2013

Abstract

The rapid growth of data volume brings big challenges to the data center computing, and energy efficiency is one of the most concerned problems. Researchers from various fields are now proposing solutions to green the data center operations. Power usage effectiveness metric plays an important role in the energy saving research. However, the exising usage effectiveness metrics focus on measuring the relationship between the total facility energy consumed and the IT equipment energy consumed, without reflecting the energy efficiency of applications. In this paper, we analyze the requirements of application-level metrics for power usage efficiency of the data centers, and propose two novel energy efficiency metrics to provide strong guidance and useful insight to data center design and optimization. We conduct comprehensive experiments in the practical data centers using BigDataBench, a big data benchmark suite, and the results demonstrate the rationality and efficiency of AxPUE in measuring the actual computation energy consumption in data centers.<br />Comment: 8 pages, 4 figures, The First Workshop on Big Data Benchmarks, Performance Optimization, and Emerging hardware (BPOE 2013) In conjunction with 2013 IEEE International Conference on Big Data (IEEE Big Data 2013)

Details

Database :
arXiv
Publication Type :
Report
Accession number :
edsarx.1310.6502
Document Type :
Working Paper
Full Text :
https://doi.org/10.1109/BigData.2013.6691705