DocumentCode :
644380
Title :
BFEPM: Best Fit Energy Prediction Modeling Based on CPU Utilization
Author :
Xiao Zhang ; Jianjun Lu ; Xiao Qin
Author_Institution :
Sch. of Comput. Sci., Northwestern Polytech. Univ., Xi´an, China
fYear :
2013
fDate :
17-19 July 2013
Firstpage :
41
Lastpage :
49
Abstract :
Energy cost becomes a major part of data center operational cost. Computer system consume more power when it runs under high workload. Many past studies focused on how to predict power consumption by performance counters. Some models retrieve performance counters from chips. Some models query performance counters from OS. Most of these researches were verified on several machines and claimed their models were accurate under the test. We found different servers have different energy consumption characters even with same CPU. In this paper, we present BFEPM, a best fit energy prediction model. It choose best model based on the power consumption benchmark result. We illustrate how to use benchmark result to find a best fit model. Then we validate the viability and effectiveness of model on all published results. At last, we apply the best fit model on two different machines to estimate the real-time energy consumption. The results show our model can get better results than single model.
Keywords :
computer centres; energy consumption; power aware computing; BFEPM modeling; CPU utilization; best fit energy prediction modeling; data center operational cost; energy cost; performance counters; power consumption benchmark result; realtime energy consumption estimation; Benchmark testing; Computational modeling; Energy consumption; Mathematical model; Power demand; Radiation detectors; Servers; data center management; energy consumption mode; green computing;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Networking, Architecture and Storage (NAS), 2013 IEEE Eighth International Conference on
Conference_Location :
Xi´an
Type :
conf
DOI :
10.1109/NAS.2013.12
Filename :
6665344
Link To Document :
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