DocumentCode :
652237
Title :
A Probabilistic Model for Estimating the Power Consumption of Processors and Network Interface Cards
Author :
Dargie, W. ; Jianjun Wen
Author_Institution :
Fac. of Comput. Sci., Tech. Univ. of Dresden, Dresden, Germany
fYear :
2013
fDate :
16-18 July 2013
Firstpage :
845
Lastpage :
852
Abstract :
Many of the proposed mechanisms aiming to achieve energy-aware adaptations in server environments rely on the existence of models that estimate the power consumption of the server as well as its individual components. Most existing or proposed models employ performance (hardware) monitoring counters and the CPU utilization to estimate power consumption, but they do not take into account the statistics of the workload the server processes. In this paper we propose a lightweight probabilistic model that can be used to estimate the power consumption of the CPU, the network interface card (NIC), and the server as a whole. We tested the model´s accuracy by executing custom-made benchmarks as well as standard benchmarks on two heterogeneous server platforms. The estimation error associated with our model is less than 1% for the custom-made benchmark whereas it is less than 12% for the standard benchmark.
Keywords :
energy consumption; power aware computing; stochastic processes; CPU utilization; NIC; energy-aware adaptations; heterogeneous server platforms; network interface cards; performance monitoring counters; power consumption estimation; probabilistic model; processors; Correlation; Hardware; Network interfaces; Power demand; Program processors; Radiation detectors; Servers; Power consumption model: probabilistic model: server power consumption: processor power consumption: NIC power consumption: cumulative distribution function: random variable;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Trust, Security and Privacy in Computing and Communications (TrustCom), 2013 12th IEEE International Conference on
Conference_Location :
Melbourne, VIC
Type :
conf
DOI :
10.1109/TrustCom.2013.103
Filename :
6680923
Link To Document :
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