DocumentCode :
1606285
Title :
Low-cost estimation of sub-system power
Author :
Sun, Yuwen ; Wanner, Lucas ; Srivastava, Mani
Author_Institution :
Network & Embedded Syst. Lab., Univ. of California, Los Angeles, CA, USA
fYear :
2012
Firstpage :
1
Lastpage :
10
Abstract :
Real-time, fine-grained power consumption information enables energy optimization and adaptation for operating systems and applications. Due to the high cost associated with dedicated power sensors, however, most computers do not have the ability to measure disaggregated power consumption at a component or subsystem level. We present DiPART (Disaggregated Power Analysis in Real Time), a tool to estimate subsystem power consumption based on performance (event) counters and a single, system-wide power sensor. With only one power sensor for overall system power consumption, DiPART is able to self-adapt to variations in subsystem power consumption present across nominally identical hardware. We validate the approach using a cluster of Intel Atom-based nodes that has been instrumented for subsystem (CPU, RAM and disk) power measurements. DiPART was tested across nodes in the cluster using varied benchmarks, resulting in a 40% reduction in estimation error when compared to a static model.
Keywords :
multiprocessing systems; operating systems (computers); performance evaluation; power aware computing; power measurement; random-access storage; real-time systems; sensors; CPU; DiPART; Intel Atom-based node cluster; RAM; disaggregated power analysis in real time; disk power measurements; energy adaptation; energy optimization; estimation error reduction; event counters; low-cost subsystem power estimation; operating systems; performance counters; real-time fine-grained power consumption information; subsystem power consumption estimation; subsystem power measurements; system-wide power sensor; Adaptation models; Estimation; Power demand; Power measurement; Radiation detectors; Random access memory; adaptive model; linear model; performance (event) counter; power estimation; subsystem power disaggregation;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Green Computing Conference (IGCC), 2012 International
Conference_Location :
San Jose, CA
Print_ISBN :
978-1-4673-2155-6
Electronic_ISBN :
978-1-4673-2153-2
Type :
conf
DOI :
10.1109/IGCC.2012.6322270
Filename :
6322270
Link To Document :
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