DocumentCode
2061822
Title
Workload-aware Power Management of Cluster Systems
Author
Liu, Zhuo ; Liang, Aihua ; Xiao, Limin ; Ruan, Li
Author_Institution
State Key Lab. of Software Dev. Environ., Beihang Univ., Beijing, China
fYear
2010
fDate
10-12 Aug. 2010
Firstpage
603
Lastpage
608
Abstract
Along with the increased awareness of energy cost, power management becomes a big issue for clusters. In this study, we investigate the workload aware power management techniques for cluster systems and propose a new power management policy. The considered power management techniques are dynamic workload consolidation and usage of dynamic power range enabled by low power states on servers. The power management policy has been implemented on OpenPBS with Maui, which reduces about ten percent power consumption and optimizes workload distribution to lower the impact on performance.
Keywords
power aware computing; power consumption; power engineering computing; power system management; statistical analysis; OpenPBS; cluster system; power consumption; power management techniques; workload aware; Hardware; Memory management; Power demand; Program processors; Servers; Sleep; cluster; power management; workload-aware scheduling;
fLanguage
English
Publisher
ieee
Conference_Titel
Distributed Computing and Applications to Business Engineering and Science (DCABES), 2010 Ninth International Symposium on
Conference_Location
Hong Kong
Print_ISBN
978-1-4244-7539-1
Type
conf
DOI
10.1109/DCABES.2010.129
Filename
5571535
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