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
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;
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
DOI :
10.1109/DCABES.2010.129
