Online strategies for dynamic power management in systems with multiple power-saving states
ACM Transactions on Embedded Computing Systems (TECS)
Making a Case for Efficient Supercomputing
Queue - Power Management
Energy-Efficient Real-Time Heterogeneous Server Clusters
RTAS '06 Proceedings of the 12th IEEE Real-Time and Embedded Technology and Applications Symposium
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ATEC '05 Proceedings of the annual conference on USENIX Annual Technical Conference
CCGRID '07 Proceedings of the Seventh IEEE International Symposium on Cluster Computing and the Grid
An Energy-Efficient Management Mechanism for Large-Scale Server Clusters
APSCC '07 Proceedings of the The 2nd IEEE Asia-Pacific Service Computing Conference
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Proceedings of the 45th annual Design Automation Conference
Sleep with Guilt and Work Faster to Minimize Flow Plus Energy
ICALP '09 Proceedings of the 36th International Colloquium on Automata, Languages and Programming: Part I
Power and environment aware control of Beowulf clusters
Cluster Computing
Energy-efficient server clusters
PACS'02 Proceedings of the 2nd international conference on Power-aware computer systems
EnergySaving cluster roll: power saving system for clusters
ARCS'10 Proceedings of the 23rd international conference on Architecture of Computing Systems
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With the scale expansion of high performance computer systems, efficient power management has developed into an important issue. To strive to balance power consumption and performance, this paper proposes an adaptive workload-driven dynamic power management policy for homogeneous clusters, which dynamically adjusts the power mode of computing nodes according to workload variation. The proposed policy combines the pre-wakeup method and the feedback mechanism to reduce performance degradation due to the wakeup delay. The experimental results demonstrate that, as compared with two existing timeout policies, adaptive workload-driven dynamic power management effectively reduced the performance loss with a slight increase in power consumption.