Name
Abstract | ||
|---|---|---|
Power consumption of HPC cluster is increasingly concerned by HPC designers and users. This paper proposes a multi-tier cluster energy management for reducing energy consumption of the cluster system with minimal effect on performance. The proposed management combines cluster-level and node-level strategies. Cluster-level strategy uses a self-learning load estimation algorithm to predict new-coming task's load and presents a novel PI control theory based node allocation mechanism to decide how many nodes should be selected to execute parallel tasks. The cluster-level strategy also uses an on-demand on/off strategy to decide how the node scales its CPU frequency and whether to be turned off. Node-level strategy uses an enhanced-conservative governor algorithm to improve the sensitivity of the frequency adjustment when load drops. Experiments show that the proposed multi-tier power management is more efficient than other traditional strategies in reducing overall system power consumption. |
Year | DOI | Venue |
|---|---|---|
2010 | 10.1109/GreenCom-CPSCom.2010.43 | GreenCom/CPSCom |
Keywords | Field | DocType |
pi control,multi-tier energy management,hpc cluster,load drop,power aware computing,overall system power consumption,power consumption,node-level strategy,traditional strategy,pi control theory,self-learning load estimation algorithm,multitier energy management strategy,hpc clusters,cluster-level strategy,multi-tier energy management strategy,energy consumption,enhanced conservative governor algorithm,cluster level strategy,multi-tier cluster energy management,cluster system,node allocation mechanism,algorithm design and analysis,energy efficiency,energy management,estimation,clustering algorithms | Power management,Energy management,Cluster (physics),Algorithm design,Efficient energy use,Computer science,Real-time computing,Cluster analysis,Governor,Energy consumption,Distributed computing | Conference |
ISBN | Citations | PageRank |
978-0-7695-4331-4 | 3 | 0.42 |
References | Authors | |
8 | 3 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Yu-Song Tan | 1 | 38 | 13.98 |
| Qingbo Wu | 2 | 399 | 39.78 |
| Huiming Tang | 3 | 57 | 13.06 |