Name
Abstract | ||
|---|---|---|
This paper analyzes workload characteristics and power usage of parallel high-performance computing system. According to the conclusions of the analysis, we propose two kinds of power-aware scheduling policies to reduce the power consumption of system by power down idle nodes reasoningly. Detailed experiments using data from the Parallel Workloads Archive indicates that both policies can achieve considerable overall system power savings while meeting the user-defined switch frequency limit for each node. |
Year | DOI | Venue |
|---|---|---|
2011 | 10.1109/GreenCom.2011.21 | GreenCom |
Keywords | Field | DocType |
power-aware scheduling policy,workload characteristic,user-defined switch frequency limit,parallel workloads archive,power usage,detailed experiment,power consumption,considerable overall system power,parallel high-performance computing system,high-performance computing system,power-aware scheduling,idle nodes reasoningly,high performance computing,resource management,resource allocation,schedule,switches,parallel processing | Resource management,Supercomputer,Workload,Idle,Computer science,Scheduling (computing),Resource allocation,Computing systems,Power consumption,Embedded system,Distributed computing | Conference |
Citations | PageRank | References |
0 | 0.34 | 2 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Junfeng Sun | 1 | 0 | 0.34 |
| Chunlin Huang | 2 | 36 | 7.22 |
| Jing Dong | 3 | 52 | 17.44 |