DocumentCode
454387
Title
Energy Reduction by Workload Adaptation in a Multi-Process Environment
Author
Xian, Changjiu ; Lu, Yung-Hsiang
Author_Institution
Dept. of Comput. Sci., Purdue Univ., West Lafayette, IN
Volume
1
fYear
2006
fDate
6-10 March 2006
Firstpage
1
Lastpage
6
Abstract
Reducing energy consumption is an important issue in modern computers. Dynamic power management (DPM) has been extensively studied in recent years. One approach for DPM is to adjust workloads, such as clustering or eliminating requests, as a way to trade-off energy consumption and quality of services. Previous studies focus on single processes. However, when multiple concurrently running processes are considered, workload adjustment must be determined based on the interleaving of the processes´ requests. When multiple processes share the same hardware component, adjusting one process may not save energy. This paper presents an approach to assign energy responsibility to individual processes based on how they affect power management. The assignment is used to estimate potential energy reduction by adjusting the processes. We use the estimation to guide runtime adaptation of workload behavior. Experiments demonstrate that our approach can save more energy and improve energy efficiency
Keywords
adaptive systems; distributed shared memory systems; multiprocessing programs; processor scheduling; quality of service; dynamic power management; energy consumption; multiprocess environment; potential energy reduction; quality of services; runtime adaptation; workload adaptation; workload behavior; Computer science; Energy consumption; Energy management; Hardware; Interleaved codes; Potential energy; Power engineering and energy; Power engineering computing; Power system management; Quality of service;
fLanguage
English
Publisher
ieee
Conference_Titel
Design, Automation and Test in Europe, 2006. DATE '06. Proceedings
Conference_Location
Munich
Print_ISBN
3-9810801-1-4
Type
conf
DOI
10.1109/DATE.2006.243861
Filename
1656935
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