DocumentCode
2992852
Title
Energy-aware application scheduling on a heterogeneous multi-core system
Author
Chen, Jian ; John, Lizy K.
Author_Institution
Electr. & Comput. Eng. Dept., Univ. of Texas, Austin, TX
fYear
2008
fDate
14-16 Sept. 2008
Firstpage
5
Lastpage
13
Abstract
Heterogeneous multi-core processors are attractive for power efficient computing because of their ability to meet varied resource requirements of diverse applications in a workload. However, one of the challenges of using a heterogeneous multi-core processor is to schedule different programs in a workload to matching cores that can deliver the most efficient program execution. This paper presents an energy-aware scheduling mechanism that employs fuzzy logic to calculate the suitability between programs and cores by analyzing important inherent program characteristics such as instruction dependency distance and branch transition rate. The obtained suitability is then used to guide the program scheduling in the heterogeneous multi-core system. The experimental results show that the proposed suitability-guided program scheduling mechanism achieves up to 15.0% average reduction in energy-delay product compared with that of the random scheduling approach. To the best of our knowledge, this study is the first to apply fuzzy logic to schedule programs in heterogeneous multi-core systems.
Keywords
fuzzy logic; power aware computing; processor scheduling; resource allocation; branch transition rate; energy-aware application scheduling mechanism; fuzzy logic; heterogeneous multicore processor; instruction dependency distance; power efficient computing; program execution; random scheduling approach; resource requirement; suitability-guided program scheduling mechanism; workload balancing; Algorithm design and analysis; Application software; Energy consumption; Fuzzy logic; Hardware; Multicore processing; Power engineering and energy; Power engineering computing; Processor scheduling; Scheduling algorithm;
fLanguage
English
Publisher
ieee
Conference_Titel
Workload Characterization, 2008. IISWC 2008. IEEE International Symposium on
Conference_Location
Seattle, WA
Print_ISBN
978-1-4244-2777-2
Electronic_ISBN
978-1-4244-2778-9
Type
conf
DOI
10.1109/IISWC.2008.4636086
Filename
4636086
Link To Document