Reference : Energy-Aware Fast Scheduling Heuristics in Heterogeneous Computing Systems
Scientific congresses, symposiums and conference proceedings : Paper published in a book
Engineering, computing & technology : Computer science
http://hdl.handle.net/10993/3827
Energy-Aware Fast Scheduling Heuristics in Heterogeneous Computing Systems
English
Diaz, Cesar mailto [University of Luxembourg > Faculty of Science, Technology and Communication (FSTC) > Computer Science and Communications Research Unit (CSC) >]
Guzek, Mateusz mailto [University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT) > >]
Pecero, Johnatan mailto [University of Luxembourg > Faculty of Science, Technology and Communication (FSTC) > Computer Science and Communications Research Unit (CSC) >]
Danoy, Grégoire mailto [University of Luxembourg > Faculty of Science, Technology and Communication (FSTC) > Computer Science and Communications Research Unit (CSC) >]
Bouvry, Pascal mailto [University of Luxembourg > Faculty of Science, Technology and Communication (FSTC) > Computer Science and Communications Research Unit (CSC) >]
Khan, Samee U. [North Dakota State University, Fargo, ND, USA]
2011
High Performance Computing and Simulation (HPCS), 2011 International Conference on
478-484
Yes
International
978-1-61284-383-4
International Conference on High Performance Computing & Simulation (HPCS 2011)
from 04-07-2011 to 08-07-2011
Istanbul
Turkey
[en] Heterogeneous computing systems ; energy efficiency ; scheduling ; optimization
[en] In heterogeneous computing systems it is crucial to sched- ule tasks in a manner that exploits the heterogeneity of the resources and applications to optimize systems perfor- mance. Moreover, the energy efficiency in these systems is of a great interest due to different concerns such as opera- tional costs and environmental issues associated to carbon emissions. In this paper, we present a series of original low complexity energy efficient algorithms for scheduling. The main idea is to map a task to the machine that executes it fastest while the energy consumption is minimum. On the practical side, the set of experimental results showed that the proposed heuristics perform as efficiently as related ap- proaches, demonstrating their applicability for the consid- ered problem and its good scalability.
University of Luxembourg: High Performance Computing - ULHPC
http://hdl.handle.net/10993/3827
Proceedings of the 2011 International Conference on High Performance Computing & Simulation (HPCS 2011)

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