Reference : Energy-Aware Fast Scheduling Heuristics in Heterogeneous Computing Systems

	Document type :	Scientific congresses, symposiums and conference proceedings : Paper published in a book
	Discipline(s) :	Engineering, computing & technology : Computer science
	To cite this reference:	http://hdl.handle.net/10993/3827

Title :	Energy-Aware Fast Scheduling Heuristics in Heterogeneous Computing Systems
Language :	English
Author, co-author :	Diaz, Cesar [University of Luxembourg > Faculty of Science, Technology and Communication (FSTC) > Computer Science and Communications Research Unit (CSC) >]
	Guzek, Mateusz [University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT) > >]
	Pecero, Johnatan [University of Luxembourg > Faculty of Science, Technology and Communication (FSTC) > Computer Science and Communications Research Unit (CSC) >]
	Danoy, Grégoire [University of Luxembourg > Faculty of Science, Technology and Communication (FSTC) > Computer Science and Communications Research Unit (CSC) >]
	Bouvry, Pascal [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]
Publication date :	2011
Main document title :	High Performance Computing and Simulation (HPCS), 2011 International Conference on
Pages :	478-484
Peer reviewed :	Yes
Audience :	International
ISBN :	978-1-61284-383-4
Event name :	International Conference on High Performance Computing & Simulation (HPCS 2011)
Event date :	from 04-07-2011 to 08-07-2011
Event place (city) :	Istanbul
Event country :	Turkey
Keywords :	[en] Heterogeneous computing systems ; energy efficiency ; scheduling ; optimization
Abstract :	[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.
Research centres :	University of Luxembourg: High Performance Computing - ULHPC
Permalink :	http://hdl.handle.net/10993/3827
Commentary :	Proceedings of the 2011 International Conference on High Performance Computing & Simulation (HPCS 2011)

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