Reference : Scalable and Energy-Efficient Scheduling Techniques for Large-Scale Systems
Scientific congresses, symposiums and conference proceedings : Paper published in a book
Engineering, computing & technology : Computer science
http://hdl.handle.net/10993/7009
Scalable and Energy-Efficient Scheduling Techniques for Large-Scale 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) >]
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
Computer and Information Technology (CIT), 2011 IEEE 11th International Conference on
641-647
Yes
No
International
978-0-7695-4388-8
IEEE International Conference On Scalable Computing SCALCOM 2011
from 31-08-2011 to 02-09-2011
Paphos
Cyprus
[en] heterogenous computing systems ; energy conservation ; scheduling ; performance of systems
[en] The scalability of a computing system can be identified by at least three components: (a) size, (b) geograph- ical distribution, and (c) administrative constraints. Newer paradigms, such as clouds, grids, and clusters bring in more parameters to the aforementioned list, namely heterogeneity, energy consumption, and transparency. To optimize the per- formance of a computing system, it is manner that exploits heterogeneity and is scalable. Moreover, newer systems also demand energy efficiency as an integral part of schedulers. In this paper, we evaluate the behavior of low complexity energy- efficient algorithms for scheduling. The set of experimental results showed that the evaluated heuristics perform as effi- ciently as related approaches; demonstrating their applicability and scalability for the considered problem.
University of Luxembourg: High Performance Computing - ULHPC
http://hdl.handle.net/10993/7009
Proceedings of the 11th IEEE International Conference on Computer and Information Technology

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