Towards Energy Auto Tuning
Energy efficiency is gaining more and more importance, since well-known ecological reasons lead to rising energy costs. In consequence, energy consumption is now also an important economical criterion. Energy consumption of single hardware resources has been thoroughly optimized for years. Now softw...
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Saechsische Landesbibliothek- Staats- und Universitaetsbibliothek Dresden
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ndltd-DRESDEN-oai-qucosa.de-bsz-14-qucosa-1169662013-08-27T03:09:25Z Towards Energy Auto Tuning Götz, Sebastian Wilke, Claas Schmidt, Matthias Cech, Sebastian Aßmann, Uwe Energieeffizienz Selbstoptimierung Nicht-funktionale Eigenschaften Energy-efficiency self-optimization non-functional properties ddc:004 rvk:ST 200 rvk:AR 26600 Energieeffizienz Selbstoptimierung Energy efficiency is gaining more and more importance, since well-known ecological reasons lead to rising energy costs. In consequence, energy consumption is now also an important economical criterion. Energy consumption of single hardware resources has been thoroughly optimized for years. Now software becomes the major target of energy optimization. In this paper we introduce an approach called energy auto tuning(EAT), which optimizes energy efficiency of software systems running on multiple resources. The optimization of more than one resource leads to higher energy savings, because communication costs can be taken into account. E.g., if two components run on the same resource, the communication costs are likely to be less, compared to be running on different resources. The best results can be achieved in heterogeneous environments as different resource characteristics enlarge the synergy effects gainable by our optimization technique. EAT software systems derive all possible distributions of themselves on a given set of hardware resources and reconfigure themselves to achieve the lowest energy consumption possible at any time. In this paper we describe our software architecture to implement EAT. Saechsische Landesbibliothek- Staats- und Universitaetsbibliothek Dresden Technische Universität Dresden, Fakultät Informatik 2013-08-21 doc-type:conferenceObject application/pdf http://nbn-resolving.de/urn:nbn:de:bsz:14-qucosa-116966 urn:nbn:de:bsz:14-qucosa-116966 PPN392708752 http://www.qucosa.de/fileadmin/data/qucosa/documents/11696/greenit.pdf Proceedings of the 1st Annual International Conference on Green Information Technology (GREEN IT 2010) eng |
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English |
format |
Others
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topic |
Energieeffizienz Selbstoptimierung Nicht-funktionale Eigenschaften Energy-efficiency self-optimization non-functional properties ddc:004 rvk:ST 200 rvk:AR 26600 Energieeffizienz Selbstoptimierung |
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Energieeffizienz Selbstoptimierung Nicht-funktionale Eigenschaften Energy-efficiency self-optimization non-functional properties ddc:004 rvk:ST 200 rvk:AR 26600 Energieeffizienz Selbstoptimierung Götz, Sebastian Wilke, Claas Schmidt, Matthias Cech, Sebastian Aßmann, Uwe Towards Energy Auto Tuning |
description |
Energy efficiency is gaining more and more importance, since well-known ecological reasons lead to rising energy costs. In consequence, energy consumption is now also an important economical criterion. Energy consumption of single hardware resources has been thoroughly optimized for years. Now software becomes the major target of energy optimization. In this paper we introduce an approach called energy auto tuning(EAT), which optimizes energy efficiency of software systems running on multiple resources. The optimization of more than one resource leads to higher energy savings, because communication costs can be taken into account. E.g., if two components run on the same resource, the communication costs are likely to be less, compared to be running on different resources. The best results can be achieved in heterogeneous environments as different resource characteristics enlarge the synergy effects gainable by our optimization technique. EAT software systems derive all possible distributions of themselves on a given set of hardware resources and reconfigure themselves to achieve the lowest energy consumption possible at any time. In this paper we describe our software architecture to implement EAT. |
author2 |
Technische Universität Dresden, Fakultät Informatik |
author_facet |
Technische Universität Dresden, Fakultät Informatik Götz, Sebastian Wilke, Claas Schmidt, Matthias Cech, Sebastian Aßmann, Uwe |
author |
Götz, Sebastian Wilke, Claas Schmidt, Matthias Cech, Sebastian Aßmann, Uwe |
author_sort |
Götz, Sebastian |
title |
Towards Energy Auto Tuning |
title_short |
Towards Energy Auto Tuning |
title_full |
Towards Energy Auto Tuning |
title_fullStr |
Towards Energy Auto Tuning |
title_full_unstemmed |
Towards Energy Auto Tuning |
title_sort |
towards energy auto tuning |
publisher |
Saechsische Landesbibliothek- Staats- und Universitaetsbibliothek Dresden |
publishDate |
2013 |
url |
http://nbn-resolving.de/urn:nbn:de:bsz:14-qucosa-116966 http://nbn-resolving.de/urn:nbn:de:bsz:14-qucosa-116966 http://www.qucosa.de/fileadmin/data/qucosa/documents/11696/greenit.pdf |
work_keys_str_mv |
AT gotzsebastian towardsenergyautotuning AT wilkeclaas towardsenergyautotuning AT schmidtmatthias towardsenergyautotuning AT cechsebastian towardsenergyautotuning AT aßmannuwe towardsenergyautotuning |
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1716596641253818368 |