Reducing the energy consumption of large scale computing systems through combined shutdown policies with multiple constraints

Anne Benoit 1, 2 Laurent Lefèvre 3, 1 Anne-Cécile Orgerie 4, 5 Issam Raïs 3, 1
2 ROMA - Optimisation des ressources : modèles, algorithmes et ordonnancement
Inria Grenoble - Rhône-Alpes, LIP - Laboratoire de l'Informatique du Parallélisme
3 AVALON - Algorithms and Software Architectures for Distributed and HPC Platforms
Inria Grenoble - Rhône-Alpes, LIP - Laboratoire de l'Informatique du Parallélisme
5 MYRIADS - Design and Implementation of Autonomous Distributed Systems
Inria Rennes – Bretagne Atlantique , IRISA_D1 - SYSTÈMES LARGE ÉCHELLE
Abstract : Large scale distributed systems (high performance computing centers, networks, data centers) are expected to consume huge amounts of energy. In order to address this issue, shutdown policies constitute an appealing approach able to dynamically adapt the resource set to the actual workload. However, multiple constraints have to be taken into account for such policies to be applied on real infrastructures: the time and energy cost of switching on and off, the power and energy consumption bounds caused by the electricity grid or the cooling system, and the availability of renewable energy. In this paper, we propose models translating these various constraints into different shutdown policies that can be combined for a multi-constraint purpose. Our models and their combinations are validated through simulations on a real workload trace.
Type de document :
Article dans une revue
International Journal of High Performance Computing Applications, SAGE Publications, 2018, 32 (1), pp.176-188. 〈10.1177/1094342017714530〉
Liste complète des métadonnées

Littérature citée [22 références]  Voir  Masquer  Télécharger

https://hal.inria.fr/hal-01557025
Contributeur : Issam Raïs <>
Soumis le : mercredi 5 juillet 2017 - 16:59:54
Dernière modification le : mardi 16 janvier 2018 - 15:35:07

Fichier

mainHALversion.pdf
Fichiers produits par l'(les) auteur(s)

Identifiants

Collections

Citation

Anne Benoit, Laurent Lefèvre, Anne-Cécile Orgerie, Issam Raïs. Reducing the energy consumption of large scale computing systems through combined shutdown policies with multiple constraints. International Journal of High Performance Computing Applications, SAGE Publications, 2018, 32 (1), pp.176-188. 〈10.1177/1094342017714530〉. 〈hal-01557025〉

Partager

Métriques

Consultations de la notice

305

Téléchargements de fichiers

84