Model-free control for resource harvesting in computing grids - Modelling and Optinal Decision for Uncertain Systems Accéder directement au contenu
Communication Dans Un Congrès Année : 2022

Model-free control for resource harvesting in computing grids

Résumé

Cloud and High-Performance Computing (HPC) systems are increasingly facing issues of dynamic variability, in particular w.r.t. performance and power consumption. They are becoming less predictable, and therefore demand more runtime management by feedback loops. In this work, we describe results addressing autonomic administration in HPC systems through a control theoretical approach. We more specifically consider the need for controllers that can adapt to variations a long time in the behavior of controlled systems, but also to being reused on different systems and processors. We therefore explore the application of Model-Free Control (MFC) in the context of resource harvesting in a Computing Grid, by regulating the injection of flexible jobs while limiting perturbation of the prioritary applications.
Fichier principal
Vignette du fichier
CCTA22.pdf (4.75 Mo) Télécharger le fichier
Origine : Fichiers produits par l'(les) auteur(s)

Dates et versions

hal-03663273 , version 1 (20-06-2022)
hal-03663273 , version 2 (02-07-2022)

Identifiants

Citer

Quentin Guilloteau, Bogdan Robu, Cédric Join, Michel Fliess, Éric Rutten, et al.. Model-free control for resource harvesting in computing grids. CCTA 2022 - Conference on Control Technology and Applications, CCTA 2022, Aug 2022, Trieste, Italy. ⟨10.1109/CCTA49430.2022.9966035⟩. ⟨hal-03663273v2⟩
265 Consultations
89 Téléchargements

Altmetric

Partager

Gmail Facebook X LinkedIn More