• Citer

Power Minimization for Parallel Real-Time Systems with Malleable Jobs and Homogeneous Frequencies

par Paolillo, Antonio ;Goossens, Joël ;Fisher, Nathan;Hettiarachchi, Pradeep M.
Organisme financeur ULB
Publication Publié, 2013

Rapport

• Accès en ligne
• Détails
• Contenu
• Statistiques

Résumé :

In this work, we investigate the potential benefit of parallelization for both meeting real-time constraints and minimizing power consumption. We consider malleable Gang scheduling of implicit-deadline sporadic tasks upon multiprocessors. By extending schedulability criteria for malleable jobs to DVFS-enabled multiprocessor platforms, we are able to derive an offline polynomial-time optimal processor/frequency-selection algorithm. Simulations of our algorithm on randomly generated task systems executing on platforms having until 16 processing cores show that the theoretical power consumption is up to 36 times better than the optimal non-parallel approach.