Maximizing Utilization and Minimizing Migration in Thermal-Aware Energy-Efficient Real-Time Multiprocessor Scheduling

• Published in: IEEE access 2021, Vol.9, p.83309-83328
• Main Authors: Rubio-Anguiano, Laura Elena, Trabanco, Abel Chils, Velasco, Jose Luis Briz, Ramirez-Trevino, Antonio
• Format: Article
• Language: English
• Subjects: Algorithms; clustering algorithms; Context; control; Design factors; Job shop scheduling; Modular design; Multiprocessing; multiprocessors; Optimization; Partitioning algorithms; Petri nets; Processor scheduling; Real time; Real-time systems; Schedules; Scheduling; Switches; Task analysis; Utilization
• ISSN: 2169-3536; 2169-3536
• DOI: 10.1109/ACCESS.2021.3086698

This work proposes CAlECs, a clustered scheduling system for MPSoCs subject to thermal and energy constraints. It calculates off-line a cyclic executive honoring temporal and thermal constraints, for a hard real-time (HRT) task set at minimum frequency to reduce consumed energy, minimizing context switches and migrations. It also provides an on-line controller able to manage system and task parametric variations and soft real-time (SRT) tasks, always meeting the HRT task set constraints and the system thermal bound. CAlECS maximizes CPU utilization to help avoid overprovisioning contributing to a low SWaP factor. Its modular design allows the utilization of different modeling and scheduling approaches, and makes the off-line and on-line components independent from each other to better suit the requirements of a specific system. We experimentally show that the cyclic executive provided by CAlECS for HRT task sets outperforms RUN, a reference off-line algorithm in terms of optimal number of context switches.