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

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 s...

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Bibliographic Details
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
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Summary: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.
ISSN:2169-3536
2169-3536
DOI:10.1109/ACCESS.2021.3086698