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Department of Electrical Engineering and Computer Science
Real-Time Computing Lab
1. Journal Articles
Thermal-aware resource management for embedded real-time systems
Lee, Youngmoon
;
Chwa, Hoon Sung
;
Shin, Kang G.
;
Wang, Shige
Department of Electrical Engineering and Computer Science
Real-Time Computing Lab
1. Journal Articles
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Title
Thermal-aware resource management for embedded real-time systems
Issued Date
2018-11
Citation
Lee, Youngmoon. (2018-11). Thermal-aware resource management for embedded real-time systems. IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems, 37(11), 2857–2868. doi: 10.1109/TCAD.2018.2857279
Type
Article
Author Keywords
Dynamic ambient temperature
;
embedded real-time systems
;
task-level power dissipation
;
thermal-aware resource management
Keywords
ENVIRONMENT
;
TASKS
ISSN
0278-0070
Abstract
With an increasing demand for complex and powerful system-on-chips, modern real-time automotive systems face significant challenges in managing on-chip-temperature. We demonstrate, via real experiments, the importance of accounting for dynamic ambient temperature and task-level power dissipation in resource management so as to meet both thermal and timing constraints. To address this problem, we propose RT-TRM, a real-time thermal-aware resource management framework. We first introduce a task-level dynamic power model that can capture different power dissipations with a simple task-level parameter called the activity factor. We then develop two new mechanisms, adaptive parameter assignment and online idle-time scheduling. The former adjusts voltage/frequency levels and task periods according to the varying ambient temperature while preserving feasibility. The latter generates a schedule by allocating idle times efficiently without missing any task/job deadline. By tightly integrating the solutions of these two mechanisms, we can guarantee both thermal and timing constraints in the presence of dynamic ambient temperature variations. We have implemented RT-TRM on an automotive microcontroller to demonstrate its effectiveness, achieving better resource utilization by 18.2% over other runtime approaches while meeting both thermal and timing constraints. © 2018 IEEE.
URI
http://hdl.handle.net/20.500.11750/9413
DOI
10.1109/TCAD.2018.2857279
Publisher
Institute of Electrical and Electronics Engineers Inc.
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