DocumentCode :
1302581
Title :
Dynamic Power-Aware Mapping of Applications onto Heterogeneous MPSoC Platforms
Author :
Schranzhofer, Andreas ; Chen, Jian-Jian ; Thiele, Lothar
Author_Institution :
ETH Zurich, Zurich, Switzerland
Volume :
6
Issue :
4
fYear :
2010
Firstpage :
692
Lastpage :
707
Abstract :
Multiprocessor SOC platforms have been adopted for a wide range of high-performance applications, like automotive and avionic systems. Task assignment and processing unit allocation are key steps in the design of predictable and efficient embedded systems. Given the execution modes of applications, we propose a methodology to compute a task to processing element mapping, such that the expected average power consumption is minimized. Changing usage scenarios are represented by varying execution probabilities of modes. Statically precomputed template mappings for each execution probability are stored on the system and applied at runtime, allowing the system to adapt to changing environmental conditions. The underlying model considers static (leakage) and dynamic power. This study shows that deriving approximative solutions with a constant worst-case approximation factor in polynomial time is not achievable unless P = NP, even if a feasible task mapping is provided as an input. A polynomial-time heuristic algorithm is proposed that applies a multiple-step heuristic to derive template mappings. At runtime a manager monitors the system and chooses an appropriate precomputed template, hence low power-consumption is maintained over the systems lifetime. Experimental results reveal the effectiveness of the proposed algorithm by comparing the derived solutions to the optimal ones, obtained via an integer linear program (ILP).
Keywords :
embedded systems; integer programming; linear programming; microprocessor chips; multiprocessing systems; power aware computing; system-on-chip; automotive systems; avionic systems; dynamic power aware mapping; embedded systems; execution probability; heterogeneous MPSoC platforms; integer linear program; multiprocessor SOC; worst case approximation factor; Algorithm design and analysis; Automotive electronics; Embedded systems; Energy consumption; Multiprocessing systems; Power demand; Resource management; System-on-a-chip; Dynamic allocation; MPSoC; power-aware allocation; probabilistic applications;
fLanguage :
English
Journal_Title :
Industrial Informatics, IEEE Transactions on
Publisher :
ieee
ISSN :
1551-3203
Type :
jour
DOI :
10.1109/TII.2010.2062192
Filename :
5556024
Link To Document :
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