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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Saha, S. Ying Lu Deogun, J.S. |
| Copyright Year | 2012 |
| Abstract | Next-generation multi-core multiprocessor real-time systems consume less energy at the cost of increased power density. This increase in power-density results in high heat density and may affect the reliability and performance of real-time systems. Thus, incorporating maximum temperature constraints in scheduling of real-time task sets is an important challenge. This paper investigates thermal-constrained energy-aware partitioning of periodic real-time tasks in heterogeneous multi-core multiprocessor systems. We adopt a power model which considers the impact of temperature and voltage on a processor's static power consumption. Two types of thermal models are used to respectively capture negligible and non-negligible amount of heat transfer among cores. We develop a novel genetic-algorithm based approach to solve the heterogeneous multi-core multiprocessor partitioning problem. Extensive simulations were performed to validate the effectiveness of the approach. Experimental results show that integrating a worst-fit based partitioning heuristic with the genetic algorithm can significantly reduce the total energy consumption of a heterogeneous multi-core multiprocessor real-time system. |
| Starting Page | 41 |
| Ending Page | 50 |
| File Size | 352686 |
| Page Count | 10 |
| File Format | |
| ISBN | 9781467330176 |
| ISSN | 15332306 |
| e-ISBN | 9780769548241 |
| DOI | 10.1109/RTCSA.2012.15 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2012-08-19 |
| Publisher Place | Korea (South) |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Biological cells Real time systems Power demand Heat transfer Energy consumption Processor scheduling Multicore processing |
| Content Type | Text |
| Resource Type | Article |
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