| Autor: |
Shivashis Saha, Ying Lu, Jitender S. Deogun |
| Rok vydání: |
2012 |
| Předmět: |
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| Zdroj: |
HPCS |
| DOI: |
10.1109/hpcsim.2012.6266904 |
| Popis: |
The designs of heterogeneous multi-core multiprocessor real-time systems are evolving for higher energy efficiency at the cost of increased heat density. This adversely effects the reliability and performance of the real-time systems. Moreover, the partitioning of periodic real-time tasks based on their worst case execution time can lead to significant energy wastage. In this paper, we investigate adaptive energy-efficient task partitioning for heterogeneous multi-core multiprocessor realtime systems. We use a power model which incorporates the impact of temperature and voltage of a processor on its static power consumption. Two different thermal models are used to estimate the peak temperature of a processor. We develop two feedback-based optimization and control approaches for adaptively partitioning real-time tasks according to their actual utilizations. Simulation results show that the proposed approaches are effective in minimizing the energy consumption and reducing the number of task migrations. |
| Databáze: |
OpenAIRE |
| Externí odkaz: |
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