Computational study demonstrates up to 64% energy reduction in lightly loaded multicore processors, suggesting substantial power gains from parallel low-frequency task execution.
For lightly loaded multicore processors that contain more processing cores than running tasks and have dynamic voltage and frequency scaling capability, we address the energy-efficient scheduling of periodic real-time tasks. First, we introduce two energy-saving techniques for the lightly loaded multicore processors: exploiting overabundant cores for executing a task in parallel with a lower frequency and turning off power of rarely used cores. Next, we verify that if the two introduced techniques are supported, then the problem of minimizing energy consumption of real-time tasks while meeting their deadlines is NP-hard on a lightly loaded multicore processor. Finally, we propose a polynomial-time scheduling scheme that provides a near minimum-energy feasible schedule. The difference of energy consumption between the provided schedule and the minimum-energy schedule is limited. The scheme saves up to 64 percent of the processing core energy consumed by the previous scheme that executes each task on a separate core.
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Wan Yeon Lee (2011) studied this question.
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