Energy-aware Implementation of Hard-real-time Systems upon Multiprocessor Platforms

Multiprocessor implementations of real-time systems tend to be more energy-eÆcient than uniprocessor implementations: since the power consumed by a CMOS processor is approximately proportional to the cube of the speed or computing capacity at which the processor executes, the total power consumed by an m-processor multiprocessor platform is approximately (1=m) times the power consumed by a uniprocessor platform of the same computing capacity. However several factors, including the non-existence of optimal multiprocessor scheduling algorithms, combine to prevent all the computing capacity of a multiprocessor platform from being guaranteed available for executing the real-time workload. In this paper, this tradeo | that while increasing the number of processors results in lower energy consumption for a given computing capacity, the fraction of the capacity of a multiprocessor platform that is guaranteed available for executing real-time work decreases as the number of processors increases | is explored in detail. Algorithms are presented for synthesizing multiprocessor implementations of hard-real-time systems comprised of independent periodic tasks in such a manner that the energy consumed by the synthesized system is minimized.