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Multiprocessor implementations of real-time systems tend to be more energy-efficient than uniprocessor implementations. However several factors, including the nonexistence 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 tradeoff - 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.