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This paper proposes a novel approach to solve the allocation and scheduling problems for variable voltage/frequency multiprocessor systems-on-chip, which minimizes overall system energy dissipation. The optimality of derived system configurations is guaranteed, while the computation efficiency of the optimizer allows for solving problem instances that were traditionally considered beyond reach for exact solvers (optimality gap). Furthermore, this paper illustrates the development- and run-time software infrastructures that assist the user in developing applications and implementing optimizer solutions. The proposed approach guarantees a high level of power, performance, and constraint satisfaction predictability as from validation on the target platform, thus bridging the abstraction gap.