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Emerging trends in applications with the requirement of considerable computational capacity and decreasing time-to-market have urged the need of multiprocessor systems. With the advent of multiprocessor systems, there is an increased demand to efficiently control their energy and power budget. As the technology scales to increasingly smaller feature sizes, the static power consumption is expected to grow exponentially which will also contribute a significant part in system's total power consumption. Moreover, modern-day applications are complex and offer limited extractable parallelism which eventually leads to poor performance by existing energy optimization techniques. In this paper, we present a two-fold framework for energy optimization. In the first step, we provide an algorithm, called MPSched (Minimum Processors for Schedulability), to optimize on the number of processors needed to fulfill execution requirement of target application. In the second step, we perform Static Voltage and Frequency Scaling (SVFS) to achieve an optimal energy profile of the system.