This paper addresses the problem of mapping an application, which is highly dynamic in the future, onto a heterogeneous multiprocessor platform in an energy efficient way. A two-phase scheduling method is used for that purpose. By exploring the Pareto curves and scenarios generated at design time, the run-time scheduler can easily find a good scheduling at a very low overhead, satisfying the system constraints and minimizing the energy consumption. A real-life example from a 3D quality of service kernel is used to show the effectiveness of our method.
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