Constraint-driven system partitioning

This paper describes how optimization techniques can be applied to efficiently solve the constrained co-design problem. This is performed by the formulation of different cost functions which will drive the hardware-software partitioning process. The use of complex cost functions allows us to capture more aspects of the design. Besides, the appropriate formulation of this kind of functions has a great impact on the results that can be obtained regarding both quality and algorithm convergence rate. A strong point of the proposed formulation is its generality. Therefore, it does not depend on the problem and can be easily extended for considering new design constraints