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Techniques for the power efficient data path synthesis of sum-of-products computations between data and coefficients are presented. The proposed techniques exploit specific features of this type of computations. Efficient heuristics for the scheduling and assignment tasks, based on the concept of the Traveling Salesman's Problem, are described. Different cost functions are proposed to drive the synthesis tasks. The proposed cost functions target the power consumption either in the interconnect buses or in the functional units. Experimental results from different relevant digital signal processing algorithmic kernels prove that the proposed synthesis techniques lead to significant power savings.