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In several digital signal processing algorithms, computational nodes are organized in consecutive stages and data is reordered between these stages. Parallel computation of such algorithms with reduced number of processing elements implies that several computational nodes are assigned to each element. As a drawback, permutations become more complex and require data storage. In this paper, a systematic design methodology for stride permutation networks is derived. These permutations are represented with Boolean matrices, which are decomposed and mapped directly onto register-based networks. The resulting networks are regular and scalable and they support any stride of power-of-two. In addition, the networks reach the lower bound in the number of registers indicating area-efficiency. Since the proposed methodology is systematic, it can be exploited in automated design generation.