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In contrast to current design practice for (programmable) processor mapping, which mainly targets performance, we focus on a systematic trade-off between cycle budget and energy consumed in the background memory organization. The latter is a crucial component in many of today's designs, including multimedia, network protocols and telecom signal processing. We have a systematic way and tool to explore both freedoms and to arrive at Pareto charts, in which for a given application the lowest cost implementation of the memory organization is plotted against the available cycle budget per submodule. This by making optimal usage of a parallelized memory architecture. We indicate, with results on a digital audio broadcasting receiver and an image compression demonstrator, how to effectively use the Pareto plot to gain significantly in overall system energy consumption within the global real-time constraints.