Global memory optimisation for embedded systems allowed by code duplication

The data transfers and storage are dominating contributors to the area and power consumption for all modern multimedia embedded systems. Modern high-level memory optimisations can ensure cost-efficient realisation of these systems. An important step in these optimisations are loop transformations performed on a geometrical model. However, these loop transformations traditionally cannot optimise code across data dependent conditions.In this paper we selectively duplicate the code in order to enable global loop transformations across data dependent conditions. We propose a technique which finds in a systematic way the Pareto curve in 2D exploration space: the better memory optimisations vs. the code increase. Our technique has been tested on an MP3 audio decoder. Results show 45.8% decrease in the number of main memory accesses which requires a 16.2% increase of code size.