Spatial locality trade-offs of wavelet-based applications in dynamic execution environments

Future dynamic applications will require new mapping strategies to deliver power-efficient performance. Fully static design-time mappings will not address the unpredictably varying application characteristics and resource requirements. Instead, the platforms will not only need to be programmable in terms of instruction set processors, but also at least partial reconfigurability will be required, while the applications themselves will need to exploit this freedom at run-time to adapt to the dynamism. In this context, it is important for applications to exploit the memory hierarchy under varying memory availability. This paper presents a mapping strategy for wavelet-based applications: depending on the run-time conditions, it switches to different memory optimized instantiations, optimally exploiting temporal and spatial locality under these conditions. A comparison is performed between the gains of fully in-placed lifting-based wavelet transforms, and non in-placed versions with higher spatial locality.