Exploiting Varying Resource Requirements in Wavelet-based Applications in Dynamic Execution Environments

Abstract

In the context of future dynamic applications, systems will exhibit unpredictably varying platform resource requirements. To deal with this, they will not only need to be programmable in terms of instruction set processors, but also at least partial reconfigurability will be required. In this context, it is important for applications to optimally exploit the memory hierarchy under varying memory availability. This article presents a mapping strategy for wavelet-based applications: depending on the encountered conditions, it switches to different memory optimized instantations or localizations, permitting up to 51% energy gains in memory accesses. Systematic and parameterized mapping guidelines indicate which localization should be selected when, for varying algorithmic wavelet parameters. The results have been formalized and generalized to be applicable to more general wavelet-based applications.