Design space exploration for low-power memory systems in embedded signal processing applications

This paper presents an energy-aware electronic design automation (EDA) methodology for the system-level exploration of hierarchical storage organizations, focusing mainly on data-intensive signal processing applications. Starting from the high-level behavioral specification of a given application, several memory management tasks are addressed in a common algebraic framework, using data-dependence analysis techniques similar to those used in modern compilers. Within this memory management software system, the designer can explore different algorithmic specifications functionally equivalent, by computing their minimum storage requirements. The system can perform an exploration based on energy consumption of signal assignments to the off- and on-chip memory layers, followed by a storage-efficient mapping of signals to the physical memories. The last phase of the methodology is an exploration approach for energy-aware banking of the on-chip memory, which takes into account both the static and dynamic energy consumption.