Energy-Aware Memory Allocation Framework for Embedded Data-Intensive Signal Processing Applications

Many signal processing systems, particularly in the multimedia and telecommunication domains, are synthesized to execute dataintensive applications: their cost related aspects — namely power consumption and chip area — are heavily influenced, if not dominated, by the data access and storage aspects. This paper presents an energy-aware memory allocation methodology. Starting from the high-level behavioral specification of a given application, this framework performs the assignment of the multidimensional signals to the memory layers — the on-chip scratchpad memory and the off-chip main memory — the goal being the reduction of the dynamic energy consumption in the memory subsystem. Based on the assignment results, the framework subsequently performs the mapping of signals into both memory layers such that the overall amount of data storage be reduced. This software system yields a complete allocation solution: the exact storage amount on each memory layer, the mapping functions that determine the exact locations for any array element (scalar signal) in the specification, and an estimation of the dynamic energy consumption in the memory subsystem. key words: multidimensional signal processing, memory management, memory allocation, dynamic energy consumption, signal-to-memory assignment