Evaluation of storage requirements and applications in the memory management for multidimensional signal processing systems

The amount of the data storage in signal processing systems, whose behavior is described by loop-organized algorithmic specifications, has an important impact on the overall energy consumption, chip area, as well as system performance. This paper presents a non-scalar approach for computing exactly the minimum data storage for high-level procedural specifications, where the main data structures are multi-dimensional arrays. In contrast, all the previous works are only estimation methods. In addition, the paper discusses two applications of this technique in the memory management of signal processing systems: (1) the evaluation of the impact of loop transformations on the data storage, and (2) the assessment of different models of mapping multi-dimensional signals into the physical memory.