Practical solutions for counting scalars and dependences in ATOMIUM-a memory management system for multidimensional signal processing

Image and video processing applications involve large multidimensional signals which have to be stored in memory modules. In application-specific architectures for real-time multidimensional signal processing, a significant cost in terms of chip area and power consumption is due to these background memory units. The multidimensional signals are usually modeled in behavioral descriptions with array variables. In the algorithmic specifications of our target applications, many of the array references cover large amounts of scalars. Therefore, the efficient handling of array references in the specifications for image and video processing is crucial for obtaining low cost memory allocation solutions. This paper addresses a central problem which arises when handling the array variables in behavioral specifications: the computation of the number of scalars covered by an array reference. This problem is closely related to the computation of dependences in data-flow analysis. The novel algorithms proposed in this paper are embedded in the ATOMIUM environment—a memory management system for multidimensional signal processing.