Computation of Memory Requirements for Multi - Dimensional Signal Processing Applications

Many integrated circuit systems, particularly in the multimedia and telecom domains , are inherently data dominant. For this class of systems, a large part of the power consumption is due to the data storage and data transfer. Moreover, the area cost is often largely dominated by memory. Hence, the optimization of the memory architecture is crucial in the design methodology for this type of applications. In deriving an optimized memory architecture, memory size computation is an important step in the exploration of the possible algorithmic specifications of multimedia applications. This thesis presents a novel non-scalar approach for computing exactly the memory size in real-time multi-dimensional signal processing algorithms, like tele-com and multimedia applications. This methodology uses both algebraic techniques specific to the data-flow analysis used in modern compilers, and also recent advances in the theory of rational polyhedra. In contrast with all the previous works which are only estimation methods, this approach performs exact memory computations even for applications with numerous and complex array references.