Memory Size Computation for Multidimensional Signal Processing Applications

In real-time multimedia processing systems a very large part of the power consumption is due to the data storage and data transfer. Moreover, the area cost is often largely dominated by memories. Hence, the optimization of the memory architecture is a crucial step in the design methodology for this type of applications. In deriving an optimized memory architecture, memory size computation is an important step in the data transfer and storage exploration stage. This paper investigates non-scalar methods for computing exactly the memory size in real-time multimedia algorithms. The approach is based on novel algebraic techniques specific to the data-flow analysis used in modern compilers. In contrast with previous works which utilize only approximate methods due to the size of the problems (in terms of number of scalars), this research aims to obtain exact determinations even for large applications.