Memory organization for video algorithms on programmable signal processors

In this paper, several DSP system design principles are presented which are valid for a large class of memory-intensive algorithms. Our main focus lies on the optimization of the memory and I/O, since these are dominant cost factors in the domain of video and imaging applications. This has resulted in several formalizable mapping principles, which allow to prevent the memory from becoming a bottleneck. First, it as shown that for this class of applications, compile-time data caching decisions not only have a large effect on the performance, but also can have an even larger effect on the overall system cost and power consumption. This is illustrated by means of experiments in which the whole range of no cache up to large cache sizes is scanned. Next, it is shown that when enforcing constant I/O rates to reduce buffer sizes, the area gain may be far more important than the small performance decrease associated with it. A technique to achieve this in an efficient way is proposed. The main test-vehicle which is used throughout the paper to demonstrate our approach is the class of motion estimation type algorithms