A clustering approach to explore grain-sizes in the definition of weakly programmable processing elements

We explore the efficiency of a class of stream-oriented dataflow architectures as a function of the grain-size, for a given set of applications. We believe the grain-size is a key parameter in balancing flexibility and efficiency of this class of architectures. We apply a clustering approach on the well-defined set of applications to determine a set of weakly programmable processing elements of different grain-sizes. The resulting architectures are compared with respect to their silicon area. For a set of twenty one industrially relevant video algorithms, we determined architectures with various grain-sizes. The results of this exercise indicate an improvement factor of two for the silicon area, while changing the grain-size from fine-grain to coarser-grain