A Clustering Approach to ExploreGrain - Sizes in the De nition of WeaklyProgrammable Processing

| We explore the eeciency of a class of stream-oriented dataaow 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 exibility and eeciency of this class of architectures. We apply a clustering approach on a well-deened set of applications to determine a set of weakly programmable processing elements of diierent grain-sizes. The resulting architectures are compared with respect to their silicon area cost. 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 ne-grain to coarser-grain.