A Clustering Approach to Explore Grain-Sizes in the Definition of Processing Elements in Dataflow Architectures

Abstract

We explore the area efficiency of a class of stream-based 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 a well-defined set of applications to derive a set of processing elements of varying 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.

DOI: 10.1023/A:1008113601237

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@article{Lieverse1999ACA, title={A Clustering Approach to Explore Grain-Sizes in the Definition of Processing Elements in Dataflow Architectures}, author={Paul Lieverse and Ed F. Deprettere and Bart Kienhuis and Erwin A. de Kock}, journal={VLSI Signal Processing}, year={1999}, volume={22}, pages={9-20} }