Methodology for behavioral synthesis-based algorithm-level design space exploration

Abstract

Numerous fast algorithms for the DiscreteCosine Transform (DCT) have been proposed. Until recently, it has been difficult to compare different DCT algorithms and select one which is best suitedfor implementation under a given set of design goals.We propose an approach for design space explorationat the algorithm and behavioral levels using behavioral synthesis tools and demonstrate its effectiveness for designing DCT ASIC. In particular, we study andcompare the following nine DCT algorithms: Lee's,Wang's, DIT, DFT, Arai's, DIF, Vetterli's, planar rotation, and direct algorithm. The main conclusions of this study are (i) the best choice among fast DCT algorithms depends on a particular set of design goals and constraints and (ii) almost always more than anorder of magnitude improvement can be achieved using algorithm and behavioral design space exploration.