A Computation Core for Communication Refinement of Digital Signal Processing Algorithms

The most popular Moore´s law formulation, which states the number of transistors on integrated circuits doubles every 18 months, is said to hold for at least another two decades. According to this prediction, if we want to take advantage of technological evolutions, designer´s productivity has to increase in the same proportions. To take up this challenge, system level design solutions have been set up, but many efforts have still to be done on system modelling and synthesis. In this paper we propose a computation core synthesis methodology that can be integrated on the communication refinement steps of electronic system level design tools. In the proposed approach, computation cores used for digital signal processing application specifications relying on coarse grain communications and synchronizations (e.g. matrix) can be refined into computation cores which can handle fine grain communications and synchronizations (e.g. scalar). Its originality is its ability to synthesize computation cores which can handle fine grain data consumptions and productions which respect the intrinsic partial orders of the algorithms while preserving their original functionalities. Such cores can be used to model fine grain input output overlapping or iteration pipelining. Our flow is based on the analysis of a fine grain signal flow graph used to extract fine grain synchronizations and algorithmic expressions