Exploiting dataflows and Petri nets mappings

Abstract

Dataflow and Petri nets are used in modeling and analyzing streaming applications, which execute indefinitely using limited resources. Therefore it is essential to know if a system model guaranties certain properties, namely, liveness, boundedness or the maximal throughput. Besides, working with hardware/ software co-design techniques helps to define architecture and platform mapping, accommodating static and dynamically reconfigurable components. Over the last two decades a multitude of dataflow domains emerged along with the specificity of the outlined model of computation, in particular the Synchronous Dataflows, which have proved their adequacy in data-dominated systems, and it is nowadays a mature model of computation. This paper describes a set of translating rules allowing the mapping from Synchronous Dataflows into Petri nets. Study on invariants is presented. Signal processing application examples are used, illustrating the effectiveness of Petri net based modeling strategies to optimize digital system design, identifying a schedule that minimizes the amount of storage resource thus improving the systems' power consumption. The proposed approach allows one to know in advance at design stage the maximum potential and effective amount of storage resource at any signal processing system.