Heterogeneous Simulation - Mixing Discrete-Event Models with Dataflow

Abstract

This paper relates to system-level design of signal processing systems, which are often heterogeneous in implementation technologies and design styles. The heterogeneous approach, by combining small, specialized models of computation, achieves generality and also lends itself to automatic synthesis and formal verification. Key to the heterogeneous approach is to define interaction semantics that resolve the ambiguities when different models of computation are brought together. For this purpose, we introduce a tagged signal model as a formal framework within which the models of computation can be precisely described and unambiguously differentiated, and their interactions can be understood. In this paper, we will focus on the interaction between dataflow models, which have partially ordered events, and discrete-event models, with their notion of time that usually defines a total order of events. A variety of interaction semantics, mainly in handling the different notions of time in the two models, are explored to illustrate the subtleties involved. An implementation based on the Ptolemy system from U.C. Berkeley is described and critiqued.