Mode-Controlled Data Flow

Abstract

In the process of choosing a Data Flow (DF) programming model for describing an application, one must make a difficult trade off between expressiveness and analytical properties. At one extreme, a Dynamic Data-flow (DDF) model is expressive enough to mimic the behavior of a Turing machine [10], but lacks many useful analytical properties; for instance, for an arbitrary DDF graph it may be impossible to verify if it is free of deadlocks, or if it can execute for indefinite time on bounded buffer space [10]. On the other hand, Static Data flow (StDF) variants (such as Multi-Rate DF [57], Single-Rate DF [80], or Cyclo-Static DF [9]) allow for powerful analysis, such as the verification of deadlock-freedom, determination of maximum achievable throughput, and verification of latency and throughput constraints, but have limited expressivity: all actors must work with fixed data rates, i.e., all quantities of data sent/received per actor firing cannot be dependent on the values of the input data. Because of these limitations, StDF models tend to be reserved for application domains where task activation is data-driven, data rates regular, and real-time guarantees required.