Static run-time mode extraction by state partitioning in synchronous process networks

Abstract

Process Networks (PNs) are used for modeling streaming-oriented applications with changing behavior, which must be mapped on a concurrent architecture to meet the performance and energy constraints of embedded devices. Finding an optimal mapping of Process Networks to the constrained architecture presumes that the behavior of the PN is statically known. In this paper we present a static analysis for synchronous PNs that partitions the state space according to extract run-time modes based on a Data Augmented Control Flow Automaton (DACFA). The result is a mode automaton whose nodes describe identified program modes and whose edges represent transitions among them. Optimizing back-ends mapping from PNs to concurrent architectures can be guided by these analysis results.