Treffer: State space reconfigurability : An implementation architecture for self modifying finite automata

Many embedded systems exhibit temporally and behaviorally disjoint behavior slices. When such behaviors are captured by state machines, the current design flow will capture it as a union of all the behavior slices, and map it using traditional state assignment followed by logic synthesis. Such implementations costs are proportional to the union of all the behavior slices (in area, energy and delay). We propose to use self-modifying finite automata (SMFA), that have been studied from complexity-theoretic perspective, for expressing and implementing such adaptive behaviors in embedded systems. Towards this end, we present an implementation architecture for SMFAs. We compare the area, time and energy costs of SMFA implementations with the classical logic space (FSM) implementations for four adaptive behaviors.