MOGAC: A multiobjective genetic algorithm for the co-synthesis of hardware-software embedded systems

In this paper, we present a hardware-software co-synthesis system, called MOGAC, that partitions and schedules embedded system specifications consisting of multiple periodic task graphs. MOGAC synthesizes real-time heterogeneous distributed architectures using an adaptive multiobjective genetic algorithm that can escape local minima. Price and power consumption are optimized while hard real-time constraints are met. MOGAC places no limit on the number of hardware or software processing elements in the architectures it syn-thesizes. Our general model for bus and point-to-point communication links allows a number of link types to be used in an architecture. Application-specific integrated circuits consisting of multiple processing elements are modeled. Heuristics are used to tackle multi-rate sys-tems, as well as systems containing task graphs whose hyperperiods are large relative to their periods. The ap-plication of a multiobjective optimization strategy allows a single co-synthesis run to produce multiple designs which trade off different architectural features. Exper-imental results indicate that MOGAC has advantages over previous work in terms of solution quality and run-ning time.