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

Abstract — In this paper, we present a hardware–software cosynthesis system, called MOGAC, that partitions and schedules embedded system specifications consisting of multiple periodic task graphs. MOGAC synthesizes real-time heterogeneous dis-tributed architectures using an adaptive multiobjective genetic algorithm that can escape local minima. Price and power con-sumption 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 synthesizes. Our general model for bus and point-to-point communication links allows a number of link types to be used in an architec-ture. Application-specific integrated circuits consisting of multiple processing elements are modeled. Heuristics are used to tackle multirate systems, as well as systems containing task graphs whose hyperperiods are large relative to their periods. The application of a multiobjective optimization strategy allows a single cosynthesis run to produce multiple designs that trade off different architectural features. Experimental results indicate that MOGAC has advantages over previous work in terms of solution quality and running time. Index Terms—Genetic algorithm, hardware–software cosynthe-sis, low-power synthesis, multiobjective optimization. I