MOGAC - A MULTIOBJECTIVE GENETIC ALGORITHM FOR HARDWARE-SOFTWARE COSYNTHESIS OF DISTRIBUTED EMBEDDED SYSTEMS

In this paper, we present a hardware-software cosynthesis system, call ed MOGAC, that partitions and schedules embedded system specifications consisting of multiple periodic task graphs. MOGAC synthesizes real-t ime heterogeneous distributed architectures using an adaptive multiobj ective genetic algorithm that can escape local minima. Price and power consumption are optimized while hard real-time constraints are met, M OGAC places no limit on the number of hardware or software processing elements in the architectures it synthesizes, Our general model for bu s and point-to-point communication links allows a number of link types to be used in an architecture. Application-specific integrated circui ts consisting of multiple processing elements are modeled, Heuristics are used to tackle multirate systems, as wed as systems containing tas k graphs whose hyperperiods are large relative to their periods. The a pplication of a multiobjective optimization strategy allows a single c osynthesis run to produce multiple designs that trade off different ar chitectural features. Experimental results indicate that MOGAC has adv antages over previous work in terms of solution quality and running ti me.