MOGAC: A multiobjective genetic algorithm for hardware-software cosynthesis of distributed embedded systems

Robert P. Dick, Niraj K. Jha

Research output: Contribution to journalArticlepeer-review

196 Scopus citations


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 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 synthesizes. 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 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.

Original languageEnglish (US)
Pages (from-to)920-935
Number of pages16
JournalIEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems
Issue number10
StatePublished - 1998

All Science Journal Classification (ASJC) codes

  • Software
  • Computer Graphics and Computer-Aided Design
  • Electrical and Electronic Engineering


  • Genetic algorithm
  • Hardware-software cosynthesis
  • Low-power synthesis
  • Multiobjective optimization


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