Performance-driven MCM partitioning through an adaptive genetic algorithm

We present a novel genetic algorithm-based partitioning scheme for Multi-Chip Modules (MCMs) which integrates four performance constraints simultaneously: pin count, area, heat dissipation and timing. Experimental studies demonstrate the superiority of this method over deterministic Fiduccia Mattheyes (FM) algorithm and simulated annealing (SA) technique. The algorithm performs better than another such algorithm recently reported. The adaptive change of crossover and mutation probabilities results in better convergence.