PERFORMANCE-DRIVEN MCM PARTITIONING THROUGH AN ADAPTIVE GENETIC ALGORITHM

We present a novel genetic algorithm-based partitioning scheme for mul tichip modules (MCM's) which integrates four performance constraints s imultaneously: pin count, area, heat dissipation, and timing. We also present a similar partitioning algorithm based on evolutionary program ming. Experimental studies demonstrate the superiority of these method s over deterministic Fiduccia-Mattheyes (FM) algorithm and simulated a nnealing (SA) technique. Our approach performs better than another gen etic algorithm-based method recently reported. The adaptive change of crossover and mutation probabilities results in better convergence of the partitioning algorithm.