VLSI floorplanning based on Particle Swarm Optimization

Abstract

Floorplanning is an important problem in the very large integrated circuit (VLSI) design automation. It’s an NP-hard combinatorial optimization problem. The Particle Swarm Optimization (PSO) has been proved to be a good optimization algorithm with outstanding global performance. However, PSO cannot be directly used in the combinatorial optimization problem due to its continuous characterisic. In this paper a novel floorplanning algorithm based on Discrete PSO (DPSO) algorithm is proposed, in which integer coding based on module number was adopted. The principles of mutation and crossover operator in the Genetic Algorithm (GA) are also incorporated into the proposed PSO algorithm to achieve better diversity and break away from local optima. Experiments employing MCN and GSRC benchmarks show that the performance of our proposed algorithm for placement is good. The proposed algorithm can avoid the solution from falling into local minimum and have good convergence performance.