Application Metaheuristic Technique for Solving VLSI Global Routing Problem

Abstract

Routing is an important and computationally intensive step in the VLSI physical design cycle. It is the process of interconnecting the cells that have been assigned positions as a solution of the placement problem. Global routing is a design action that precedes local routing and follows placement. Global routing decides about the distribution of the interconnections across the available routing channels. Then, all required connections can be established by solving the local routing problem in each channel separately. The combination of evolutionary algorithms with local search is named “Memetic Algorithms”. These methods are inspired by models of natural systems that combine the evolutionary adaptation of a population with individual learning within the lifetimes of its members. In the context of heuristic optimization, a meme is taken to represent a learning or development strategy. Thus a memetic model of adaptation exhibits the plasticity of individuals that a strictly genetic model fails to capture. This paper deals with application of memetic algorithms to solve the problem of global routing. More particularly the emphasis is on the topics of wire length minimization and reduction of channel capacitances, and congestion estimation which are of utmost priority in any global routing scenario.