A hybrid bio-inspired optimisation approach for wirelength minimisation of hardware tasks placement in field programmable gate array devices

Abstract

In computer-aided design (CAD) flow of VLSI circuits, placement process is an NP-complete problem which requires an optimisation approach to obtain the system performance better. The main objective of placement is to reduce the wire length between the tasks with zero overlap. Fast response and better convergence algorithms are required to meet these desires. In this regard, bio-inspired optimisation algorithms such as genetic algorithm (GA) and particle swarm optimisation (PSO) algorithm have been considered. By using the salient features of these two algorithms, the optimised solution for placement problem has been obtained. The concept of GA has been applied followed by genetic algorithm to obtain optimised result. For experimentation, various directed data flow graphs (DDFGs) are randomly generated and the comparison is made between the GA, PSO and hybrid (GA-PSO) methods. The hybrid approach using GA-PSO produces better experimental results in wire length minimisation and, hence outperforms than the others.