원문정보
초록
영어
Known as an NP-Complete problem, the channel routing problem is very important in the automatic layout design of VLSI circuit and printed circuit boards. A distributed hybrid algorithm for this channel routing problem is presented in MPI environments. This system is implemented on a network of personal computers running Linux operating system connected via 100Mbps Ethernet. Each slave processor generates its own sub-population using genetic operations and communicates with the master processor in an asynchronous manner to form the global population. The proposed hybrid algorithm of Mean Field Annealing and Simulated annealing-like Genetic Algorithm combines the benefit of rapid convergence property of MFA and the effective genetic operations of SGA. The experimental results show that the proposed algorithm maintains the convergence properties of sequential genetic algorithm while it achieves linear speedup as the nets of the channel routing and the number of computing processors increase.
목차
1. Introduction
2. Genetic Operations for Channel Routing
2.1 Representation of Chromosome
2.2 Objective Function
2.3 Genetic Operators
3. The Proposed Distributed Algorithm
3.1 Distributed Mean Field Annealing (MFA)
3.2 Distributed Simulated Annealing-like Genetic Algorithm (SGA)
3.3 MGA Hybrid Algorithm
4. Simulated and Evaluation
5. Conclusions
References