Boltzmann-NSGAⅡ算法的NoC映射研究

Research of Network-on-Chip Mapping for Boltzmann-NSGAⅡ Algorithm

传统NSGAⅡ算法在解决NoC映射问题时容易出现局部最优和种群多样性的问题。为此,提出一个均衡优化时延模型和一种基于Boltzmann-NSGAⅡ的映射算法,时延模型从宏观链路负载和单个节点排队时延进行优化,映射算法引入Boltzmann机制、多点交叉算子、随机变异算子,以保持种群多样性并提高局部搜索能力。实验结果表明,Boltzmann-NSGAⅡ算法能获得更好的映射效果,最优解集的收敛性和均匀性更好。

Traditional NSGA II algorithms are easy to get local optimization and less diversity of the population. Aiming at the problems, this paper proposes a balanced optimized delay model and the Boltzmann-NSGA II mapping algorithm. The delay model is constructed fi＇om the macroscopic link load distribution and the single node queue latency. The Boltzmann mechanism, multi-point crossover operator, random mutation operator are introduced into the algorithm to maintain the diversity of the population and increase the local search capability. Simulation results prove that the optimal solution set obtained by the Boltzmann-NSGA II algorithm is better in the convergence and uniformity, and the mapping effect of the Boltzmann-NSGA II algorithm is better.