基于蚁群混沌遗传算法的片上网络映射

Ant Colony Chaos Genetic Algorithm for Mapping Task Graphs to a Network on Chip

蚁群算法可以在兼顾功耗和负载平衡的情况下进行任务映射,但是由于传统蚁群算法对初始化参数的设置比较敏感,所以使用遗传算法来调整蚁群算法参数,在蚁群算法陷入局部最优时引入混沌模型来修改蚁群参数.修改后的算法在能耗方面相较于传统算法改善了11%,在负载平衡方面改善了1%,两者联合优化改善了4%.

Ant colony algorithm is one of the solutions to task mapping,which optimizes the communication energy and the distribution of link load.Because the ant colony algorithm is very sensitive to the initialization of the parameters,we use genetic algorithm to set the parameter.To avoid getting the local optimal solution,we use chaos module to optimizing the parameter.The algorithm we improved gives a solution,which is 11% lower than the traditional algorithm on power,1% better than the traditional algorithm on load balance and 4% better when optimizing both of them.