自适应混沌遗传退火的片上网络映射  

NoC Mapping of Adaptive Chaos Genetic Annealing

作　　者：张剑贤[1] 杨银堂[1] 周端[2] 董刚[1] 赖睿[1] 高翔[1] 

机构地区：[1]西安电子科技大学微电子学院,西安710071 [2]西安电子科技大学计算机学院,西安710071

出　　处：《北京邮电大学学报》2011年第4期6-9,共4页Journal of Beijing University of Posts and Telecommunications

基　　金：国家杰出青年科学基金项目(60725415);国家自然科学基金项目(60676009;90407016;60902080)

摘　　要：针对带宽和时延约束的低能耗片上网络(NoC)映射问题,提出了一种自适应的混沌遗传退火映射算法.该算法利用Boltzmann更新机制选择遗传个体,引入自适应混沌方法优化适应度较差个体,采用多邻域的退火策略优化较优个体.实验结果表明,所提算法有效地避免了早熟收敛,提高了算法收敛速度,与标准遗传算法和混沌遗传算法相比,平均节能分别为45%和22.6%,有效地降低了NoC系统通信能耗.An adaptive chaos genetic annealing algorithm is proposed to solve the mapping problem of low-energy consumption network-on-chip （NoC） subject to the constraints of bandwidth and communication latency. Based on Bohzmann update mechanism, the algorithm makes a selection of genetic individuals. Individuals with poor fitness are optimized by the adaptive chaos method, while the optimum individuals are optimized by the strategy of multi-neighborhood annealing. Experiments suggest that the proposed algorithm is able to avoid premature convergence and increase the convergence speed. Compared with the standard genetic algorithm and the chaos genetic algorithm, 45% and 22.6% energy savings are achieved on average, respectively, thus effectively reducing the energy consumption of NoC system communications.

关 键 词：片上网络 映射算法 低能耗 自适应混沌 遗传退火 

分 类 号：TP302[自动化与计算机技术—计算机系统结构]