通信学报2016，Vol.37Issue(11)：23-30,8.DOI:10.11959/j.issn.1000-436x.2016215
基于动态自适应离散粒子群算法的3D NoC低功耗映射方法
Dynamic adaptive discrete particle swarm optimization algorithm based method on low-power mapping in network-on-chip
摘要
Abstract
Compared to 2D NoC, 3D NoC has better integrated density and system performance, which was a reliable method to solve the problem about low-power mapping. On the basis of the traditional particle swarm optimization algo-rithm (PSOA), a dynamic adaptive discrete particle swarm optimization algorithm (DADPSOA) was proposed . Parame-ter in this algorithm was adjusted dynamically based on the degree of early convergence and the charge of individual adap-tive value to approach the optimal solution. At the same time, the reasonable structure of the particles was made aiming at reducing the time complexity of this algorithm. Experimental results show that comparing with the random mapping, genetic algorithm (GA), PSOA and dynamic ant colony algorithm (DACA), DADPSOA can save the execution time, reduce the communication power consumption of mapping results. The power consumption of the task graph is reduced.关键词
3D NoC/低功耗映射/解构造/自适应离散粒子群算法Key words
3D NoC/low-power mapping/deconstruction/adaptive discrete particle swarm optimization algorithm分类
信息技术与安全科学引用本文复制引用
刘勤让,戴启华,沈剑良,赵博..基于动态自适应离散粒子群算法的3D NoC低功耗映射方法[J].通信学报,2016,37(11):23-30,8.基金项目
国家高技术研究发展计划（“863”计划）基金资助项目(No.2014AA01A704)；国家自然科学基金创新群体基金资助项目（No.61521003）；国家自然科学基金面上基金资助项目（No.61572520）Foundation Items:The National High Technology Research and Development Program of China (863 program)(No.2014AA01A704), The Innovation Group Program Project of National Natural Science Foundation of China (No.61521003), The General Program of National Natural Science Foundation of China (No.61572520) （No.2014AA01A704）
