WOAGA: A new metaheuristic mapping algorithm for large-scale mesh-based NoC

作     者：Wang, Xilu Sun, Yongjun Gu, Huaxi Liu, Zujun 

作者机构：Xidian Univ State Key Lab Integrated Serv Networks Xian 710071 Shaanxi Peoples R China 

出 版 物：《IEICE ELECTRONICS EXPRESS》 (日本电子情报通信学会电子快报)

年 卷 期：2018年第15卷第17期

页      面：20180738-20180738页

核心收录：

学科分类：0810[工学-信息与通信工程] 0808[工学-电气工程] 08[工学] 081001[工学-通信与信息系统] 

基　　金：National Science Foundation of China [61571340, 61634004] Fundamental Research Funds for the Central Universities [JB180309, JB170107] key research and development plan of Shaanxi province [2017ZDCXL-GY-05-01] General Armament Department and Ministry of Education United Fund [6141A0224-003] program of Introducing Talents of Discipline to Universities [B0803] 

主　　题：network-on-chip mapping metaheuristic algorithm 

摘      要：The mapping of IP cores to the topology is one of the most important steps for NoC (Network-on-Chip) design. Metaheuristic algorithms (MAs) are widely employed since the mapping is an NP-hard problem. Most mapping algorithms only consider small-scale NoC and ignore stability. In this letter, a stable metaheuristic algorithm called WOAGA, based on Whale Optimization Algorithm (WOA) and Genetic Algorithm (GA), is proposed for large-scale NoC mapping to achieve the low-energy consumption and stability. In the proposed algorithm, irregular crossover and mutation operations are integrated into the modified WOA. A perturbation is utilized to jump out of local optima effectively. Simulation results show that the proposed algorithm is more stable and achieve better solution with energy consumption reduced significantly.