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

Abstract

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.