Optimization strategy of regular noc mapping using genetic-based hyper-heuristic algorithm

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SUMMARY

    The industry usually uses heuristic algorithms to solve the NoC mapping problems for a particular application, such as simulated annealing (SA), particle swarm optimization (PSO) algorithm, and genetic algorithm (GA), as well as some hybrid algorithms. Previous work mainly considered the possible negative effects of isomorphism solution on GA, but did not consider the introduction of isomorphism research into the hyperheuristic algorithm that is more suitable for NoC mapping and did not consider the possible positive effects of isomorphism solution during algorithm iteration. Based on the working mechanism of crossover operators in genetic algorithm . . .

     

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