| Summary: | Complex embedded systems with multi-processing units are important platforms for running complex tasks. In the development of complex embedded systems, hardware/software partitioning plays an important role. In practical application, there are many dynamic tasks which require the hardware/software partitioning to be done in real time. It is necessary to design efficient algorithms to do this. In this paper, the shuffled frog leaping algorithm (SFLA) and the greedy algorithm (GRA) are used to generate a hybrid algorithm named SFLA-GRA. On the basis of the SFLA, the SFLA-GRA uses the greedy idea to terminate invalid iterations and adjust the search step size. By these greedy strategies, the algorithm can be effectively accelerated. Experimental results show that compared with the other swarm intelligence (SI) algorithms, the efficiency of the proposed algorithm has been improved.
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