Abstract
To solve underperforming particle swarm optimization algorithm for the optimization problem of discrete and easy to fall into local optimum problem in network on chip mapping algorithm, a hybrid optimization mapping Algorithm based on particle swarm optimization and genetic algorithm is proposed. It will implement separately GA and PSO operations by the two groups, by the superior individuals from GA algorithm instead of the initial random particles from PSO algorithm, which not only maintains the diversity of the group but also improves search efficiency. Simulation results based on NS-2 show that the Network-on-Chip from the automatic generation tools based on hybrid optimization mapping algorithm have a good performance in network latency, throughput, and link bandwidth optimization comparing the results of the random mapping under the same amount of computation scale.
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The work is supported in part by Department of Education of Guangdong Province under Grant 2015KTSCX162, 2015KTSCX163.
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Li, C., Chen, Y. (2016). Research on Network-on-Chip Automatically Generate Method Based on Hybrid Optimization Mapping. In: Gong, M., Pan, L., Song, T., Zhang, G. (eds) Bio-inspired Computing – Theories and Applications. BIC-TA 2016. Communications in Computer and Information Science, vol 682. Springer, Singapore. https://doi.org/10.1007/978-981-10-3614-9_31
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DOI: https://doi.org/10.1007/978-981-10-3614-9_31
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