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  • 标题:Network Partitioning Domain Knowledge Multiobjective Application Mapping for Large-Scale Network-on-Chip
  • 本地全文:下载
  • 作者:Yin Zhen Tei ; Yuan Wen Hau ; N. Shaikh-Husin
  • 期刊名称:Applied Computational Intelligence and Soft Computing
  • 印刷版ISSN:1687-9724
  • 电子版ISSN:1687-9732
  • 出版年度:2014
  • 卷号:2014
  • DOI:10.1155/2014/867612
  • 出版社:Hindawi Publishing Corporation
  • 摘要:This paper proposes a multiobjective application mapping technique targeted for large-scale network-on-chip (NoC). As the number of intellectual property (IP) cores in multiprocessor system-on-chip (MPSoC) increases, NoC application mapping to find optimum core-to-topology mapping becomes more challenging. Besides, the conflicting cost and performance trade-off makes multiobjective application mapping techniques even more complex. This paper proposes an application mapping technique that incorporates domain knowledge into genetic algorithm (GA). The initial population of GA is initialized with network partitioning (NP) while the crossover operator is guided with knowledge on communication demands. NP reduces the large-scale application mapping complexity and provides GA with a potential mapping search space. The proposed genetic operator is compared with state-of-the-art genetic operators in terms of solution quality. In this work, multiobjective optimization of energy and thermal-balance is considered. Through simulation, knowledge-based initial mapping shows significant improvement in Pareto front compared to random initial mapping that is widely used. The proposed knowledge-based crossover also shows better Pareto front compared to state-of-the-art knowledge-based crossover.
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