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Energy and Thermal Aware Mapping for NoC Using Non-dominated Sorting Genetic Algorithm Ⅱ

机译:基于非支配排序遗传算法的NoC能量和热感知映射Ⅱ

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摘要

In order to overcome the hotspot problem caused by local high temperature, based on the establishment of the hotspot temperature assessment model, a mapping method was proposed which could reduce communication energy and weaken hotspot temperature. A Multi-objective optimization model of communication energy and hotspot temperature is constructed, then insertion positioning code method and non-dominated sorting genetic algorithm Ⅱ (NSGA-Ⅱ) with elite strategy are applied to find its Pareto optimal set. The algorithm is evaluated for two real traffic scenarios. Experimental results verify correctness of the hotspot temperature evaluation model, confirm effectiveness of the method in terms of both optimizing energy consumption and thermal balance, and show the solution found by the method outperforms other mono-objective methods.
机译:为了克服局部高温引起的热点问题,在建立热点温度评估模型的基础上,提出了一种可以降低通信能量,减弱热点温度的映射方法。建立了通信能量和热点温度的多目标优化模型,然后采用插入定位编码法和精英策略的非支配排序遗传算法Ⅱ(NSGA-Ⅱ)寻找其Pareto最优集。针对两个实际交通场景评估了该算法。实验结果验证了热点温度评估模型的正确性,在优化能耗和热平衡方面证实了该方法的有效性,并表明该方法获得的解决方案优于其他单目标方法。

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