By lowering the number of vertical connections in fully connected 3D networks-on-chip (NoCs), partially connected 3D NoCs (PC-3DNoCs) help alleviate reliability and fabrication issues. This paper proposes a novel, adaptive congestion- and energy-aware elevator-selection scheme called AdEle to improve the traffic distribution in PC-3DNoCs. AdEle employs an offline multi-objective simulated-annealing-based algorithm to find good elevator subsets and an online elevator selection policy to enhance elevator selection during routing. Compared to the state-of-the-art techniques under different real-application traffics and configuration scenarios, AdEle improves the network latency by 14.9% on average (up to 21.4%) with less than 10.5% energy consumption overhead.

中文翻译：

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AdEle：适用于部分连接的3D NoC的自适应拥塞和能耗感知电梯选择

通过减少完全连接的3D片上网络（NoC）中​​的垂直连接数，部分连接的3D NoC（PC-3DNoC）有助于减轻可靠性和制造问题。本文提出了一种新颖的，自适应的，拥塞和能量感知的电梯选择方案，称为AdEle，以改善PC-3DNoC中的流量分配。AdEle采用离线多目标基于模拟退火的算法来查找良好的电梯子集，并采用在线电梯选择策略来增强路由选择过程中的电梯选择。与不同实际应用流量和配置方案下的最新技术相比，AdEle平均将网络延迟提高了14.9％（最高达到21.4％），而能耗开销却不到10.5％。