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By lowering the number of vertical connections in fully connected 3Dnetworks-on-chip (NoCs), partially connected 3D NoCs (PC-3DNoCs) help alleviatereliability and fabrication issues. This paper proposes a novel, adaptivecongestion- and energy-aware elevator-selection scheme called AdEle to improvethe traffic distribution in PC-3DNoCs. AdEle employs an offline multi-objectivesimulated-annealing-based algorithm to find good elevator subsets and an onlineelevator selection policy to enhance elevator selection during routing.Compared to the state-of- the-art techniques under different real-applicationtraffics and configuration scenarios, AdEle improves the network latency by10.9% on average (up to 14.6%) with less than 6.9% energy consumption overhead.

AdEle: An Adaptive Congestion-and-Energy-Aware Elevator Selection for Partially Connected 3D NoCs