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AdEle: An Adaptive Congestion-and-Energy-Aware Elevator Selection for Partially Connected 3D NoCs
arXiv - CS - Hardware Architecture Pub Date : 2021-02-16 , DOI: arxiv-2102.08323 Ebadollah Taheri, Ryan G. Kim, Mahdi Nikdast
arXiv - CS - Hardware Architecture Pub Date : 2021-02-16 , DOI: arxiv-2102.08323 Ebadollah Taheri, Ryan G. Kim, Mahdi Nikdast
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:
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%。
更新日期:2021-02-17
中文翻译:
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%。