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Delay estimates for graphene nanoribbons: A novel measure of fidelity and experiments with global routing trees

机译:石墨烯纳米带的延迟估计:保真度的新方法和使用全局路由树的实验

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With extreme miniaturization of traditional CMOS devices in deep sub-micron design levels, the delay of a circuit, as well as power dissipation and area are dominated by interconnections between logic blocks. In an attempt to search for alternative materials, Graphene nanoribbons (GNRs) have been found to be potential for both transistors and interconnects due to its outstanding electrical and thermal properties. GNRs provide better options as materials used for global routing trees in VLSI circuits. However, certain special characteristics of GNRs prohibit direct application of existing VLSI routing tree construction methods for the GNR-based interconnection trees. In this paper, we address this issue possibly for the first time, and propose a heuristic method for construction of GNR-based minimum-delay Steiner trees based on linear-cum-bending hybrid delay model. Experimental results demonstrate the effectiveness of our proposed methods. We propose a novel technique for analyzing the relative accuracy of the delay estimates using rank correlation and statistical significance test. We also compute the delays for the trees generated by hybrid delay heuristic using Elmore delay approximation and use them for determining the relative accuracy of the hybrid delay estimate.
机译:随着传统CMOS器件在超亚微米设计级别上的极度小型化,电路的延迟以及功耗和面积都由逻辑模块之间的互连所支配。在寻找替代材料的尝试中,石墨烯纳米带(GNR)由于其出色的电学和热学性质,对于晶体管和互连都有潜力。作为VLSI电路中全局路由树的材料,GNR提供了更好的选择。但是,GNR的某些特殊特性禁止将现有的VLSI路由树构造方法直接应用于基于GNR的互连树。在本文中,我们可能是首次解决该问题,并提出了一种基于线性暨弯曲混合时滞模型构造基于GNR的最小时延Steiner树的启发式方法。实验结果证明了我们提出的方法的有效性。我们提出了一种新的技术,用于使用秩相关和统计显着性检验来分析延迟估计的相对准确性。我们还使用Elmore延迟近似来计算由混合延迟启发法生成的树的延迟,并将其用于确定混合延迟估计的相对精度。

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