基于电流追踪的供电网络温度感知电迁移分析方法
Temperature-Aware Electromigration Analysis with Current-Tracking in Power Grid Networks
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摘要: 1、研究背景(context)。
近年来,随着集成电路技术的发展,电迁移(EM)成为影响现代VLSI芯片可靠性的最为严重的问题。供电网络互连线电流密度的增大和线宽的减小,导致导线产生跟高的焦耳热和热耦合,进一步降低了芯片的可靠性。现有电迁移分析缺乏对互连线温度的准确评估,基于有限元温度仿真的模型,无法解决电迁移分析中应力,电流和温度的过程变化。通孔用了连接不同金属层的互连线和传导热量,具有特殊的电迁移特性,但温度对通孔电迁移分影响尚未得到充分解决。
2、目的(Objective):本研究提出了一种通孔的温度感知EM模型,考虑了供电网络互连线的自热和热耦合的影响,提高了分析精度。在全电网EM分析中,提出了基于电流追踪的分析方法,相应的结果可以确保在不牺牲准确性的情况下,提高大型供电网络EM评估分析的足够效率。
3、方法(Method):研究了供电网络互连线产焦耳热和热耦合的现象,得到温度模型,既通孔温度的升高受相连导线产生的焦耳热和相邻导线的热耦合离散叠加影响。在温度模型的基础上绘制电网局部温度分布图,结合电流追踪方法,从C4下方的通孔开始进行分析。
4、结果(Result&Findings):实验结果表明,考虑温度的EM分析与comsol仿真结果一致。基于电流追踪的全电网EM分析结果可以确保在不牺牲精度的情况下,分析效率明显提升。
5、结论(Conclusions):结果表明,温度对互连线EM有很大影响,考虑多种温度影响的电迁移分析,在精度上有了明显改善。结合供电网络的结构和局部性原理,基于电流追踪的全电网EM分析结果可以确保在不牺牲精度的情况下,对大型电网网络进行EM评估分析的足够效率。Abstract: Electromigration (EM) is a severe reliability issue in power grid networks. The via array possesses special EM characteristics and suffers from Joule heating and current crowding, closely related to EM violations. In this study, a power grid EM analysis method was developed to solve temperature variation effects for the via array EM. The new method is based on the temperature-aware EM model, which considers the effects of self-heating and thermal coupling of interconnected lines in a power grid. According to the model, the proposed methodology introduces a locality-driven strategy and current tracking to perform full-chip EM assessment for multilayered power grids. The results show that temperature due to Joule heating indeed has significant impacts on the via EM failure. The results further demonstrate that the proposed method might reasonably improve efficiency while ensuring the accuracy of the analysis.-
Keywords:
- electromigration (EM) /
- self-heating /
- thermal coupling /
- via
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期刊类型引用(1)
1. Farzaneh Asadzadeh, Akram Reza, Midia Reshadi, et al. Thermal-aware application mapping using genetic and fuzzy logic techniques for minimizing temperature in three-dimensional network-on-chip. The Journal of Supercomputing, 2024. 必应学术
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