NFGen: Normalizing Flow-Based Joint Generative Model for Variability-Aware Design Technology Co-Optimization

doi:10.1109/TCAD.2025.3604349

2025-08-29

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DOI：10.1109/TCAD.2025.3604349

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随着晶体管尺寸的不断缩小，变异性在电路设计和制造中的影响日益凸显。模型卡片中的精确表征有助于节省设计余量，并为设计技术协同优化（DTCO）提供适当的指导原则。为应对这一挑战，我们提出了一种基于归一化流的联合生成（NFGen）模型的新型机器学习框架，该模型能够从有限的模型卡片中生成全面的模型库。与传统生成方法不同，后者主要关注模型卡片参数的边缘分布，而NFGen是首个能够近似其联合分布的模型，该分布包含参数间的相关性信息，从而能够更准确地表示变异性效应。此外，我们引入了两种相似性度量方法，以严格评估生成模型卡片的质量。实验结果表明，与现有最先进方法相比，NFGen将总体误差降低了2倍至8倍，验证了其在变异性感知DTCO中的优越性。

Keyword:

Compact model card

design technology co-optimization (DTCO)

joint distribution

normalizing flow

parameter generation

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IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems

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2.9

论文数:

681

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9.6K

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beihang university

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5.2K

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被引数: 21

university of glasgow

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3.5W

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被引数: 37

peking university

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11.9W

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被引数: 146

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