.png){kind=icon}
.png){kind=icon}
Return
DiffPattern-Flex: Efficient Layout Pattern Generation via Discrete Diffusion
.png){kind=icon}
PRE
AI
DOI：10.1109/TCAD.2025.3569493.png)
.png){kind=icon}
Original request for help.png){kind=icon}
Share.png){kind=icon}
Save
Abstract
En 中文
Recent advancements in layout pattern generation have been dominated by deep generative models. However, relying solely on neural networks for legality guarantees raises concerns in many practical applications. In this article, we present $\textsf {DiffPattern}$ -Flex, a novel approach designed to generate reliable layout patterns efficiently. $\textsf {DiffPattern}$ -Flex incorporates a new method for generating diverse topologies using a discrete diffusion model while maintaining a lossless and compute-efficient layout representation. To ensure legal pattern generation, we employ an optimization-based, glass-box pattern assessment process based on specific design rules. Furthermore, fast sampling and efficient legalization technologies are employed to accelerate the generation process. Experimental results across various benchmarks demonstrate that $\textsf {DiffPattern}$ -Flex significantly outperforms existing methods and excels at producing reliable layout patterns.
Keywords:
Design for manufacturability (DFM)
diffusion models
legalization
pattern generation
Journal
I
IF:
2.9
Papers:
586
Citations:
9.6K