PatternPaint: Practical Layout Pattern Generation Using Diffusion-Based Inpainting
Dept. of Electrical & Computer Engineering, Duke University（杜克大学电气与计算机工程系）；Intel Corporation（英特尔公司）；Dept. of Electrical & Computer Engineering, TAMU, College Station（塔拉斯大学电气与计算机工程系）
Generating diverse VLSI layout patterns is essential for various downstream tasks in design for manufacturing, as design rules continually evolve during the development of new technology nodes. However, existing training-based methods for layout pattern generation rely on large datasets. In practical scenarios, especially when developing a new technology node, obtaining such extensive layout data is challenging. Consequently, training models with large datasets becomes impractical, limiting the scalability and adaptability of prior approaches. To this end, we propose PatternPaint, a diffusion-based framework capable of generating legal patterns with limited design-rule-compliant training samples. PatternPaint simplifies complex layout pattern generation into a series of inpainting processes with a template-based denoising scheme. Furthermore, we perform few-shot finetuning on a pretrained image foundation model with only 20 design-rule-compliant samples. Experimental results show that using a sub-3nm technology node (Intel 18A), our model is the only one that can generate legal patterns in complex 2D metal interconnect design rule settings among all previous works and achieves a high diversity score. Additionally, our few-shot finetuning can boost the legality rate with 1.87X improvement compared to the original pretrained model. As a result, we demonstrate a production-ready approach for layout pattern generation in developing new technology nodes.
Towards Geometric and Textural Consistency 3D Scene Generation via Single Image-guided Model Generation and Layout Optimization
Harbin Institute of Technology, Shenzhen（哈尔滨工业大学深圳分校）；Peng Cheng Laboratory（鹏城实验室）；Harbin Institute of Technology（哈尔滨工业大学）；Harbin Institute of Technology, Suzhou Research Institute（哈尔滨工业大学苏州研究院）
