用离散扩散模型高效生成合规版图，兼顾多样性与速度
DiffPattern-Flex: Efficient Layout Pattern Generation via Discrete Diffusion
- 基于离散扩散模型生成多样版图拓扑
- 通过优化评估确保版图符合设计规则且无计算损耗
- 速度快、效率高，适合芯片设计等严苛场景
近年来，版图模式生成主要依赖深度生成模型。然而，仅靠神经网络保障合法性在实际应用中存在隐患。本文提出新方法 DiffPattern-Flex，利用离散扩散模型生成多样化拓扑结构，同时保持无损且高效的版图表示。为确保生成结果合法，采用基于设计规则的白盒优化评估流程。结合快速采样与高效合法性验证技术，显著加速生成过程。在多个基准测试中，DiffPattern-Flex 显著优于现有方法，能高效生成可靠版图。
原文摘要 · Abstract (English)
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 paper, we present \tool{DiffPattern}-Flex, a novel approach designed to generate reliable layout patterns efficiently. \tool{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, white-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 \tool{DiffPattern}-Flex significantly outperforms existing methods and excels at producing reliable layout patterns.
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