As the feature size of semiconductor technology shrinks to 10 nm and beyond, the multiple patterning lithography (MPL) attracts more attention from the industry. In this paper, we model the layout decomposition of MPL as a generalized graph coloring problem, which is addressed by a distribution evolutionary algorithm based on a population of probabilistic model (DEA-PPM). DEA-PPM can strike a balance between decomposition results and running time, being scalable for varied settings of mask number and lithography resolution. Due to its robustness of decomposition results, this could be an alternative technique for multiple patterning layout decomposition in next-generation technology nodes.

翻译：随着半导体工艺特征尺寸缩小至10纳米及以下，多重图案光刻技术（MPL）正受到工业界更多关注。本文将多重图案光刻的布局分解问题建模为广义图着色问题，并通过基于概率模型种群的分布进化算法（DEA-PPM）进行求解。DEA-PPM能够在分解结果与运行时间之间取得平衡，对掩模数量及光刻分辨率等不同参数设置具有良好的可扩展性。由于分解结果的鲁棒性，该方法有望成为下一代技术节点中多重图案布局分解的备选技术。