# DAMO: Deep Agile Mask Optimization for Full Chip Scale

arXiv: https://arxiv.org/abs/2008.00806 · HTML: https://mlsanity.com/paper/2008.00806/

## Key facts

- Cited by 24 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 21 Jul 2020.

## Built on by (most cited first, 24 of 24)

- [AnalogCoder: Analog Circuit Design via Training-Free Code Generation](https://mlsanity.com/paper/2405.14918/) (2024)
- [Machine Learning for Electronic Design Automation: A Survey](https://mlsanity.com/paper/2102.03357/) (2021)
- [Generic Lithography Modeling with Dual-band Optics-Inspired Neural Networks](https://mlsanity.com/paper/2203.08616/) (2022)
- [LLM-Enhanced Bayesian Optimization for Efficient Analog Layout Constraint Generation](https://mlsanity.com/paper/2406.05250/) (2024)
- [Large Scale Mask Optimization Via Convolutional Fourier Neural Operator and Litho-Guided Self Training](https://mlsanity.com/paper/2207.04056/) (2022)
- [ILILT: Implicit Learning of Inverse Lithography Technologies](https://mlsanity.com/paper/2405.03574/) (2024)
- [AdaOPC: A Self-Adaptive Mask Optimization Framework For Real Design Patterns](https://mlsanity.com/paper/2303.12723/) (2023)
- [Physics-Informed Optical Kernel Regression Using Complex-valued Neural Fields](https://mlsanity.com/paper/2303.08435/) (2023)
- [Inverse Lithography Physics-informed Deep Neural Level Set for Mask Optimization](https://mlsanity.com/paper/2308.12299/) (2023)
- [Keeping Deep Lithography Simulators Updated: Global-Local Shape-Based Novelty Detection and Active Learning](https://mlsanity.com/paper/2201.09717/) (2022)
- [CAMO: Correlation-Aware Mask Optimization with Modulated Reinforcement Learning](https://mlsanity.com/paper/2404.00980/) (2024)
- [Intelligent OPC Engineer Assistant for Semiconductor Manufacturing](https://mlsanity.com/paper/2408.12775/) (2024)
- [An Adversarial Active Sampling-based Data Augmentation Framework for Manufacturable Chip Design](https://mlsanity.com/paper/2210.15765/) (2022)
- [Optimizing Predictive AI in Physical Design Flows with Mini Pixel Batch Gradient Descent](https://mlsanity.com/paper/2402.06034/) (2024)
- [Fast inverse lithography based on a model-driven block stacking convolutional neural network](https://mlsanity.com/paper/2412.14599/) (2024)
- [MaskOpt: A Large-Scale Mask Optimization Dataset to Advance AI in Integrated Circuit Manufacturing](https://mlsanity.com/paper/2512.20655/) (2025)
- [Pushing the Limits of Inverse Lithography with Generative Reinforcement Learning](https://mlsanity.com/paper/2602.19027/) (2026)
- [DevelSet: Deep Neural Level Set for Instant Mask Optimization](https://mlsanity.com/paper/2303.12529/) (2023)
- [GPU-accelerated Matrix Cover Algorithm for Multiple Patterning Layout Decomposition](https://mlsanity.com/paper/2303.14335/) (2023)
- [Novel End-to-End Production-Ready Machine Learning Flow for Nanolithography Modeling and Correction](https://mlsanity.com/paper/2401.02536/) (2024)
- [Differentiable Edge-based OPC](https://mlsanity.com/paper/2408.08969/) (2024)
- [MorphOPC: Advancing Mask Optimization with Multi-scale Hierarchical Morphological Learning](https://mlsanity.com/paper/2605.12528/) (2026)
- [LithoGRPO: Fast Inverse Lithography via GRPO Reinforced Flow Matching](https://mlsanity.com/paper/2606.00228/) (2026)
- [VPEvolve: A Self-Evolving Virtual Process Engineer for Computational Lithography](https://mlsanity.com/paper/2609.32473/) (2026)

## Abstract (arXiv)

Continuous scaling of the VLSI system leaves a great challenge on manufacturing and optical proximity correction (OPC) is widely applied in conventional design flow for manufacturability optimization. Traditional techniques conducted OPC by leveraging a lithography model and suffered from prohibitive computational overhead, and mostly focused on optimizing a single clip without addressing how to tackle the full chip. In this paper, we present DAMO, a high performance and scalable deep learning-enabled OPC system for full chip scale. It is an end-to-end mask optimization paradigm which contains a Deep Lithography Simulator (DLS) for lithography modeling and a Deep Mask Generator (DMG) for mask pattern generation. Moreover, a novel layout splitting algorithm customized for DAMO is proposed to handle the full chip OPC problem. Extensive experiments show that DAMO outperforms the state-of-the-art OPC solutions in both academia and industrial commercial toolkit.