GPU-Accelerated Inverse Lithography Towards High Quality Curvy Mask Generation

TL;DR

This paper presents a GPU-accelerated inverse lithography algorithm that enhances the quality, precision, and process window of curvilinear mask generation, addressing key challenges in mask rule checking for large-scale production.

Contribution

The paper introduces a novel GPU-accelerated ILT method that improves mask shape accuracy and process window, advancing curvilinear mask design for high-quality lithography.

Findings

Significant improvement in contour quality over existing ILT methods

Enhanced process window demonstrated on benchmark datasets

GPU acceleration enables faster and more precise mask optimization

Abstract

Inverse Lithography Technology (ILT) has emerged as a promising solution for photo mask design and optimization. Relying on multi-beam mask writers, ILT enables the creation of free-form curvilinear mask shapes that enhance printed wafer image quality and process window. However, a major challenge in implementing curvilinear ILT for large-scale production is mask rule checking, an area currently under development by foundries and EDA vendors. Although recent research has incorporated mask complexity into the optimization process, much of it focuses on reducing e-beam shots, which does not align with the goals of curvilinear ILT. In this paper, we introduce a GPU-accelerated ILT algorithm that improves not only contour quality and process window but also the precision of curvilinear mask shapes. Our experiments on open benchmarks demonstrate a significant advantage of our algorithm over leading academic ILT engines.