Large-scale analytical Fourier transform of photomask layouts using graphics processing units

J. A. Sakamoto
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Abstract

Compensation of lens-heating effects during the exposure scan in an optical lithographic system requires knowledge of the heating profile in the pupil of the projection lens. A necessary component in the accurate estimation of this profile is the total integrated distribution of light, relying on the squared modulus of the Fourier transform (FT) of the photomask layout for individual process layers. Requiring a layout representation in pixelated image format, the most common approach is to compute the FT numerically via the fast Fourier transform (FFT). However, the file size for a standard 26- mm×33-mm mask with 5-nm pixels is an overwhelming 137 TB in single precision; the data importing process alone, prior to FFT computation, can render this method highly impractical. A more feasible solution is to handle layout data in a highly compact format with vertex locations of mask features (polygons), which correspond to elements in an integrated circuit, as well as pattern symmetries and repetitions (e.g., GDSII format). Provided the polygons can decompose into shapes for which analytical FT expressions are possible, the analytical approach dramatically reduces computation time and alleviates the burden of importing extensive mask data. Algorithms have been developed for importing and interpreting hierarchical layout data and computing the analytical FT on a graphics processing unit (GPU) for rapid parallel processing, not assuming incoherent imaging. Testing was performed on the active layer of a 392- μm×297-μm virtual chip test structure with 43 substructures distributed over six hierarchical levels. The factor of improvement in the analytical versus numerical approach for importing layout data, performing CPU-GPU memory transfers, and executing the FT on a single NVIDIA Tesla K20X GPU was 1.6×104, 4.9×103, and 3.8×103, respectively. Various ideas for algorithm enhancements will be discussed.
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使用图形处理单元的光掩模布局的大规模解析傅立叶变换
在光学光刻系统中,曝光扫描期间透镜加热效应的补偿需要了解投影透镜瞳孔中的加热剖面。准确估计该轮廓的必要组成部分是光的总积分分布,依赖于各个工艺层的掩膜布局的傅里叶变换(FT)的平方模量。由于需要像素化图像格式的布局表示,最常用的方法是通过快速傅里叶变换(FFT)对FT进行数值计算。然而,5纳米像素的标准26- mm×33-mm掩模的文件大小在单精度下是惊人的137 TB;在FFT计算之前,数据导入过程本身会使该方法非常不实用。更可行的解决方案是以高度紧凑的格式处理布局数据,其中包含掩模特征(多边形)的顶点位置,这些顶点位置对应于集成电路中的元素,以及图案对称和重复(例如,GDSII格式)。如果多边形可以分解为可以解析FT表达式的形状,则解析方法可以大大减少计算时间并减轻导入大量掩模数据的负担。已经开发了用于导入和解释分层布局数据以及在图形处理单元(GPU)上计算分析FT的算法,以实现快速并行处理,而不是假设非相干成像。在392- μm×297-μm虚拟芯片测试结构的有源层上进行了测试,该结构具有分布在6个层次上的43个子结构。在导入布局数据、执行CPU-GPU内存传输和在单个NVIDIA Tesla K20X GPU上执行FT方面,分析方法与数值方法的改进因素分别为1.6×104、4.9×103和3.8×103。将讨论算法增强的各种想法。
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