High-Speed Algorithms for Scatterometry Diagnosis and GPU-based Optical Lithography Simulation
Date Issued
2010
Date
2010
Author(s)
Chiu, Meng-chun
Abstract
To ensure the quality of the nano-imprint fabricated optical gratings, optical scatterometry (OS) is an efficient and effective mean to diagnose the actual fabricated geometry. To facilitate the diagnosis process,
efficient pattern matching algorithms over a huge database are of great importance.
In my thesis, I will present an efficient algorithm to perform the least-square pattern matching in a huge
simulated spectrum database. Equipped with singular value decomposition and hierarchical moment
matching algorithm, the searching and diagnosis algorithm is extremely fast and accurate. It is over
$3000 imes$ faster than a plain searching algorithm within 0.1\% accuracy.
Optical micro-lithography image technology is a critical step in semiconductor manufacturing. As the VLSI manufacture technology develops, the feature size of micro-electronic devices shrinks smaller than the wavelength of exposure light source and challenges the limit of micro-lithography image system. Therefore, non-ideal effects in various processes of the stage of design and verification must be accurately taken into account and simulated to ensure a good yield of wafer and functional correctness. For this reason, high speed micro-lithography simulator is in strong demand for growing computational complexity to state-of-art resolution enhancement technology(RET) when handling modern industrial cases with millions of devices. In this work, we utilize parallel computing to speed up the image generation in micro-lithography simulation in order to provide more efficient optimization and verification.
Subjects
OS(optical scatterometry)
spectrum diagnosis
SVD(singular value decomposition)
moment matching
optical micro-lithography
GPU-based parallel computing
CUDA(compute unified device architecture)
Type
thesis
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