Computational lithography method for model-driven convolution neural network

A convolutional neural network and model-driven technology, applied in the field of computational imaging, can solve problems such as high computational complexity, affecting the imaging quality of the lithography system, and large convergence errors
CN108535952AActive Publication Date: 2018-09-14BEIJING INSTITUTE OF TECHNOLOGYGY
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Patent Information

Authority / Receiving Office
CN · China
Current Assignee / Owner
BEIJING INSTITUTE OF TECHNOLOGYGY
Publication Date
2018-09-14

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Abstract

The invention discloses a computational lithography method for a model-driven convolution neural network (MCNN), and the method can improve the computation speed and convergence performance of OPC (optical proximity correction) method. The technical scheme includes: expanding and truncating the gradient iterative algorithm, and constructing a model-driven convolution neural network (MCNN); based on an imaging model of a lithography system, constructing a decoder corresponding to the MCNN; bringing the MCNN and the decoder to end-to-end connection, and subjecting the MCNN to the following training: optimizing the parameters of the MCNN by back propagation algorithm to minimize the error between the input data of MCNN and the decoder; separating the decoder from the MCNN at the end of the training; inputting a to-be-optimized circuit layout into the trained MCNN so as to obtain an estimated result of an OPC mask; taking the estimated result of OPC mask as the initial value, and carryingout iterative updating on the set number of times of the mask by gradient iterative algorithm, thus obtaining the final OPC mask optimization result.
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Description

technical field

[0001] The invention relates to the technical field of computational imaging, in particular to a computational lithography method based on a model-driven convolution neural network (MCNN). Background technique

[0002] Lithography is one of the core technologies used to manufacture VLSI. The lithography system uses a light source to illuminate the mask, and the integrated circuit layout on the mask is reproduced on the silicon wafer through the projection objective lens. At present, the semiconductor industry mainly uses computational lithography to improve the resolution and imaging quality of lithography systems. Optical proximity correction (OPC for short) is one of the important computational lithography techniques. OPC technology modulates the amplitude of the light wave transmitted through the mask by modifying the mask pattern or adding necessary auxiliary patterns on the mask pattern, thereby compensating for imaging distortion caused by diffraction...

Claims

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