Abstract: A method for optical proximity correction (OPC) comprises creating a semi-physical model of a mask for a current layer in an IC design layout using physical parameters of a lithography process used to create the mask, the semi-physical model specifying contours of the plurality of features of the mask. It is determined from design information whether the current layer is deformed by the one or more reference layers that overlap the current layer near the contours. Responsive to determining that the current layer is deformed by the one or more reference layers, the semi-physical model and the design information of the one or more reference layers are input into a trained machine learning algorithm to generate a contour shift prediction for the current layer, the contour shift prediction estimating a residual error of the semi-physical model. The contour shift prediction is then used for multilayer OPC correction of the current layer.

Abstract: Methods and apparatus for a knowledge-based deep learning refactoring model with tightly integrated functional nonparametric memory are disclosed. An example non-transitory computer readable medium comprises instructions that, when executed, cause a machine to at least estimate a first information extraction cost corresponding to retrieval of information from a local knowledge base, estimate a second information extraction cost corresponding retrieval of information from a remote knowledge base, select an information source based on the first and second estimated information extraction costs, query the selected information source, in response to determining that the selected information source was an external information source, store the queried information in the local knowledge base, organize the stored information in the local knowledge base, and return the queried information.

Abstract: A method for optical proximity correction (OPC) comprises creating a semi-physical model of a mask for a current layer in an IC design layout using physical parameters of a lithography process used to create the of the mask, the semi-physical model specifying contours of the plurality of features of the mask. It is determined from design information whether the current layer is deformed by the one or more reference layers that overlap the current layer near the contours. Responsive to determining that the current layer is deformed by the one or more reference layers, the semi-physical model and the design information of the one or more reference layers are input into a trained machine learning algorithm to generate a contour shift prediction for the current layer, the contour shift prediction estimating a residual error of the semi-physical model. The contour shift prediction is then used for multilayer OPC correction of the current layer.