Abstract: Embodiments of the present disclosure relate to parallel mask rule checking on evolving mask shapes in optical proximity correction (OPC) flows for integrated circuit designs. Systems and methods are disclosed that perform mask (manufacturing) rule checks (MRC) in parallel, sharing information to maintain symmetry when violations are corrected. In an embodiment the shared information is also used to minimize changes to the geometric area of proposed mask shapes resulting from the OPC. In contrast to conventional systems, MRC is performed for multiple edges in parallel, sharing information between the different edges to encourage symmetry. In an embodiment, all edges may be adjusted in parallel to reduce mask-edge traversal bias.

Abstract: A semantic pattern extraction system can distill tremendous amounts of silicon wafer manufacturing data to generate a small set of simple sentences (semantic patterns) describing physical design geometries that may explain manufacturing defects. The system can analyze many SEM images for manufacturing defects in areas of interest on a wafer. A tagged continuous itemset is generated from the images, with items comprising physical design feature values corresponding to the areas of interest and tagged with the presence or absence of a manufacturing defect. Entropy-based discretization converts the continuous itemset into a discretized one. Frequent set mining identifies a set of candidate semantic patterns from the discretized itemset. Candidate semantic patterns are reduced using reduction techniques and are scored. A ranked list of final semantic patterns is presented to a user. The final semantic patterns can be used to improve a manufacturing process.

Abstract: A machine readable storage medium, a method and an apparatus. The method comprises selecting a candidate set of parameters from a plurality of available parameters comprising variables that affect an outcome of a lithography process; performing a set of optimizations wherein each optimization of the set of optimizations is subject to a plurality of objectives and tolerances and a set of constraints, wherein performance of said each optimization comprises: modifying values of at least a portion of the candidate set of parameters to derive a predicted outcome for said each optimization; and determining whether a difference between the predicted outcome and an intended outcome is within an error threshold; and if the difference exceeds the error threshold, perform a subsequent optimization, and otherwise generate an input file including modified values, corresponding to a last one of the set of optimizations, for the at least a portion of the candidate set of parameters.

Abstract: A machine readable storage medium, a method and an apparatus. The method comprises selecting a candidate set of parameters from a plurality of available parameters comprising variables that affect an outcome of a lithography process; performing a set of optimizations wherein each optimization of the set of optimizations is subject to a plurality of objectives and tolerances and a set of constraints, wherein performance of said each optimization comprises: modifying values of at least a portion of the candidate set of parameters to derive a predicted outcome for said each optimization; and determining whether a difference between the predicted outcome and an intended outcome is within an error threshold; and if the difference exceeds the error threshold, perform a subsequent optimization, and otherwise generate an input file including modified values, corresponding to a last one of the set of optimizations, for the at least a portion of the candidate set of parameters.

Abstract: A semantic pattern extraction system can distill tremendous amounts of silicon wafer manufacturing data to generate a small set of simple sentences (semantic patterns) describing physical design geometries that may explain manufacturing defects. The system can analyze many SEM images for manufacturing defects in areas of interest on a wafer. A tagged continuous itemset is generated from the images, with items comprising physical design feature values corresponding to the areas of interest and tagged with the presence or absence of a manufacturing defect. Entropy-based discretization converts the continuous itemset into a discretized one. Frequent set mining identifies a set of candidate semantic patterns from the discretized itemset. Candidate semantic patterns are reduced using reduction techniques and are scored. A ranked list of final semantic patterns is presented to a user. The final semantic patterns can be used to improve a manufacturing process.