Pattern Selection for Computational Lithography
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Solution Overview
Problem
Current tools for identifying unique portions of a pattern layout in computational lithography produce a large number of unique portions with redundant information, burdening downstream computing processes with significant resource requirements.
Innovation Solution
A method for selecting an optimized, geometrically diverse subset of unique portions, reducing the number by up to 100 times while ensuring adequate pattern representation, using techniques such as set cover solvers and discrete optimizers to identify a subset of representative portions that encompass maximum unique geometry.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If current tools are used to identify unique portions of pattern layout, then complete pattern representation is achieved, but computing resource requirements increase significantly
Solution Approach 1:
The patent extracts only the essential geometric information from the complete pattern layout by identifying and selecting representative portions that capture unique geometric features. This extraction process filters out redundant information while preserving the core pattern characteristics needed for computational lithography, thereby reducing computing resource requirements without sacrificing representation completeness
Solution Approach 2:
The patent creates a simplified copy or representation of the original pattern layout by generating a reduced set of representative portions. This copy retains the essential geometric diversity and uniqueness of the original pattern while using significantly fewer data elements, enabling efficient computational processing with maintained pattern representation fidelity
2Adaptability or versatility
If all unique portions are included in the analysis, then comprehensive pattern coverage is achieved, but downstream computing processes become burdened
Solution Approach 1:
The patent segments the complete pattern layout into distinct representative portions, each capturing specific unique geometric features. By dividing the complex pattern into these segmented representative units, the system maintains comprehensive pattern coverage while reducing the overall complexity of downstream computing processes through manageable data granularity
Solution Approach 2:
The patent applies local quality by selectively representing different regions of the pattern layout with appropriate detail levels. Each representative portion is optimized to capture the unique geometric characteristics of its specific location, allowing comprehensive pattern coverage while reducing overall data volume and computing complexity through localized optimization
Data Source
AI summary
Selecting an optimized, geometrically diverse subset of clips for a design layout for a semiconductor wafer is described. A complete representation of the design layout is received. A set of representative clips of the design layout is determined such that individual representative clips comprise different combinations of one or more unique patterns of the design layout. A subset of the representative clips is selected based on the one or more unique patterns. The subset of the representative clips is configured to include: (1) each geometrically unique pattern in a minimum number of representative clips; or (2) as many geometrically unique patterns of the design layout as possible in a maximum number of representative clips. The subset of representative clips is provided as training data for training an optical proximity correction or source mask optimization semiconductor process machine learning model, for example.