Semiconductor Layout Context Analysis Using Kernel Convolution
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Solution Overview
Problem
Traditional semiconductor layout analysis methods face challenges in efficiently extracting features around points of interest due to high computational time and memory requirements, especially when dealing with complex layouts containing billions of patterns, and are limited by edge-based pattern matching which struggles with random logic designs and hotspot detection.
Innovation Solution
A computer-implemented method that uses kernels to convolve with the semiconductor layout design, generating signatures for points of interest, which are then analyzed to extract relevant features tailored to specific downstream applications, such as optical proximity correction and hotspot detection, thereby expanding information content and improving modeling and simulation applications.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional image or pattern-based analysis methods are used to capture layout context, then the analysis can be performed with existing tools, but the computational time and memory requirements become excessively high due to the complexity of layouts with billions of patterns
Solution Approach 1:
The patent extracts only the essential geometric parameters needed for layout context analysis (e.g., distances to nearest polygons, orientation angles, area ratios) rather than processing the entire layout image or pattern data. This extraction approach retrieves critical information while discarding redundant data, significantly reducing computational time and memory requirements while maintaining analysis accuracy.
Solution Approach 2:
The patent transforms the layout analysis from image/pattern-based processing to parameter-based processing by defining specific geometric parameters (distances, angles, ratios) that characterize the layout context. This parameter transformation enables efficient computation using simple geometric calculations instead of complex image processing algorithms, resolving the contradiction between analysis precision and computational efficiency.
2Measurement precision
If traditional image or pattern-based analysis methods are used to capture layout context, then the analysis can be performed with existing tools, but the memory requirements become excessively high due to the complexity of layouts with billions of patterns
Solution Approach 1:
The patent extracts only the essential geometric parameters needed for layout context analysis (e.g., distances to nearest polygons, orientation angles, area ratios) rather than processing the entire layout image or pattern data. This extraction approach retrieves critical information while discarding redundant data, significantly reducing computational time and memory requirements while maintaining analysis accuracy.
Solution Approach 2:
Instead of processing the layout from the macro level (entire layout image or pattern) down to the point of interest, the patent inverts the approach by directly calculating local geometric parameters at the point of interest using efficient geometric queries. This inversion eliminates the need to load and process massive layout data into memory, achieving both accuracy and memory efficiency.
3Ease of manufacture
If edge-based pattern matching is used for layout analysis, then the implementation is straightforward, but the method fails to effectively detect hotspots and analyze random logic designs
Solution Approach 1:
The patent transitions from edge-based pattern matching to a parameter-based geometric analysis approach, defining parameters such as distances to nearest polygons, orientation angles, and area ratios. This parameter transformation enables the detection of subtle geometric patterns associated with hotspots and random logic designs while maintaining implementation simplicity through straightforward geometric calculations.
Solution Approach 2:
The patent introduces geometric parameters as intermediaries between the layout geometry and the analysis objectives. These parameters (distances, angles, ratios) serve as mediators that capture the essential characteristics of layout contexts, enabling reliable hotspot detection and random logic analysis without requiring complex pattern matching algorithms.
4Measurement precision
If comprehensive layout context is captured for each point of interest, then the analysis accuracy improves, but the computational complexity increases significantly
Solution Approach 1:
The patent transforms comprehensive layout context capture into efficient parameter calculation by defining specific geometric parameters (distances to nearest polygons, orientation angles, area ratios) that can be computed using simple geometric queries. This parameter-based approach achieves high analysis accuracy while maintaining low computational complexity through efficient algorithms for calculating distances, angles, and ratios.
Solution Approach 2:
The patent segments the comprehensive layout context into discrete geometric parameters (distance parameters, orientation parameters, area parameters) that can be independently calculated and combined. This segmentation enables accurate context capture by focusing on specific geometric relationships rather than processing the entire layout, thereby reducing computational complexity while maintaining analysis precision.
Data Source
AI summary
Systems and methods for analyzing a semiconductor layout design around a point of interest (POI) are disclosed. Semiconductor layout designs are a representation of an integrated circuit in terms of planar geometric shapes which make up the components of the integrated circuit, and are used to manufacture the integrated circuit. The layout design may be analyzed using one or more POI-based approaches to determine whether to modify the layout design. In one POI-based approach, set of kernels, tailored to the downstream application, are convolved with a representation of the layout design about or around the POI in order to generate a signature associated with the POI. In turn, the signatures may be analyzed based on the downstream application. Another POI-based approach consists of analyzing geometrical parameters associated with the POI, which may be used during a design stage to identify and modify problem areas in the layout design.