Edge-Based Camera for Semiconductor Layout Characterization
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Solution Overview
Problem
Traditional pixel-based image analysis in semiconductor layout design is computationally expensive, limits the ability to decompose contextual polygon effects, and struggles with pattern matching and reconstruction, leading to inefficiencies in hotspot detection and layout optimization.
Innovation Solution
An edge-based camera system that characterizes Points of Interest (POIs) using topological and dimensional features, generating image representations based on relations and measurements, allowing for efficient analysis and reconstruction of layout designs without the need for traditional pixel-based approaches.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If pixel-based image analysis is used to characterize layout designs, then comprehensive image representation is achieved, but computational time and memory requirements increase significantly
Solution Approach 1:
The patent extracts only the essential topological and dimensional features from the complete pixel-based image representation. By taking out only the necessary geometric properties (topology, dimensions, orientations) rather than processing all pixel data, the system achieves efficient characterization with reduced computational overhead while maintaining analysis accuracy.
Solution Approach 2:
The patent creates simplified copies of the layout design by representing it through topological and dimensional features rather than full pixel data. These feature-based copies capture the essential geometric information needed for hotspot detection and layout analysis, enabling efficient processing without requiring the original high-resolution pixel representation.
2Loss of information
If pixel-based image analysis is used to characterize layout designs, then complete pattern information is captured, but memory requirements increase significantly
Solution Approach 1:
The patent extracts only the essential topological and dimensional features from the complete pixel-based image representation. By taking out only the necessary geometric properties (topology, dimensions, orientations) rather than processing all pixel data, the system achieves efficient characterization with reduced computational overhead while maintaining analysis accuracy.
Solution Approach 2:
Instead of representing the layout design through complete pixel data and then analyzing it, the patent inverts the approach by directly extracting topological and dimensional features from the geometric shapes. This inversion eliminates the need to store and process redundant pixel information, significantly reducing memory requirements while preserving all necessary pattern information for analysis.
3Adaptability or versatility
If traditional image analysis methods are used, then analysis can be performed on layout patterns, but the ability to decompose contextual polygon effects is limited
Solution Approach 1:
The patent segments the layout design into discrete geometric shapes and characterizes each shape's topological and dimensional features independently. This segmentation enables the system to decompose contextual polygon effects by analyzing individual shapes and their relationships, providing versatile pattern analysis capability while maintaining manageable system complexity through modular feature extraction.
Solution Approach 2:
The patent applies local quality analysis by extracting specific topological and dimensional features that are relevant to each local context in the layout design. Rather than applying uniform image analysis across the entire layout, the system adapts its feature extraction to capture locally relevant geometric properties, enhancing the ability to decompose contextual effects while keeping the overall system complexity manageable.
Data Source
AI summary
System and methods for an edge-based camera are disclosed. Semiconductor layout designs are a representation of an integrated circuit that are used to manufacture the integrated circuit. Parts of the layout design, such as points of Interest (POIs), may be subject to analysis with regard to a downstream application, such as hotspot detection. Unlike pixel-based characterizations, POIs are characterized using topological features indicative of quantized values and dimensional features indicative of analog values. For example, an edge may be characterized using a set of relations, which characterizes corners and polygons (including the polygon on which the POI resides and external polygons). In turn, the set of relations may be used to define image representations, including images in different directions relative to the POI (including cardinal and ordinal image). In this way, the topological/dimensional characterization of the POI may be used to analyze the POI in the layout design.