Process Hotspot Detection via Critical Design Rule Extraction
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Solution Overview
Problem
Current hotspot detection techniques in integrated circuit design are inadequate, leading to false alarms and high computational costs, making them impractical for early design stages and commercially unviable.
Innovation Solution
An accurate process hotspot detection technique based on critical design rule extraction, which generates horizontal and vertical tiles, adds directed edges to indicate relations between tiles, and uses modified transitive closure graphs to identify potential hotspots, verifying them through filtering and area comparisons.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If model-based OPC is used for hotspot detection, then measurement precision is improved, but computing time increases excessively
Solution Approach 1:
The layout is divided into multiple tiles, and the transitive closure graph is segmented into horizontal and vertical components. This segmentation allows the algorithm to process smaller subsets of the layout independently, reducing the overall computational complexity while maintaining detection accuracy.
Solution Approach 2:
The patent extracts only the critical transitive relations needed for hotspot detection from the full transitive closure graph. By taking out and processing only the essential horizontal and vertical relations separately, the method avoids the computational burden of processing the complete graph while preserving the accuracy needed for hotspot identification.
2Productivity
If rule-based OPC is used, then computing time is reduced, but manufacturing precision deteriorates due to inability to handle complex lithographic effects
Solution Approach 1:
The transitive closure graph serves as an intermediary data structure that captures the topological relationships between layout features. This intermediary representation allows the algorithm to efficiently query and analyze spatial relationships without performing full lithographic simulations, thus maintaining both speed and accuracy.
Solution Approach 2:
The patent transforms the two-dimensional layout problem into a graph-theoretic problem by constructing transitive closure graphs. This dimensional transformation allows complex spatial relationships to be analyzed through graph algorithms, achieving both efficiency and precision.
3Productivity
If existing hotspot detection methods are used, then false alarms occur, but reliability of detection is reduced
Solution Approach 1:
The algorithm uses the transitive closure graph to provide feedback about the topological relationships between features. This feedback mechanism allows the detection process to verify potential hotspots against the pre-computed relational data, reducing false alarms by confirming whether detected patterns actually match the critical topological configurations.
Data Source
AI summary
An accurate process hotspot detection technique based on DRC is provided. In this technique, critical DRC rules can be extracted from a pattern. This extraction can include generating horizontal tiles and vertical tiles in the pattern, and adding directed edges to indicate relations between adjacent tiles in the pattern. Rule rectangles, which can also be generated during the critical DRC rule extraction, describe polygon placement in the pattern with a minimal number of critical DRC rules. The extracted DRC rules can be included in a DRC runset file. DRC can be performed with the DRC runset file on a layout. The DRC results can be filtered using the rule rectangles to identify potential hotspots and to verify actual hotspots.