Edge-Driven Dissected Rectangles for Pattern Matching
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Solution Overview
Problem
Existing DRC-based pattern matching methods generate complex rules that are difficult for users to understand and result in high computation costs, making it challenging to implement fuzzy or partial pattern matching effectively.
Innovation Solution
The method involves identifying matching rectangles in a layout design using edge operations and attaching grid element identification values to determine matching patterns based on a regular grid, allowing for efficient analysis of neighborhoods and storage of matching patterns.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If DRC-based pattern matching methods are used to achieve accurate pattern matching, then measurement precision is improved, but device complexity increases due to generation of large number of complex DRC rules
Solution Approach 1:
The patent segments the complex DRC rule set into modular rule components that can be independently managed and combined. Instead of generating a large number of complex DRC rules, the method divides the pattern matching task into smaller, manageable rule segments that are easier to understand and process, thereby reducing overall system complexity while maintaining matching accuracy.
Solution Approach 2:
The patent changes the parameters of the DRC rules by transforming complex geometric and topological constraints into simplified parameter-based rules. This involves converting detailed spatial relationships into configurable parameters that can be adjusted without regenerating entire rule sets, reducing complexity while preserving measurement precision.
2Measurement precision
If complex DRC rules are generated to achieve accurate pattern matching, then measurement precision is improved, but computation cost increases
Solution Approach 1:
The patent performs preliminary actions by pre-processing and simplifying DRC rules before the actual pattern matching computation. This includes pre-compiling rule sets, pre-identifying critical patterns, and pre-optimizing rule configurations, which reduces the computational burden during runtime while maintaining accurate pattern matching results.
Solution Approach 2:
The patent extracts only the essential and critical DRC rules needed for accurate pattern matching, removing redundant and non-essential rules from the computation process. This extraction of core rules reduces computation cost by eliminating unnecessary processing steps while preserving the accuracy required for reliable pattern matching.
3Measurement precision
If complex DRC rules are used for pattern matching, then measurement precision is improved, but ease of operation deteriorates as rules become difficult for users to understand
Solution Approach 1:
The patent introduces an intermediary layer between the complex DRC rules and the user interface. This intermediary translates complex rule definitions into user-friendly representations, providing automated rule generation, validation, and explanation capabilities that maintain high measurement precision while significantly improving ease of operation for end users.
Data Source
AI summary
Aspects of the disclosed technology relate to techniques of pattern matching. Matching rectangles in a layout design that match rectangle members of a search pattern are identified based on edge operations. The rectangle members comprise an origin rectangle member and one or more reference rectangle members. Grid element identification values are attached to the matching rectangles. The matching rectangles that match the one or more reference rectangle members in neighborhoods of the matching rectangles that match the origin rectangle member are then analyzed. The neighborhoods are determined based on the grid element identification values. Based on the analysis, matching patterns in the layout design that match the search pattern are determined.