Standard Cell Extraction in IC Layouts Using Coarse-Fine Segmentation
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Solution Overview
Problem
Current automated systems for extracting standard cells from integrated circuit (IC) layouts are inefficient due to excessive processing time, sensitivity issues with low contrast and noise, misalignment of layers, and the need for extensive template matching, limiting their applicability to structured circuits and requiring manual operator direction.
Innovation Solution
A computationally efficient method involving feature extraction, characterization of points of interest with 32-bit descriptors, coarse and fine filtering, and confidence voting to determine high probability locations of standard cells, using morphological dilation and order statistics to account for noise and texture variations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If classical template matching is used to identify standard cells, then location accuracy is improved, but processing time increases excessively
Solution Approach 1:
The patent segments the template matching process into two distinct stages: coarse matching using simplified features (polysilicon layer geometry) to quickly identify candidate regions, and fine matching using detailed features (metal layer patterns) to confirm precise locations. This segmentation allows the system to achieve high accuracy without excessive processing time by applying computationally intensive operations only where necessary.
Solution Approach 2:
The patent performs preliminary coarse matching to pre-identify candidate standard cell locations before conducting detailed fine matching. By preparing candidate regions in advance through simplified comparison, the system reduces the search space for subsequent detailed analysis, thereby maintaining high accuracy while significantly reducing overall processing time.
2Productivity
If automated template matching is implemented, then extraction efficiency is improved, but reliability decreases due to sensitivity to noise and misalignment
Solution Approach 1:
The patent divides the matching process into coarse and fine stages, where the coarse stage uses robust polysilicon layer features that are less sensitive to noise and misalignment, while the fine stage uses detailed metal layer patterns for precise verification. This segmentation allows automated processing to proceed efficiently through the robust coarse stage while maintaining reliability through the verification-oriented fine stage.
Solution Approach 2:
The patent introduces an intermediary coarse matching stage that bridges the gap between automated efficiency and reliable accuracy. This intermediate stage uses simplified features to pre-filter candidate regions, reducing the impact of noise and misalignment on the final results while maintaining high extraction efficiency through automated processing.
3Measurement precision
If manual extraction of standard cells is performed, then accuracy is improved, but productivity decreases
Solution Approach 1:
The patent segments the extraction task into automated coarse matching that identifies candidate regions with high productivity, and automated fine matching that verifies locations with high accuracy. Both stages are fully automated, eliminating manual intervention while achieving accuracy comparable to manual extraction through the two-stage verification process.
Solution Approach 2:
The patent enables the system to perform self-verification through the two-stage matching process, where the coarse stage identifies candidates and the fine stage automatically verifies them against detailed patterns. This self-service mechanism eliminates the need for manual verification while maintaining high accuracy, thereby achieving both productivity and precision goals.
4Reliability
If comprehensive template matching is applied to all cells, then completeness is improved, but device complexity increases
Solution Approach 1:
The patent segments the matching process into two distinct algorithms with different complexity levels: coarse matching using simple polysilicon geometry and fine matching using detailed metal patterns. This segmentation allows the system to achieve comprehensive extraction by applying the appropriate level of complexity at each stage, avoiding the need for uniformly complex processing across all cells.
Solution Approach 2:
The patent applies partial action by using simplified coarse matching for initial identification and reserving detailed fine matching only for verification of candidate regions. This approach avoids the excessive complexity of applying comprehensive detailed matching to all cells uniformly, while still ensuring extraction completeness through targeted verification of promising candidates.
Data Source
AI summary
The present invention involves a computationally efficient method of determining the locations of standard cells in an image of an IC layout. The initial step extracts and characterizes points of interest of the image. A coarse localization of possible standard cell locations is performed and is based on a comparison of the points of interest of an instance of an extracted standard cell and the remaining points of interest in the image. A more rigid comparison is made on the list of possible locations comprising a coarse match and a fine match. The coarse match results in a shortlist of possible locations. The fine match performs comparisons between the template and the shortlist. Further filtering is done to remove the effects of noise and texture variations and statistics on the results are generated to achieve the locations of the standard cells on the IC layout.