Dummy Feature Removal in VLSI Layout Data Structures
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Solution Overview
Problem
Current methods for reducing the size and complexity of VLSI device layout data structures are inefficient as they only compress dummy features without removing them, leading to increased processing time and obscured signal tracing due to the presence of non-functional elements.
Innovation Solution
A method and apparatus that detect and delete dummy features from source data structures by selecting a reference pattern, calculating correlation coefficients, and comparing them to a cut-off threshold value to identify and remove electrically non-functional elements, thereby reducing the size and complexity of the data structure.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If dummy features are compressed but not removed from the data structure, then the data size is reduced, but the processing time increases and signal tracing becomes obscured
Solution Approach 1:
The patent extracts and removes dummy features from the data structure entirely, rather than merely compressing them. By identifying dummy features through correlation analysis and deleting them from the layout data structure, the system eliminates the source of processing overhead and visual obstruction, achieving both data size reduction and processing time reduction simultaneously
2Quantity of substance
If dummy features are compressed but not removed, then data size is reduced, but signal tracing and analysis become more difficult
Solution Approach 1:
The patent removes dummy features from the data structure to eliminate visual obstruction during signal tracing. By extracting and deleting these non-functional elements, the system maintains data size reduction while simultaneously improving the clarity and ease of signal tracing and circuit analysis
3Quantity of substance
If a complex compression method is used to reduce data size, then the data structure becomes smaller, but the computing power required increases significantly
Solution Approach 1:
The patent employs a self-service approach where the system automatically identifies and removes dummy features through correlation analysis without requiring complex external compression algorithms. The method uses the data structure's own characteristics (correlation between adjacent pixels) to enable automatic detection and removal, significantly reducing computing power requirements compared to traditional compression methods
Data Source
AI summary
A method and apparatus to reduce occurrences of electrically non-functional elements, known as dummy features, from a source data structure is described. The source data structure may be image data, a vector based data structure or some other data format. Dummy features in the source data structure are detected and then deleted. Dummy features may be detected by selecting a representative dummy feature, using it as a reference pattern or polygon and comparing it to features in the source data structure. The step of comparing the selected reference to the comprises selecting a cut-off correlation threshold value, and computing the correlation coefficients between the reference and the feature. Features are selectively removed based on a comparison between their correlation coefficients and the selected cut-off correlation threshold value. This threshold value may require updating to remove all dummy features in the source data structure. When different shaped dummy features in the same data structure are encountered, a further reference feature may be selected and the process repeated.