Template-Based IC Layout Placement for Analog Boundary Constraints
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Solution Overview
Problem
The increasing design complexity and time required for semiconductor layout, particularly in analog circuits, necessitates an automatic layout generation method that can accommodate various boundary conditions while maintaining design preferences.
Innovation Solution
A layout placement method involving the extraction of sub-cells from netlist data, virtual placement of layout elements based on templates, evaluation using a machine learning model, and selective routing to minimize wire length and area, leveraging a template-based approach to automate layout generation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If manual layout placement is performed by designing engineers, then design preferences and analog constraints can be considered, but time consumption and efficiency are reduced
Solution Approach 1:
The system performs preliminary actions by pre-defining multiple template layouts with different configuration options before actual placement. These templates contain pre-configured arrangement patterns for circuit components that can be directly applied, eliminating the need for manual layout design while preserving design quality through evaluated template selection.
Solution Approach 2:
The system changes parameters by evaluating multiple template layouts based on different criteria (area, wire length, design rules) and selecting the optimal template. This parameter-based evaluation and selection process automates the decision-making that previously required engineer judgment, maintaining layout quality while reducing time consumption.
2Productivity
If automatic layout generation is implemented, then time efficiency is improved, but adaptability to various boundary conditions and design preferences may be reduced
Solution Approach 1:
The system segments the layout design into multiple independent template options, each representing a different configuration approach. By dividing the design space into discrete templates with varying characteristics, the system can automatically evaluate and select the most appropriate template for specific boundary conditions, maintaining adaptability while enabling automation.
Solution Approach 2:
The system implements dynamics by making the template selection process adaptive to different boundary conditions. The evaluation mechanism dynamically chooses the most suitable template based on specific design requirements and constraints, allowing the automatic generation system to adapt to various scenarios rather than using a fixed approach.
3Manufacturing precision
If multiple template layouts are evaluated and selected based on optimization criteria, then layout quality is improved, but computational complexity increases
Solution Approach 1:
The system applies partial action by evaluating multiple templates but selecting only the single best option based on optimization criteria. This approach provides sufficient optimization quality by considering multiple possibilities while avoiding the excessive complexity of evaluating all possible layout configurations, achieving a balance between quality and computational effort.
Data Source
AI summary
An example method includes extracting a plurality of sub-cells based on netlist data; generating a first plurality of layout elements corresponding to the plurality of sub-cells; performing virtual placement of the first plurality of layout elements to obtain at least one virtually placed layout, the first plurality of layout elements corresponding to a plurality of layout elements that at least one template contains; selecting, based on evaluating the at least one virtually placed layout, a first template from the at least one template; and placing and routing the first plurality of layout elements based on the first template.