Circuit Topology Recognition with Auto-Interactive Constraint Application
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Solution Overview
Problem
The complexity of modern electronic circuit design has led to challenges in manually creating and managing constraints for sub-circuits, resulting in errors, inefficiencies, and the inability of existing automated approaches to scale with rapidly changing design requirements and high-performance analog circuits.
Innovation Solution
A computer-implemented method and system that allows designers to interactively apply constraints to sub-circuits by selecting and modifying their topologies, using a graph-based search process to identify matching instances and apply recommended constraints, enabling a learn-by-example approach to automate the constraint assignment process.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If automated approaches are used to apply constraints to sub-circuits, then productivity is improved, but the ability to handle complex and changing design requirements deteriorates
Solution Approach 1:
The system dynamically adapts its constraint application behavior based on the complexity and characteristics of the circuit design. The graph-based search process adjusts its depth and breadth based on design requirements, allowing the same automated system to handle both simple and complex designs effectively.
Solution Approach 2:
The system changes operational parameters such as search depth, matching criteria, and constraint application thresholds based on the detected complexity of the circuit design. This allows the automated approach to scale with design requirements while maintaining high productivity.
2Adaptability or versatility
If manual constraint creation is used, then adaptability to specific design requirements is improved, but productivity and error rate deteriorate
Solution Approach 1:
The system performs self-service by automatically identifying sub-circuits, determining appropriate constraints, and applying them without requiring manual intervention for each step. The graph-based search process autonomously navigates the circuit design to find matching patterns and apply constraints consistently.
Solution Approach 2:
The system incorporates feedback mechanisms where designers can review and correct automated constraint applications. This feedback loop allows the system to learn from corrections and improve its automated performance, combining the speed of automation with the adaptability of human expertise.
3Productivity
If existing automated approaches are used, then productivity is improved, but measurement precision and reliability of constraint application deteriorate
Solution Approach 1:
The system segments the circuit design into a graph representation where nodes represent circuit elements and edges represent connections. This segmentation allows precise identification of sub-circuits and their relationships, improving the accuracy of constraint application while maintaining automation.
Solution Approach 2:
The system replaces mechanical manual inspection with an automated graph-based search algorithm that systematically traverses the circuit representation. This substitution improves both productivity and precision by eliminating human error while maintaining comprehensive coverage of the design.
4Measurement precision
If detailed manual analysis of each sub-circuit is performed, then measurement precision is improved, but loss of time increases
Solution Approach 1:
The system performs preliminary action by pre-processing the circuit design into a graph structure and pre-identifying potential sub-circuit patterns. This preparation allows for rapid constraint application without requiring time-consuming analysis during the actual constraint assignment process.
Solution Approach 2:
The system uses copying by creating a graph representation of the circuit design that can be rapidly traversed and searched. This digital copy allows repeated analysis and constraint application without re-processing the original design, significantly reducing time while maintaining precision.
Data Source
AI summary
A computer-implemented method of identifying sub-circuits in circuit designs includes: receiving a selection of a sub-circuit; specifying a match expression for the sub-circuit, where the match expression characterizes matching properties of components of the sub-circuit; modifying the match expression to change the matching properties of components of the sub-circuit; and producing an information structure in a computer readable medium, where the information structure associates a graph representing a topology of the selected sub-circuit with the modified match expression. Subsequently, the information structure corresponding to the selected sub-circuit can be identified in a given circuit design.