IC Component Clustering via Dynamic Graph Migration
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Solution Overview
Problem
Current IC reverse engineering technologies require substantial expert-level human effort for organizing and analyzing integrated circuit components into functional, modular, and hierarchical blocks, making the process time-consuming and cost-ineffective.
Innovation Solution
A reverse engineering data analysis system and integrated circuit component data processing tool that uses a digital data processor to render a dynamic graph of IC component data nodes, attracting connected nodes and repulsing unconnected ones to cluster related components, facilitating automated organization and classification into functional groups.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If automated processes are used to create IC designs and route components, then productivity and design efficiency are improved, but the resulting circuit layouts become less visually intuitive and logically ordered
Solution Approach 1:
The patent creates a visual copy or representation of the automated circuit layout that reorganizes components into a more intuitive format. The system generates an alternative visualization that preserves the functional connectivity while presenting components in a logically ordered manner that is easier for humans to understand and analyze.
Solution Approach 2:
The patent transforms the circuit layout representation by introducing a new organizational dimension. Instead of displaying components solely in their physical automated placement positions, the system reorganizes them based on functional relationships, creating a multi-dimensional view that combines physical layout information with logical grouping.
2Measurement precision
If expert-level human effort is used to organize and analyze IC components into functional blocks, then analysis accuracy is improved, but time consumption and cost increase significantly
Solution Approach 1:
The patent implements a system where the IC design data structure performs self-organization and self-analysis. The circuit components automatically group themselves into functional blocks based on their connectivity and relationships, eliminating the need for expert human intervention while maintaining high accuracy in the analysis results.
Solution Approach 2:
The patent changes the organizational parameters of the circuit data from physical placement coordinates to functional relationship metrics. By analyzing connectivity patterns, signal flows, and component relationships, the system reorganizes the data structure to reflect functional blocks, achieving accurate analysis through automated parameter transformation rather than manual expert review.
3Loss of information
If IC components are organized into functional blocks using traditional methods, then functional understanding is improved, but the process becomes highly cost-ineffective
Solution Approach 1:
The patent replaces the mechanical process of manual expert analysis with an automated computational system. Instead of relying on human experts to physically examine and organize circuit data, the system uses algorithmic processing to automatically identify functional blocks, thereby maintaining complete functional understanding while dramatically reducing costs.
Data Source
AI summary
Described are reverse engineering data analysis systems, and integrated circuit component data processing tools and methods thereof. A system can comprise: a data storage device operable to store a data structure comprising extracted IC component data nodes representative of corresponding IC components of target IC and a connectivity therebetween; a graphical user interface (GUI); and a digital data processor operable on said data structure to: render, via said GUI, a dynamic graph of said data nodes; graphically migrate at least some of said data nodes on said dynamic graph as a function of a connectivity thereof with other nodes, wherein connected nodes are attractively displaced relative to one another such that said migrating nodes progressively cluster with related nodes to define distinct IC component clusters representative of distinct groups of related IC components of the target IC, whereas unconnected notes are repulsively displaced so to progressively distance said unconnected nodes.