Automated Data Trend Analysis for IC Simulation Error Detection
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Solution Overview
Problem
Current data error detection techniques in semiconductor fabrication are inefficient and prone to human error, lacking accuracy in identifying errors within characterized electrical data from integrated circuit simulations, which can lead to defects in the fabrication process.
Innovation Solution
A method and system utilizing machine learning techniques to identify data trends within electrical data tables, flagging entries that deviate from these trends as bad data, and employing mathematical algorithms to determine distribution-based errors, reducing the need for human intervention and additional debugging steps.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional manual error detection techniques are used, then human operators can identify errors in electrical data, but the process is inefficient and prone to human error
Solution Approach 1:
The patent replaces manual mechanical error detection with automated electronic data processing systems. The system uses computational algorithms to automatically analyze electrical data, identify trends, and detect errors without human intervention, thereby eliminating human error while significantly improving processing efficiency and productivity.
2Reliability
If exhaustive testing is performed on cell designs before fabrication, then accuracy of simulation results is improved, but the fabrication process becomes more time-consuming and costly
Solution Approach 1:
The patent implements preliminary automated error detection and validation of electrical data before the fabrication process begins. By automatically identifying and flagging erroneous data points in advance, the system ensures simulation accuracy is maintained while significantly reducing the time required for validation compared to traditional exhaustive manual testing.
3Measurement precision
If manual debugging steps are performed to verify data accuracy, then errors can be identified, but the process requires extensive human intervention and additional time
Solution Approach 1:
The patent implements a self-service automated error detection system that independently validates electrical data without requiring human debugging intervention. The system automatically identifies trends, detects deviations, flags erroneous data, and provides validation results, thereby simplifying the debugging process while maintaining high data accuracy verification.
Data Source
AI summary
Various implementations described herein are directed to a system and methods for validating data points associated with an integrated circuit. In one implementation, the method may include retrieving data table associated with an integrated circuit, wherein the data table includes characterized electrical data associated with one or more cells of the integrated circuit. Further, the method may include converting the data table to one or more relative matrices. The one or more relative matrices are analyzed to determine a trend formed by entries of the one or more relative matrices. Further, the method may include determining whether one or more entries of the one or more relative matrices deviate from the trend. In response to the determination, the data table is flagged.