EDA Quality Assessment Parser and Viewer for Root Cause Analysis
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Solution Overview
Problem
In electronic design automation (EDA), designers face challenges in rapidly assessing the quality of results from intermediate design states and identifying the root cause of failures to meet target criteria, due to the large volume of reports and outputs generated, which can lead to misdiagnosis and overlooked issues.
Innovation Solution
A system comprising parsers and a viewer apparatus that extracts key information from task outputs, providing a unified GUI interface for analyzing metrics across multiple tasks and tools, and suggesting adjustments to inputs for improving design flow outcomes.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If designers manually examine reports and outputs from each design task, then they can assess quality of results and identify root causes, but the process is time-consuming and prone to human error
Solution Approach 1:
The patent introduces an intermediary system consisting of parsers and a viewer apparatus that mediates between the design tasks generating reports and the designer needing to assess quality. The parser automatically extracts relevant information from task outputs, and the viewer presents synthesized quality assessments, eliminating the need for manual examination while maintaining accurate root cause identification.
Solution Approach 2:
The system enables self-service by automatically generating quality assessments and root cause analyses without requiring designer intervention. The parser autonomously processes task outputs, identifies issues, and the viewer automatically presents findings, allowing the design process to continue without time-consuming manual review while maintaining high accuracy through systematic analysis.
2Reliability
If designers review all reports and outputs generated by design tasks, then comprehensive quality assessment is achieved, but the volume of information makes timely decision-making difficult
Solution Approach 1:
The parser extracts only the essential and relevant information from the comprehensive task outputs, separating critical quality indicators from the vast amount of unnecessary data. This extraction process maintains complete and reliable quality assessment by focusing on key metrics while eliminating information overload, enabling timely decision-making without sacrificing assessment thoroughness.
Solution Approach 2:
The system segments the comprehensive quality assessment into structured, manageable components through the parser that categorizes information by task type and issue severity. The viewer then presents these segmented findings in an organized manner, allowing designers to quickly understand overall quality status while maintaining access to detailed information when needed, thus preserving both reliability and productivity.
3Adaptability or versatility
If manual analysis of design outputs is performed, then designer judgment and experience can be applied, but misdiagnosis and overlooked problems occur due to human error
Solution Approach 1:
The system incorporates feedback mechanisms where the parser continuously monitors task outputs against known issue patterns and design criteria. The viewer presents synthesized findings that reflect both automated analysis and configured design requirements, providing consistent, error-free diagnosis while maintaining adaptability to different design contexts through configurable parameters and patterns that encode designer expertise.
Data Source
AI summary
Method and System for determining a next task in an Electronic Design Automation Flow, computer system and computer program product. One or more parsers configurable to identify one or more associated pre-defined data characteristics may be executed by a processor on a task output. Selected values obtained from the parser execution may be used to make a decision about the appropriate next action to be performed in the EDA flow. Selected values may provide suggestions or decisions about the appropriate next action to be performed in the EDA flow. Input for an associated task in the EDA flow may be suggested by the selected result values.