Scan Cluster Reordering for Low-Power Testing
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Solution Overview
Problem
The increasing size of circuits leads to higher power consumption during scan testing, causing reliability issues and the need for low-power scan structures, with existing methods either relying on test patterns or logic topology analysis, which are not fully effective in reducing test power.
Innovation Solution
A scan cluster reordering method that constructs a distance matrix between scan cells using a test pattern, performs scan correlation clustering to create a hierarchical structure, and reorders the scan chain based on this structure to place highly correlated scan cells adjacent to each other, reducing test power consumption.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If scan chain size is increased to test larger circuits, then test coverage is improved, but power consumption during scan testing increases
Solution Approach 1:
The scan chain is divided into multiple scan clusters, each processed independently. This segmentation allows the total power consumption to be distributed across multiple smaller groups rather than one large chain, reducing peak power demands while maintaining comprehensive test coverage across all circuit elements.
Solution Approach 2:
Scan cells are pre-ordered within clusters based on correlation analysis before the actual testing begins. This preliminary arrangement groups highly correlated cells together, optimizing the test sequence to minimize switching activity and power consumption during the scan operations.
2Use of energy by moving object
If scan cells are reordered to reduce power consumption, then power efficiency is improved, but test pattern effectiveness may be reduced
Solution Approach 1:
Different ordering strategies are applied to different regions (clusters) of the scan chain based on local correlation characteristics. Each cluster is optimized independently with high-correlation cells grouped together, while the overall test pattern effectiveness is maintained through the systematic construction of clusters that preserve necessary test coverage.
3Manufacturing precision
If hierarchical clustering is performed on scan cells, then scan chain reordering accuracy is improved, but computational complexity increases
Solution Approach 1:
The clustering process is segmented into hierarchical levels where scan cells are first grouped into small clusters, then these clusters are progressively merged into larger groups. This divide-and-conquer approach achieves accurate reordering through multiple passes of correlation analysis rather than requiring a single complex computation, reducing the peak computational burden.
Data Source
AI summary
The exemplary embodiments of the present invention provides a scan cluster reordering method and apparatus which perform a scan correlation aware scan cluster reordering to reduce a power generated during the scan test and place scan cells having a high correlation to be adjacent to each other by analyzing the correlation between scan cells, and reduce a test power generated during the scan test.