Diagnosis technique for Clustered Multiple Transition Delay Faults
作者： Yan-Shen You , Chih-Yan Liu , Mu-Ting Wu , Po-Wei Chen , James Chien-Mo Li
DOI: 10.1109/ITC-ASIA51099.2020.00021
关键词:
摘要: Power supply noise induced IR drop can cause transition delay faults (TDF) clustered in a small region. However, traditional diagnosis technique cannot handle multiple TDF very well. This paper proposes tool for TDF. Star tracing is applied to find possible suspects. To tolerate fault masking and reinforcement effects, we propose an approximate covering heuristic group of During covering, extract important suspects which are likely be true We assume many physically cluster around so our prunes based on this assumption. use correlation coefficient determine the optimal number clusters (Optimal NC) apply K-means algorithm Finally, prune least but keep Simulation benchmark circuits shows that average accuracy (0.80) much better than commercial (0.47). Average resolution (0.35) also (0.23).
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