Test challenges for deep sub-micron technologies
Proceedings of the 37th Annual Design Automation Conference
Defect-Based Delay Testing of Resistive Vias-Contacts A Critical Evaluation
ITC '99 Proceedings of the 1999 IEEE International Test Conference
Statistical delay computation considering spatial correlations
ASP-DAC '03 Proceedings of the 2003 Asia and South Pacific Design Automation Conference
Proceedings of the 43rd annual Design Automation Conference
Variation-aware performance verification using at-speed structural test and statistical timing
Proceedings of the 2007 IEEE/ACM international conference on Computer-aided design
On efficient Monte Carlo-based statistical static timing analysis of digital circuits
Proceedings of the 2008 IEEE/ACM International Conference on Computer-Aided Design
Critical path selection for delay fault testing based upon a statistical timing model
IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems
Statistical Timing Analysis: From Basic Principles to State of the Art
IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems
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Critical path selection plays an important role in testing of small delay defects (SDD). For some timing-balanced circuits, the numbers of candidate critical paths may be very large, and this will make Monte Carlo simulation based statistical timing analysis very inefficient. A fast path selection approach based on graph partition is proposed in this paper. First, a critical path graph (CPG) is generated to implicitly enumerate almost all candidate critical paths, and then the CPG is partitioned into several sub graphs which contain limited numbers of paths using two graph partition approaches. After that, Monte Carlo simulation is applied on each sub graph for path selection. At last, according to the partition topology of the CPG and path sets selected from each sub graph, a path set for the original CPG is generated using Union and Cartesian product operations for testing SDDs. Experimental results show that for circuits containing large numbers of candidate critical paths, the proposed path selection approach can reduce the CPU time significantly and maintain a higher probability of capturing delay failures compared to path selection methods based on general Monte Carlo simulation.