A Pruning and Feedback Strategy for Locating Reliability-Critical Gates in Combinational Circuits
A Pruning and Feedback Strategy for Locating Reliability-Critical Gates in Combinational Circuits
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DOI：
10.1109/tr.2022.3197787
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发表时间：
2023-09
影响因子：
5.9
通讯作者：
Jie Xiao;Weidong Zhu;Qing Shen;Haixia Long;Jungang Lou
中科院分区：
文献类型：
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作者：
Jie Xiao;Weidong Zhu;Qing Shen;Haixia Long;Jungang Lou
In nanometric integrated circuits, to harden reliability-critical gates (RCGs) is an important step to improve overall circuit reliability at a low cost. To locate RCGs quickly and efficiently is a key prerequisite for selective hardening at the early stage of circuit design. This article develops a new approach for locating RCGs for multiple input vectors in combinational circuits, using an input vector-oriented pruning technology to identify RCGs, and a sensitivity-based algorithm to measure the criticality of gate reliability (CGR) for each identified RCG. To accelerate the location of RCGs, a feedback-based algorithm mines the accumulated simulation data for each RCG, and a grouping algorithm handles RCGs with similar CGR in the stage of convergence checking. Simulations on 74-series and ISCAS 85 benchmark circuits show that the average accuracy of the proposed method is 0.986 with Monte–Carlo (MC) as the reference and it is 7181 times faster than the MC model. Also, this method performs better than other approximate algorithms in terms of location accuracy and time overhead.
