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Quantum-dot cellular automata (QCA) is considered as a promising emerging technology due to its low power dissipation and high device density. Since the majority function is the main operation in QCA circuits, minimizing the number of majority gates in QCA circuits is crucial to the corresponding QCA circuit minimization. A previous work used the node-merging technique to replace one target node with an existing substitute node in majority circuits for optimization. However, this technique may fail when no substitute nodes exist for a target node. In this article, we propose an enhanced optimization technique for majority circuits by adding a new node into the circuits and removing the target node and its fanin nodes. The experimental results show that this technique improves the results of the node-merging technique on a set of EPFL logic synthesis benchmarks. Additionally, this enhanced technique can work together with other optimization techniques. The circuit size reduction in the integrated approach reaches 1.26 times as compared to the results using the node-merging technique. [ABSTRACT FROM AUTHOR]

Single-electron transistor (SET) at room temperature has been demonstrated as a promising device for extending Moore’s law due to its ultralow power consumption. However, early realizations of SET array lacked variability and reliability due to their fixed architectures and high defect rates of nanowire segments. Therefore, a reconfigurable version of SET was proposed to deal with these issues. Recently, several automated mapping approaches have been proposed for area minimization of reconfigurable SET arrays. However, to the best of our knowledge, seldom mapping algorithms that consider the existence of defective nanowire segments were proposed. Furthermore, before the defect-aware mapping, we have to know the locations of defects in SET arrays. Thus, this paper presents the first diagnosis approach to identify the locations of defects in SET arrays followed by two defect-aware algorithms for mapping SET arrays in different scenarios. The experimental results show that the proposed diagnosis method can detect 100% of defects under a defect rate and distribution in SET arrays. As for the mapping algorithms, the results show that our approach can successfully map the SET arrays with 11.13% and 7.69% width overhead on average in the baseline detour mapping algorithm and defect-reuse mapping algorithm, respectively, in the presence of 5000-ppm defects. [ABSTRACT FROM AUTHOR]

This paper presents a logic restructuring technique named node addition and removal (NAR). It works by adding a node into a circuit to replace an existing node and then removing the replaced node. Previous node-merging techniques focus on replacing one node with an existing node in a circuit, but fail to replace a node that has no substitute node. To enhance the node-merging techniques on logic restructuring and optimization, we propose an NAR approach in this paper. We first present two sufficient conditions that state the requirements of added nodes for safely replacing a target node. Then, an NAR approach is proposed to quickly detect the added nodes by performing logic implications based on these conditions. We apply the NAR approach to circuit minimization together with two techniques: redundancy removal and mandatory assignment reuse. We also apply it to satisfiability (SAT)-based bounded sequential equivalence checking (BSEC) to reduce the computation complexity of SAT solving. The experimental results show that our approach can enhance our prior automatic test pattern generation-based node-merging approach. Additionally, our approach has a competitive capability of circuit minimization with 44 times speedup compared to a SAT-based node-merging approach. For BSEC, our approach can work together with other optimization technique to save a total of approximately 39-h verification time for all the benchmarks. [ABSTRACT FROM AUTHOR]