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研究生： 吳家承
Wu, Chia-Cheng
論文名稱： 具有更廣義缺陷模型的可重構單電子電晶體陣列之診斷
Diagnosis for Reconfigurable Single-Electron Transistor Arrays with a More Generalized Defect Model
指導教授： 王俊堯
Wang, Chun-Yao
口試委員: 黃俊達
Huang, Juinn-Dar
陳勇志
Chen, Yung-Chih
學位類別： 碩士
Master
系所名稱： 電機資訊學院 - 資訊工程學系
Computer Science
論文出版年： 2019
畢業學年度： 107
語文別： 英文
論文頁數： 35
中文關鍵詞： 可重構單電子電晶體 、缺陷 、診斷
外文關鍵詞： Reconfigurable Single-Electron Transistor, Defect, Diagnosis
相關次數： 點閱：3  下載：0 
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    • 單晶電子晶體可以成為未來用於替代或與CMOS電路共存的低功率器件的候選硬體之一。在這項研究中，我們提出了一種更廣義的缺陷模型下的單晶電子晶體陣列的診斷方法。這個更廣義的缺陷模型，將使得診斷方法更加實用，與此同時，也會使得有缺陷之單晶電子晶體陣列診斷更加複雜。因此，針對更複雜的有缺陷之單晶電子晶體陣列，我們提出了與以前不同的診斷方法。我們對一組具有不同尺寸的單晶電子晶體陣列進行了實驗，實驗結果顯示， 我們的方法可以達到100%的覆蓋率，平均假陰性率為2.29%； 每個實驗在診斷過程可以於幾秒鐘內終止，因此，我們提出的診斷方法是非常有效率的。這項研究所提出的診斷方法， 可以用於更複雜的有缺陷之單晶電子晶體陣列診斷，並提高單晶電子晶體陣列的可靠性，使合成流程更加完整。

    Singe-Electron Transistor (SET) operations can be the promising candidate of low-power devices for replacement or co-existence with CMOS transistors/circuits in the future. In this work, we propose a diagnosis approach for SET array under a more generalized defect model. With the more generalized defect model, the diagnosis approach will become more practical but complicated. We conducted experiments on a set of SET arrays with different dimensions. The experimental results show that our approach can achieve 100% coverage with 2.29% false-negative rate on average. And the diagnosis approach is efficient since the diagnosis process can be terminated in a few seconds of each experiment. Therefore, our proposed diagnosis approach can diagnose the defective SET arrays with more complex defected SET array and elevate the reliability of the SET arrays to make the synthesis flow more complete.

    中文摘要---------------------------------------------i Abstract--------------------------------------------ii 誌謝辭----------------------------------------------iii Contents--------------------------------------------iv List of Tables--------------------------------------vi List of Figures-------------------------------------vii 1 Introduction---------------------------------------1 2 Preliminaries--------------------------------------4 2.1 Recon gurable SET Array---------------------------4 2.2 Symmetric Fabric Constraint----------------------6 2.3 Defect Model-------------------------------------7 2.4 Assumption of Defect Distribution ---------------8 3 Algorithm------------------------------------------10 3.1 Overview-----------------------------------------10 3.2 Vertical path diagnosis--------------------------14 3.3 Horizontal path diagnosis------------------------17 3.3.1 Boundary case ---------------------------------18 3.3.2 Normal case -----------------------------------20 3.4 Con rming the defect types of the candidates------21 4 Experimental Results-------------------------------24 5 Conclusions----------------------------------------31 6 Bibliography---------------------------------------32

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