Fine-grained defect diagnosis for CMOL FPGA circuits

Jihye Kim, Seokjun Jang, Sungho Kang

Research output: Contribution to journalArticlepeer-review

Abstract

Nanotechnology is an important technological alternative to overcome the limitations of complementary metal-oxide-semiconductor (CMOS) technology. Various circuit implementation methods based on nanotechnology have been proposed, and their most important characteristics are a high defect ratio and defect tolerance through circuit reconfiguration. CMOS-nanowire-MOLecular (CMOL) fieldprogrammable gate array (FPGA) circuits are advanced logic circuit structures that combine the advantages of CMOS and nanotechnology. However, researches on defect diagnosis methods for the reconfiguration of CMOL FPGA circuits are barely conducted. In this paper, efficient circuit configuration methods for defect diagnosis of the CMOL FPGA circuits are proposed to address the problem. Also, diagnosis algorithms for both stuck-at open and stuck-at close defects are introduced. Experimental results show that with the proposed methods, diagnosis is possible for CMOL fabrics with up to 20% stuck-at open defects and 0.02% or more stuck-at close defects.

Original languageEnglish
Pages (from-to)163140-163151
Number of pages12
JournalIEEE Access
Volume8
DOIs
Publication statusPublished - 2020

Bibliographical note

Funding Information:
This work was supported by the National Research Foundation of Korea (NRF) grant funded by the Korea government (MSIT) (No. 2019R1A2C3011079).

Publisher Copyright:
© 2020 Institute of Electrical and Electronics Engineers Inc.. All rights reserved.

All Science Journal Classification (ASJC) codes

  • Computer Science(all)
  • Materials Science(all)
  • Engineering(all)

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