Detection, diagnosis, and repair of faults in memristor-based memories

Sachhidh Kannan, Naghmeh Karimi, Ramesh Karri, Ozgur Sinanoglu

Research output: Chapter in Book/Report/Conference proceedingConference contribution


Memristors are an attractive option for use in future memory architectures due to their non-volatility, high density and low power operation. Notwithstanding these advantages, memristors and memristor-based memories are prone to high defect densities due to the non-deterministic nature of nanoscale fabrication. The typical approach to fault detection and diagnosis in memories entails testing one memory cell at a time. This is time consuming and does not scale for the dense, memristor-based memories. In this paper, we integrate solutions for detecting and locating faults in memristors, and ensure post-silicon recovery from memristor failures. We propose a hybrid diagnosis scheme that exploits sneak-paths inherent in crossbar memories, and uses March testing to test and diagnose multiple memory cells simultaneously, thereby reducing test time. We also provide a repair mechanism that prevents faults in the memory from being activated. The proposed schemes enable and leverage sneak paths during fault detection and diagnosis modes, while still maintaining a sneak-path free crossbar during normal operation. The proposed hybrid scheme reduces fault detection and diagnosis time by ∼44%, compared to traditional March tests, and repairs the faulty cell with minimal overhead.

Original languageEnglish (US)
Title of host publicationProceedings - 2014 IEEE 32nd VLSI Test Symposium, VTS 2014
PublisherIEEE Computer Society
ISBN (Print)9781479926114
StatePublished - 2014
Event2014 IEEE 32nd VLSI Test Symposium, VTS 2014 - Napa, CA, United States
Duration: Apr 13 2014Apr 17 2014

Publication series

NameProceedings of the IEEE VLSI Test Symposium


Other2014 IEEE 32nd VLSI Test Symposium, VTS 2014
Country/TerritoryUnited States
CityNapa, CA


  • Memory
  • Memristor
  • Sneak-paths
  • Testing

ASJC Scopus subject areas

  • Computer Science Applications
  • Electrical and Electronic Engineering


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