An Efficient BIRA Utilizing Characteristics of Spare Pivot Faults

Cho, Keewon; Lee, Young-Woo; Seo, Sungyoul; Kang, Sungho

doi:10.1109/tcad.2018.2818725

Cited by 6 publications

(1 citation statement)

References 30 publications

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“…Cho et al [26] presented a BIRA scheme that uses CAM. It categorizes a new fault as a pivot if it does not share a row and column with already identified faults.…”

Section: Cam Usage For Repair Analysismentioning

confidence: 99%

Memory built-in self-repair and correction for improving yield: a review

Sontakke,

Atchina

2024

IJECE

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Nanometer memories are highly prone to defects due to dense structure, necessitating memory built-in self-repair as a must-have feature to improve yield. Today’s system-on-chips contain memories occupying an area as high as 90% of the chip area. Shrinking technology uses stricter design rules for memories, making them more prone to manufacturing defects. Further, using 3D-stacked memories makes the system vulnerable to newer defects such as those coming from through-silicon-vias (TSV) and micro bumps. The increased memory size is also resulting in an increase in soft errors during system operation. Multiple memory repair techniques based on redundancy and correction codes have been presented to recover from such defects and prevent system failures. This paper reviews recently published memory repair methodologies, including various built-in self-repair (BISR) architectures, repair analysis algorithms, in-system repair, and soft repair handling using error correcting codes (ECC). It provides a classification of these techniques based on method and usage. Finally, it reviews evaluation methods used to determine the effectiveness of the repair algorithms. The paper aims to present a survey of these methodologies and prepare a platform for developing repair methods for upcoming-generation memories.

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“…Cho et al [26] presented a BIRA scheme that uses CAM. It categorizes a new fault as a pivot if it does not share a row and column with already identified faults.…”

Section: Cam Usage For Repair Analysismentioning

confidence: 99%