Ajou University repository

A Built-In Self-Repair With Maximum Fault Collection and Fast Analysis Method for HBM
  • Yoon, Joonsik ;
  • Lee, Hayoung ;
  • Moon, Youngki ;
  • Shin, Seung Ho ;
  • Kang, Sungho
Citations

SCOPUS

0

Citation Export

Publication Year
2024-01-01
Publisher
Institute of Electrical and Electronics Engineers Inc.
Citation
IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems
Keyword
Analysis timebuilt-in redundancy analysis (BIRA)built-in self-repair (BISR)content-addressable memory (CAM)repair rate
Mesh Keyword
Analysis timeBandwidth memoryBuild-in redundancy analyzeBuild-in self-repairBuilt-in redundancy analysisBuiltin self repairsContent-addressable memoryHigh bandwidthRepair rate
All Science Classification Codes (ASJC)
SoftwareComputer Graphics and Computer-Aided DesignElectrical and Electronic Engineering
Abstract
High Bandwidth Memory (HBM) represents a significant advancement in memory technology, requiring quick and accurate data processing. Built-in self-repair (BISR) is crucial for ensuring high-capacity and reliable memories, as it automatically detects and repairs faults within memory systems, preventing data loss and enhancing overall memory reliability. The proposed BISR aims to enhance the repair rate and reliability by using a content-addressable memory structure that operates effectively in both offline and online modes. Furthermore, a new redundancy analysis algorithm reduces both analysis time and area overhead by converting fault information into a matrix format and focusing on fault-free areas for each repair solution. Experimental results demonstrate that the proposed BISR improves repair rates and derives a final repair solution immediately after the test sequences are completed. Moreover, hardware comparisons have shown that the proposed approach reduces the area overhead as memory size increases. Consequently, the proposed BISR enhances the overall performance of BISR and the reliability of HBM.
Language
eng
URI
https://dspace.ajou.ac.kr/dev/handle/2018.oak/34605
DOI
https://doi.org/10.1109/tcad.2024.3499903
Fulltext

Type
Article
Funding
This work was supported by the National Research Foundation of Korea (NRF) grant funded by the Korea government (MSIT) (No. 2022R1A2B5B03002504).
Show full item record

Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.

Related Researcher

 Lee, Hayoung Image
Lee, Hayoung이하영
Department of Intelligence Semiconductor Engineering
Read More

Total Views & Downloads

File Download

  • There are no files associated with this item.