Efficient TSV Fault Detection Scheme for High Bandwidth Memory Using Pattern Analysis

Kwanho Bae, Jongsun Park

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

1 Citation (Scopus)

Abstract

For an efficient data transmission between logic die and core die in HBM DRAM, Through-Silicon-Via (TSV) is an essential part that connects stacked memories. TSV is a vertical component which cannot be found in the conventional 2D memory. It plays an important role in improving integration in 3D memory structure. However, due to its temporal variation and technological weakness, error cases occur frequently in TSV. Following this, to increase the reliability of the memory operation, fault detection and correction method for TSV is a new challenge in 3D memory. For the efficient fault correction, fault detection method that classifies hard fault and soft error has been studied. In this paper, a new TSV fault detection method using error pattern analysis will be presented. As a result, the proposed scheme shows higher detection success rate with low area overhead, compared to the conventional scheme.

Original languageEnglish
Title of host publicationProceedings - International SoC Design Conference, ISOCC 2020
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages19-20
Number of pages2
ISBN (Electronic)9781728183312
DOIs
Publication statusPublished - 2020 Oct 21
Event17th International System-on-Chip Design Conference, ISOCC 2020 - Yeosu, Korea, Republic of
Duration: 2020 Oct 212020 Oct 24

Publication series

NameProceedings - International SoC Design Conference, ISOCC 2020

Conference

Conference17th International System-on-Chip Design Conference, ISOCC 2020
Country/TerritoryKorea, Republic of
CityYeosu
Period20/10/2120/10/24

Keywords

  • Error-Correction-Code(ECC)
  • High Bandwidth memory(HBM)
  • Through-Silicon-Via(TSV)

ASJC Scopus subject areas

  • Energy Engineering and Power Technology
  • Electrical and Electronic Engineering
  • Instrumentation
  • Artificial Intelligence
  • Hardware and Architecture

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