Fame: A Fault-Pattern Based Memory Failure Analysis Framework

Kuo Liang Cheng, Chih Wea Wang, Jih Nung Lee, Yung Fa Chou, Chih Tsun Huang, Cheng Wen Wu

Research output: Contribution to journalConference articlepeer-review

11 Citations (Scopus)

Abstract

A memory failure analysis framework is developed - the Failure Analyzer for MEmories (FAME). The FAME integrates the Memory Error Catch and Analysis (MECA) system and the Memory Defect Diagnostics (MDD) system. The fault-type based diagnostics approach used by MECA can improve the efficiency of the test and diagnostic algorithms. The fault-pattern based diagnostics approach used by MDD further improves the defect identification capability. The FAME also comes with a powerful viewer for inspecting the failure patterns and fault patterns. It provides an easy way to narrow down the potential cause of failures and identify possible defects more accurately during the memory product development and yield ramp-up stage. An experiment has been done on an industrial case, demonstrating very accurate results in a much shorter time as compared with the conventional way.

Original languageEnglish
Pages (from-to)595-598
Number of pages4
JournalIEEE/ACM International Conference on Computer-Aided Design, Digest of Technical Papers
Publication statusPublished - 2003 Dec 26
EventIEEE/ACM International Conference on Computer Aided Design ICCAD 2003: IEEE/ACM Digest of Technical Papers - San Jose, CA, United States
Duration: 2003 Nov 92003 Nov 13

All Science Journal Classification (ASJC) codes

  • Software
  • Computer Science Applications
  • Computer Graphics and Computer-Aided Design

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