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IMPROVED REPRESENTATIVES FOR JUDGING UNREPAIRABILITY AND DECIDING ECONOMIC REPAIR SOLUTIONS OF MEMORIES.

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Title: IMPROVED REPRESENTATIVES FOR JUDGING UNREPAIRABILITY AND DECIDING ECONOMIC REPAIR SOLUTIONS OF MEMORIES.
Authors: LIANG, HSING-CHUNG1 hcliang@cycu.edu.tw
Source: Journal of Circuits, Systems & Computers. Feb2009, Vol. 18 Issue 1, p81-95. 15p. 8 Diagrams, 2 Charts, 4 Graphs.
Subjects: Memory maps (Computer science), Computer science, Repairing, Technology, Dynamic storage allocation (Computer science)
Abstract: This paper introduces a novel method of identifying better representatives of faulty cells in a memory map to help judge unrepairability and provide economical repair solutions. These representatives, called leading elements (LE), are classified into four primary types based on their characteristics. The proposed method primarily assigns the faulty cells without row or column complements as LE, making them more useful in judging unrepairability and providing economical repair solutions. Some initially identified LE are further replaced with suitable faulty cells for being LE. Experiments on many example maps show the distribution of LE in various sizes of memories with distinct numbers of faulty cells. Compared to the previous work, the improved procedure can identify 7.3% more LE, with only 1.5% additional run time. [ABSTRACT FROM AUTHOR]
Copyright of Journal of Circuits, Systems & Computers is the property of World Scientific Publishing Company and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Database: Engineering Source
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DbLabel: Engineering Source
An: 37045998
AccessLevel: 6
PubType: Academic Journal
PubTypeId: academicJournal
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  Data: IMPROVED REPRESENTATIVES FOR JUDGING UNREPAIRABILITY AND DECIDING ECONOMIC REPAIR SOLUTIONS OF MEMORIES.
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  Data: <searchLink fieldCode="AR" term="%22LIANG%2C+HSING-CHUNG%22">LIANG, HSING-CHUNG</searchLink><relatesTo>1</relatesTo><i> hcliang@cycu.edu.tw</i>
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  Data: <searchLink fieldCode="DE" term="%22Memory+maps+%28Computer+science%29%22">Memory maps (Computer science)</searchLink><br /><searchLink fieldCode="DE" term="%22Computer+science%22">Computer science</searchLink><br /><searchLink fieldCode="DE" term="%22Repairing%22">Repairing</searchLink><br /><searchLink fieldCode="DE" term="%22Technology%22">Technology</searchLink><br /><searchLink fieldCode="DE" term="%22Dynamic+storage+allocation+%28Computer+science%29%22">Dynamic storage allocation (Computer science)</searchLink>
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  Data: This paper introduces a novel method of identifying better representatives of faulty cells in a memory map to help judge unrepairability and provide economical repair solutions. These representatives, called leading elements (LE), are classified into four primary types based on their characteristics. The proposed method primarily assigns the faulty cells without row or column complements as LE, making them more useful in judging unrepairability and providing economical repair solutions. Some initially identified LE are further replaced with suitable faulty cells for being LE. Experiments on many example maps show the distribution of LE in various sizes of memories with distinct numbers of faulty cells. Compared to the previous work, the improved procedure can identify 7.3% more LE, with only 1.5% additional run time. [ABSTRACT FROM AUTHOR]
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  Data: <i>Copyright of Journal of Circuits, Systems & Computers is the property of World Scientific Publishing Company and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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      – Type: doi
        Value: 10.1142/S0218126609004946
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      – Code: eng
        Text: English
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        PageCount: 15
        StartPage: 81
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      – SubjectFull: Memory maps (Computer science)
        Type: general
      – SubjectFull: Computer science
        Type: general
      – SubjectFull: Repairing
        Type: general
      – SubjectFull: Technology
        Type: general
      – SubjectFull: Dynamic storage allocation (Computer science)
        Type: general
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      – TitleFull: IMPROVED REPRESENTATIVES FOR JUDGING UNREPAIRABILITY AND DECIDING ECONOMIC REPAIR SOLUTIONS OF MEMORIES.
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              Text: Feb2009
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              Y: 2009
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