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  5. Diverse Double Modular Redundancy: A New Direction for Soft Error Detection and Correction
 
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Diverse Double Modular Redundancy: A New Direction for Soft Error Detection and Correction

Author(s)
Reviriego, P.  
Bleakley, Chris J.  
Maestro, J.A.  
Uri
http://hdl.handle.net/10197/7091
Date Issued
2013-04
Date Available
2015-09-23T15:45:08Z
Abstract
Soft errors are becoming an important issue for deep submicron technologies. To protect circuits against soft errors, designers routinely introduce modular redundancy to detect and correct these errors. A commonly used technique, Double Modular Redundancy (DMR) involves duplication of the basic module. Conventionally, DMR only allows error detection since voting cannot be used to determine the module in error. Recently, however, it has been found that DMR can, for some circuits, be enhanced to provide soft error correction as well as detection. The general approach, DDMR (Diverse DMR), relies on introducing design diversity between the original and redundant modules so that they produce different error patterns when a soft error occurs. The module in error can be found by examining these patterns. Herein, the generalized approach is described. A number of techniques for producing diverse designs with distinct error patterns are identified and illustrated with examples. New DDMR solutions are presented and finally, the future direction of DDMR research is discussed.
Type of Material
Journal Article
Publisher
IEEE
Journal
IEEE Design and Test of Computers
Volume
30
Issue
2
Start Page
87
End Page
95
Copyright (Published Version)
2012 IEEE
Subjects

Integrated circuit de...

Radiation hardening (...

DOI
10.1109/MDT.2012.2232964
Language
English
Status of Item
Peer reviewed
This item is made available under a Creative Commons License
https://creativecommons.org/licenses/by-nc-nd/3.0/ie/
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Diverse_Double_Modular_Redundancy_A_New_Direction_for_Soft_Error_Detection_and_Correction.pdf

Size

457 KB

Format

Adobe PDF

Checksum (MD5)

0516b4d0a7eb88b28afb3b630c8f1463

Owning collection
Computer Science Research Collection

Item descriptive metadata is released under a CC-0 (public domain) license: https://creativecommons.org/public-domain/cc0/.
All other content is subject to copyright.

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