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On capture power-aware test data compression for scan-based testing
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International Conference on Computer Aided Design archive
Proceedings of the 2008 IEEE/ACM International Conference on Computer-Aided Design table of contents
San Jose, California
SESSION: Test power and temperature control table of contents
Pages 67-72  
Year of Publication: 2008
ISBN ~ ISSN:1092-3152 , 978-1-4244-2820-5
Authors
Jia Li  Key Laboratory of Computer System and Architecture, ICT, CAS, Beijing, China and Graduate University of Chinese Academy of Sciences, Beijing, China
Xiao Liu  The Chinese University of Hong Kong, Shatin, N.T., Hong Kong
Yubin Zhang  The Chinese University of Hong Kong, Shatin, N.T., Hong Kong
Yu Hu  Key Laboratory of Computer System and Architecture, ICT, CAS, Beijing, China
Xiaowei Li  Key Laboratory of Computer System and Architecture, ICT, CAS, Beijing, China
Qiang Xu  The Chinese University of Hong Kong, Shatin, N.T., Hong Kong
Sponsors
: IEEE CASS/CANDE
: IEEE Council on Electronic Design Automation (CEDA)
SIGDA: ACM Special Interest Group on Design Automation
Publisher
IEEE Press  Piscataway, NJ, USA
Bibliometrics
Downloads (6 Weeks): 8,   Downloads (12 Months): 33,   Citation Count: 0
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ABSTRACT

Large test data volume and high test power are two of the major concerns for the industry when testing large integrated circuits. With given test cubes in scan-based testing, the "don't-care" bits can be exploited for test data compression and/or test power reduction. Prior work either targets only one of these two issues or considers to reduce test data volume and scan shift power together. In this paper, we propose a novel capture power-aware test compression scheme that is able to keep scan capture power under a safe limit with little loss in test compression ratio. Experimental results on benchmark circuits demonstrate the efficacy of the proposed approach.


REFERENCES

Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.

 
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Collaborative Colleagues:
Jia Li: colleagues
Xiao Liu: colleagues
Yubin Zhang: colleagues
Yu Hu: colleagues
Xiaowei Li: colleagues
Qiang Xu: colleagues