Extreme Enumeration on GPU and in Clouds-Reference-Cited by-同舟云学术

Extreme Enumeration on GPU and in Clouds

Published:2011 Issue: Volume: Page:176-191
ISSN:0302-9743
Container-title:Cryptographic Hardware and Embedded Systems – CHES 2011
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Author:

Kuo Po-Chun,Schneider Michael,Dagdelen Özgür,Reichelt Jan,Buchmann Johannes,Cheng Chen-Mou,Yang Bo-Yin

Publisher

Springer Berlin Heidelberg

Link

http://link.springer.com/content/pdf/10.1007/978-3-642-23951-9_12.pdf

Reference22 articles.

1. Ajtai, M., Kumar, R., Sivakumar, D.: A sieve algorithm for the shortest lattice vector problem. In: STOC 2001, pp. 601–610. ACM, New York (2001)

2. Dean, J., Ghemawat, S.: MapReduce: Simplified data processing on large clusters. In: OSDI 2004: Sixth Symposium on Operating System Design and Implementation, San Francisco, CA, USA (December 2004)

3. Lecture Notes in Computer Science;J. Detrey,2010

4. Lecture Notes in Computer Science;Ö. Dagdelen,2010

5. Lecture Notes in Computer Science;U. Fincke,1983

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