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Exploiting idle CPU cores to improve file access performance
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Source Conference On Ubiquitous Information Management And Communication archive
Proceedings of the 3rd International Conference on Ubiquitous Information Management and Communication table of contents
Suwon, Korea
SESSION: Systems and applications IV table of contents
Pages 529-535  
Year of Publication: 2009
ISBN:978-1-60558-405-8
Authors
Takanori Ueda  Waseda University, Okubo, Shinjuku-ku, Tokyo, Japan
Yu Hirate  Waseda University, Okubo, Shinjuku-ku, Tokyo, Japan
Hayato Yamana  Waseda University, Okubo, Shinjuku-ku, Tokyo, Japan
Sponsor
SIGKDD: ACM Special Interest Group on Knowledge Discovery in Data
Publisher
ACM  New York, NY, USA
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ABSTRACT

Many-core CPUs require many parallel computation tasks to reach their full potential because CPU cores become idle if they do not have enough computation tasks. How best to utilize a number of cores in many-core CPUs should be examined. In this paper, we propose exploitation of idle cores for improving file access performance. Idle cores are used to extract file access patterns from access logs and the extracted patterns are used to improve file cache efficiency by reordering the LRU (Least Recently Used) list based on the extracted patterns. Data mining techniques are used to extract access patterns to reduce computation overhead. Our method was evaluated by simulation and also implemented on Linux kernel 2.6.26 as a prototype system. In the simulation experiment, our method improved the cache-hit ratio up to 1.09% on DBT-2 (TPC-C) trace logs. Our prototype implementation on Linux improves DBT-2 performance up to 5.24% on a real machine.


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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L. Yu, G. Chen and J. Dong, "Mining Infrequently-Accessed File Correlations in Distributed File System," In Proc. of the Joint Conf. of the 9th Asia-Pacific Web Conf. and the 8th Int'l Conf. on Web-Age Information Management (APWeb/WAIM), pp.630--641, Huang Shan, China, Jun. 2007.
 
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X. Yan, J. Han and R. Afshar, "CloSpan: Mining closed sequential patterns in large datasets," In Proc. of the 2003 SIAM Int'l Conf. Data Mining (SDM'03), San Francisco, US-CA, May 2003.
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Database Test Suite, http://osdldbt.sourceforge.net/.
 
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Transaction Processing Performance Council, http://www.tpc.org/.

Collaborative Colleagues:
Takanori Ueda: colleagues
Yu Hirate: colleagues
Hayato Yamana: colleagues