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Dealing with big data outside of the cloud: GPU accelerated sort

Research output: Contribution to conference - Without ISBN/ISSN › Conference paper › peer-review

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Dealing with big data outside of the cloud: GPU accelerated sort. / Vidler, John; Rayson, Paul; Anthony, Laurence et al.
2014. 21-24 Paper presented at LREC2014 Workshop on Challenges in the Management of Large Corpora (CMLC-2), Reykjavik, Iceland.

Research output: Contribution to conference - Without ISBN/ISSN › Conference paper › peer-review

Harvard

Vidler, J, Rayson, P, Anthony, L, Scott, A & Mariani, J 2014, 'Dealing with big data outside of the cloud: GPU accelerated sort', Paper presented at LREC2014 Workshop on Challenges in the Management of Large Corpora (CMLC-2), Reykjavik, Iceland, 31/05/14 pp. 21-24. <http://www.lrec-conf.org/proceedings/lrec2014/workshops/LREC2014Workshop-CMLC2%20Proceedings-rev2.pdf>

APA

Vidler, J., Rayson, P., Anthony, L., Scott, A., & Mariani, J. (2014). Dealing with big data outside of the cloud: GPU accelerated sort. 21-24. Paper presented at LREC2014 Workshop on Challenges in the Management of Large Corpora (CMLC-2), Reykjavik, Iceland. http://www.lrec-conf.org/proceedings/lrec2014/workshops/LREC2014Workshop-CMLC2%20Proceedings-rev2.pdf

Vancouver

Vidler J, Rayson P, Anthony L, Scott A, Mariani J. Dealing with big data outside of the cloud: GPU accelerated sort. 2014. Paper presented at LREC2014 Workshop on Challenges in the Management of Large Corpora (CMLC-2), Reykjavik, Iceland.

Author

Vidler, John ; Rayson, Paul ; Anthony, Laurence et al. / Dealing with big data outside of the cloud : GPU accelerated sort. Paper presented at LREC2014 Workshop on Challenges in the Management of Large Corpora (CMLC-2), Reykjavik, Iceland.4 p.

Bibtex

@conference{cfe9816bc6e94b498439aa60ba14f9c5,
title = "Dealing with big data outside of the cloud: GPU accelerated sort",
abstract = "The demands placed on systems to analyse corpus data increase with input size, and the traditional approaches to processing this data are increasingly having impractical run-times. We show that the use of desktop GPUs presents a significant opportunity to accelerate a number of stages in the normal corpus analysis pipeline. This paper contains our exploratory work and findings into applying high-performance computing technology and methods to the problem of sorting large numbers of concordance lines.",
keywords = "Very Large Corpora, CONCURRENCY, GPU Computing, High Performance Computing, Concordances, Sorting",
author = "John Vidler and Paul Rayson and Laurence Anthony and Andrew Scott and John Mariani",
year = "2014",
month = may,
day = "31",
language = "English",
pages = "21--24",
note = "LREC2014 Workshop on Challenges in the Management of Large Corpora (CMLC-2) ; Conference date: 31-05-2014",

}

RIS

TY - CONF

T1 - Dealing with big data outside of the cloud

T2 - LREC2014 Workshop on Challenges in the Management of Large Corpora (CMLC-2)

AU - Vidler, John

AU - Rayson, Paul

AU - Anthony, Laurence

AU - Scott, Andrew

AU - Mariani, John

PY - 2014/5/31

Y1 - 2014/5/31

N2 - The demands placed on systems to analyse corpus data increase with input size, and the traditional approaches to processing this data are increasingly having impractical run-times. We show that the use of desktop GPUs presents a significant opportunity to accelerate a number of stages in the normal corpus analysis pipeline. This paper contains our exploratory work and findings into applying high-performance computing technology and methods to the problem of sorting large numbers of concordance lines.

AB - The demands placed on systems to analyse corpus data increase with input size, and the traditional approaches to processing this data are increasingly having impractical run-times. We show that the use of desktop GPUs presents a significant opportunity to accelerate a number of stages in the normal corpus analysis pipeline. This paper contains our exploratory work and findings into applying high-performance computing technology and methods to the problem of sorting large numbers of concordance lines.

KW - Very Large Corpora

KW - CONCURRENCY

KW - GPU Computing

KW - High Performance Computing

KW - Concordances

KW - Sorting

M3 - Conference paper

SP - 21

EP - 24

Y2 - 31 May 2014

ER -