Standard
Experiences with parallelisation of an existing NLP pipeline: tagging Hansard. /
Wattam, Stephen; Rayson, Paul; Alexander, Marc et al.
LREC 2014, Ninth International Conference on Language Resources and Evaluation. ed. / Nicoletta Calzolari; Khalid Choukri; Thierry Declerck; Hrafn Loftsson; Bente Maegaard; Joseph Mariani; Asuncion Moreno; Jan Odijk; Stelios Piperidis. Paris: EUROPEAN LANGUAGE RESOURCES ASSOC-ELRA, 2014. p. 4093-4096.
Research output: Contribution in Book/Report/Proceedings - With ISBN/ISSN › Conference contribution/Paper › peer-review
Harvard
Wattam, S, Rayson, P, Alexander, M & Anderson, J 2014,
Experiences with parallelisation of an existing NLP pipeline: tagging Hansard. in N Calzolari, K Choukri, T Declerck, H Loftsson, B Maegaard, J Mariani, A Moreno, J Odijk & S Piperidis (eds),
LREC 2014, Ninth International Conference on Language Resources and Evaluation. EUROPEAN LANGUAGE RESOURCES ASSOC-ELRA, Paris, pp. 4093-4096, 9th International Conference on Language Resources and Evaluation (LREC), Iceland,
26/05/14. <
http://www.lrec-conf.org/proceedings/lrec2014/pdf/687_Paper.pdf>
APA
Wattam, S., Rayson, P., Alexander, M., & Anderson, J. (2014).
Experiences with parallelisation of an existing NLP pipeline: tagging Hansard. In N. Calzolari, K. Choukri, T. Declerck, H. Loftsson, B. Maegaard, J. Mariani, A. Moreno, J. Odijk, & S. Piperidis (Eds.),
LREC 2014, Ninth International Conference on Language Resources and Evaluation (pp. 4093-4096). EUROPEAN LANGUAGE RESOURCES ASSOC-ELRA.
http://www.lrec-conf.org/proceedings/lrec2014/pdf/687_Paper.pdf
Vancouver
Wattam S, Rayson P, Alexander M, Anderson J.
Experiences with parallelisation of an existing NLP pipeline: tagging Hansard. In Calzolari N, Choukri K, Declerck T, Loftsson H, Maegaard B, Mariani J, Moreno A, Odijk J, Piperidis S, editors, LREC 2014, Ninth International Conference on Language Resources and Evaluation. Paris: EUROPEAN LANGUAGE RESOURCES ASSOC-ELRA. 2014. p. 4093-4096
Author
Bibtex
@inproceedings{fe434b57ae2e489e9361734971775ffb,
title = "Experiences with parallelisation of an existing NLP pipeline: tagging Hansard",
abstract = "This poster describes experiences processing the two-billion-word Hansard corpus using a fairly standard NLP pipeline on a high performance cluster. Herein we report how we were able to parallelise and apply a {"}traditional{"} single-threaded batch-oriented application to a platform that differs greatly from that for which it was originally designed. We start by discussing the tagging toolchain, its specific requirements and properties, and its performance characteristics. This is contrasted with a description of the cluster on which it was to run, and specific limitations are discussed such as the overhead of using SAN-based storage. We then go on to discuss the nature of the Hansard corpus, and describe which properties of this corpus in particular prove challenging for use on the system architecture used. The solution for tagging the corpus is then described, along with performance comparisons against a naive run on commodity hardware. We discuss the gains and benefits of using high-performance machinery rather than relatively cheap commodity hardware. Our poster provides a valuable scenario for large scale NLP pipelines and lessons learnt from the experience",
keywords = "High-performance Computing, Parallelisation, Tagging",
author = "Stephen Wattam and Paul Rayson and Marc Alexander and Jean Anderson",
year = "2014",
language = "English",
isbn = "9782951740884",
pages = "4093--4096",
editor = "Nicoletta Calzolari and Khalid Choukri and Thierry Declerck and Hrafn Loftsson and Bente Maegaard and Joseph Mariani and Asuncion Moreno and Jan Odijk and Stelios Piperidis",
booktitle = "LREC 2014, Ninth International Conference on Language Resources and Evaluation",
publisher = "EUROPEAN LANGUAGE RESOURCES ASSOC-ELRA",
note = "9th International Conference on Language Resources and Evaluation (LREC) ; Conference date: 26-05-2014 Through 31-05-2014",
}
RIS
TY - GEN
T1 - Experiences with parallelisation of an existing NLP pipeline
T2 - 9th International Conference on Language Resources and Evaluation (LREC)
AU - Wattam, Stephen
AU - Rayson, Paul
AU - Alexander, Marc
AU - Anderson, Jean
PY - 2014
Y1 - 2014
N2 - This poster describes experiences processing the two-billion-word Hansard corpus using a fairly standard NLP pipeline on a high performance cluster. Herein we report how we were able to parallelise and apply a "traditional" single-threaded batch-oriented application to a platform that differs greatly from that for which it was originally designed. We start by discussing the tagging toolchain, its specific requirements and properties, and its performance characteristics. This is contrasted with a description of the cluster on which it was to run, and specific limitations are discussed such as the overhead of using SAN-based storage. We then go on to discuss the nature of the Hansard corpus, and describe which properties of this corpus in particular prove challenging for use on the system architecture used. The solution for tagging the corpus is then described, along with performance comparisons against a naive run on commodity hardware. We discuss the gains and benefits of using high-performance machinery rather than relatively cheap commodity hardware. Our poster provides a valuable scenario for large scale NLP pipelines and lessons learnt from the experience
AB - This poster describes experiences processing the two-billion-word Hansard corpus using a fairly standard NLP pipeline on a high performance cluster. Herein we report how we were able to parallelise and apply a "traditional" single-threaded batch-oriented application to a platform that differs greatly from that for which it was originally designed. We start by discussing the tagging toolchain, its specific requirements and properties, and its performance characteristics. This is contrasted with a description of the cluster on which it was to run, and specific limitations are discussed such as the overhead of using SAN-based storage. We then go on to discuss the nature of the Hansard corpus, and describe which properties of this corpus in particular prove challenging for use on the system architecture used. The solution for tagging the corpus is then described, along with performance comparisons against a naive run on commodity hardware. We discuss the gains and benefits of using high-performance machinery rather than relatively cheap commodity hardware. Our poster provides a valuable scenario for large scale NLP pipelines and lessons learnt from the experience
KW - High-performance Computing
KW - Parallelisation
KW - Tagging
M3 - Conference contribution/Paper
SN - 9782951740884
SP - 4093
EP - 4096
BT - LREC 2014, Ninth International Conference on Language Resources and Evaluation
A2 - Calzolari, Nicoletta
A2 - Choukri, Khalid
A2 - Declerck, Thierry
A2 - Loftsson, Hrafn
A2 - Maegaard, Bente
A2 - Mariani, Joseph
A2 - Moreno, Asuncion
A2 - Odijk, Jan
A2 - Piperidis, Stelios
PB - EUROPEAN LANGUAGE RESOURCES ASSOC-ELRA
CY - Paris
Y2 - 26 May 2014 through 31 May 2014
ER -
