Summary of the paper

Title Experiences with Parallelisation of an Existing NLP Pipeline: Tagging Hansard
Authors Stephen Wattam, Paul Rayson, Marc Alexander and Jean anderson
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.
Topics Corpus (Creation, Annotation, etc.), Tools, Systems, Applications
Full paper Experiences with Parallelisation of an Existing NLP Pipeline: Tagging Hansard
Bibtex @InProceedings{WATTAM14.687,
  author = {Stephen Wattam and Paul Rayson and Marc Alexander and Jean anderson},
  title = {Experiences with Parallelisation of an Existing NLP Pipeline: Tagging Hansard},
  booktitle = {Proceedings of the Ninth International Conference on Language Resources and Evaluation (LREC'14)},
  year = {2014},
  month = {may},
  date = {26-31},
  address = {Reykjavik, Iceland},
  editor = {Nicoletta Calzolari (Conference Chair) and Khalid Choukri and Thierry Declerck and Hrafn Loftsson and Bente Maegaard and Joseph Mariani and Asuncion Moreno and Jan Odijk and Stelios Piperidis},
  publisher = {European Language Resources Association (ELRA)},
  isbn = {978-2-9517408-8-4},
  language = {english}
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