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International Conference on Business Process Management

BPM 2016: Business Process Management Workshops pp 36–48Cite as

Parallelization of Transition Counting for Process Mining on Multi-core CPUs and GPUs

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Part of the book series: Lecture Notes in Business Information Processing ((LNBIP,volume 281))

Abstract

Many process mining tools and techniques produce output models based on the counting of transitions between tasks or users in an event log. Although this counting can be performed in a forward pass through the event log, when analyzing large event logs according to different perspectives it may become impractical or time-consuming to perform multiple such passes. In this work, we show how transition counting can be parallelized by taking advantage of CPU multi-threading and GPU-accelerated computing. We describe the parallelization strategies, together with a set of experiments to illustrate the performance gains that can be expected with such parallelizations.

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Notes

  1. 1.

    http://www.win.tue.nl/bpi/doku.php?id=2016:challenge.

  2. 2.

    https://data.3tu.nl/repository/uuid:9b99a146-51b5-48df-aa70-288a76c82ec4.

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Author information

Authors and Affiliations

  1. Instituto Superior Técnico (IST), University of Lisbon, Lisbon, Portugal

    Diogo R. Ferreira & Rui M. Santos

Authors
  1. Diogo R. Ferreira
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  2. Rui M. Santos
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Corresponding author

Correspondence to Diogo R. Ferreira .

Editor information

Editors and Affiliations

  1. Institute of Computer Science, University of Tartu, Tartu, Estonia

    Marlon Dumas

  2. School of Arts, Sciences and Humanities, University of São Paulo, Sao Paulo, São Paulo, Brazil

    Marcelo Fantinato

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Ferreira, D.R., Santos, R.M. (2017). Parallelization of Transition Counting for Process Mining on Multi-core CPUs and GPUs. In: Dumas, M., Fantinato, M. (eds) Business Process Management Workshops. BPM 2016. Lecture Notes in Business Information Processing, vol 281. Springer, Cham. https://doi.org/10.1007/978-3-319-58457-7_3

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  • DOI: https://doi.org/10.1007/978-3-319-58457-7_3

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-58456-0

  • Online ISBN: 978-3-319-58457-7

  • eBook Packages: Computer ScienceComputer Science (R0)

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