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A Graphics Processing Unit Implementation of the Particle Filter
Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.ORCID iD: 0000-0002-1971-4295
Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
2007 (English)In: Proceedings of the 15th European Statistical Signal Processing Conference, European Association for Signal, Speech, and Image Processing , 2007, 1639-1643 p.Conference paper, Published paper (Refereed)
Abstract [en]

Modern graphics cards for computers, and especially their graphics processing units (GPUs), are designed for fast rendering of graphics. In order to achieve this GPUs are equipped with a parallel architecture which can be exploited for general-purpose computing on GPU (GPGPU) as a complement to the central processing unit (CPU). In this paper GPGPU techniques are used to make a parallel GPU implementation of state-of-the-art recursive Bayesian estimation using particle filters (PF). The modifications made to obtain a parallel particle filter, especially for the resampling step, are discussed and the performance of the resulting GPU implementation is compared to one achieved with a traditional CPU implementation. The resulting GPU filter is faster with the same accuracy as the CPU filter for many particles, and it shows how the particle filter can be parallelized.

Place, publisher, year, edition, pages
European Association for Signal, Speech, and Image Processing , 2007. 1639-1643 p.
Series
European Signal Processing Conference, ISSN 2219-5491
Keyword [en]
Parallel programming, Monte Carlo methods, Estimation, Particle filtering, Graphics processing unit
National Category
Control Engineering
Identifiers
URN: urn:nbn:se:liu:diva-38777Local ID: 45625ISBN: 978-839213402-2 (print)OAI: oai:DiVA.org:liu-38777DiVA: diva2:259626
Conference
15th European Statistical Signal Processing Conference, Poznan, Poland, September, 2007
Available from: 2009-10-10 Created: 2009-10-10 Last updated: 2016-06-10

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Hendeby, GustafHol, JeroenKarlsson, RickardGustafsson, Fredrik

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CiteExportLink to record
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Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • oxford
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf