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The Use of GPGPU in Continuous and Discrete Models of Crowd Dynamics

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Parallel Processing and Applied Mathematics (PPAM 2013)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 8385))

Abstract

The aim of the study is twofold: firstly to compare the possibilities of using GPGPU (General-Purpose Computing on Graphics Processing Units) in continuous and discrete crowd dynamics simulation, secondly to draw conclusions on the applicability of GPUs in engines of professional crowd simulations. For this purpose the authors have implemented two models of pedestrian dynamics: continuous - Social Forces model and discrete, Cellular Automata based - Social Distances model. The presented simulations refer to outdoor, large area pedestrian movement.

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Notes

  1. 1.

    This model was originally designed as a hybrid: cellular automaton with a component of force, however in the study it is implemented exclusively as floor field, cellular automaton based model [23]

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Acknowledgment

This research is partially supported by FP7 project SOCIONICAL, No 231288.

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Authors and Affiliations

  1. AGH University of Science and Technology, al. Mickiewicza 30, 30-059, Kraków, Poland

    Hubert Mróz, Jarosław Wąs & Paweł Topa

Authors
  1. Hubert Mróz
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  2. Jarosław Wąs
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  3. Paweł Topa
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Corresponding author

Correspondence to Jarosław Wąs .

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Editors and Affiliations

  1. Institute of Computer and Information Science, Czestochowa University of Technology, Czestochowa, Poland

    Roman Wyrzykowski

  2. University of Tennessee, Department of Computer Science, Knoxville, Tennessee, USA

    Jack Dongarra

  3. Institute of Computer and Information Science, Czestochowa University of Technology, Czestochowa, Poland

    Konrad Karczewski

  4. Technical University of Denmark Informatics and Mathematical Modelling, Kongens Lyngby, Denmark

    Jerzy Waśniewski

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Mróz, H., Wąs, J., Topa, P. (2014). The Use of GPGPU in Continuous and Discrete Models of Crowd Dynamics. In: Wyrzykowski, R., Dongarra, J., Karczewski, K., Waśniewski, J. (eds) Parallel Processing and Applied Mathematics. PPAM 2013. Lecture Notes in Computer Science(), vol 8385. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-55195-6_64

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  • DOI: https://doi.org/10.1007/978-3-642-55195-6_64

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