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Fast and Efficient Parallel Computations Using a Cluster of Workstations to Simulate Flood Flows

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Intelligence in the Era of Big Data (ICSIIT 2015)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 516))

Abstract

A strategy is proposed for fast and efficient parallel computations using a cluster of workstations to simulate flood flows. We implement ANUGA software to conduct flood simulations. ANUGA solves the two-dimensional shallow water equations using a finite volume method. ANUGA can be run in either sequential or parallel. We focus our work on parallel computations. Our computation scenarios are implemented on a cluster of workstations. Parallel computation results are assessed based on execution time and efficiency. The strategy that we propose gives a significant advantage when we want to get fast and efficient computations using a cluster of workstations.

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References

  1. Baldock, T.E., Barnes, M.P., Guard, P.A., Hie, T., Hanslow, D., Ranasinghe, R., Gray, D., Nielsen, O.: Modelling Tsunami Inundation on Coastlines with Characteristic Form. In: 16th Australasian Fluid Mechanics Conference, pp. 939–942. AFMS (2007)

    Google Scholar 

  2. Cousins, W.J., Power, W.L., Destegul, U.Z., King, A.B., Trevethick, R., Blong, R., Weir, B., Miliauskas, B.: Earthquake and Tsunami Losses from Major Earthquakes Affecting the Wellington Region. In: 2009 New Zealand Society for Earthquake Engineering Conference, Paper Number 24, NZSEE (2009)

    Google Scholar 

  3. Davies, G.: A Well-Balanced Discretization for a Shallow Water Inundation Model. In: 2011 International Congress on Modelling and Simulation (MODSIM), pp. 2824–2830. MSSANZ (2011)

    Google Scholar 

  4. Foster, I.: Designing and Building Parallel Programs: Concepts and Tools for Parallel Software Engineering. Addison-Wesley, Boston (1995)

    MATH  Google Scholar 

  5. Guinot, V.: Wave Propagation in Fluids: Models and Numerical Techniques. ISTE, Wiley, London, Hoboken (2008)

    Google Scholar 

  6. Jakeman, J.D., Bartzis, N., Nielsen, O., Roberts, S.: Inundation Modelling of the Indian Ocean Tsunami. In: 2007 International Congress on Modelling and Simulation (MODSIM), pp. 1667–1673. MSSANZ (2007)s

    Google Scholar 

  7. Jakeman, J.D., Nielsen, O.M., Putten, K.V., Mleczko, R., Burbidge, D., Horspool, N.: Towards Spatially Distributed Quantitative Assessment of Tsunami Inundation Models. Ocean Dynamics 60, 1115–1138 (2010)

    Article  Google Scholar 

  8. LeVeque, R.J.: Finite Volume Methods for Hyperbolic Problems. Cambridge University Press, Cambridge (2002)

    Book  MATH  Google Scholar 

  9. Mache, J.: An Assessment of Gigabit Ethernet as Cluster Interconnect. In: 1st IEEE Computer Society International Workshop on Cluster Computing. IEEE (1999)

    Google Scholar 

  10. Mungkasi, S., Roberts, S.G.: A Finite Volume Method for Shallow Water Flows on Triangular Computational Grids. In: 2011 International Conference on Advanced Computer Science and Information System (ICACSIS), pp. 79–84. IEEE (2011)

    Google Scholar 

  11. Mungkasi, S.: A Study of Well-Balanced Finite Volume Methods and Refinement Indicators for the Shallow Water Equations. PhD Thesis, Australian National University, Canberra, Australia (2012)

    Google Scholar 

  12. Mungkasi, S., Roberts, S.G.: Predictions on Arrival Times of Water of the St. Francis Dam Break Flood Using ANUGA. In: 2013 International Congress on Modelling and Simulation (MODSIM), pp. 304–309. MSSANZ (2013)

    Google Scholar 

  13. Nielsen, O., Sexton, J., Gray, D., Bartzis, N.: Modelling Answers Tsunami Questions. AusGeo News 83, 1–5 (2006)

    Google Scholar 

  14. Roberts, S.G., Nielsen, O.M., Jakeman, J.: Simulation of Tsunami and Flash Floods. In: Modeling, Simulation and Optimization of Complex Processes, pp. 489–498. Springer, Berlin (2008)

    Google Scholar 

  15. Roberts, S., Nielsen, O., Gray, D., Sexton, J.: ANUGA User Manual. Geoscience Australia and Australian National University, Canberra (2010)

    Google Scholar 

  16. Sterling, T.: Beowulf Cluster Computing with Linux. MIT Press, Cambridge (2001)

    Google Scholar 

  17. Tan, W.Y.: Shallow Water Hydrodynamics. Elsevier, Amsterdam (1992)

    Google Scholar 

  18. Yang, J., Shen, W., Yan, G.: Construct COW Based on MPICH in Linux Environment. In: 1st International Workshop on Education Technology and Computer Science. IEEE (2009)

    Google Scholar 

  19. AnugaParallel, https://anuga.anu.edu.au/wiki/AnugaParallel

  20. Message Passing Interface (MPI) Standard, http://www.mcs.anl.gov/research/projects/mpi

  21. MPICH High-Performance Portable MPI, http://www.mpich.org

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Author information

Authors and Affiliations

  1. Department of Mathematics, Faculty of Science and Technology, Sanata Dharma University, Mrican, Tromol Pos 29, Yogyakarta, 55002, Indonesia

    Sudi Mungkasi

  2. Department of Informatics, Faculty of Science and Technology, Sanata Dharma University, Mrican, Tromol Pos 29, Yogyakarta, 55002, Indonesia

    J. B. Budi Darmawan

Authors
  1. Sudi Mungkasi
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  2. J. B. Budi Darmawan
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Corresponding author

Correspondence to Sudi Mungkasi .

Editor information

Editors and Affiliations

  1. Informatics, Petra Christian University, Surabaya, Indonesia

    Rolly Intan

  2. CSIRO, Hobart, Tasmania, Australia

    Chi-Hung Chi

  3. Informatics, Petra Christian University, Surabaya, Indonesia

    Henry N. Palit

  4. Informatics, Petra Christian University, Surabaya, Indonesia

    Leo W. Santoso

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© 2015 Springer-Verlag Berlin Heidelberg

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Mungkasi, S., Darmawan, J.B.B. (2015). Fast and Efficient Parallel Computations Using a Cluster of Workstations to Simulate Flood Flows. In: Intan, R., Chi, CH., Palit, H., Santoso, L. (eds) Intelligence in the Era of Big Data. ICSIIT 2015. Communications in Computer and Information Science, vol 516. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-46742-8_43

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  • DOI: https://doi.org/10.1007/978-3-662-46742-8_43

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-662-46741-1

  • Online ISBN: 978-3-662-46742-8

  • eBook Packages: Computer ScienceComputer Science (R0)

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