COMPARING PARALLEL PROGRAMMING ENVIRONMENTS FOR THE JOINT INVERSION OF GEOELECTRICAL DATA

Anna Pięta, Justyna Bała

Abstract


The article presents the comparison of the implementation of the inverse problem in geoelectricalmethods in two different parallel computational environments. Combination of MonteCarlo method and Multistart algorithm was applied in the inversion process. Parallelizationwas done by fine grain decomposition. Execution time, speed-up and efficiency received forparallel algorithms in both computational environments were presented and analyzed.

Keywords


parallel computing; inverse problem; geoelectrical methods

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References


Danek T., Franczyk A.: Parallel and distributed seismic wave-field modeling. TASK Quarterly: scientific bulletin of Academic Computer Centre in Gdansk, vol. 8, 2004, 573–582

Snieder R., Trampert J.: Inverse Problems in Geophysics. New York, Springer 1999

McNeill J. D.: Use of Electromagnetic Methods for Groundwater Studies. Geotechnical and Environmental Geophysicsv. vol. 1, 1990, Society of Exploration Geophysicists, Tulsa, OK, 191–218

Moscicki W., Antoniuk J.: Application of geoelectric methods into studying of geological environment influenced by human activity. Publications of the Institute of Geophysics Polish Academy of Sciences, 2002, 179–193

Zhdanov M. S., Keller G. V.: The geoelectrical methods in geophysical exploration. Amsterdam, Elsevier 1994

Sharma S.P., Kaikkonen P.: Appraisal of equivalence and suppression problems in 1D EM and DC measurements using global optimization and joint inversion. Geophysical Prospecting, vol. 47, 1999, 219–249

Pszczoła G., Lesniak A.: Non-linear optimization methods for small earthquake locations. TASK Quarterly: scientific bulletin of Academic Computer Centre in Gdansk, vol. 8, 2004, 583–590

Press W. H., Teukolsky S. A., Vetterling W. T., Flannery B.P.: Numerical Recipes in C: the art of scientific computing. Second Edition, New York, Cambridge University Press 1992

Schnabel R. B.: A Wiew of the Limitations, Opportunities and Challenges in Parallel Nonlinear Optimization. Parallel Computing, vol. 21, 1995, 875–905




DOI: https://doi.org/10.7494/csci.2009.10.3.85

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