COMPARING PARALLEL PROGRAMMING ENVIRONMENTS FOR THE JOINT INVERSION OF GEOELECTRICAL DATA
DOI:
https://doi.org/10.7494/csci.2009.10.3.85Keywords:
parallel computing, inverse problem, geoelectrical methodsAbstract
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.Downloads
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