New approaches to the formulation of domain decomposition method and algorithm of the large-block parallelization for mathematical modeling problems
https://doi.org/10.23947/2587-8999-2017-2-141-147
Abstract
Domain decomposition method based on adjoint equation and inverse problem theory is discussed. The mathematical model of the Baltic Sea circulation, developed in INM RAS, is considered. The splitting method is used for time approximations. Domain decomposition method is studied to convection-diffusion problem. Also using domain decomposition method on multiprocessor computer system is possible to create algorithms for the parallel calculations.
Keywords
domain decomposition method,
inverse problems,
numerical methods,
adjoint equations,
parallel algorithms
Supporting agencies: The research is done with the financial support from the RSF (Grant 14-11-00609, within which the numerical experiments were carried out) and the RFBR (grant 16-01-00548, within which the research of the formulated tasks was carried out).
About the Authors
Valery Ivanovich Agoshkov
Institute of Numerical Mathematics Russian
Academy of Sciences
(8 Moscow, Gubkin St., Russian Federation),
Russian Federation
Russian Federation
Agoshkov Valery Ivanovich, Principal Researcher of the Institute of Numerical Mathematics Russian
Academy of Sciences (8 Moscow, Gubkin St., Russian Federation), Professor, Doctor of Science in
Physics and Maths, Honored Scientist of the Russian Federation
Romanovna Lezina Natalia
Institute of Numerical Mathematics Russian Academy of Sciences
(8 Moscow, Gubkin St., Russian Federation)
Russian Federation
Russian Federation
Natalia Romanovna Lezina, graduate school of the Institute of Numerical Mathematics Russian Academy of Sciences (8 Moscow, Gubkin St., Russian Federation)
References
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Review
For citations:
Agoshkov V.I., Natalia R.L. New approaches to the formulation of domain decomposition method and algorithm of the large-block parallelization for mathematical modeling problems. Computational Mathematics and Information Technologies. 2017;1(2). https://doi.org/10.23947/2587-8999-2017-2-141-147
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