Abstract
This paper describes the implementation of parallel computing to model seismic waves in heterogeneous media based on Laguerre transform with respect to time. The main advantages of the transform are a definite sign of the spatial part of the operator and its independence of the parameter of separation. This property allows one to efficiently organize parallel computations by means of decomposition of the computational domain with successive application of the additive Schwarz method. At each step of the Schwarz alternations, a system of linear algebraic equations in each subdomain is resolved independently of all the others. A proper choice of Domain Decomposition reduces the size of matrices and ensures the use of direct solvers, in particular, the ones based on LU decomposition. Thanks to the independence of the matrix of the parameter of Laguerre transform with respect to time, LU decomposition for each subdomain is done only once, saved in the memory and used afterwards for different right-hand sides.
A software is being developed for a cluster using hybrid OpenMP and MPI parallelization. At each cluster node, a system of linear algebraic equations with different right-hand sides is solved by the direct sparse solver PARDISO from Intel Math Kernel Library (Intel MKL). The solver is extensively parallelized and optimized for the high performance on many core systems with shared memory. A high performance parallel algorithm to solve the problem has been developed. The algorithm scalability and efficiency is investigated. For a two-dimensional heterogeneous medium, describing a realistic geological structure, which is typical of the North Sea, the results of numerical modeling are presented.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
Similar content being viewed by others
References
Plessix, R.E.: A Helmholtz iterative solver for 3D seismic-imaging problems. Geophysics 72(5), 185–194 (2007)
Mikhailenko, B.G., Mikhailov, A.A., Reshetova, G.V.: Numerical viscoelastic modeling by the spectral Laguerre method. Geophysical Prospecting 51, 37–48 (2003)
Chan, T., Mathew, T.P.: Domain decomposition. Acta Numerica 3, 61–143 (1994)
Gander, M., Halpern, L., Nataf, F.: Optimized Schwarz Methods. In: 12th International Conference on Domain Decomposition Methods, pp. 15–27 (2001)
Suetin, P.K.: Classical orthogonal polynomials. Nauka, M. 203–243 (1974)
Nepomnyashchikh, S.V.: Domain decomposition methods. Radon Series Comput. Appl. Math. 1, 81–159 (2007)
Collino, F., Tsogka, C.: Application of the PML absorbing layer model to the linear elastodynamic problem in anisotropic heterogeneous media. Geophysics 66(1), 294–307 (2001)
Reshetova, G.V., Tcheverda, V.A.: Implementation of Laguerre transform to construct perfectly matched layer without splitting. Mathematical Modelling 18(1), 91–101 (2006)
Virieux, J.: P-SV wave propagation in heterogeneous media: Velocity - stress finite-difference method. Geophysics 51(4), 889–901 (1986)
Zahradnik, J., Priolo, E.: Heterogeneous formulations of elastodynamic equations and finite-difference schemes. Geophysical Journal International 120(3), 663–676 (1995)
Karypis, G., Kumar, V.: A fast and High Quality Multilevel Scheme for Partitioning Irregular Graphs. SIAM Journal on Scientific Computing 20(1), 359–392 (1998)
Schenk, O., Gartner, K., Fichtner, W.: Efficient Sparce LU Factorization with Left-right Looking Strategy on Shared Memory Multiprocessors. BIT 240(1), 158–176 (2000)
Schenk, O., Gartner, K.: Two-level scheduling in PARDISO: Improved Scalability on Shared Memory Multiprocessing Systems. Parallel Computing 28, 187–197 (2002)
Colella, P., Bell, J., Keen, N., Ligocki, T., Lijewski, M., van Straalen, B.: Performance and scaling of locally-structured grid methods for partial differential equations. Journal of Physics: Conference Series 78, 012013 (2007)
Fossen, H., Hesthammer, J.: Structural geology of the Gullfaks Field, northern North Sea, vol. 127, pp. 231–261. Geological Society, London (1998) (Special Publications)
Zhang, Z., Zha, H., Simon, H.: Low-Rank Approximation with Sparce Factors: Basic Algorithms and Error Analysis. SIAM J. of Matrix Analysis and Applications (3), 706–727 (1999)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2013 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Belonosov, M.A., Kostov, C., Reshetova, G.V., Soloviev, S.A., Tcheverda, V.A. (2013). Parallel Numerical Simulation of Seismic Waves Propagation with Intel Math Kernel Library. In: Manninen, P., Öster, P. (eds) Applied Parallel and Scientific Computing. PARA 2012. Lecture Notes in Computer Science, vol 7782. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-36803-5_11
Download citation
DOI: https://doi.org/10.1007/978-3-642-36803-5_11
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-36802-8
Online ISBN: 978-3-642-36803-5
eBook Packages: Computer ScienceComputer Science (R0)