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Parallelization of Linear Algebra Algorithms Using ParSol Library of Mathematical Objects

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Part of the book series: Springer Optimization and Its Applications ((SOIA,volume 27))

Abstract

The linear algebra problems are an important part of many algorithms, such as numerical solution of PDE systems. In fact, up to 80% or even more of computing time in this kind of algorithms is spent for linear algebra tasks. The parallelization of such solvers is the key for parallelization of many advanced algorithms. The mathematical objects library ParSol not only implements some important linear algebra objects in C++, but also allows for semiautomatic parallelization of data parallel and linear algebra algorithms, similar to High Performance Fortran (HPF). ParSol library is applied to implement the finite difference scheme used to solve numerically a system of PDEs describing a nonlinear interaction of two counterpropagating laser waves. Results of computational experiments are presented.

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References

  1. Akcelik, V., Biros, G., Ghattas, O., Hill, J. et al.: Frontiers of parallel computing. In: M. Heroux, P. Raghaven, H. Simon (eds.) Parallel Algorithms for PDE-Constrained Optimization. SIAM, Philadelphia (2006)

    Google Scholar 

  2. Balay, S., Buschelman, K., Eijkhout, V., Gropp, W.D., Kaushik, D., Knepley, M.G., Curfman McInnes, L., Smith, B.F., Zhang, H.: PETSc user manual. ANL-95/11 - Revision 2.1.5. Argonne National Laboratory (2004)

    Google Scholar 

  3. Bastian, P., Birken, K., Johannsen, K., Lang, S. et al.: A parallel software-platform for solving problems of partial differential equations using unstructured grids and adaptive multigrid methods. In: W. Jage, E. Krause (eds.) High Performance Computing in Science and Engineering, pp. 326–339. Springer, New York (1999)

    Google Scholar 

  4. Blatt, M., Bastian, P.: The iterative solver template library. In: B. Kågström, E. Elmroth, J. Dongarra, J. Wasniewski (eds.) Applied Parallel Computing: State of the Art in Scientific Computing, Lecture Notes in Scientific Computing, vol. 4699, pp. 666–675. Springer, Berlin Heidelberg New York (2007)

    Chapter  Google Scholar 

  5. Čiegis, Raim, Čiegis, Rem., Jakušev, A., Šaltenienė, G.: Parallel variational iterative algorithms for solution of linear systems. Mathematical Modelling and Analysis 12(1), 1– 16 (2007)

    Article  MATH  MathSciNet  Google Scholar 

  6. Čiegis, R., Jakušev, A., Krylovas, A., Suboč, O.: Parallel algorithms for solution of nonlinear diffusion problems in image smoothing. Mathematical Modelling and Analysis 10(2), 155– 172 (2005)

    MATH  MathSciNet  Google Scholar 

  7. Čiegis, R., Jakušev, A., Starikovičius, V.: Parallel tool for solution of multiphase flow problems. In: R. Wyrzykowski, J. Dongarra, N. Meyer, J. Wasniewski (eds.) Sixth International conference on Parallel Processing and Applied Mathematics. Poznan, Poland, September 10- 14, 2005, Lecture Notes in Computer Science, vol. 3911, pp. 312–319. Springer, Berlin Heidelberg New York (2006)

    Google Scholar 

  8. Geist, A., Beguelin, A., Dongarra, J. et al.: PVM: Parallel Virtual Machine. A User’s Guide and Tutorial for Networked Parallel Computing. MIT Press, Cambridge, MA (1994)

    Google Scholar 

  9. Jakušev, A.: Application of template metaprogramming technologies to improve the efficiency of parallel arrays. Mathematical Modelling and Analysis 12(1), 71–79 (2007)

    MATH  Google Scholar 

  10. Koelbel, C.H., Loveman, D.B., Schreiber, R.S., Steele, G.L., Zosel, M.E.: The High Performance Fortran Handbook. The MIT Press, Cambridge, MA (1994)

    Google Scholar 

  11. Kumar, V., Grama, A., Gupta, A., Karypis, G.: Introduction to Parallel Computing: Design and Analysis of Algorithms. Benjamin/Cummings, Redwood City (1994)

    Google Scholar 

  12. Langtangen, H.P.: Computational Partial Differential Equations – Numerical Methods and Diffpack Programming, Lecture Notes in Computational Science and Engineering. Springer- Verlag, New York (1999)

    Google Scholar 

  13. Le Veque, R.: Finite Volume Methods for Hyperbolic Problems. Cambridge University Press, Cambridge, UK (2002)

    Google Scholar 

  14. Nieplocha, J., Palmer, B., Tipparaju, V., Krishnan, M., Trease, H., Apra, E.: Advances, applications and performance of the Global Arrays shared memory programming toolkit. International Journal of High Performance Computing Applications 20(2), 203-231 (2006)

    Article  Google Scholar 

  15. Nikitenko, K.Y., Trofimov, V.A.: Optical bistability based on nonlinear oblique reflection of light beams from a screen with an aperture on its axis. Quantum Electronics 29(2), 147– 150 (1999)

    Article  Google Scholar 

  16. OpenFOAM: The Open Source CFD Toolbox. URL http://www.opencfd.co.uk/openfoam/

  17. Snir, M., Oto, S., Hus-Lederman, S., Walker, D., Dongarra, J.: MPI. The Complete Reference. The MIT Press, Cambridge, Reading, MA (1995)

    Google Scholar 

  18. Stroustrup, B.: The C++ Programming Language. Addison-Wesley, MA (1997)

    Google Scholar 

  19. Tereshin, E.B., Trofimov, V.A.: Conservative finite difference scheme for the problem of propagation of a femtosecond pulse in a photonic crystal with combined nonlinearity. Comput. Math. and Mathematical Physics 46(12), 2154–2165 (2006)

    Article  MathSciNet  Google Scholar 

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Jakusšev, A., Čiegis, R., Laukaitytė, I., Trofimov, V. (2009). Parallelization of Linear Algebra Algorithms Using ParSol Library of Mathematical Objects. In: Parallel Scientific Computing and Optimization. Springer Optimization and Its Applications, vol 27. Springer, New York, NY. https://doi.org/10.1007/978-0-387-09707-7_2

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