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A Static Parallel Multifrontal Solver for Finite Element Meshes

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Parallel and Distributed Processing and Applications (ISPA 2006)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 4330))

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Abstract

We present a static parallel implementation of the multifrontal method to solve unsymmetric sparse linear systems on distributed-memory architectures. We target Finite Element (FE) applications where numerical pivoting can be avoided, since an implicit minimum-degree ordering based on the FE mesh topology suffices to achieve numerical stability. Our strategy is static in the sense that work distribution and communication patterns are determined in a preprocessing phase preceding the actual numerical computation. To balance the load among the processors, we devise a simple model-driven partitioning strategy to precompute a high-quality balancing for a large family of structured meshes. The resulting approach is proved to be considerably more efficient than the strategies implemented by MUMPS and SuperLU_DIST, two state-of-the-art parallel multifrontal solvers.

Support for the authors was provided in part by MIUR of Italy under Project ALGO-NEXT and by the European Union under the FP6-IST/IP Project AEOLUS.

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References

  1. Amestoy, P.R., Duff, I.S., Koster, J., L’Excellent, J.-Y.: A fully asynchronous multifrontal solver using distributed dynamic scheduling. SIAM Journal of Matrix Analysis and Applications 23(1), 15–41 (2001)

    Article  MATH  MathSciNet  Google Scholar 

  2. Amestoy, P.R., Duff, I.S., L’Excellent, J.-Y., Li, X.S.: Analysis and comparison of two general sparse solvers for distributed memory computers. ACM Trans. Math. Softw. 27(4), 388–421 (2001)

    Article  MATH  MathSciNet  Google Scholar 

  3. Amestoy, P.R., Guermouche, A., L’Excellent, J.-Y., Pralet, S.: Hybrid scheduling for the parallel solution of linear systems. Technical Report RR-5404, INRIA (2004)

    Google Scholar 

  4. Bertoldo, A., Bianco, M., Pucci, G.: A fast multifrontal solver for non-linear multi-physics problems. In: International Conference on Computational Science, pp. 614–617 (2004)

    Google Scholar 

  5. Bianco, M., Bilardi, G., Pesavento, F., Pucci, G., Schrefler, B.A.: An accurate and efficient frontal solver for fully-coupled hygro-thermo-mechanical problems. In: International Conference on Computational Science, vol. 1, pp. 733–742 (2002)

    Google Scholar 

  6. Bianco, M., Bilardi, G., Pesavento, F., Pucci, G., Schrefler, B.A.: A frontal solver tuned for fully-coupled non-linear hygro-thermo-mechanical problems. International Journal for Numerical Methods in Engineering 57(13), 1801–1818 (2003)

    Article  MATH  Google Scholar 

  7. Cormen, T.H., Stein, C., Rivest, R.L., Leiserson, C.E.: Introduction to Algorithms. McGraw-Hill Higher Education (2001)

    Google Scholar 

  8. Js, W.D., Eisenstat, S.C., Gilbert, J.R., Li, X.S., Liu, J.W.H.: A supernodal approach to sparse partial pivoting. SIAM J. Matrix Analysis and Applications 20(3), 720–755 (1999)

    Article  Google Scholar 

  9. Dongarra, J.J., Du Croz, J., Hammarling, S., Duff, I.: A set of level 3 Basic Linear Algebra Subprograms. ACM Transactions on Mathematical Software 16(1), 1–17 (1990)

    Article  MATH  Google Scholar 

  10. Dongarra, J.J., Duff, I.S., Sorensen, D.C., van der Vorst, H.A.: Numerical Linear Algebra for High Performance Computers. In: Society for Industrial and Applied Mathematics, Philadelphia, PA, USA (1998)

    Google Scholar 

  11. Duff, I.S., Reid, J.K.: The multifrontal solution of unsymmetric sets of linear systems. SIAM Journal on Scientific and Statistical Computing 5, 633–641 (1984)

    Article  MATH  MathSciNet  Google Scholar 

  12. Gupta, A., Kumar, V.: Parallel algorithms for forward and back substitution in direct solution of sparse linear systems. In: Supercomputing 1995: Proceedings of the 1995 ACM/IEEE conference on Supercomputing (CDROM), p. 74 (1995)

    Google Scholar 

  13. Karypis, G., Kumar, V.: METIS: A Software Package for Partitioning Unstructured Graphs, Partitioning Meshes, and Computing Fill-Reducing Orderings of Sparse Matrices Version 4.0 (September 1998)

    Google Scholar 

  14. Li, X.S., Demmel, J.W.: SuperLU_DIST: A scalable distributed-memory sparse direct solver for unsymmetric linear systems. ACM Trans. Mathematical Software 29(2), 110–140 (2003)

    Article  MATH  MathSciNet  Google Scholar 

  15. Liu, J.W.H.: The multifrontal method for sparse matrix solution: theory and practice. SIAM Rev. 34(1), 82–109 (1992)

    Article  MATH  MathSciNet  Google Scholar 

  16. Zienkiewicz, O.C., Taylor, R.L.: The finite element method, 5th edn. Butterworth, Heinemann (2000)

    MATH  Google Scholar 

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Bertoldo, A., Bianco, M., Pucci, G. (2006). A Static Parallel Multifrontal Solver for Finite Element Meshes. In: Guo, M., Yang, L.T., Di Martino, B., Zima, H.P., Dongarra, J., Tang, F. (eds) Parallel and Distributed Processing and Applications. ISPA 2006. Lecture Notes in Computer Science, vol 4330. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11946441_67

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  • DOI: https://doi.org/10.1007/11946441_67

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-68067-3

  • Online ISBN: 978-3-540-68070-3

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