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The Effect of Parallelization on a Tetrahedral Mesh Optimization Method

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Book cover Parallel Processing and Applied Mathematics (PPAM 2013)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 8385))

Abstract

A parallel algorithm for simultaneous untangling and smoothing of tetrahedral meshes is proposed in this paper. This algorithm is derived from a sequential mesh optimization method. We provide a detailed analysis of its parallel scalability and efficiency, load balancing, and parallelism bottlenecks using six benchmark meshes. In addition, the influence of three previously-published graph coloring techniques on the performance of our parallel algorithm is evaluated. We demonstrate that the proposed algorithm is highly scalable when run on a shared-memory computer with up to 128 Itanium 2 processors. However, some parallel deterioration is observed. Here, we analyze its main causes using a theoretical performance model and experimental results.

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References

  1. Bazaraa, M., Sherali, H., Shetty, C.M.: Nonlinear Programming. Wiley, New York (1993)

    MATH  Google Scholar 

  2. Benitez, D., Rodríguez, E., Escobar, J.M., Montenegro, R.: Performance evaluation of a parallel algorithm for simultaneous untangling and smoothing of tetrahedral meshes. In: Proceedings of the 22nd International Meshing Roundtable, pp. 579–598. Springer (2014)

    Google Scholar 

  3. Bronevetsky, G., Gyllenbaal, J., De Supinski, B.R.: CLOMP: accurately characterizing OpenMP application overheads. Int. J. Parallel Prog. 37(3), 250–265 (2009)

    Article  Google Scholar 

  4. Browne, S., Dongarra J., Garner N., London, K., Mucci, P.: A scalable cross-platform infrastructure for application performance tuning using hardware counters. In: Proceedings of the ACM/IEEE Conference on Supercomputing. IEEE Computer Society (2000)

    Google Scholar 

  5. Catalyurek, U.V., Feo, J., Gebremedhin, A.H., Halappanavar, M., Pothen, A.: Graph coloring algorithms for multicore and massively multithreaded architectures. Parallel Comput. 38(10–11), 576–594 (2012)

    Article  MathSciNet  Google Scholar 

  6. Dompierre, J., Labbé, P., Guibault, F., Camarero, R.: Proposal of benchmarks for 3D unstructured tetrahedral mesh optimization. In: Proceedings of the 7th International Meshing Roundtable, pp. 459–478. Sandia National Laboratories (1998)

    Google Scholar 

  7. Ekman, P.: Studying program performance on the Itanium 2 with pfmon. www.pdc.kth.se/~pek/ia64-profiling.txt (2003)

  8. Escobar, J.M., Rodríguez, E., Montenegro, R., Montero, G., González-Yuste, J.M.: Simultaneous untangling and smoothing of tetrahedral meshes. Comput. Methods Appl. Mech. Eng. 192, 2775–2787 (2003)

    Article  MATH  Google Scholar 

  9. Escobar, J.M., Cascón, J.M., Rodríguez, E., Montenegro, R.: A new approach to solid modeling with trivariate T-splines based on mesh optimization. Comput. Methods Appl. Mech. Eng. 200(45–46), 3210–3222 (2011)

    Article  MATH  Google Scholar 

  10. Freitag, L., Jones, M.T., Plassmann, P.E.: A parallel algorithm for mesh smoothing. SIAM J. Sci. Comput. 20(6), 2023–2040 (1999)

    Article  MATH  MathSciNet  Google Scholar 

  11. Intel: Intel Itanium 2 processor reference manual (251110-003). Intel (2004)

    Google Scholar 

  12. Jones, M.T., Plassmann, P.E.: A parallel graph coloring heuristic. SIAM J. Sci. Comput. 14(3), 654–669 (1993)

    Article  MATH  MathSciNet  Google Scholar 

  13. Knupp, P.M.: Algebraic mesh quality metrics. SIAM J. Sci. Comput. 23(1), 193–218 (2001)

    Article  MATH  MathSciNet  Google Scholar 

  14. Luby, M.: A simple parallel algorithm for the maximal independent set problem. SIAM J. Comput. 4, 1036–1053 (1986)

    Article  MathSciNet  Google Scholar 

  15. Montenegro, R., Cascón, J.M., Escobar, J.M., Rodríguez, E., Montero, G.: An automatic strategy for adaptive tetrahedral mesh generation. Appl. Numer. Math. 59(9), 2203–2217 (2009)

    Article  MATH  MathSciNet  Google Scholar 

  16. Shape repositories. www.cyberware.com, http://graphics.stanford.edu/data/3Dscanrep, www-roc.inria.fr/gamma/gamma/download/download.php

  17. Shontz, S.M., Nistor, D.M.: CPU-GPU algorithms for triangular surface mesh simplification. In: Proceedings of the 21st International Meshing Roundtable, pp. 475–492. Springer (2013)

    Google Scholar 

  18. Von Cottrell, J.A., Hughes, T.J.R., Bazilevs, Y.: Isogeometric Analysis: Toward Integration of CAD and FEA. Wiley, New York (2009)

    Book  Google Scholar 

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Acknowledgments

This work has been supported by the Spanish Sec. Estado Univ. e Inv., Min. Economa y Competitividad and FEDER, contract: CGL2011-29396-C03-01. It has been also supported by Fondo Sec. CONACYT SENER Hidrocarburos, contract: 163723, and two CESGA ICTS projects.

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Correspondence to Domingo Benitez .

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Benitez, D., Rodríguez, E., Escobar, J.M., Montenegro, R. (2014). The Effect of Parallelization on a Tetrahedral Mesh Optimization Method. In: Wyrzykowski, R., Dongarra, J., Karczewski, K., Waśniewski, J. (eds) Parallel Processing and Applied Mathematics. PPAM 2013. Lecture Notes in Computer Science(), vol 8385. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-55195-6_15

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  • DOI: https://doi.org/10.1007/978-3-642-55195-6_15

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