Browse > Article
http://dx.doi.org/10.12989/sem.2009.32.1.095

Parallel processing in structural reliability  

Pellissetti, M.F. (Institute of Engineering Mechanics, University of Innsbruck)
Publication Information
Structural Engineering and Mechanics / v.32, no.1, 2009 , pp. 95-126 More about this Journal
Abstract
The present contribution addresses the parallelization of advanced simulation methods for structural reliability analysis, which have recently been developed for large-scale structures with a high number of uncertain parameters. In particular, the Line Sampling method and the Subset Simulation method are considered. The proposed parallel algorithms exploit the parallelism associated with the possibility to simultaneously perform independent FE analyses. For the Line Sampling method a parallelization scheme is proposed both for the actual sampling process, and for the statistical gradient estimation method used to identify the so-called important direction of the Line Sampling scheme. Two parallelization strategies are investigated for the Subset Simulation method: the first one consists in the embarrassingly parallel advancement of distinct Markov chains; in this case the speedup is bounded by the number of chains advanced simultaneously. The second parallel Subset Simulation algorithm utilizes the concept of speculative computing. Speedup measurements in context with the FE model of a multistory building (24,000 DOFs) show the reduction of the wall-clock time to a very viable amount (<10 minutes for Line Sampling and ${\approx}$ 1 hour for Subset Simulation). The measurements, conducted on clusters of multi-core nodes, also indicate a strong sensitivity of the parallel performance to the load level of the nodes, in terms of the number of simultaneously used cores. This performance degradation is related to memory bottlenecks during the modal analysis required during each FE analysis.
Keywords
structural reliability; stochastic structural mechanics; parallel computing; Monte Carlo simulation;
Citations & Related Records

Times Cited By Web Of Science : 3  (Related Records In Web of Science)
Times Cited By SCOPUS : 5
연도 인용수 순위
1 Alonso, J., de Alfonso, C., García, G. and Hernández, V. (2007), "Grid technology for structural analysis", Adv. Eng. Software, 38(11-12), 738-749   DOI   ScienceOn
2 Au, S.K. and Beck, J. (2001), "Estimation of small failure probabilities in high dimensions by subset simulation", Probabilist. Eng. Mech., 16(4), 263-277   DOI   ScienceOn
3 Bitzarakis, S., Papadrakakis, M. and Kotsopulos, A. (1997), "Parallel solution techniques in computational structural mechanics", Comput. Meth. Appl. Mech. Eng., 148(1-2), 75-104   DOI   ScienceOn
4 Charmpis, D. and Papadrakakis, M. (2005), "Improving the computational efficiency in finite element analysis of shells with uncertain properties", Comput. Meth. Appl. Mech. Eng., 194(12-16), 1447-1478   DOI   ScienceOn
5 Coutinho, A., Martins, M., Sydenstricker, R. and Elias, R. (2006), "Performance comparison of data-reordering algorithms for sparse matrix-vector multiplication in edge-based unstructured grid computations", Int. J. Numer. Meth. Eng., 66, 431-460   DOI   ScienceOn
6 Ditlevsen, O. and Madsen, H.O. (1996), Structural Reliability Methods, John Wiley & Sons, Chichester
7 Farhat, C., Cortial, J., Dastillung, C. and Bavestrello, H. (2006), "Time-parallel implicit integrators for the nearreal-time prediction of linear structural dynamic responses", Int. J. Numer. Meth. Eng., 67, 697-724   DOI   ScienceOn
8 Farhat, C. and Lesoinne, M. (1993), "Automatic partitioning of unstructured meshes for the parallel solution of problems in computational mechanics", Int. J. Numer. Meth. Eng., 36(5), 745-764   DOI
9 Ghanem, R. and Kruger, R. (1996), "Numerical solution of spectral stochastic finite element systems", Comput. Meth. Appl. Mech. Eng., 129, 289-303   DOI   ScienceOn
10 Hartmann, J., Krahnke, A. and Zenger, C. (2008), "Cache efficient data structures and algorithms for adaptive multidimensional multilevel finite element solvers", Appl. Numer. Math., 58, 435-448   DOI   ScienceOn
11 Johnson, E.A., Wojtkiewicz, S.F., Bergman, L.A. and Jr., B.F.S. (1997), "Observations with regard to massively parallel computation for monte carlo simulation of stochastic dynamical systems", Int. J. Non-linear Mech., 32(4), 721-734   DOI   ScienceOn
12 Johnson, E., Proppe, C., Spencer Jr, B., Bergman, L., Sz$\acute{e}$kely, G. and Schu$\ddot{e}$ller, G.I. (2003), "Parallel processing in computational stochastic dynamics", Probabilist. Eng. Mech., 18(1), 37-60   DOI   ScienceOn
13 Lehoucq, R., Sorensen, D. and Yang, C. (1998), ARPACK Users Guide: Solution of Large-Scale Eigenvalue Problems by Implicitly Restarted Arnoldi Methods, SIAM: Philadelphia, PA
14 Keese, A. and Matthies, H. (2005), "Hierarchical parallelisation for the solution of stochastic finite element equations", Comput. Struct., 83, 1033-1047   DOI   ScienceOn
15 Koutsourelakis, P., Pradlwarter, H.J. and Schu$\ddot{e}$ller, G.I. (2004), "Reliability of structures in high dimensions, part I: Algorithms and applications", Probabilist. Eng. Mech., 19(4), 409-417   DOI   ScienceOn
16 Krysl, P. and Bittnar, Z. (2001), "Parallel explicit finite element solid dynamics with domain decomposition and message passing: Dual partitioning scalability", Comput. Struct., 79(3), 345-360   DOI   ScienceOn
17 Leite, J.P.B. and Topping, B.H.V. (1999), "Parallel simulated annealing for structural optimization", Comput. Struct., 73, 545-564   DOI   ScienceOn
18 Mackay, D. and Law, K. (1996), "A parallel implementation of a generalized lanczos procedure for structural dynamic analysis", Int. J. High Speed Comput., 8(2), 171-204   DOI   ScienceOn
19 Metropolis, N. and Ulam, S. (1949), "The monte carlo method", J. Am. Stat. Assoc., 44, 335-341   DOI   ScienceOn
20 Papadrakakis, M. and Kotsopulos, A. (1999), "Parallel solution methods for stochastic finite element analysis using monte carlo simulation", Comput. Meth. Appl. Mech. Eng., 168(1-4), 305-320   DOI   ScienceOn
21 Papadrakakis, M., Lagaros, N. and Fragakis, Y. (2003), "Parallel computational strategies for structural optimization", Int. J. Numer. Meth. Eng., 58(9), 1347-1380   DOI   ScienceOn
22 Rubinstein, R. (1981), Simulation and the Monte Carlo Method, John Wiley & Sons, New York, Chichester, Brisbane, Toronto
23 Pellissetti, M.F., Pradlwarter, H.J. and Schuëller, G.I. (2007), "Relative importance of uncertain structural parameters, Part II: Applications", Comput. Mech., 40(4), 637-649   DOI   ScienceOn
24 Pradlwarter, H.J. (2007), "Relative importance of uncertain structural parameters, Part I: Algorithm", Comput. Mech., 40(4), 627-635   DOI   ScienceOn
25 Pradlwarter, H. and Schu$\ddot{e}$ller, G. (2008, submitted), "Uncertain linear systems in dynamics, Part 2: Efficient reliability assessment", Comput. Struct
26 Saleh, A. and Adeli, H. (1996), "Parallel eigenvalue algorithms for large-scale control-optimization problems", J. Aerospace Eng., 9(3), 70-79   DOI   ScienceOn
27 Schu$\ddot{e}$ller (Ed.), G.I. (1997), "A state-of-the-art report on computational stochastic mechanics", Probabilist. Eng. Mech., 12(4), 197-321   DOI   ScienceOn
28 Schu$\ddot{e}$ller, G.I. (2007), "On the Treatment of Uncertainties in Structural Mechanics and Analysis (based on a Plenary Keynote Lecture Presented at the Third M.I.T. Conference on Computational Fluids and Solids Mechanics), Boston, USA", Comput. Struct., 85(5-6), 235-243   DOI   ScienceOn
29 Schu$\ddot{e}$ller, G.I. and Pradlwarter, H.J. (2007), "Benchmark study on reliability estimation in higher dimensions of structural systems - an overview", Struct. Safety, 29(3), 167-182   DOI   ScienceOn
30 Schu$\ddot{e}$ller, G.I., Pradlwarter, H.J. and Koutsourelakis, P. (2004), "A critical appraisal of reliability estimation procedures for high dimensions", Probabilist. Eng. Mech., 19(4), 463-474   DOI   ScienceOn
31 Sz$\acute{e}$kely, G. and Schu$\ddot{e}$ller, G.I. (2001), "Computational procedure for a fast calculation of eigenvectors and eigenvalues of structures with random properties", Comput. Meth. Appl. Mech. Eng., 191(8-10), 799-816   DOI   ScienceOn
32 Shinozuka, M. and Deodatis, G. (1997), "Parallel implementation of mcs - synthesis of seismic ground motion using a stochastic barrier model", Probabilist. Eng. Mech., Special Issue on Computational Stochastic Mechanics, 12(4), 213-216
33 Sotelino, E. (2003), "Parallel processing techniques in structural engineering applications", Struct. Eng., ASCE, 129(12), 1698-1706   DOI   ScienceOn
34 Sz$\acute{e}$kely, G., Pradlwarter, H.J. and Schu$\ddot{e}$ller, G.I. (1998), Computational Stochastic Structural Analysis - Software Development, in S. Lydersen et al., ed., Proceedings of the ESREL'98 -Safety and Reliability, Vol. 2, A.A. Balkema, Rotterdam, Trondheim, Norway, 1013-1020
35 Umesha, P.K., Venuraju, M.T., Hartmann, D. and Leimbach, K.R. (2005), "Parallel computing techniques for sensitivity analysis in optimum structural design", J. Comput. Civil Eng., 21(6), 463-477   DOI   ScienceOn
36 Valdebenito, M. and Schu$\ddot{e}$ller, G. (2008), Quality Assurance of Uncertain Mechanical Systems Considering the effects of Fatigue and Fracture, in '8th World Congress on Computational Mechanics, (WCCM8)', Venice, Italy, EU
37 Wriggers, P. and Boersma, A. (1998), "A parallel algebraic multigrid solver for problems in solid mechanics discretisized by finite elements", Comput. Struct., 69(1), 129-137   DOI   ScienceOn
38 Zienkiewicz, O. and Taylor, R. (2000), The Finite Element Method, 5th edn, Butterworth-Heinemann, Oxford, UK