MPI–CUDA parallelization of a finite-strip program for geometric nonlinear analysis: A hybrid approach

A finite-strip geometric nonlinear analysis is presented for elastic problems involving folded-plate structures. Compared with the standard finite-element method, its main advantages are in data preparation, program complexity, and execution time. The finite-strip method, which satisfies the von Kar...

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Bibliographic Details
Published in:Advances in engineering software (1992) 2011-05, Vol.42 (5), p.273-285
Main Authors: RakiAe, P S, MilasinoviAe, D D, Aa[frac]ivanov, Aa[frac], Suvajdzin, Z, NikoliAe, M, HajdukoviAe, M
Format: Article
Language:English
Subjects:
Complexity
Computation
CUDA
Finite-strip method
Geometric nonlinear analysis
GPGPU
Harmonic coupled analysis
Joining
Mathematical analysis
Mathematical models
MPI
Nonlinearity
Parallel processing
Plates (structural members)
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Summary:A finite-strip geometric nonlinear analysis is presented for elastic problems involving folded-plate structures. Compared with the standard finite-element method, its main advantages are in data preparation, program complexity, and execution time. The finite-strip method, which satisfies the von Karman plate equations in the nonlinear elastic range, leads to the coupling of all harmonics. However, coupling of series terms dramatically increases computation time in existing finite-strip sequential programs when a large number of series terms is used. The research reported in this paper combines various parallelization techniques and architectures (computing clusters and graphic processing units) with suitable programming models (MPI and CUDA) to speed up lengthy computations. In addition, a metric expressing the computational weight of input sets is presented. This metric allows computational complexity comparison of different inputs.
ISSN:0965-9978
DOI:10.1016/j.advengsoft.2010.10.008