Using CUDA architecture for computer simulations of thermomechanical phenomena

• Autorzy: Michalski G. , Sczygiol N. , Leonov S.
• Języki publikacji: EN

Abstrakty

EN

This paper presents a simulation of the casting solidification process performed on graphics processors compatible with nVidia CUDA architecture. Indispensable for the parallel implementation of a computer simulation of the solidification process, it was necessary to modify the numerical model. The new approach shown in this paper allows the process of matrix building to be divided into two independent phases. The first is independent from the nodal temperature values computed in successive time-steps. The second is performed on the basis of nodal temperature values, but does not require a description of the finite element mesh. This phase is performed in each time step of the simulation of the casting solidification process. The separation of these two phases permits an effective implementation of the simulation software of the casting solidification process on the nVidia CUDA architecture or any other multi-/manycore architecture. The use of GPUs nVidia for the implementation of a computer simulation of the solidification process significantly reduced the waiting time for results. In the course of computer simulations important speedup of the computations was observed.

Słowa kluczowe

EN

numerical modelling; solidification; distributed and parallel processing; CUDA

PL

modelowanie numeryczne; krzepnięcie; przetwarzanie rozproszone i równoległe

• Wydawca: Wydawnictwo Politechniki Częstochowskiej
• Czasopismo: Journal of Applied Mathematics and Computational Mechanics
• Rocznik: 2014
• Tom: Vol. 13, nr 3
• Strony: 167--174
• Opis fizyczny: Bibliogr. 8 poz., rys.

Twórcy

autor

Michalski G.

• Institute of Computer and Information Sciences, Czestochowa University of Technology Częstochowa, Poland

autor

Sczygiol N.

• Institute of Computer and Information Sciences, Czestochowa University of Technology Częstochowa, Poland

autor

Leonov S.

• I.I. Polzunov Altai State Technical University Altai, Russia

Bibliografia

• [1] Meng H.T., Nie B.L., Wong S., Macon C., Jin J.M., GPU accelerated finite-element computation for electromagnetic analysis, Antennas and Propagation Magazine, IEEE, 2014, 56, 2, 39-62.
• [2] Che S., Boyer M., Meng J., Tarjan D., Sheaffer J.W., Skadron K., A performance study of generalpurpose applications on graphics processors using CUDA, Journal of Parallel and Distributed Computing 2008, 10, 68, 1370-1380.
• [3] nVidia, CUDA C Best Practices Guide v. 3.2 2010.
• [4] Pospichal P., Schwarz J., Jaros J., Parallel genetic algorithm solving 0/1 knapsack problem running on the GPU, 16th International Conference on Soft Computing MENDEL 2010, Brno University of Technology, 64-70.
• [5] Lee C., Wei X., Kysar J.W., Hone J., Measurement of the elastic properties and intrinsic strength of monolayer graphene, Science 2008, 321, 385-388.
• [6] nVidia, Optimization. OpenlCL Best Practices Guide, 2010.
• [7] Zienkiewicz O., The Finite Element, Volume I, the Basis 5th Edition, Butterworth-Heinemann, Oxford 2003.
• [8] Sczygiol N., Szwarc G., Wyrzykowski R., Numerical modeling of equiaxed structure formation during solidification of a two-component alloy, 2nd European Conference on Computational Mechanics, Kraków 2001, 820-821.