These past few years, new types of computational architectures based on graphics processors have emerged. These technologies provide important computational resources at low cost and low energy consumption. Lots of developments have been done around GPU and many tools and libraries are now available to implement efficiently softwares on those architectures.
This article contains the two contributions of the mini-symposium about GPU organized by Loïc Gouarin (Laboratoire de Mathématiques d’Orsay), Alexis Hérault (CNAM) and Violaine Louvet (Institut Camille Jordan). This mini-symposium was an opportunity to explore the upcoming role of hardware accelerators and how it will affect the way applications are designed and developed.
As the main issue of the mini-symposium was graphical cards, this document contains contributions about two feedbacks on the behavior of different numerical methods on GPU:
- ones on particle method for transport equations,
- the other on Lattice Boltzmann Methods for Navier–Stokes equations, Finite Volume schemes for Euler equations and particles methods for kinetic equations.
Ces dernières années, de nouveaux types d’architectures basés sur les processeurs graphiques ont émergés. Ces technologies fournissent d’importantes ressources computationelles à faible coût et faible consommation d’énergie. Les nombreux dévelopements effectués sur le GPU ont alors permis la création et l’implémentation de logiciels sur ce type d’architecture.
Cet article contient les deux contributions de ce mini-symposium GPU organisé par Loïc Gouarin (Laboratoire de Mathématiques d’Orsay), Alexis Hérault (CNAM) et Violaine Louvet (Institut Camille Jordan). La premiere concerne les méthodes particulaires pour les équations de transport, la seconde concerne la résolution des équations de Navier-Stokes et des équations d’Euler.
Keywords: GPU, méthode particulaire, EDP, Mécanique des Fluides, interaction, visualisation, calcul instantané, volumes finis, méthode Lattice Boltzmann, méthode particulaire, programmation multicœur
Mot clés : PDE, GPU, CFD, interaction, visualization, instant computation, finite volumes, Lattice Boltzmann method, particle method, multicore programming
@article{AMBP_2013__20_1_75_0, author = {Cottet, Georges-Henri and Etancelin, Jean-Matthieu and Perignon, Franck and Picard, Christophe and De Vuyst, Florian and Labourdette, Christophe}, title = {Is {GPU} the future of {Scientific} {Computing} ?}, journal = {Annales math\'ematiques Blaise Pascal}, pages = {75--99}, publisher = {Annales math\'ematiques Blaise Pascal}, volume = {20}, number = {1}, year = {2013}, doi = {10.5802/ambp.322}, zbl = {1296.68027}, mrnumber = {3112240}, language = {en}, url = {http://archive.numdam.org/articles/10.5802/ambp.322/} }
TY - JOUR AU - Cottet, Georges-Henri AU - Etancelin, Jean-Matthieu AU - Perignon, Franck AU - Picard, Christophe AU - De Vuyst, Florian AU - Labourdette, Christophe TI - Is GPU the future of Scientific Computing ? JO - Annales mathématiques Blaise Pascal PY - 2013 SP - 75 EP - 99 VL - 20 IS - 1 PB - Annales mathématiques Blaise Pascal UR - http://archive.numdam.org/articles/10.5802/ambp.322/ DO - 10.5802/ambp.322 LA - en ID - AMBP_2013__20_1_75_0 ER -
%0 Journal Article %A Cottet, Georges-Henri %A Etancelin, Jean-Matthieu %A Perignon, Franck %A Picard, Christophe %A De Vuyst, Florian %A Labourdette, Christophe %T Is GPU the future of Scientific Computing ? %J Annales mathématiques Blaise Pascal %D 2013 %P 75-99 %V 20 %N 1 %I Annales mathématiques Blaise Pascal %U http://archive.numdam.org/articles/10.5802/ambp.322/ %R 10.5802/ambp.322 %G en %F AMBP_2013__20_1_75_0
Cottet, Georges-Henri; Etancelin, Jean-Matthieu; Perignon, Franck; Picard, Christophe; De Vuyst, Florian; Labourdette, Christophe. Is GPU the future of Scientific Computing ?. Annales mathématiques Blaise Pascal, Volume 20 (2013) no. 1, pp. 75-99. doi : 10.5802/ambp.322. http://archive.numdam.org/articles/10.5802/ambp.322/
[1] A Lagrangian particle-wavelet method, Multiscale Models. Simul., Volume 5 (2006) no. 3, pp. 980-995 | DOI | MR | Zbl
[2] Stabilization of the lattice Boltzmann method using the Ehrenfests’ coarse-graining data, Physical Review E, Volume 74 (2006), pp. 037703 | DOI
[3] The Boltzmann Equation and Its Applications, 67, Springer-Verlag, 1988 | MR | Zbl
[4] Numerical approximation of hyperbolic conservation laws, 118, Applied Mathematical Sciences, Springer-Verlag, Boston, 1996 | MR
[5] An implicit Flux-Vector Splitting Scheme for the computation of viscous hypersonic flow, AIAA Paper, Volume 25 (1989) (Paper 89-0274)
[6] On upstream differencing and Godunov-type schemes for hyperbolic conservation laws, SIAM Review, Volume 25 (1983), pp. 35-61 | DOI | MR | Zbl
[7] Accurate, non-oscillatory, remeshing schemes for particle methods, J. Comput. Phys., Volume 231 (2012) no. 1, pp. 152-172 | DOI | MR
[8] The OpenCL Specification, Khronos OpenCL Working Group (2011)
[9] The lattice Boltzmann equation method: theoretical interpretation, numerics and implications, Int. J. of Multiphase Flow, Volume 29 (2003), pp. 117-169 | DOI | Zbl
[10] CUDA C Best Practices Guide 4.1, NVIDIA (2012) http://developer.download.nvidia.com/compute/DevZone/docs/html/C/doc/CUDA_C_Best_Practices_Guide.pdf
[11] GPU accelerated simulations of bluff body flows using vortex methods, J. Comput. Phys., Volume 229 (2010) no. 9, pp. 3316-3333 | DOI | MR
[12] The Lattice Boltzmann Equation for Fluid Dynamics and Beyond, Oxford, 2001 (ISBN:0-19-850398-9) | MR | Zbl
[13] A Flux Vector Splitting method that preserves stationary contact discontinuities, Acta Mathematicae Applicandae (2013) (accepted, under revision)
[14] GPU-Accelerated numerical simulations of the Knudsen gas on time-dependent domains, Computer Physics Communications, Volume 184 (2013) no. 3, pp. 532-536 http://hal.archives-ouvertes.fr/docs/00/68/75/66/PDF/GPU_DeVuyst_Salvarani3.pdf | DOI | MR
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