Next-generation CFD: Real-Time Computation and Visualization

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1 Next-generation CFD: Real-Time Computation and Visualization Christian F. Janßen Hamburg University of Technology

2 Tesla C1060, ~20 million lattice nodes [2010] Kinetic approaches for the simulation of non-linear free surface flow problems in civil and environmental engineering. C. F. Janßen, PhD Thesis, Nov

3 Towards simulation-based design (SBD) Typical applications in Civil, Environmental and Naval Engineering include the simulation of Tsunami propagation and inundation Violent wave impact Wave-structure interactions Vortex-induced vibrations Ship hydrodynamics Ship-ice interactions Our goal: Supercomputing on the Desktop Solve an engineering problem as fast as possible and with the locally available HPC resources to reduce the total amount of time to solution Need for efficient models for (I) the flow field solution, (ii) preprocessing and (iii) postprocessing GPU-accelerated CFD for large-scale free surface flow problems in civil and environmental engineering C. F. Janßen, S. Gralher, D. Mierke. M. Überrück and T. Rung, submitted to Computation, Jan

4 elbe efficient lattice boltzmann environment 1d, 2d and 3d Lattice Boltzmann models on Cartesian grids Advanced features: LES turbulence modeling, VOF interface capturing, bidirectional fluid-structure interaction, grid refinement Extensively validated implemented using NVIDIA CUDA Grid sizes of up to 120 million lattice nodes and an average performance of 500 MNUPS (million node updates per second) per GPU board supported by NVIDIA Best Presentation on GPU Computing Award (ICMMES 2011) Academic Partnership Program (URI, 2011; TUHH, 2012) CUDA Research Center (TUHH, since 2014) J. Tölke, Lattice Boltzmann Multi-Phase Simulations in Porous Media using GPUs, GTC 2010 J. Tölke and M. Krafczyk, Teraflop computing on a desktop PC with GPUs for 3D CFD, Int. J. CFD,

5 Validation GPGPU-accelerated simulation of wave-ship interactions using LBM and a quaternion-based motion modeler. C. Janßen, H. Nagrelli and T. Rung. Proc. of MARINE

6 Validation 12 mins (GTX Titan) 5.4 hrs (10 CPU cores) 2s GPGPU-accelerated simulation of wave-ship interactions using LBM and a quaternion-based motion modeler. C. Janßen, H. Nagrelli and T. Rung. Proc. of MARINE

7 Towards next-generation CFD tools 7

8 Towards next-generation CFD tools State of the art in many GPU-accelerated CFD solvers: efficient and accurate flow field calculations are combined with conventional pre- and post-processing routines, e.g. Bottle necks: Grid generation and dynamic grid updates Post-processing and File-IO 8

9 Efficient grid generation Geometries are commonly described as tessellated surface meshes, e.g. in STL format 270,000 Δ 12 Δ 2,800,000 Δ 6,500 Δ A fast and rigorously parallel surface voxelization technique for GPGPU-accelerated CFD simulations. C. Janßen, N. Koliha and T. Rung. Communications in Comp. Physics, accepted for publication, Oct

10 CUDA-accelerated voxelizer A fast and rigorously parallel surface voxelization technique for GPGPU-accelerated CFD simulations. C. Janßen, N. Koliha and T. Rung. Communications in Comp. Physics, accepted for publication, Oct

11 CUDA-accelerated voxelizer A fast and rigorously parallel surface voxelization technique for GPGPU-accelerated CFD simulations. C. Janßen, N. Koliha and T. Rung. Communications in Comp. Physics, accepted for publication, Oct

12 CUDA-accelerated voxelizer A fast and rigorously parallel surface voxelization technique for GPGPU-accelerated CFD simulations. C. Janßen, N. Koliha and T. Rung. Communications in Comp. Physics, accepted for publication, Oct

13 CUDA-accelerated voxelizer A fast and rigorously parallel surface voxelization technique for GPGPU-accelerated CFD simulations. C. Janßen, N. Koliha and T. Rung. Communications in Comp. Physics, accepted for publication, Oct

14 Performance test MNAPS = million node activations per second A fast and rigorously parallel surface voxelization technique for GPGPU-accelerated CFD simulations. C. Janßen, N. Koliha and T. Rung. Communications in Comp. Physics, accepted for publication, Oct

15 Debris flow Tesla C2075, ~6.4m nodes, 18hrs GPU-accelerated CFD for large-scale free surface flow problems in civil and environmental engineering C. F. Janßen, S. Gralher, D. Mierke. M. Überrück and T. Rung, submitted to Computation, Jan

16 Ship-ice interactions Tesla K40m, ~48.8m nodes, 12hrs MARINE 2015 D. Mierke, C. F. Janßen and T. Rung, submitted to MARINE 2015 Proceedings, March

17 Towards next-generation CFD tools State of the art in many available solvers: efficient and accurate flow field calculations are combined with conventional pre- and postprocessing routines, e.g. Bottle necks: Grid generation and dynamic grid updates Postprocessing and File-IO 17

18 Design philosophy of elbevis 18

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20 Design philosophy of elbevis 20

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22 Future applications 22

23 I. elbevis on external GPUs 23

24 II. elbevis in the classroom 24

25 III. elbevis for real-time CFD 25

26 Summary and Conclusions A highly efficient numerical method in combination with tailor-made pre- and postprocessing tools allows for numerical simulations near real-time Model extensions (in terms of hybrid models and grid refinement strategies) will further increase the model accuracy while keeping the high performance The use of locally available HPC hardware has great potential for simulation-based design and problembased learning 26

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28 Next-generation CFD: Real-Time Computation and Visualization Christian F. Janßen Hamburg University of Technology 28