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Abstrakty
The simulation of blood flow in the cardiac system has the potential to become an attractive diagnostic tool for many cardiovascular diseases, such as in the case of aneurysm. This potential could be reached if the simulations were to be completed in hours rather than days and without resorting to the use of expensive supercomputers. Therefore we have investigated a possibility of acceleratingmedical computational fluid dynamics (CFD) simulations using graphics processing units (GPUs). Our results for the 3D blood flow in the human abdominal aorta show that by transferring only a part of the computations (linear system solvers) to the GPU, it is possible to make the typical CFD simulations three to four times faster depending on the CFD model being used. Since these simulations were performed on widely available GPUs that had been designed as mass-market PC extension cards, our results suggest that porting larger parts of CFD to GPUs could really bring the technology into hospitals.
Czasopismo
Rocznik
Tom
Strony
137--137
Opis fizyczny
-–161, Bibliogr. 29 poz.
Twórcy
autor
autor
autor
autor
autor
autor
autor
- Faculty of Power and Mechanical Engineering, Wrocław University of Technology, Poland, ziemowit.malecha@pwr.wroc.pl
Bibliografia
- 1. V. Kurtcuoglu et al., Computational investigation of subject-specific cerebrospinal fluid flow in the third ventricle and aqueduct of sylvius, Journal of Biomechanics, 40, 6, 1235–1245, 2007.
- 2. T. Gohil et al., Simulation of Oscillatory Flow in an Aortic Bifurcation Using FVM and FEM: a Comparative Study of Implementation Strategies, International Journal for Numerical Methods in Fluids, 2010.
- 3. S. Hirsch et al., A mechano-chemical model of a solid tumor for therapy outcome predictions [in:] Computational Science – ICCS 2009, Lecture Notes in Computer Science, 5544/2009, 715–724, Springer Berlin/Heidelberg, 2009.
- 4. D. Szczerba et al., Mechanism and localization of wall failure during abdominal aortic aneurysm formation [in:] ISBMS ’08: Proceedings of the 4th international symposium on Biomedical Simulation, 119–126, Berlin, Heidelberg: Springer-Verlag, 2008.
- 5. D. Szczerba, G. Szekely, Simulating Vascular Systems in Arbitrary Anatomies, [in:] Medical Image Computing and Computer-Assisted Intervention, Springer, 2005.
- 6. OpenFOAM. The Open Source CFD Toolbox. User Guide, Free Software Foundation, Inc., 2009.
- 7. OpenFOAM. The Open Source CFD Toolbox. Programmer’s Guide, Free Software Foundation, Inc., 2009.
- 8. L. Mirosław et al., Integration of GPU-Accelerated Linear Solvers with OpenFoam and Their Application to CFD, submitted to The Computer Journal, 2010.
- 9. H. Oertel, Ed., Prandtl’s Essentials of Fluid Mechanics, Springer-Verlag, 2000.
- 10. R. Issa, Solution of implicitly discretized fluid flow equations by operator-splitting, J. Comput. Phys. 62, 40–65, 1986.
- 11. T. Chung, Computational fluid dynamics, Cambridge University Press, 2002.
- 12. J. Ferziger, M. Perić, Computational methods for fluid dynamics, Springer Berlin, 1999.
- 13. H. Versteeg, W. Malalsekera, An introduction to computational fluid dynamics, Longman Scientific & Technical, 1995.
- 14. NVIDIA CUDA Programming Guide Version 3.0, NVIDIA, 2010. [on-line:] http://developer.download.nvidia.com/compute/cuda/3_0/toolkit/docs/NVIDIA_CUDA_Program-mingGuide.pdf.
- 15. ATI Stream Technology, http://www.amd.com/us/products/technologies/stream-techno-logy/Pages/stream-technology.aspx, 2009.
- 16. J. Tölke, M. Krafczyk, TeraFLOP computing on a desktop PC with GPUs for 3D CFD, International Journal of Computational Fluid Dynamics, 22, 7, 443–456, 2008.
- 17. E. Elsen, P. LeGresley, E. Darve, Large calculation of the flow over a hypersonic vehicle using a GPU, J. Comput. Phys., 227, 24, 10 148–10 161, 2008.
- 18. J.M. Cohen, M.J. Molemaker, A fast double precision CFD code using CUDA, [in:] 21st International Conference on Parallel Computational Fluid Dynamics (ParCFD2009), 2009.
- 19. J.C. Thibault, I. Senocak, CUDA Implementation of a Navier–Stokes Solver on Multi- GPU Desktop Platforms for Incompressible Flows, [in:] 47th AIAA Aerospace Sciences Meeting Including The New Horizons Forum and Aerospace Exposition, American Institute of Aeronautics and Astronautics, Inc., 2009.
- 20. I. Senocak, J. Thibault, M. Caylor, Rapid-Response Urban CFD Simulations Using a GPU Computing Paradigm on Desktop Supercomputers, [in:] Eighth Symposium on the Urban Environment, 2009.
- 21. D.A. Jacobsen, J.C. Thibault, I. Senocak, An MPI-CUDA Implementation for Massively Parallel Incompressible Flow Computations on Multi-GPU Clusters, [in:] 48th AIAA Aerospace Sciences Meeting, American Institute of Aeronautics and Astronautics, Inc., 2010.
- 22. D. Göddeke et al., GPU acceleration of an unmodified parallel finite element Navier-Stokes solver, [in:] W.W. Smari, J.P. McIntire [Eds.], High Performance Computing & Simulation 2009, 12–21, 2009.
- 23. C. Fletcher, Computational Techniques for Fluid Dynamics 2, Springer-Verlag, 1991.
- 24. K. Hoffmann, S. Chiang, Computational Fluid dynamics, Vol. II, Engineering Education System, 2000.
- 25. Y. Saad, Iterative Methods for Sparse Linear Systems, SIAM, 2003.
- 26. R. Barrett et al., Templates for the Solution of Linear Systems: Building Blocks for Iterative Methods, 2nd Edition, Philadelphia, PA: SIAM, 1994.
- 27. N. Bell, M. Garland, Implementing sparse matrix-vector multiplication on throughput-oriented processors, [in:] SC ’09: Proceedings of the Conference on High Performance Computing Networking, Storage and Analysis, 1–11, New York, NY, USA, ACM, 2009.
- 28. T.A. Davis, Y. Hu, The University of Florida Sparse Matrix Collection, submitted to ACM Transactions on Mathematical Software.
- 29. A. Christ et al., The virtual family-development of surface-based anatomical models of two adults and two children for dosimetric simulations, Physics in Medicine and Biology, 55, 2, N23, 2010.
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-article-BAT4-0010-0015