CU++: an object oriented framework for computational fluid dynamics applications using graphics processing units (original) (raw)

Access this article

Log in via an institution

Subscribe and save

Buy Now

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

References

  1. Cohen JM, Molemaker MJ (2009) A fast double precision code using CUDA. In: Proceedings of parallel CFD, Moffett Field, CA
    Google Scholar
  2. General-purpose computation on graphics hardware. http://gpgpu.org
  3. Hagen TR, Lie K-A, Natvig JR (2006) Solving the Euler Equations on Graphics Processing Units/ In. Lecture Notes in Computer Science, vol 3994. Springer, Berlin, pp 220–227
    Google Scholar
  4. Elsen E, LeGresley P, Darve E (2008) Large calculation of the flow over a hypersonic vehicle using a GPU. J Comput Phys 227(24):10148–10161
    Article MATH Google Scholar
  5. Brandvik T, Pullan G (2008) Acceleration of a 3D Euler solver using commodity graphics hardware. 46th AIAA aerospace sciences meeting and exhibit, AIAA-2008-0607, Reno, NV
    Google Scholar
  6. Buck I (2003) Data parallel computing on graphics hardware. Graphics Hardware
  7. NVIDIA CUDA C programming Guide 4.0. http://developer.nvidia.com/cuda-toolkit-40
  8. Phillips EH, Zhang Y, Davis RL, Owens JD (2009) Rapid aerodynamic performance prediction on a cluster of graphics processing units. In: 47th aerospace sciences meeting and exhibit, AIAA-2009-0565, Orlando, FL
    Google Scholar
  9. Bailey P, Myre J, Walsh SDC, Lilja DJ (2009) Accelerating lattice Boltzmann fluid flow simulations using graphics processors. In: Parallel processing, Vienna, Austria, pp 550–557. doi:10.1109/ICPP.2009.38
    Google Scholar
  10. NAS parallel benchmarks. http://www.nas.nasa.gov/publications/npb.html. Accessed 10 June 2013
  11. Lu F, Song J, Cao X, Zhu X (2011) Acceleration for CFD applications on large GPU clusters: an NPB case study. In: Computer sciences and convergence information technology, Seogwipo, South Korea, pp 534–538. ISBN:978-1-4577-0472-7
    Google Scholar
  12. Vandevoorde D, Josuttis N (2003) C++ templates: the complete guide. Pearson Education, Upper Sadle River
    Google Scholar
  13. Cohen J (2012) Processing device arrays with C++ metaprogramming. In: GPU computing gems, Jade edition. Morgan Kaufmann, San Mateo. doi:10.1016/B978-0-12-385963-1.00044-7
    Google Scholar
  14. Chen J, Joo B, Watson W, Edwards R (2012) Automatic offloading C++ expression templates to CUDA enabled GPUs. In: Parallel and distributed processing symposium workshops and PhD forum, Shanghai, China, pp 2359–2368. doi:10.1109/IPDPSW.2012.293
    Google Scholar
  15. Enmyren J, Kessler CW (2010) SkePU: A multi-backend skeleton programming library for multi-GPU systems. In: Proc 4th int workshop on high-level parallel programming and applications (HLPP-2010), Baltimore, Maryland, USA, September 2010. ACM, New York
    Google Scholar
  16. Corrigan A, Camelli F, Lohner R, Mut F (2011) Semi-automatic porting of a large-scale Fortran CFD code to GPUs. Int J Numer Methods Fluids 69(6):314–331
    Google Scholar
  17. Poole D (2012) Introduction to OpenACC directives. In: NVIDIA GPU technology conference
    Google Scholar
  18. Quinlan D (2000) A++P++ manual. UCRL Report No: UCRL-MA-136511, Lawrence Livermore National Laboratory
  19. Brown DL, Chesshire GS, Henshaw WD, Quinlan DJ (1997) Overture: an object oriented software system for solving partial differential equations in serial and parallel environments. In: Eighth conference on parallel processing for scientific computing. Society for Industrial and Applied Mathematics, Paper CP97
    Google Scholar
  20. Chandar D, Damodaran M (2008) Computational study of unsteady low Reynolds number airfoil aerodynamics on moving overlapping meshes. AIAA J 46(2):429–438
    Article Google Scholar
  21. Chandar D, Damodaran M (2010) Numerical study of the free flight characteristics of a flapping wing in low Reynolds numbers. J Aircr 47(1):141–150
    Article Google Scholar
  22. Chandar D, Damodaran M (2009) Computation of low Reynolds number flexible flapping wing aerodynamics on overlapping grids. AIAA 2009-1273, presented at the 47th AIAA aerospace sciences meeting and exhibit, Orlando, FL, USA, January 2009
  23. Pulliam TH (1984) Euler and thin layer Navier–Stokes codes: ARC2D, ARC3D. UTSI E02-4005-023-84. Computational fluid dynamics, University of Tennessee Space Institute
  24. Sankaran V, Sitaraman J, Wissink A, Datta A, Jayaraman B, Potsdam M, Mavriplis D, Yang Z, O’Brien D, Saberi H, Cheng R, Hariharan N, Strawn R (2010) Application of the Helios computational platform to rotorcraft flowfields. In: 48th AIAA aerospace sciences meeting and exhibit, AIAA-2010-1230, Orlando, FL
    Google Scholar
  25. Soni K, Chandar DDJ, Sitaraman J (2011) Development of an overset grid computational fluid dynamics solver on graphical processing units. In: 49th AIAA aerospace sciences meeting and exhibit, AIAA-2011-1268, Orlando, FL
    Google Scholar
  26. Chandar D, Sitaraman J, Mavriplis D (2012) Dynamic overset grid computations for CFD applications on graphics processing units. Paper ICCFD7-12-2. In: Proceedings of the international conference on computational fluid dynamics, Big Island, Hawaii
    Google Scholar
  27. Kennedy CA, Carpenter MH, Lewis RM (1999) Low-storage, explicit Runge–Kutta schemes for the compressible Navier–Stokes equations. NASA/CR 1999-209349
  28. Henshaw WD (2011) Cgins reference manual: an overture solver for the incompressible Navier–Stokes equations on composite overlapping grids. Lawrence Livermore National Laboratory Report LLNL-SM-455871, 2011
  29. Crumpton PI, Moinier P, Giles MB (1997) An unstructured algorithm for high Reynolds number flows on highly stretched grids. In: Numerical methods in laminar and turbulent flow. Pineridge Press, Whiting, pp 561–572
    Google Scholar
  30. Chandar D, Sitaraman J, Mavriplis DJ (2012) On the integral constraint of the pressure Poisson equation for incompressible flows on an unstructured grid. Int J Comput Fluid Dyn. doi:10.1080/10618562.2012.723127
    MathSciNet Google Scholar
  31. NVIDIA GPUDirect Technology, Mellanox technologies white paper, http://www.mellanox.com/pdf/whitepapers/TB_GPU_Direct.pdf. Accessed 25 July 2012
  32. Jones KD, Dohring CM, Platzer MF (1998) Experimental and computational investigation of the Knoller–Betz effect. AIAA J 36(7):1240–1246
    Article Google Scholar
  33. Tuncer IH, Kaya M (2003) Thrust generation caused by flapping airfoils in a biplane configuration. J Aircr 40:509–515
    Google Scholar
  34. Chandar D, Sitaraman J, Mavriplis DJ (2013) Overset grid based computations for rotary wing flows on GPU architectures. Presented at the American helicopter society forum, AHS69, May 2013

Download references