cuIBM — A GPU-accelerated Immersed Boundary Method

Simon K Layton, Anush Krishnan, Lorena A. Barba
Department of Mechanical Engineering, Boston University, Boston, MA, 02215, USA
ParCFD 2011, arXiv:1109.3524v1 [cs.CE] (16 Sep 2011)


   author={Layton}, S.~K and {Krishnan}, A. and {Barba}, L.~A.},

   title={"{cuIBM — A GPU-accelerated Immersed Boundary Method}"},

   journal={ArXiv e-prints},




   keywords={Computer Science – Computational Engineering, Finance, and Science},




   adsnote={Provided by the SAO/NASA Astrophysics Data System}


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A projection-based immersed boundary method is dominated by sparse linear algebra routines. Using the open-source Cusp library, we observe a speedup (with respect to a single CPU core) which reflects the constraints of a bandwidth-dominated problem on the GPU. Nevertheless, GPUs offer the capacity to solve large problems on commodity hardware. This work includes validation and a convergence study of the GPU-accelerated IBM, and various optimizations.
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