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An Efficient Implementation of Entropic Lattice Boltzmann Method in a Hybrid CPU-GPU Computing Environment

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Parallel Computational Fluid Dynamics (ParCFD 2013)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 405))

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Abstract

In the high performance computing market, CPU-GPU hybrid computing is gradually becoming the tendency. Entropic Lattice Boltzmann method(ELBM) parallelization, like many parallel algorithms in the field of rapid scientific and engineering computing, has given rise to much attention for applications of computational fluid dynamics. This paper presents an efficient implementation of ELBM for a D3Q19 lattice Boltzmann flow simulation in a hybrid CPU-GPU computing environment, which is consisted of AMD multi-core CPU with NVIDIA graphics processors unit (GPU). To overcome the GPU memory size limitation and communication overhead, we propose a set of techniques that can be used to develop efficient ELBM algorithms for the hybrid system. Considering that the respective contributions of CPU versus GPU and the lattice scale of application, the optimal load balancing model is built. These approaches result in an efficient implementation with balanced use of multi-core processor and a graphics processor based on software framework OpenMP and CUDA. Finally, we show that the comparison of performance results using both CPU and GPU with using either a CPU core or a GPU.

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Author information

Authors and Affiliations

  1. College of Information Science and Engineering, Hunan University, Changsha, 410082, China

    Yu Ye & Yan Wang

  2. National Supercomputing Center of Changsha, Hunan University Office, Changsha, 410082, China

    Peng Chi

Authors
  1. Yu Ye
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  2. Peng Chi
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  3. Yan Wang
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Editor information

Editors and Affiliations

  1. College of Information Science and Engineering, Hunan University, 410082, Changsha, China

    Kenli Li

  2. College of Information Science and Engineering, Hunan University, #2, South Lushan Road, Yuelu District, 410082, Changsha, China

    Zheng Xiao  & Jiayi Du  & 

  3. College of Information Science and Engineering, Northeastern University, 110004, Shenyang, China

    Yan Wang

  4. Hunan University, State University of New York at New Paltz,, 12561, New Paltz, NY, USA

    Keqin Li

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Ye, Y., Chi, P., Wang, Y. (2014). An Efficient Implementation of Entropic Lattice Boltzmann Method in a Hybrid CPU-GPU Computing Environment . In: Li, K., Xiao, Z., Wang, Y., Du, J., Li, K. (eds) Parallel Computational Fluid Dynamics. ParCFD 2013. Communications in Computer and Information Science, vol 405. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-53962-6_12

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  • DOI: https://doi.org/10.1007/978-3-642-53962-6_12

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-53961-9

  • Online ISBN: 978-3-642-53962-6

  • eBook Packages: Computer ScienceComputer Science (R0)

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