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Using LAMA for efficient AMG on hybrid clusters

Computer Science - Research and Development volume 28, pages 211–220 (2013)Cite this article

Abstract

In this paper, we describe the implementation of an AMG solver for a hybrid cluster that exploits distributed and shared memory parallelization and uses the available GPU accelerators on each node. This solver has been written by using LAMA (Library for Accelerated Math Applications). This library does not only provide an easy-to-use framework for solvers that might run on different devices with different matrix formats, but also comes with features to optimize and hide communication and memory transfers between CPUs and GPUs. These features are explained and their impact on the efficiency of the AMG solver is shown in this paper. The benchmark results show that an efficient use of hybrid clusters is even possible for multi-level methods like AMG where fast solutions are needed on all levels for multiple problem sizes.

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Notes

  1. Open MPI 1.4.4. Tests with Intel MPI 4.0.2.003 showed a similar behavior.

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Authors and Affiliations

  1. Fraunhofer Institute for Algorithms and Scientific Computing SCAI, Schloss Birlinghoven, 53754, Sankt Augustin, Germany

    Jiri Kraus, Malte Förster, Thomas Brandes & Thomas Soddemann

Authors
  1. Jiri Kraus
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  2. Malte Förster
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  3. Thomas Brandes
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  4. Thomas Soddemann
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Corresponding author

Correspondence to Jiri Kraus.

Additional information

Granted by Fraunhofer, ITEA2 project H4H—BMBF 01|S10036H, BMBF project GASPI 01|H11007F.

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Kraus, J., Förster, M., Brandes, T. et al. Using LAMA for efficient AMG on hybrid clusters. Comput Sci Res Dev 28, 211–220 (2013). https://doi.org/10.1007/s00450-012-0223-3

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  • DOI: https://doi.org/10.1007/s00450-012-0223-3

Keywords

  • LAMA
  • AMG
  • Hybrid
  • MPI
  • Multithreading
  • CUDA
  • OpenMP
  • Heterogeneous