A parallel algebraic multigrid solver on graphics processing units

  • Authors:
  • Gundolf Haase;Manfred Liebmann;Craig C. Douglas;Gernot Plank

  • Affiliations:
  • Institute for Mathematics and Scientific Computing, University of Graz;Institute for Mathematics and Scientific Computing, University of Graz;Department of Mathematics, University of Wyoming;Computing Laboratory, Oxford University

  • Venue:
  • HPCA'09 Proceedings of the Second international conference on High Performance Computing and Applications
  • Year:
  • 2009

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Abstract

The paper presents a multi-GPU implementation of the preconditioned conjugate gradient algorithm with an algebraic multigrid preconditioner (PCG-AMG) for an elliptic model problem on a 3D unstructured grid. An efficient parallel sparse matrix-vector multiplication scheme underlying the PCG-AMG algorithm is presented for the many-core GPU architecture. A performance comparison of the parallel solver shows that a singe Nvidia Tesla C1060 GPU board delivers the performance of a sixteen node Infiniband cluster and a multi-GPU configuration with eight GPUs is about 100 times faster than a typical server CPU core.