Hybrid MPI-Thread Parallelization of the Fast Multipole Method
COULAUD, Olivier
Algorithms and high performance computing for grand challenge applications [SCALAPPLIX]
Algorithms and high performance computing for grand challenge applications [SCALAPPLIX]
FORTIN, Pierre
Algorithms and high performance computing for grand challenge applications [SCALAPPLIX]
Algorithms and high performance computing for grand challenge applications [SCALAPPLIX]
ROMAN, Jean
Algorithms and high performance computing for grand challenge applications [SCALAPPLIX]
Laboratoire Bordelais de Recherche en Informatique [LaBRI]
Algorithms and high performance computing for grand challenge applications [SCALAPPLIX]
Laboratoire Bordelais de Recherche en Informatique [LaBRI]
COULAUD, Olivier
Algorithms and high performance computing for grand challenge applications [SCALAPPLIX]
Algorithms and high performance computing for grand challenge applications [SCALAPPLIX]
FORTIN, Pierre
Algorithms and high performance computing for grand challenge applications [SCALAPPLIX]
Algorithms and high performance computing for grand challenge applications [SCALAPPLIX]
ROMAN, Jean
Algorithms and high performance computing for grand challenge applications [SCALAPPLIX]
Laboratoire Bordelais de Recherche en Informatique [LaBRI]
< Reduce
Algorithms and high performance computing for grand challenge applications [SCALAPPLIX]
Laboratoire Bordelais de Recherche en Informatique [LaBRI]
Language
en
Communication dans un congrès
This item was published in
ISPDC 2007, 6th International Symposium on Parallel and Distributed Computing, 2007-07-05, Hagenberg, Austria. 2007-07-05p. 391-398
English Abstract
We present in this paper multi-thread and multi-process parallelizations of the Fast Multipole Method (FMM) for Laplace equation, for uniform and non uniform distributions. These parallelizations apply to the original FMM ...Read more >
We present in this paper multi-thread and multi-process parallelizations of the Fast Multipole Method (FMM) for Laplace equation, for uniform and non uniform distributions. These parallelizations apply to the original FMM formulation and to our new matrix formulation with BLAS (Basic Linear Algebra Subprograms) routines. Differences between the multi-thread and the multi-process versions are detailed, and a hybrid MPI-thread approach enables to gain parallel efficiency and memory scalability over the pure MPI one on clusters of SMP nodes. On 128 processors, we obtain 85% (respectively 75%) parallel efficiency for uniform (respectively non uniform) distributions with up to 100 million particles.Read less <
English Keywords
Fast Multipole Methods
parallel algorithmics
MPI
POSIX threads
hybrid MPI-thread programming
BLAS routines
Origin
Hal imported