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The Journal of Supercomputing

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01-04-2013

Parallelization of the FMM on distributed-memory GPGPU systems for acoustic-scattering prediction

Authors: Miguel López-Portugués, Jesús A. López-Fernández, José Ranilla, R. G. Ayestarán, Fernando Las-Heras

Published in: The Journal of Supercomputing | Issue 1/2013

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Abstract

In this work, we carry out the parallelization of the single level Fast Multipole Method (FMM) for solving acoustic-scattering problems (using the Helmholtz equation) on distributed-memory GPGPU systems. With the aim of enlarging the scope of feasible simulations, the presented solution combines the techniques developed for our distributed-memory CPU solver with our shared-memory GPGPU solver. The performance of the developed solution is proved using two different GPGPU clusters: the first one consists of two workstations with NVIDIA GTX 480 GPUs linked by a Gigabit Ethernet network, and the second one comprises four nodes with NVIDIA Tesla M2090 GPUs linked by an Infiniband network.

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Title: Parallelization of the FMM on distributed-memory GPGPU systems for acoustic-scattering prediction
Authors: Miguel López-Portugués
Jesús A. López-Fernández
José Ranilla
R. G. Ayestarán
Fernando Las-Heras
Publication date: 01-04-2013
Publisher: Springer US
Published in: The Journal of Supercomputing / Issue 1/2013
Print ISSN: 0920-8542
Electronic ISSN: 1573-0484
DOI: https://doi.org/10.1007/s11227-012-0786-6

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