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
Affiliations:
Departamento de Ingeniería Eléctrica, Electrónica, de Computadores y de Sistemas, Universidad de Oviedo, Gijón, Spain;Departamento de Ingeniería Eléctrica, Electrónica, de Computadores y de Sistemas, Universidad de Oviedo, Gijón, Spain;Departamento de Informática, Universidad de Oviedo, Gijón, Spain;Departamento de Ingeniería Eléctrica, Electrónica, de Computadores y de Sistemas, Universidad de Oviedo, Gijón, Spain;Departamento de Ingeniería Eléctrica, Electrónica, de Computadores y de Sistemas, Universidad de Oviedo, Gijón, Spain
Venue:
The Journal of Supercomputing
Year:
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.