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Issue No.01 - Jan. (2014 vol.25)
pp: 43-52
Eugenio Rustico , University of Catania, Catania
Giuseppe Bilotta , Istituto Nazionale di Geofisica e Vulcanologia - Osservatorio Etneo, Catania
Alexis Herault , Département Ingénierie Mathématique, Conservatoire National des Arts et Métiers, Paris
Ciro Del Negro , Istituto Nazionale di Geofisica e Vulcanologia - Osservatorio Etneo, Catania
Giovanni Gallo , University of Catania, Catania
ABSTRACT
We present a multi-GPU version of GPUSPH, a CUDA implementation of fluid-dynamics models based on the smoothed particle hydrodynamics (SPH) numerical method. The SPH is a well-known Lagrangian model for the simulation of free-surface fluid flows; it exposes a high degree of parallelism and has already been successfully ported to GPU. We extend the GPU-based simulator to run simulations on multiple GPUs simultaneously, to obtain a gain in speed and overcome the memory limitations of using a single device. The computational domain is spatially split with minimal overlapping and shared volume slices are updated at every iteration of the simulation. Data transfers are asynchronous with computations, thus completely covering the overhead introduced by slice exchange. A simple yet effective load balancing policy preserves the performance in case of unbalanced simulations due to asymmetric fluid topologies. The obtained speedup factor (up to 4.5x for 6 GPUs) closely follows the expected one (5x for 6 GPUs) and it is possible to run simulations with a higher number of particles than would fit on a single device. We use the Karp-Flatt metric to formally estimate the overall efficiency of the parallelization.
INDEX TERMS
Graphics processing units, Computational modeling, Kernel, Numerical models, Load modeling, Parallel processing, Load management,HPC, GPU, multi-GPU, SPH, CUDA, fluid dynamics, numerical simulations, load balancing, parallel computing
CITATION
Eugenio Rustico, Giuseppe Bilotta, Alexis Herault, Ciro Del Negro, Giovanni Gallo, "Advances in Multi-GPU Smoothed Particle Hydrodynamics Simulations", IEEE Transactions on Parallel & Distributed Systems, vol.25, no. 1, pp. 43-52, Jan. 2014, doi:10.1109/TPDS.2012.340
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