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Petascale Application of a Coupled CPU-GPU Algorithm for Simulation and Analysis of Multiphase Flow Solutions in Porous Medium Systems

James E. McClure, Hao Wang, Jan F. Prins, Cass T. Miller, Wu-chun Feng
Advanced Research Computing, Virginia Tech, Blacksburg, Virginia
IEEE International Parallel and Distributed Processing Symposium, 2014

@InProceedings{mcclure-multiphase-flow-ipdps14,

   author={E. McClure, James and Wang, Hao and F. Prins, Jan and T. Miller, Cass and Feng, Wu-chun},

   title={Petascale Application of a Coupled CPU-GPU Algorithm for Simulation and Analysis of Multiphase Flow Solutions in Porous Medium Systems},

   booktitle={IEEE International Parallel and Distributed Processing Symposium},

   address={Phoenix, Arizona},

   month={May},

   year={2014}

}

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Large-scale simulation can provide a wide range of information needed to develop and validate theoretical models for multiphase flow in porous medium systems. In this paper, we consider a coupled solution in which a multiphase flow simulator is coupled to an analysis approach used to extract the interfacial geometries as the flow evolves. This has been implemented using MPI to target heterogeneous nodes equipped with GPUs. The GPUs evolve the multiphase flow solution using the lattice Boltzmann method while the CPUs compute upscaled measures of the morphology and topology of the phase distributions and their rate of evolution. Our approach is demonstrated to scale to 4,096 GPUs and 65,536 CPU cores to achieve a maximum performance of 244,754 million-lattice-node updates per second (MLUPS) in double precision execution on Titan. In turn, this approach increases the size of systems that can be considered by an order of magnitude compared with previous work and enables detailed in situ tracking of averaged flow quantities at temporal resolutions that were previously impossible. Furthermore, it virtually eliminates the need for post-processing and intensive I/O and mitigates the potential loss of data associated with node failures.
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