Abstract
To address the demand for high-performance large-scale simulation of two-phase flows, a momentum-conserving weakly compressible Navier-Stokes solver with multi-GPU computation is proposed. Following the principle of consistent transport, the phase-field model and VOF method are coupled with the momentum equation respectively. Combined with the evolving pressure projection method to damp the acoustic wave, this solver aims at a robust and accurate computation of violent two-phase flows with a high density ratio, while taking advantage of fully explicit time integration of the weakly compressible Navier-Stokes equations. Factors affecting the performance and scalability of multi-GPU computing, including domain partitioning, communication hiding, and solver choice, are discussed and analyzed. Finally, the conservative solver is used to simulate the Rayleigh-Taylor instability, milk crown and liquid jet atomization problems. Accurate and delicate evolution process of the two-phase interface is demonstrated.
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Acknowledgements
This research was partly supported by a Grant-in-Aid for Scientific Research (S) 19H05613, from the Japan Society for the Promotion of Science (JSPS), and Joint Usage/Research Center for Interdisciplinary Large-scale Information Infrastructures (JHPCN), jh200018 and jh210013, and High Performance Computing Infrastructure (HPCI) hp210129 projects, and JST SPRING, grant number JPMJSP2106. The authors thank the Global Scientific Information and Computing Center, Tokyo Institute of Technology for use of the computing resources of the TSUBAME 3.0 supercomputer and the Information Technology Center of Nagoya University for use of the computing resources of the Flow Type II supercomputer.
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Yang, K., Aoki, T. (2023). Multi-GPU Scaling of a Conservative Weakly Compressible Solver for Large-Scale Two-Phase Flow Simulation. In: Takizawa, H., Shen, H., Hanawa, T., Hyuk Park, J., Tian, H., Egawa, R. (eds) Parallel and Distributed Computing, Applications and Technologies. PDCAT 2022. Lecture Notes in Computer Science, vol 13798. Springer, Cham. https://doi.org/10.1007/978-3-031-29927-8_2
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