Multi-GPU Scaling of a Conservative Weakly Compressible Solver for Large-Scale Two-Phase Flow Simulation

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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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Yang, K., & Aoki, T. (2023). Multi-GPU Scaling of a Conservative Weakly Compressible Solver for Large-Scale Two-Phase Flow Simulation. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 13798 LNCS, pp. 16–27). Springer Science and Business Media Deutschland GmbH. https://doi.org/10.1007/978-3-031-29927-8_2

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