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ParallelDualSPHysics: Supporting Efficient Parallel Fluid Simulations Through MPI-enabled SPH Method

51ST INTERNATIONAL CONFERENCE ON PARALLEL PROCESSING, ICPP 2022(2022)

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摘要
Smoothed Particle Hydrodynamics (SPH) is a classical mesh-free particle method which has been successfully applied in the field of Computational Fluid Dynamics (CFD). Its advantages over traditional mesh-based methods have made it very popular in simulating problems involving large deformation and free-surface flow. The high computational cost of the SPH method has obstructed its vast application. A lot of research effort has been devoted to accelerating the SPH method using GPU and multi threading. However, developing efficient parallel SPH algorithms on modern high-performance computers (HPCs) remains significantly challenging, especially for simulating real-world engineering problems involving hundreds of millions of particles. In this paper, we proposed an MPI-enabled parallel SPH algorithm and developed the ParallelDualSPHysics1, an open-source software supporting efficient parallel fluid simulations. Based on an efficient domain decomposition scheme, the essential data structure and algorithms of DualSPHysics were refactored to build the parallel version. For collaborating with evenly distributed particles on a distributed-memory HPC system, the parallel particle interaction and particle update modules were introduced, which enabled the SPH solver to synchronize computations among multiple processors using MPI. In addition, the redesigned pre-processing and post-processing capabilities of the ParallelDualSPHysics supported the applications of this software in a wide range of areas. Real-life test cases with up to 120 million particles were simulated and analyzed on a modern HPC system. The results showed that the parallel efficiency of ParallelDualSPHysics exceeds 90 with up to 1024 CPU cores. It indicated that ParallelDualSPHysics has the potential for large-scale engineering applications.
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关键词
Smoothed Particle Hydrodynamics,Parallel Computing,ParallelDualSPHysics,Computational Fluid Dynamics
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