| Citation: | WANG Zhi, WANG Xuede. Parallel DSMC algorithm for unstructured grids on CUDA platform[J]. Journal of Aerospace Power, 2022, X（X）：20250348 doi: 10.13224/j.cnki.jasp.20250348
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To enhance the computational efficiency of rarefied gas flow simulations, a compute unified device architecture (CUDA) platform-based parallel direct simulation Monte Carlo (DSMC) algorithm for unstructured grids was developed considering the adaptability of unstructured meshes to complex geometries. A general DSMC framework was established, and efficient grid-search and particle-tracking mechanisms were designed. The core computational modules—including flow-field initialization, particle movement, collision, sorting, and sampling—were parallelized and optimized on the CUDA platform. By rationally allocating threads and memory resources, issues such as data consistency, thread divergence, and load imbalance in graphics processing unit (GPU) computing were effectively addressed. The algorithm was validated through simulation of supersonic flow over a circular cylinder. Results showed that the overall speedup on a single GPU reached 52.5; the speedups of individual modules based on the grid-parallel strategy ranged from 24.7 to 53.7, while those based on the molecule-parallel strategy ranged from 47 to 68. The proposed algorithm significantly improved the parallel performance of DSMC simulations on unstructured grids, thus providing a feasible approach for efficient numerical simulation of high-Mach-number rarefied gas flows.
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