Parallelization of Flow Calculations for a Passenger Airplane Benchmark Model on a Multi-GPU Server
Authors: 
Liu Yang, Jian YangAuthors Info & Claims
Pages 7 - 11
Abstract
In this paper, a GPU-based explicit Runge-Kutta flow solver is extended with Message Passing Interface (MPI) parallelization. The data at MPI boundaries are first packed on the Graphics Processing Unit (GPU) memory and then transferred to the Central Processing Unit (CPU) memory. Subsequently, the data are exchanged between MPI processes. Finally, the exchanged data are transferred back to the GPU memory. Flow simulations of a passenger airplane benchmark model CHN-T1 are performed on various numbers of GPUs. The results of strong and weak scaling tests on an 8-GPU server show that the current implementation is able to distribute over multiple GPUs without a significant degradation in performance.
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Index Terms
- Parallelization of Flow Calculations for a Passenger Airplane Benchmark Model on a Multi-GPU Server
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Published In
June 2024
161 pages
ISBN:9798400716904
DOI:10.1145/3675018
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Published: 04 August 2024
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HP3C 2024
HP3C 2024: 2024 8th International Conference on High Performance Compilation, Computing and Communications
June 7 - 9, 2024
Guangzhou, China
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