Large scale water entry simulation with smoothed particle hydrodynamics on single- and multi-GPU systems

详细信息    查看全文

• 作者：Zhe Ji^a ; ^{jzzr@mail.nwpu.edu.cn" class="auth_mail" title="E-mail the corresponding author} ; Fei Xu^a ; ^{xufei@nwpu.edu.cn" class="auth_mail" title="E-mail the corresponding author} ; Akiyuki Takahashi^b ; ^{takahash@rs.noda.tus.ac.jp" class="auth_mail" title="E-mail the corresponding author} ; Yu Sun^a ; ^{yusun@mail.nwpu.edu.cn" class="auth_mail" title="E-mail the corresponding author}
• 关键词：SPH ; HPC ; GPU ; Multi-GPU ; Water entry
• 刊名：Computer Physics Communications
• 出版年：2016
• 出版时间：December 2016
• 年：2016
• 卷：209
• 期：Complete
• 页码：1-12
• 全文大小：2757 K

文摘

In this paper, a Weakly Compressible Smoothed Particle Hydrodynamics (WCSPH) framework is presented utilizing the parallel architecture of single- and multi-GPU (Graphic Processing Unit) platforms. The program is developed for water entry simulations where an efficient potential based contact force is introduced to tackle the interaction between fluid and solid particles. The single-GPU SPH scheme is implemented with a series of optimization to achieve high performance. To go beyond the memory limitation of single GPU, the scheme is further extended to multi-GPU platform basing on an improved 3D domain decomposition and inter-node data communication strategy. A typical benchmark test of wedge entry is investigated in varied dimensions and scales to validate the accuracy and efficiency of the program. The results of 2D and 3D benchmark tests manifest great consistency with the experiment and better accuracy than other numerical models. The performance of the single-GPU code is assessed by comparing with serial and parallel CPU codes. The improvement of the domain decomposition strategy is verified, and a study on the scalability and efficiency of the multi-GPU code is carried out as well by simulating tests with varied scales in different amount of GPUs. Lastly, the single- and multi-GPU codes are further compared with existing state-of-the-art SPH parallel frameworks for a comprehensive assessment.