Lightweight GPU-Accelerated Parallel Processing of the SCHISM Model Using CUDA Fortran
文献类型：期刊论文
| 作者 | Zhang, Hongchun6,7,8; Cao, Qian5; Wu, Changmao4; Xu, Guangjun3; Liu, Yuli5; Feng, Xingru2; Jin, Meibing5; Dong, Changming1,5,7,8 |
| 刊名 | JOURNAL OF MARINE SCIENCE AND ENGINEERING
 |
| 出版日期 | 2025-03-26 |
| 卷号 | 13期号:4页码:15 |
| 关键词 | SCHISM model GPU acceleration lightweight computing |
| DOI | 10.3390/jmse13040662 |
| 通讯作者 | Dong, Changming(cmdong@nuist.edu.cn) |
| 英文摘要 | The SCHISM model is widely used for ocean numerical simulations, but its computational efficiency is constrained by the substantial resources it requires. To enhance its performance, this study develops GPU-SCHISM, a GPU-accelerated parallel version of SCHISM using the CUDA Fortran framework, and this study evaluates its acceleration performance on a single GPU-enabled node. The research results demonstrate that the GPU-SCHISM model achieves computational acceleration while maintaining high simulation accuracy. For small-scale classical experiments, a single GPU improves the efficiency of the Jacobi solver-identified as a performance hotspot-by 3.06 times and accelerates the overall model by 1.18 times. However, increasing the number of GPUs reduces the computational workload per GPU, which hinders further acceleration improvements. The GPU is particularly effective for performing higher-resolution calculations, leveraging its computational power. For large-scale experiments with 2,560,000 grid points, the GPU speedup ratio is 35.13; however, CPU has more advantages in small-scale calculations. Moreover, a comparison between CUDA and OpenACC-based GPU acceleration shows that CUDA outperforms OpenACC under all experimental conditions. This study marks the first successful GPU acceleration of the SCHISM model within the CUDA Fortran framework, laying a preliminary foundation for lightweight GPU-accelerated parallel processing in ocean numerical simulations. |
| WOS关键词 | WAVES |
| 资助项目 | National Key Research and Development Program of China ; Science & Technology Innovation Project of Laoshan Laboratory[LSKJ202400203] ; Southern Marine Science and Engineering Guangdong Laboratory (Zhuhai)[SML2022SP505] ; [2023YFC3008200] |
| WOS研究方向 | Engineering ; Oceanography |
| 语种 | 英语 |
| WOS记录号 | WOS:001475635300001 |
| 出版者 | MDPI |
| 源URL | [http://ir.qdio.ac.cn/handle/337002/201713]  |
| 专题 | 海洋研究所_海洋环流与波动重点实验室 |
| 通讯作者 | Dong, Changming |
| 作者单位 | 1.Southern Marine Sci & Engn Guangdong Lab Zhuhai, Zhuhai 519000, Peoples R China 2.Chinese Acad Sci, Key Lab Ocean Circulat & Waves, Inst Oceanol, Qingdao 266071, Peoples R China 3.Guangdong Ocean Univ, Sch Elect & Informat Engn, Zhanjiang 524088, Peoples R China 4.Chinese Acad Sci, Inst Software, Beijing 100190, Peoples R China 5.Nanjing Univ Informat Sci & Technol, Sch Marine Sci, Nanjing 210044, Peoples R China 6.Nanjing Univ Informat Sci & Technol, Sch Artificial Intelligence, Sch Future Technol, Nanjing 210044, Peoples R China 7.Int Geophys Fluid Res Ctr, Nanjing 210044, Peoples R China 8.State Key Lab Climate Syst Predict & Risk Manageme, Nanjing 210044, Peoples R China |
| 推荐引用方式 GB/T 7714 | Zhang, Hongchun,Cao, Qian,Wu, Changmao,et al. Lightweight GPU-Accelerated Parallel Processing of the SCHISM Model Using CUDA Fortran[J]. JOURNAL OF MARINE SCIENCE AND ENGINEERING,2025,13(4):15. |
| APA | Zhang, Hongchun.,Cao, Qian.,Wu, Changmao.,Xu, Guangjun.,Liu, Yuli.,...&Dong, Changming.(2025).Lightweight GPU-Accelerated Parallel Processing of the SCHISM Model Using CUDA Fortran.JOURNAL OF MARINE SCIENCE AND ENGINEERING,13(4),15. |
| MLA | Zhang, Hongchun,et al."Lightweight GPU-Accelerated Parallel Processing of the SCHISM Model Using CUDA Fortran".JOURNAL OF MARINE SCIENCE AND ENGINEERING 13.4(2025):15. |
入库方式： OAI收割
来源：海洋研究所
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