A GPU accelerated Red-Black SOR algorithm for computational fluid dynamics problems
文献类型：会议论文
| 作者 | Liu JT(刘继棠) ; Ma ZS(马照松); Li SH(李世海); Zhao Y(赵颖)
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| 出版日期 | 2011 |
| 会议名称 | International Conference on Key Engineering Materials and Computer Science (KEMCS 2011) |
| 会议日期 | AUG 06-07, 2011 |
| 会议地点 | Dalian, PEOPLES R CHINA |
| 通讯作者邮箱 | ljt_1987624@163.com |
| 关键词 | (Computational Fluid Dynamics) CFD (Graphics Processing Units) GPU Red-Black SOR Memory hierarchy Shared Memory Allocation |
| 卷号 | 320 |
| 页码 | 335-340 |
| 通讯作者 | Liu, JT (通讯作者) Chinese Acad Sci, Institte Mech, Beijing 100190, Peoples R China. |
| 中文摘要 | GPUs are high performance co-processors of CPU for scientific computing including CFD. We present an optimistic shared memory allocation strategy to solve 2D CFD problems using Red-Black SOR method on GPU with CUDA (Compute Unified Device Architecture). Lid-driven results are compared with the benchmark data. The speed up ratio of same problem size by using NVDIA GTX480 and Intel Core-Dual 3.0GHz processor is discussed, the performance of GPU is 120 times faster than the sequential code on CPU with the problem size of 756×756. Based on this work, we conclude that using the memory hierarchy properly has a key role in improving the computational performance of GPU. |
| 收录类别 | CPCI ; EI |
| 产权排序 | 1 Institute of Mechanics, Chinese Academy of Sciences, Beijing 100190, China |
| 会议网址 | http://www.scientific.net/AMR.320.335 |
| 会议录 | KEY ENGINEERING MATERIALS AND COMPUTER SCIENCE
 |
| 会议录出版者 | TRANS TECH PUBLICATIONS LTD, LAUBLSRUTISTR 24, CH-8717 STAFA-ZURICH, SWITZERLAND |
| 语种 | 英语 |
| ISSN号 | 1022-6680 |
| ISBN号 | 978-3-03785-211-8 |
| 源URL | [http://dspace.imech.ac.cn/handle/311007/46856]  |
| 专题 | 力学研究所_环境力学重点实验室(2009-2011) |
| 推荐引用方式 GB/T 7714 | Liu JT,Ma ZS,Li SH,et al. A GPU accelerated Red-Black SOR algorithm for computational fluid dynamics problems[C]. 见:International Conference on Key Engineering Materials and Computer Science (KEMCS 2011). Dalian, PEOPLES R CHINA. AUG 06-07, 2011.http://www.scientific.net/AMR.320.335. |
入库方式： OAI收割
来源：力学研究所
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