Large scale satellite imagery simulations with physically based ray tracing on tianhe-1A supercomputer
文献类型：会议论文
| 作者 | Wu, Changmao (1) ; Zhang, Yunquan (2) ; Yang, Congli (1) |
| 出版日期 | 2014 |
| 会议名称 | 15th IEEE International Conference on High Performance Computing and Communications, HPCC 2013 and 11th IEEE/IFIP International Conference on Embedded and Ubiquitous Computing, EUC 2013 |
| 会议日期 | November 13, 2013 - November 15, 2013 |
| 会议地点 | Zhangjiajie, Hunan, China |
| 页码 | 549-556 |
| 通讯作者 | Zhang, Y.(changmaowu@gmail.com) |
| 中文摘要 | Developing highly scalable algorithms for satellite imagery simulations is becoming increasingly important as scientists inquire to understand the mechanism of satellite imagery before satellites are launched into orbit. Although physically based ray tracing technique for image rendering has produced some of the most realistic images to date, studies on satellite imagery simulations using this technique are still very less to be seen, due in large part to both the complex physical processes and the computational difficulties of the mathematical models. In this paper, we present a highly scalable physically based ray tracer for satellite imagery simulations. Our ray tracer is based on a Master-Worker-Receiver framework which can overcome the performance bottleneck of Master node. Besides, a novel sample distribution strategy is presented by the authors, aiming at removing high additional computation overhead which is introduced by the currently available pixel distribution strategy. Compared to the pixel distribution strategy, our sample distribution strategy drops the computation overhead by 0.25 to 4 times. We also discuss the issue with granularity of assignment partitioning for Inter-Nodes and Intra-Nodes, then a hybrid scheduling strategy combining static and dynamic scheduling strategies is presented. Experiments show that our physically based ray tracer almost reaches to a linear speedup by using 16,800 CPU cores on Tianhe-1A Supercomputer. Our ray tracer is more efficient and highly scalable. © 2013 IEEE. |
| 英文摘要 | Developing highly scalable algorithms for satellite imagery simulations is becoming increasingly important as scientists inquire to understand the mechanism of satellite imagery before satellites are launched into orbit. Although physically based ray tracing technique for image rendering has produced some of the most realistic images to date, studies on satellite imagery simulations using this technique are still very less to be seen, due in large part to both the complex physical processes and the computational difficulties of the mathematical models. In this paper, we present a highly scalable physically based ray tracer for satellite imagery simulations. Our ray tracer is based on a Master-Worker-Receiver framework which can overcome the performance bottleneck of Master node. Besides, a novel sample distribution strategy is presented by the authors, aiming at removing high additional computation overhead which is introduced by the currently available pixel distribution strategy. Compared to the pixel distribution strategy, our sample distribution strategy drops the computation overhead by 0.25 to 4 times. We also discuss the issue with granularity of assignment partitioning for Inter-Nodes and Intra-Nodes, then a hybrid scheduling strategy combining static and dynamic scheduling strategies is presented. Experiments show that our physically based ray tracer almost reaches to a linear speedup by using 16,800 CPU cores on Tianhe-1A Supercomputer. Our ray tracer is more efficient and highly scalable. © 2013 IEEE. |
| 收录类别 | EI |
| 会议录出版地 | IEEE Computer Society |
| 语种 | 英语 |
| ISBN号 | 9780769550886 |
| 源URL | [http://ir.iscas.ac.cn/handle/311060/16637]  |
| 专题 | 软件研究所_软件所图书馆_会议论文 |
| 推荐引用方式 GB/T 7714 | Wu, Changmao ,Zhang, Yunquan ,Yang, Congli . Large scale satellite imagery simulations with physically based ray tracing on tianhe-1A supercomputer[C]. 见:15th IEEE International Conference on High Performance Computing and Communications, HPCC 2013 and 11th IEEE/IFIP International Conference on Embedded and Ubiquitous Computing, EUC 2013. Zhangjiajie, Hunan, China. November 13, 2013 - November 15, 2013. |
入库方式： OAI收割
来源：软件研究所
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