In-situ Visualization for Peta-scale Scientific Computation
Shan Guihua, Tian Dong, Xie Maojin, Liu Jun, Wang Yang, and Chi Xuebin
(Supercomputing Center, Computer Network Information Center, Chinese Academy of Sciences, Beijing 100192)
Scientific visualization is indispensable in high performance computing for data analysis. Computing capacity provided by Peta-scale supercomputer enables scientists to research much more complex model and to do much larger scaled simulation, which produce huge complex time-vary data at TB/PB scale or EB scale. Due to the limit of I/O width and storage capacity, traditional visualization mode is unable to process such huge data. In-situ visualization combines simulation and visualization computation together, by which the data is directly processed in the exact computer node by rendering in an image or feature extraction. So the data needed to transfer or store is largely reduced. In-situ visualization is possibly the most efficient way to deal with the data produced by Peta-scale computation. In this paper, the related work on in-situ visualization, including in-situ data organization and compression, in-situ feature extraction and tracing, in-situ rendering, is summarized. At last, future work of this research topic is also discussed.