In Situ Visualization at Extreme Scale: Challenges and Opportunities

被引:94
|
作者
Ma, Kwan-Liu [1 ]
机构
[1] Univ Calif Davis, Davis, CA 95616 USA
基金
美国国家科学基金会;
关键词
Computer graphics; Scalability; Scientific discovery; Supercomputing; Visualization;
D O I
10.1109/MCG.2009.120
中图分类号
TP31 [计算机软件];
学科分类号
081202 ; 0835 ;
摘要
Scientific computing at the petascale level enables us to answer many difficult scientific questions, but the resulting data are too large to store and study directly with conventional postprocessing visualization tools. This problem will only become more severe as we reach exascale computing. A plausible, attractive solution involves processing data in situ with the simulation to reduce the data that must be transferred over networks and stored and to prepare the data for more cost-effective postprocessing visualization. The data could be reduced with compression, feature extraction, and visualization methods. This article discusses critical issues in realizing in situ visualization and data reduction and suggests important research directions. © 2009 IEEE.
引用
收藏
页码:14 / 19
页数:6
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