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	Efficient unsteady flow visualization with high-order access dependencies
	Zhang, Jiang ; Guo, Hanqi ; Yuan, Xiaoru
	2016
英文摘要	We present a novel high-order access dependencies-based model for efficient pathline computation in unsteady flow visualization. By taking longer access sequences into account to model more sophisticated data access patterns in particle tracing, our method greatly improves the accuracy and reliability in data access prediction. In our work, high-order access dependencies are calculated by tracing uniformly seeded pathlines in both forward and backward directions in a preprocessing stage. The effectiveness of our approach is demonstrated through a parallel particle tracing framework with high-order data prefetching. Results show that our method achieves higher data locality and hence improves the efficiency of pathline computation. ? 2016 IEEE.; EI; 80-87; 2016-May
语种	英语
出处	9th IEEE Pacific Visualization Symposium, PacificVis 2016
DOI标识	10.1109/PACIFICVIS.2016.7465254
内容类型	其他
源URL	[http://ir.pku.edu.cn/handle/20.500.11897/436178]
专题	信息科学技术学院
推荐引用方式 GB/T 7714	Zhang, Jiang,Guo, Hanqi,Yuan, Xiaoru. Efficient unsteady flow visualization with high-order access dependencies. 2016-01-01.

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