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	High performance flow field visualization with high-order access dependencies
	Zhang, Jiang ; Guo, Hanqi ; Yuan, Xiaoru
	2015
英文摘要	We present a novel model based on high-order access dependencies for high performance pathline computation in flow field. The high-order access dependencies are defined as transition probabilities from one data block to other blocks based on a few historical data accesses. Compared with existing methods which employed first-order access dependencies, our approach takes the advantages of high order access dependencies with higher accuracy and reliability in data access prediction. In our work, high-order access dependencies are calculated by tracing densely-seeded pathlines. The efficiency of our proposed approach is demonstrated through a parallel particle tracing framework with high-order data prefetching. Results show that our method can achieve higher data locality than the first-order access dependencies based method, thereby reducing the I/O requests and improving the efficiency of pathline computation in various applications. ? 2015 IEEE.; EI; 165-166
语种	英语
出处	IEEE Scientific Visualization Conference, SciVis 2015
DOI标识	10.1109/SciVis.2015.7429515
内容类型	其他
源URL	[http://ir.pku.edu.cn/handle/20.500.11897/436231]
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. High performance flow field visualization with high-order access dependencies. 2015-01-01.

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