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High Performance Flow Field Visualization with High-Order Access Dependencies
Zhang, Jiang ; Guo, Hanqi ; Yuan, Xiaoru
2015
关键词Flow visualization High-Order Data prefetching
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.; CPCI-S(ISTP); jiang.zhang@pku.edu.cn; hguo@anl.gov; xiaoru.yuan@pku.edu.cn; 165-166
语种英语
出处2015 IEEE Scientific Visualization Conference
内容类型其他
源URL[http://ir.pku.edu.cn/handle/20.500.11897/450252]  
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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