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    Xu Pingjun, Shen Weichao, and Liao Li. Multiresolution Data Organization and Interactive Visualization in JaVis[J]. Journal of Computer Research and Development, 2010, 47(6): 996-1004.
    Citation: Xu Pingjun, Shen Weichao, and Liao Li. Multiresolution Data Organization and Interactive Visualization in JaVis[J]. Journal of Computer Research and Development, 2010, 47(6): 996-1004.

    Multiresolution Data Organization and Interactive Visualization in JaVis

    • With the rapid development of high performance computer and technology, scientists can model complex physical phenomena at a scale and fidelity to answer some of the most important and difficult questions in science. The output from these simulations, however, is so voluminous and complex that advanced visualization technologies are necessary to interpret the calculated results. Even though visualization technology has progressed significantly in recent years, it is difficult to visualize and analyze terascale or much larger data interactively to full extent. Interactive speed of dealing with large data embarrasses the operation of data visualization and analysis severely. How to reduce I/O data size and improve interactive speed are the main challenges in developing visualization system designed for large scale data analysis. Many studies indicate that multiresolution technique is an important and feasible means of addressing these problems. In this paper the authors present some new multiresolution techniques implemented in JaVis, a large-scale data analysis and visualization system, to accelerate interactive visualization of large dataset. The key techniques developed are summarized as follows: multiresolution data organization, multiresolution data operator plugin implementation and multi-level data switch. Also demonstrated are the efficiency and robustness of the interactive visualization techniques with some real physical datasets.
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