Scientific visualization and HPC applications: Minisymposium abstract

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Abstract

High Performance Computing (HPC) produces enormous amounts of data. This simple truth has been the perennial bane of the HPC user and there is no sign of the problem going away. The results of the computational process are often large data sets in the form of molecular structures and property fields, fluid density and velocity fields, particle positions and momenta or any of a diverse host of other types all sharing the single property that they are large and so difficult to interpret. In the case of many computational methods it is, in addition, often useful to retain state information, perhaps as large as the final output, from each step of the computational process for a post-mortem analysis of the optimization or for computational steering. The size of the data produced often scales with the problem size, the problem size typically increases with the available computational power and so the ever-growing improvement in computational power is likely to continue to make this problem more difficult as time progresses. To aid in the analysis of complex multidimensional, multivariate and often time-varying data, visualization systems exploiting computer graphics and complex interaction mechanisms are becoming required tools but the size of these data sets presents unique problems in the efficient processing and graphical rendering of representations of the data which will permit their interpretation. This mini-symposium brings together researchers and developers from a range of disciplines, both experts in the scientific fields which produce the data for interpretation and experts in the techniques which are being used to provide the visualization tools for this work. We hope this diverse panel will stimulate an interesting and informative discussion with the audience, giving some ideas about how visualization is likely to change in the future and how visualization systems need to change to meet the needs of the user community. © Springer-Verlag Berlin Heidelberg 2007.

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APA

Cooper, M., & Ynnerman, A. (2007). Scientific visualization and HPC applications: Minisymposium abstract. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 4699 LNCS, p. 658). Springer Verlag. https://doi.org/10.1007/978-3-540-75755-9_79

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