Abstract
We present adaptive coarsening, a multi-resolution lossy compression algorithm for scientific datasets. The algorithm provides guaranteed error bounds according to the user’s requirements for subsequent post-processing. We demonstrate compression factors of up to an order of magnitude with datasets coming from solutions to time-dependent partial differential equations in one and two dimensions.
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Shafaat, T.M., Baden, S.B. (2007). A Method of Adaptive Coarsening for Compressing Scientific Datasets. In: Kågström, B., Elmroth, E., Dongarra, J., Waśniewski, J. (eds) Applied Parallel Computing. State of the Art in Scientific Computing. PARA 2006. Lecture Notes in Computer Science, vol 4699. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-75755-9_94
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DOI: https://doi.org/10.1007/978-3-540-75755-9_94
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-75754-2
Online ISBN: 978-3-540-75755-9
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