Fast and Effective Lossy Compression Algorithms for Scientific
نویسندگان
چکیده
This paper focuses on developing effective and efficient algorithms for compressing scientific simulation data computed on structured and unstructured grids. A paradigm for lossy compression of this data is proposed in which the data computed on the grid is modeled as a graph, which gets decomposed into sets of vertices which satisfy a user defined error constraint ǫ. Each set of vertices is replaced by a constant value with reconstruction error bounded by ǫ. A comprehensive set of experiments is conducted by comparing these algorithms and other state-of-the-art scientific data compression methods. Over our benchmark suite, our methods obtained compression of 1% of the original size with average PSNR of 43.00 and 3% of the original size with average PSNR of 63.30. In addition, our schemes outperform other stateof-the-art lossy compression approaches and require on the average 25% of the space required by them for similar or better PSNR levels.
منابع مشابه
Fast and Effective Lossy Compression Algorithms for Scientific Datasets
This paper focuses on developing effective and efficient algorithms for compressing scientific simulation data computed on structured and unstructured grids. A paradigm for lossy compression of this data is proposed in which the data computed on the grid is modeled as a graph, which gets decomposed into sets of vertices which satisfy a user defined error constraint . Each set of vertices is rep...
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