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We developed the error-bounded HPC data compressor, by proposing a novel HPC data compression method that works very effectively on compressing large-scale HPC data sets.

The compression method starts by linearizing multi-dimensional snapshot data. The key idea is to fit/predict the successive data points with the bestfit selection of curve fitting models. The data that can be predicted precisely will be replaced by the code of the corresponding curve-fitting model. As for the unpredictable data that cannot be approximated by curve-fitting models, we perform an inoptimized lossy compression via a binary representation analysis.The key features of SZ are listed below. 

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6. Download

Version SZ 1.3

-->>> Code download <<<--

(Contact: disheng222@gmail.com or sdi1@anl.gov)

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