Podcast: How the EZ Project is Providing Exascale with Lossy Compression for Scientific Data

In this podcast, Franck Cappello from Argonne describes EZ, an effort to effort to compress and reduce the enormous scientific data sets that some of the ECP applications are producing. "There are different approaches to solving the problem. One is called lossless compression, a data-reduction technique that doesn't lose any information or introduce any noise. The drawback with lossless compression, however, is that user-entry floating-point values are very difficult to compress: the best effort reduces data by a factor of two. In contrast, ECP applications seek a data reduction factor of 10, 30, or even more."

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