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6. If you mention SZ in your paper, please use at least two references as follows because they both address the main design in SZ.the following two references.

  • SZ 0.1-0.15: Sheng Di, Franck Cappello, "Fast Error-bounded Lossy HPC Data Compression with SZ," in International Parallel and Distributed Processing Symposium (IEEE/ACM IPDPS 2016), 2016.
  • SZ 1.0-1.4.13: Dingwen Tao, Sheng Di, Franck Cappello, "A Novel Algorithm for Significantly Improving Lossy Compression of Scientific Data Sets, " in International Parallel and Distributed Processing Symposium (IEEE/ACM IPDPS 2017), Orlando, Florida, 2017.
  • SZ 2.0+: Xin Liang, Sheng Di, Dingwen Tao, Zizhong Chen, Franck Cappello, "Error-Controlled Lossy Compression Optimized for High Compression Ratios of Scientific Datasets", in IEEE Bigdata2018, 2018.
  • As for the point-wise relative error bound mode (i.e., PW_REL), our CLUSTER18 paper describes the key design: Xin Liang, Sheng Di, Dingwen Tao, Zizhong Chen, Franck Cappello, "Efficient Transformation Scheme for Lossy Data Compression with Point-wise Relative Error Bound", in IEEE CLUSTER 2018. (best paper)

7. Download

Version SZ 2.0.2.0

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