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Error-bounded lossy compression has been identified as a promising solutionfor significantly reducing scientific data volumes upon users' requirements ondata distortion. For the existing scientific error-bounded lossy compressors,some of them (such as SPERR and FAZ) can reach fairly high compression ratiosand some others (such as SZx, SZ, and ZFP) feature high compression speeds, butthey rarely exhibit both high ratio and high speed meanwhile. In this paper, wepropose HPEZ with newly-designed interpolations and quality-metric-drivenauto-tuning, which features significantly improved compression quality upon theexisting high-performance compressors, meanwhile being exceedingly faster thanhigh-ratio compressors. The key contributions lie in the following points: (1)We develop a series of advanced techniques such as interpolation re-ordering,multi-dimensional interpolation, and natural cubic splines to significantlyimprove compression qualities with interpolation-based data prediction. (2) Theauto-tuning module in HPEZ has been carefully designed with novel strategies,including but not limited to block-wise interpolation tuning, dynamic dimensionfreezing, and Lorenzo tuning. (3) We thoroughly evaluate HPEZ compared withmany other compressors on six real-world scientific datasets. Experiments showthat HPEZ outperforms other high-performance error-bounded lossy compressors incompression ratio by up to 140% under the same error bound, and by up to 360%under the same PSNR. In parallel data transfer experiments on the distributeddatabase, HPEZ achieves a significant performance gain with up to 40% time costreduction over the second-best compressor.

High-performance Effective Scientific Error-bounded Lossy Compression with Auto-tuned Multi-component Interpolation