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20242026
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cs.DC2026

pMSz: A Distributed Parallel Algorithm for Correcting Extrema and Morse Smale Segmentations in Lossy Compression

Yuxiao Li, Mingze Xia, Xin Liang +7

Lossy compression, widely used by scientists to reduce data from simulations, experiments, and observations, can distort features of interest even under bounded error. Such distort…

cs.DC2026

FFCz: Fast Fourier Correction for Spectrum-Preserving Lossy Compression of Scientific Data

Congrong Ren, Robert Underwood, Sheng Di +5

This paper introduces a novel technique to preserve spectral features in lossy compression based on a novel fast Fourier correction algorithm\added{ for regular-grid data}. Preserv…

cs.DC2025

To Compress or Not To Compress: Energy Trade-Offs and Benefits of Lossy Compressed I/O

Grant Wilkins, Sheng Di, Jon C. Calhoun +2

Modern scientific simulations generate massive volumes of data, creating significant challenges for I/O and storage systems. Error-bounded lossy compression (EBLC) offers a solutio…

cs.DC2025

A Survey on Error-Bounded Lossy Compression for Scientific Datasets

Sheng Di, Jinyang Liu, Kai Zhao +23

Error-bounded lossy compression has been effective in significantly reducing the data storage/transfer burden while preserving the reconstructed data fidelity very well. Many error…

cs.DC2024

LCP: Enhancing Scientific Data Management with Lossy Compression for Particles

Longtao Zhang, Ruoyu Li, Congrong Ren +10

Many scientific applications opt for particles instead of meshes as their basic primitives to model complex systems composed of billions of discrete entities. Such applications spa…

cs.DC2024

HoSZp: An Efficient Homomorphic Error-bounded Lossy Compressor for Scientific Data

Tripti Agarwal, Sheng Di, Jiajun Huang +7

Error-bounded lossy compression has been a critical technique to significantly reduce the sheer amounts of simulation datasets for high-performance computing (HPC) scientific appli…