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20242026
most citedMGARD: A multigrid framework for high-performance, error-controlled data compression and refactoring

35 citations · 37 across the 6 of their papers we have counts for

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5 papers · 1 filter

cs.DC2026

Improving Progressive Compression with Adaptive Interpolation and Coefficient Decomposition

Wenbo Li, Xuan Wu, Qian Gong +6

Exascale simulations generate data far faster than it can be stored or analyzed, making efficient data reduction essential. Error-controlled lossy compression offers high compressi…

cs.DC2026

BlockMGARD: Accelerating Adaptive Scientific Data Reduction with Region-of-Interest Error Control on GPUs

Yanliang Li, Qian Gong, Qing Liu +5

The growing scale of scientific data makes lossy compression essential for reducing data volume under controllable error. Transformation-based compressors using multilevel decompos…

cs.DC2025

HP-MDR: High-performance and Portable Data Refactoring and Progressive Retrieval with Advanced GPUs

Yanliang Li, Wenbo Li, Qian Gong +5

Scientific applications produce vast amounts of data, posing grand challenges in the underlying data management and analytic tasks. Progressive compression is a promising way to ad…

cs.DC2025

HPDR: High-Performance Portable Scientific Data Reduction Framework

Jieyang Chen, Qian Gong, Yanliang Li +5

The rapid growth of scientific data is surpassing advancements in computing, creating challenges in storage, transfer, and analysis, particularly at the exascale. While data reduct…

cs.DC2024

Error-controlled Progressive Retrieval of Scientific Data under Derivable Quantities of Interest

Xuan Wu, Qian Gong, Jieyang Chen +4

The unprecedented amount of scientific data has introduced heavy pressure on the current data storage and transmission systems. Progressive compression has been proposed to mitigat…