3 papers
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…