13 citations · 25 across the 10 of their papers we have counts for
Showing 2024 · cs.DCShow all
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cs.DC2024
NeurLZ: An Online Neural Learning-Based Method to Enhance Scientific Lossy Compression
Wenqi Jia, Zhewen Hu, Youyuan Liu +10
Large-scale scientific simulations generate massive datasets, posing challenges for storage and I/O. Traditional lossy compression struggles to advance more in balancing compressio…
cs.DC2024
A High-Quality Workflow for Multi-Resolution Scientific Data Reduction and Visualization
Daoce Wang, Pascal Grosset, Jesus Pulido +8
Multi-resolution methods such as Adaptive Mesh Refinement (AMR) can enhance storage efficiency for HPC applications generating vast volumes of data. However, their applicability is…
cs.DC2024★ 2 cited
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…