Evaluation on production-scale scientific datasets demonstrates that TZ achieves approximately 10 × higher compression ratios than state-of-the-art GPU compressors under the same error bound, while maintaining competitive, high-throughput performance.
Zhuoxun Yang, Ruoyu Li, A. Subrahmanya et al.· IEEE International Symposium...· 0 citations
This paper develops a novel framework that characterizes compressibility limits for scientific datasets under realistic tiling constraints, and is the first framework to rigorously characterize lossy compressibility limits for scientific datasets and compressor, moving beyond classical asymptotic 1D source models.
Sujata Sinha, Sheng Di, Vishwas Rao et al.· IEEE International Symposium...· 0 citations
The OPAL universal framework is the OPAL universal framework, an adaptive architecture that endows generic lossy compressors with on-demand retrieval capabilities, enabling flexible and progressive access across multiple spatial regions, resolutions, and precisions.
Longtao Zhang, Ruoyu Li, Zhuoxun Yang et al.· IEEE International Symposium...· 2 citations
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