98 citations · 99 across the 3 of their papers we have counts for
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cs.DC2022
SIMD Lossy Compression for Scientific Data
Griffin Dube, Jiannan Tian, Sheng Di +3
Modern HPC applications produce increasingly large amounts of data, which limits the performance of current extreme-scale systems. Data reduction techniques, such as lossy compress…
cs.DC2020★ 98 cited
cuSZ: An Efficient GPU-Based Error-Bounded Lossy Compression Framework for Scientific Data
Jiannan Tian, Sheng Di, Kai Zhao +8
Error-bounded lossy compression is a state-of-the-art data reduction technique for HPC applications because it not only significantly reduces storage overhead but also can retain h…
cs.DC2020★ 1 cited
FRaZ: A Generic High-Fidelity Fixed-Ratio Lossy Compression Framework for Scientific Floating-point Data
Robert Underwood, Sheng Di, Jon C. Calhoun +1
With ever-increasing volumes of scientific floating-point data being produced by high-performance computing applications, significantly reducing scientific floating-point data size…