98 citations · 99 across the 2 of their papers we have counts for
2 papers
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…