2 citations · 2 across the 7 of their papers we have counts for
5 papers · 1 filter
FaCTz: Fast Critical-Point and Topology-Aware GPU Compression for Scientific Vector Fields
Mingze Xia, Yuxiao Li, Sheng Di +6
Error-bounded lossy compression is essential for storing and transferring the vector-field data produced by large-scale scientific simulations. Although it enforces a user-specifie…
EXaCTz: Guaranteed Extremum Graph and Contour Tree Preservation for Distributed- and GPU-Parallel Lossy Compression
Yuxiao Li, Mingze Xia, Xin Liang +2
This paper introduces EXaCTz, a parallel algorithm that corrects lossy-compressed scalar field data to preserve extremum graphs and contour trees concurrently. While error-bounded…
TopoSZp: Lightweight Topology-Aware Error-controlled Compression for Scientific Data
Tripti Agarwal, Sheng Di, Xin Liang +5
Error-bounded lossy compression is essential for managing the massive data volumes produced by large-scale HPC simulations. While state-of-the-art compressors such as SZ and ZFP pr…
pMSz: A Distributed Parallel Algorithm for Correcting Extrema and Morse Smale Segmentations in Lossy Compression
Yuxiao Li, Mingze Xia, Xin Liang +7
Lossy compression, widely used by scientists to reduce data from simulations, experiments, and observations, can distort features of interest even under bounded error. Such distort…
MSz: An Efficient Parallel Algorithm for Correcting Morse-Smale Segmentations in Error-Bounded Lossy Compressors
Yuxiao Li, Xin Liang, Bei Wang +3
This research explores a novel paradigm for preserving topological segmentations in existing error-bounded lossy compressors. Today's lossy compressors rarely consider preserving t…