6 papers
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…
Preserving Discrete Morse-Smale Complexes in Error-Bounded Lossy Compression
Yuxiao Li, Mingze Xia, Xin Liang +2
Scientific applications are generating unprecedented volumes of data that overwhelm storage and transmission systems, posing significant challenges for the design of data managemen…
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 concurrently preserves extremum graphs and contour trees in lossy-compressed scalar field data. While error-bounded lossy co…
Time-varying Vector Field Compression with Preserved Critical Point Trajectories
Mingze Xia, Yuxiao Li, Pu Jiao +3
Scientific simulations and observations are producing vast amounts of time-varying vector field data, making it hard to store them for archival purposes and transmit them for analy…
Mitigating Artifacts in Pre-quantization Based Scientific Data Compressors with Quantization-aware Interpolation
Pu Jiao, Sheng Di, Jiannan Tian +5
Error-bounded lossy compression has been regarded as a promising way to address the ever-increasing amount of scientific data in today's high-performance computing systems. Pre-qua…
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…