2 citations · 2 across the 8 of their papers we have counts for
8 papers
FZ-VIS: A Visual Analytics Framework for Quantities-of-Interest-Aware Scientific Lossy Compression
Guoxi Liu, Yuxiao Li, Congrong Ren +6
Modern scientific simulations generate massive volumes of data, making lossy compression essential for efficient storage and transmission. However, preserving critical quantities o…
Preserving Clusters in Error-Bounded Lossy Compression of Scientific Particle Data
Congrong Ren, Sheng Di, Katrin Heitmann +2
Scientific particle simulations in cosmology, molecular dynamics, and fluid dynamics produce large-scale datasets whose storage, movement, and analysis increasingly rely on lossy c…
FFCz: Fast Fourier Correction for Spectrum-Preserving Lossy Compression of Scientific Data
Congrong Ren, Robert Underwood, Sheng Di +5
This paper introduces a novel technique to preserve spectral features in lossy compression based on a novel fast Fourier correction algorithm\added{ for regular-grid data}. Preserv…
LCP: Enhancing Scientific Data Management with Lossy Compression for Particles
Longtao Zhang, Ruoyu Li, Congrong Ren +10
Many scientific applications opt for particles instead of meshes as their basic primitives to model complex systems composed of billions of discrete entities. Such applications spa…
An Error-Bounded Lossy Compression Method with Bit-Adaptive Quantization for Particle Data
Congrong Ren, Sheng Di, Longtao Zhang +2
This paper presents error-bounded lossy compression tailored for particle datasets from diverse scientific applications in cosmology, fluid dynamics, and fusion energy sciences. As…
A Survey on Error-Bounded Lossy Compression for Scientific Datasets
Sheng Di, Jinyang Liu, Kai Zhao +23
Error-bounded lossy compression has been effective in significantly reducing the data storage/transfer burden while preserving the reconstructed data fidelity very well. Many error…
A Prediction-Traversal Approach for Compressing Scientific Data on Unstructured Meshes with Bounded Error
Congrong Ren, Xin Liang, Hanqi Guo
We explore an error-bounded lossy compression approach for reducing scientific data associated with 2D/3D unstructured meshes. While existing lossy compressors offer a high compres…
Simplicial Approximation of Deforming 3D Spaces for Visualizing Fusion Plasma Simulation Data
Congrong Ren, Hanqi Guo
We introduce a fast and invertible approximation for data simulated as 2D planar meshes with connectivities along the poloidal dimension in deforming 3D toroidal (donut-like) space…