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20232026
most citedBoosting Scientific Error-Bounded Lossy Compression through Optimized Synergistic Lossy-Lossless Orchestration

6 citations · 11 across the 10 of their papers we have counts for

collaborators

11 papers

cs.DB2026

Enabling Homomorphic Analytical Operations on Compressed Scientific Data with Multi-stage Decompression

Xuan Wu, Sheng Di, Tripti Agarwal +3

Error-controlled lossy compressors have been widely used in scientific applications to reduce the unprecedented size of scientific data while keeping data distortion within a user-…

cs.DC2025★ 6 cited

Boosting Scientific Error-Bounded Lossy Compression through Optimized Synergistic Lossy-Lossless Orchestration

Shixun Wu, Jinwen Pan, Jinyang Liu +8

As high-performance computing architectures evolve, more scientific computing workflows are being deployed on advanced computing platforms such as GPUs. These workflows can produce…

cs.DC2025

GPZ: GPU-Accelerated Lossy Compressor for Particle Data

Ruoyu Li, Yafan Huang, Longtao Zhang +10

Particle-based simulations and point-cloud applications generate massive, irregular datasets that challenge storage, I/O, and real-time analytics. Traditional compression technique…

cs.DC2025

IPComp: Interpolation Based Progressive Lossy Compression for Scientific Applications

Zhuoxun Yang, Sheng Di, Longtao Zhang +6

Compression is a crucial solution for data reduction in modern scientific applications due to the exponential growth of data from simulations, experiments, and observations. Compre…

cs.DC2025

ZCCL: Significantly Improving Collective Communication With Error-Bounded Lossy Compression

Jiajun Huang, Sheng Di, Xiaodong Yu +12

With the ever-increasing computing power of supercomputers and the growing scale of scientific applications, the efficiency of MPI collective communication turns out to be a critic…

cs.DB2024★ 1 cited

QPET: A Versatile and Portable Quantity-of-Interest-Preservation Framework for Error-Bounded Lossy Compression

Jinyang Liu, Pu Jiao, Kai Zhao +3

Error-bounded lossy compression has been widely adopted in many scientific domains because it can address the challenges in storing, transferring, and analyzing unprecedented amoun…

cs.DC2024★ 1 cited

HoSZp: An Efficient Homomorphic Error-bounded Lossy Compressor for Scientific Data

Tripti Agarwal, Sheng Di, Jiajun Huang +7

Error-bounded lossy compression has been a critical technique to significantly reduce the sheer amounts of simulation datasets for high-performance computing (HPC) scientific appli…

cs.IT2024

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…

cs.DC2024★ 2 cited

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…

cs.DC2023★ 1 cited

cuSZ-: High-Ratio Scientific Lossy Compression on GPUs with Optimized Multi-Level Interpolation

Jinyang Liu, Jiannan Tian, Shixun Wu +10

Error-bounded lossy compression is a critical technique for significantly reducing scientific data volumes. Compared to CPU-based compressors, GPU-based compressors exhibit substan…

cs.DC2023

High-performance Effective Scientific Error-bounded Lossy Compression with Auto-tuned Multi-component Interpolation

Jinyang Liu, Sheng Di, Kai Zhao +7

Error-bounded lossy compression has been identified as a promising solution for significantly reducing scientific data volumes upon users' requirements on data distortion. For the…