activity
20232026
most citedA Survey on Error-Bounded Lossy Compression for Scientific Datasets

2 citations · 4 across the 6 of their papers we have counts for

collaborators

7 papers

cs.DC2026

Detecting Soft Errors in Parallel Software with LLM-tuned Instruction Duplication

Yafan Huang, Guanpeng Li

We propose PaRID (PaRallel Instruction Duplication), a software-directed soft error detection framework that requires only compile-time effort for multithreading parallel programs.…

cs.DC2026

Not All Errors Are Equal: A Systematic Study of Error Propagation in Large Language Model Inference

Yafan Huang, Sheng Di, Guanpeng Li

Large language models (LLMs) are increasingly integrated into high-performance computing (HPC) workflows, accelerating scientific discovery through diverse perspectives such as cod…

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.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.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

gZCCL: Compression-Accelerated Collective Communication Framework for GPU Clusters

Jiajun Huang, Sheng Di, Xiaodong Yu +11

GPU-aware collective communication has become a major bottleneck for modern computing platforms as GPU computing power rapidly rises. A traditional approach is to directly integrat…