activity
20232025
most citedFZ-GPU: A Fast and High-Ratio Lossy Compressor for Scientific Computing Applications on GPUs

26 citations · 52 across the 10 of their papers we have counts for

collaborators

10 papers

cs.DC2025★ 1 cited

STZ: A High Quality and High Speed Streaming Lossy Compression Framework for Scientific Data

Daoce Wang, Pascal Grosset, Jesus Pulido +9

Error-bounded lossy compression is one of the most efficient solutions to reduce the volume of scientific data. For lossy compression, progressive decompression and random-access d…

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

Overcoming Memory Constraints in Quantum Circuit Simulation with a High-Fidelity Compression Framework

Boyuan Zhang, Bo Fang, Fanjiang Ye +4

Full-state quantum circuit simulation requires exponentially increased memory size to store the state vector as the number of qubits scales, presenting significant limitations in c…

cs.DC2024

NeurLZ: An Online Neural Learning-Based Method to Enhance Scientific Lossy Compression

Wenqi Jia, Zhewen Hu, Youyuan Liu +10

Large-scale scientific simulations generate massive datasets, posing challenges for storage and I/O. Traditional lossy compression struggles to advance more in balancing compressio…

cs.LG2024

Accelerating Communication in Deep Learning Recommendation Model Training with Dual-Level Adaptive Lossy Compression

Hao Feng, Boyuan Zhang, Fanjiang Ye +9

DLRM is a state-of-the-art recommendation system model that has gained widespread adoption across various industry applications. The large size of DLRM models, however, necessitate…

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…

quant-ph2023

MEMQSim: Highly Memory-Efficient and Modularized Quantum State-Vector Simulation

Boyuan Zhang, Bo Fang, Qiang Guan +2

In this extended abstract, we have introduced a highly memory-efficient state vector simulation of quantum circuits premised on data compression, harnessing the capabilities of bot…

cs.DC2023★ 26 cited

FZ-GPU: A Fast and High-Ratio Lossy Compressor for Scientific Computing Applications on GPUs

Boyuan Zhang, Jiannan Tian, Sheng Di +5

Today's large-scale scientific applications running on high-performance computing (HPC) systems generate vast data volumes. Thus, data compression is becoming a critical technique…

cs.DC2023★ 22 cited

GPULZ: Optimizing LZSS Lossless Compression for Multi-byte Data on Modern GPUs

Boyuan Zhang, Jiannan Tian, Sheng Di +4

Today's graphics processing unit (GPU) applications produce vast volumes of data, which are challenging to store and transfer efficiently. Thus, data compression is becoming a crit…