activity
20202025
most citedMGARD: A multigrid framework for high-performance, error-controlled data compression and refactoring

35 citations · 106 across the 11 of their papers we have counts for

collaborators

11 papers

cs.SE2025

Toward Automated and Trustworthy Scientific Analysis and Visualization with LLM-Generated Code

Apu Kumar Chakroborti, Yi Ding, Lipeng Wan

As modern science becomes increasingly data-intensive, the ability to analyze and visualize large-scale, complex datasets is critical to accelerating discovery. However, many domai…

cs.DC2025

HPDR: High-Performance Portable Scientific Data Reduction Framework

Jieyang Chen, Qian Gong, Yanliang Li +5

The rapid growth of scientific data is surpassing advancements in computing, creating challenges in storage, transfer, and analysis, particularly at the exascale. While data reduct…

cs.CV2024★ 35 cited

MGARD: A multigrid framework for high-performance, error-controlled data compression and refactoring

Qian Gong, Jieyang Chen, Ben Whitney +13

We describe MGARD, a software providing MultiGrid Adaptive Reduction for floating-point scientific data on structured and unstructured grids. With exceptional data compression capa…

cs.CV2024★ 8 cited

Spatiotemporally adaptive compression for scientific dataset with feature preservation -- a case study on simulation data with extreme climate events analysis

Qian Gong, Chengzhu Zhang, Xin Liang +10

Scientific discoveries are increasingly constrained by limited storage space and I/O capacities. For time-series simulations and experiments, their data often need to be decimated…

eess.IV2023

High-performance Data Management for Whole Slide Image Analysis in Digital Pathology

Haoju Leng, Ruining Deng, Shunxing Bao +8

When dealing with giga-pixel digital pathology in whole-slide imaging, a notable proportion of data records holds relevance during each analysis operation. For instance, when deplo…

cs.DC2021★ 28 cited

Improving I/O Performance for Exascale Applications through Online Data Layout Reorganization

Lipeng Wan, Axel Huebl, Junmin Gu +12

The applications being developed within the U.S. Exascale Computing Project (ECP) to run on imminent Exascale computers will generate scientific results with unprecedented fidelity…

cs.DC2021★ 21 cited

Transitioning from file-based HPC workflows to streaming data pipelines with openPMD and ADIOS2

Franz Poeschel, Juncheng E, William F. Godoy +11

This paper aims to create a transition path from file-based IO to streaming-based workflows for scientific applications in an HPC environment. By using the openPMP-api, traditional…

cs.DC2021

Scalable Multigrid-based Hierarchical Scientific Data Refactoring on GPUs

Jieyang Chen, Lipeng Wan, Xin Liang +10

Rapid growth in scientific data and a widening gap between computational speed and I/O bandwidth makes it increasingly infeasible to store and share all data produced by scientific…

cs.DC2020★ 4 cited

MGARD+: Optimizing Multilevel Methods for Error-bounded Scientific Data Reduction

Xin Liang, Ben Whitney, Jieyang Chen +8

Data management is becoming increasingly important in dealing with the large amounts of data produced by large-scale scientific simulations and instruments. Existing multilevel com…

cs.DC2020★ 7 cited

FTRANS: Energy-Efficient Acceleration of Transformers using FPGA

Bingbing Li, Santosh Pandey, Haowen Fang +7

In natural language processing (NLP), the "Transformer" architecture was proposed as the first transduction model replying entirely on self-attention mechanisms without using seque…

cs.DC2020★ 3 cited

Accelerating Multigrid-based Hierarchical Scientific Data Refactoring on GPUs

Jieyang Chen, Lipeng Wan, Xin Liang +8

Rapid growth in scientific data and a widening gap between computational speed and I/O bandwidth make it increasingly infeasible to store and share all data produced by scientific…