115 citations · 460 across the 43 of their papers we have counts for
45 papers
Improving Progressive Compression with Adaptive Interpolation and Coefficient Decomposition
Wenbo Li, Xuan Wu, Qian Gong +6
Exascale simulations generate data far faster than it can be stored or analyzed, making efficient data reduction essential. Error-controlled lossy compression offers high compressi…
BlockMGARD: Accelerating Adaptive Scientific Data Reduction with Region-of-Interest Error Control on GPUs
Yanliang Li, Qian Gong, Qing Liu +5
The growing scale of scientific data makes lossy compression essential for reducing data volume under controllable error. Transformation-based compressors using multilevel decompos…
QoI-Aware Provisional Rollout and Retrospective Reconciliation for Reduced-State Scientific Twins
Liangji Zhu, Scott Klasky, Jaemoon Lee +3
Scientific twins may need to continue operating when updates from an authoritative primary system are temporarily unavailable. Once synchronization resumes, the new boundary can al…
RaivenTracks: Branching Provenance for Conversational Visualization Workflows
Ella Hugie, Alexandra Irger, Grace Guo +4
As AI agents increasingly participate in scientific workflows, scientists are shifting from direct authorship toward oversight, inspection, and steering. LLM-driven visualization s…
GS-Surrogate: Deformable Gaussian Splatting for Parameter Space Exploration of Ensemble Simulations
Ziwei Li, Rumali Perera, Angus Forbes +5
Exploring ensemble simulations is increasingly important across many scientific domains. However, supporting flexible post-hoc exploration remains challenging due to the trade-off…
Data Management System Analysis for Distributed Computing Workloads
Kuan-Chieh Hsu, Sairam Sri Vatsavai, Ozgur O. Kilic +20
Large-scale international collaborations such as ATLAS rely on globally distributed workflows and data management to process, move, and store vast volumes of data. ATLAS's Producti…
CGSim: A Simulation Framework for Large Scale Distributed Computing Environment
Sairam Sri Vatsavai, Raees Khan, Kuan-Chieh Hsu +20
Large-scale distributed computing infrastructures such as the Worldwide LHC Computing Grid (WLCG) require comprehensive simulation tools for evaluating performance, testing new alg…
Machine Learning-Driven Predictive Resource Management in Complex Science Workflows
Tasnuva Chowdhury, Tadashi Maeno, Fatih Furkan Akman +23
The collaborative efforts of large communities in science experiments, often comprising thousands of global members, reflect a monumental commitment to exploration and discovery. R…
Towards an Introspective Dynamic Model of Globally Distributed Computing Infrastructures
Ozgur O. Kilic, David K. Park, Yihui Ren +18
Large-scale scientific collaborations like ATLAS, Belle II, CMS, DUNE, and others involve hundreds of research institutes and thousands of researchers spread across the globe. Thes…
JANUS: Resilient and Adaptive Data Transmission for Enabling Timely and Efficient Cross-Facility Scientific Workflows
Vladislav Esaulov, Jieyang Chen, Norbert Podhorszki +4
In modern science, the growing complexity of large-scale scientific projects has led to an increasing reliance on cross-facility scientific workflows, where resources and expertise…
HP-MDR: High-performance and Portable Data Refactoring and Progressive Retrieval with Advanced GPUs
Yanliang Li, Wenbo Li, Qian Gong +5
Scientific applications produce vast amounts of data, posing grand challenges in the underlying data management and analytic tasks. Progressive compression is a promising way to ad…
Performance Models for a Two-tiered Storage System
Aparna Sasidharan, Xian-He, Jay Lofstead +1
This work describes the design, implementation and performance analysis of a distributed two-tiered storage software. The first tier functions as a distributed software cache imple…
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…
Alternative Mixed Integer Linear Programming Optimization for Joint Job Scheduling and Data Allocation in Grid Computing
Shengyu Feng, Jaehyung Kim, Yiming Yang +18
This paper presents a novel approach to the joint optimization of job scheduling and data allocation in grid computing environments. We formulate this joint optimization problem as…
A General Framework for Error-controlled Unstructured Scientific Data Compression
Qian Gong, Zhe Wang, Viktor Reshniak +10
Data compression plays a key role in reducing storage and I/O costs. Traditional lossy methods primarily target data on rectilinear grids and cannot leverage the spatial coherence…
The Artificial Scientist -- in-transit Machine Learning of Plasma Simulations
Jeffrey Kelling, Vicente Bolea, Michael Bussmann +19
Increasing HPC cluster sizes and large-scale simulations that produce petabytes of data per run, create massive IO and storage challenges for analysis. Deep learning-based techniqu…
Error-controlled Progressive Retrieval of Scientific Data under Derivable Quantities of Interest
Xuan Wu, Qian Gong, Jieyang Chen +4
The unprecedented amount of scientific data has introduced heavy pressure on the current data storage and transmission systems. Progressive compression has been proposed to mitigat…
A framework for compressing unstructured scientific data via serialization
Viktor Reshniak, Qian Gong, Rick Archibald +2
We present a general framework for compressing unstructured scientific data with known local connectivity. A common application is simulation data defined on arbitrary finite eleme…
AI Surrogate Model for Distributed Computing Workloads
David K. Park, Yihui Ren, Ozgur O. Kilic +18
Large-scale international scientific collaborations, such as ATLAS, Belle II, CMS, and DUNE, generate vast volumes of data. These experiments necessitate substantial computational…
Optimising the Processing and Storage of Visibilities using lossy compression
Richard Dodson, Alex Williamson, Qian Gong +7
The next-generation radio astronomy instruments are providing a massive increase in sensitivity and coverage, through increased stations in the array and frequency span. Two primar…
Deep Investigation of Neutral Gas Origins (DINGO): Options for the Processing and Storage of Radio Astronomy Data for robust Deep Spectral Line Imaging in the SKA-Era using uv-Grids
Alexander Williamson, Richard Dodson, Pascal J. Elahi +9
The next generation of radio astronomy telescopes are challenging existing data analysis paradigms, as they have an order of magnitude more antennas and larger bandwidth. Foremost…
Streaming Data in HPC Workflows Using ADIOS
Greg Eisenhauer, Norbert Podhorszki, Ana Gainaru +12
The "IO Wall" problem, in which the gap between computation rate and data access rate grows continuously, poses significant problems to scientific workflows which have traditionall…
Enabling High-Throughput Parallel I/O in Particle-in-Cell Monte Carlo Simulations with openPMD and Darshan I/O Monitoring
Jeremy J. Williams, Daniel Medeiros, Stefan Costea +14
Large-scale HPC simulations of plasma dynamics in fusion devices require efficient parallel I/O to avoid slowing down the simulation and to enable the post-processing of critical i…
Lifting MGARD: construction of (pre)wavelets on the interval using polynomial predictors of arbitrary order
Viktor Reshniak, Evan Ferguson, Qian Gong +3
MGARD (MultiGrid Adaptive Reduction of Data) is an algorithm for compressing and refactoring scientific data, based on the theory of multigrid methods. The core algorithm is built…