A comprehensive hybrid first principles/machine learning modeling framework for complex industrial processes

B Sun, C Yang, Y Wang, W Gui, I Craig… - Journal of Process Control, 2020 - Elsevier
The selection of an appropriate descriptive system and modeling framework to capture
system dynamics and support process control applications is a fundamental problem in the …

GENESIS CGDYN: large-scale coarse-grained MD simulation with dynamic load balancing for heterogeneous biomolecular systems

J Jung, C Tan, Y Sugita - Nature Communications, 2024 - nature.com
Residue-level coarse-grained (CG) molecular dynamics (MD) simulation is widely used to
investigate slow biological processes that involve multiple proteins, nucleic acids, and their …

Smartcube: An adaptive data management architecture for the real-time visualization of spatiotemporal datasets

C Liu, C Wu, H Shao, X Yuan - IEEE transactions on …, 2019 - ieeexplore.ieee.org
Interactive visualization and exploration of large spatiotemporal data sets is difficult without
carefully-designed data preprocessing and management tools. We propose a novel …

Performance-portable particle advection with vtk-m

D Pugmire, A Yenpure, MB Kim, JM Kress, R Maynard… - 2018 - osti.gov
Particle advection is the fundamental kernel behind most vector field visualization methods.
Yet, the efficient parallel computation of large amounts of particle traces remains …

Reinforcement learning for load-balanced parallel particle tracing

J Xu, H Guo, HW Shen, M Raj… - … on Visualization and …, 2022 - ieeexplore.ieee.org
We explore an online reinforcement learning (RL) paradigm to dynamically optimize parallel
particle tracing performance in distributed-memory systems. Our method combines three …

Curve Complexity Heuristic KD‐trees for Neighborhood‐based Exploration of 3D Curves

Y Lu, L Cheng, T Isenberg, CW Fu… - Computer Graphics …, 2021 - Wiley Online Library
We introduce the curve complexity heuristic (CCH), a KD‐tree construction strategy for 3D
curves, which enables interactive exploration of neighborhoods in dense and large line …

A survey of parallel particle tracing algorithms in flow visualization

J Zhang, X Yuan - Journal of Visualization, 2018 - Springer
Particle tracing is a very important method in flow field data visualization and analysis. By
placing particle seeds in the flow domain and tracing the trajectory of each particle, users …

Parallel particle advection bake-off for scientific visualization workloads

R Binyahib, D Pugmire, A Yenpure… - 2020 IEEE International …, 2020 - ieeexplore.ieee.org
There are multiple algorithms for parallelizing particle advection for scientific visualization
workloads. While many previous studies have contributed to the understanding of individual …

BaPa: A novel approach of improving load balance in parallel matrix factorization for recommender systems

R Guo, F Zhang, L Wang, W Zhang… - IEEE Transactions …, 2020 - ieeexplore.ieee.org
A simplified approach to accelerate matrix factorization of big data is to parallelize it. A
commonly used method is to divide the matrix into multiple non-intersecting blocks and …

Extreme-scale stochastic particle tracing for uncertain unsteady flow visualization and analysis

H Guo, W He, S Seo, HW Shen… - IEEE transactions on …, 2018 - ieeexplore.ieee.org
We present an efficient and scalable solution to estimate uncertain transport behaviors-
stochastic flow maps (SFMs)-for visualizing and analyzing uncertain unsteady flows …