A comprehensive hybrid first principles/machine learning modeling framework for complex industrial processes
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 …
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
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 …
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
Interactive visualization and exploration of large spatiotemporal data sets is difficult without
carefully-designed data preprocessing and management tools. We propose a novel …
carefully-designed data preprocessing and management tools. We propose a novel …
Performance-portable particle advection with vtk-m
Particle advection is the fundamental kernel behind most vector field visualization methods.
Yet, the efficient parallel computation of large amounts of particle traces remains …
Yet, the efficient parallel computation of large amounts of particle traces remains …
Reinforcement learning for load-balanced parallel particle tracing
We explore an online reinforcement learning (RL) paradigm to dynamically optimize parallel
particle tracing performance in distributed-memory systems. Our method combines three …
particle tracing performance in distributed-memory systems. Our method combines three …
Curve Complexity Heuristic KD‐trees for Neighborhood‐based Exploration of 3D Curves
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 …
curves, which enables interactive exploration of neighborhoods in dense and large line …
A survey of parallel particle tracing algorithms in flow visualization
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 …
placing particle seeds in the flow domain and tracing the trajectory of each particle, users …
Parallel particle advection bake-off for scientific visualization workloads
There are multiple algorithms for parallelizing particle advection for scientific visualization
workloads. While many previous studies have contributed to the understanding of individual …
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
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 …
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
We present an efficient and scalable solution to estimate uncertain transport behaviors-
stochastic flow maps (SFMs)-for visualizing and analyzing uncertain unsteady flows …
stochastic flow maps (SFMs)-for visualizing and analyzing uncertain unsteady flows …