A5070307393- Computer Graphics and Visualization Techniques
- Distributed and Parallel Computing Systems
- Advanced Data Storage Technologies
- Parallel Computing and Optimization Techniques
- Lattice Boltzmann Simulation Studies
- Atmospheric aerosols and clouds
- Atmospheric and Environmental Gas Dynamics
- Fluid Dynamics and Heat Transfer
- Digital Image Processing Techniques
- Peer-to-Peer Network Technologies
- Cloud Computing and Resource Management
- Service-Oriented Architecture and Web Services
- Advanced Neural Network Applications
- Graph Theory and Algorithms
- Mobile Agent-Based Network Management
- Chaos-based Image/Signal Encryption
- Scientific Computing and Data Management
- Block Copolymer Self-Assembly
- Computational Geometry and Mesh Generation
- Image Enhancement Techniques
Kitware (United States)
2023-2025
University of Oregon
2021-2024
Oak Ridge National Laboratory
2022
Abstract. The E3SMv2 model, like various other global climate models that include representations of aerosol-cloud interactions, uses an empirically chosen lower bound on the simulated in-cloud cloud droplet number concentration (CDNC) to help constrain effective radiative forcing anthropogenic aerosols, ERFaer. This study identifies where ultra-low CDNCs (i.e., concentrations than 10 cm-3) occur in stratiform and shallow convective clouds by which occurrences have strongest impact...
The VTK-m software library enables scientific visualization on exascale-class supercomputers. Exascale machines are particularly challenging for development in part because they use GPU accelerators to provide the vast majority of their computational throughput. Algorithmic designs GPUs and GPU-centric computing often deviate from those that worked well previous generations high-performance computers relied traditional CPUs. Fortunately, provides algorithms other accelerators. also a...
A significant challenge on an exascale computer is the speed at which we compute results exceeds by many orders of magnitude save these results. Therefore Exascale Computing Project (ECP) ALPINE project focuses providing exascale-ready visualization solutions including in situ processing. In and analysis runs as simulation run, simulations are they generated avoiding need to entire storage for later analysis. The made post hoc tools, ParaView VisIt, ready developed algorithms...
Abstract The computational work to perform particle advection‐based flow visualization techniques varies based on many factors, including number of particles, duration, and mesh type. In cases, the total is significant, execution time (“performance”) a critical issue. This state‐of‐the‐art report considers existing optimizations for advection, using two high‐level categories: algorithmic hardware efficiency. sub‐categories include solvers, cell locators, I/O efficiency, precomputation, while...
There are multiple algorithms for parallelizing particle advection scientific visualization workloads. While many previous studies have contributed to the understanding of individual algorithms, our study aims provide a holistic how perform relative each other on various To accomplish this, we consider four popular parallelization and run "bake-off" (i.e., an empirical study) identify best matches each. The includes 216 tests, going concurrency up 8192 cores considering data sets as large 34...
Grid Computing has been around for as long the modern computers themselves yet have failed in obtaining a clear standard which would define its implementation across computing domain.This project focuses on Process Migration aspects of Computing/Clusters Java Applications.The available solutions and Mobile Agent Development require high level Expertise user itself let alone developer.These also changes to be made JVM (Java Virtual Machine) is hassle SMEs who cannot afford put such into...
We introduce and evaluate a new algorithm for the in situ extraction of Lagrangian flow maps, which we call Boundary Termination Optimization (BTO). Our approach is communication-free model, requiring no message passing or synchronization between processes, improving scalability, thereby reducing overall execution time alleviating encumbrance placed on simulation codes from processing. terminate particle integration at node boundaries store only subset map that would have been extracted by...
The performance of particle advection-based flow visualization techniques is complex, since computational work can vary based on many factors, including number particles, duration, and mesh type. Further, while approaches have been introduced to optimize performance, the efficacy a given approach be similarly complex. In this work, we seek establish guide for advection by conducting comprehensive survey area. We begin identifying building blocks establishing simple cost model incorporating...