A5041347658- Distributed and Parallel Computing Systems
- Parallel Computing and Optimization Techniques
- Magnetic confinement fusion research
- Scientific Computing and Data Management
- Advanced Data Storage Technologies
- Cloud Computing and Resource Management
- Advanced Battery Technologies Research
- Particle accelerators and beam dynamics
- Fusion materials and technologies
- Superconducting Materials and Applications
- Advancements in Battery Materials
- Simulation Techniques and Applications
- Distributed systems and fault tolerance
- Software System Performance and Reliability
- Plasma Diagnostics and Applications
- Radiation Effects in Electronics
- Advanced Battery Materials and Technologies
- Quantum Computing Algorithms and Architecture
- Vehicle emissions and performance
- Nuclear Materials and Properties
- Computer Graphics and Visualization Techniques
- Embedded Systems Design Techniques
- Gas Dynamics and Kinetic Theory
- Ionosphere and magnetosphere dynamics
- Innovative Microfluidic and Catalytic Techniques Innovation
Oak Ridge National Laboratory
2016-2025
University of Illinois Urbana-Champaign
2022
Institute of Technology of Cambodia
2022
University of Basel
2022
Swisscom (Switzerland)
2022
CSCS - Swiss National Supercomputing Centre
2022
Sandia National Laboratories
2022
Helmholtz-Zentrum Dresden-Rossendorf
2022
Nvidia (United States)
2022
University of Delaware
2022
The Common Component Architecture (CCA) provides a means for software developers to manage the complexity of large-scale scientific simulations and move toward plug-and-play environment high-performance coputing. In computing context, component models also promote collaboration using independently developed software, thereby allowing particular individals or groups focus on aspects greatest interest them. CCA supports parallel distributed coputing as well local connections between components...
Accurate prediction of fusion performance in present and future tokamaks requires taking into account the strong interplay between core transport, pedestal structure, current profile, plasma equilibrium. An integrated modeling workflow capable calculating steady-state self-consistent solution to this strongly coupled problem has been developed. The leverages state-of-the-art components for collisional turbulent equilibrium stability. Testing against a DIII-D discharge shows that is robustly...
In the past twenty years, there has been a wealth of theoretical research on minimizing expected running time program in presence failures by employing checkpointing and rollback recovery. same period, little experimental to corroborate these results. We study three separate projects that monitor failure workstation networks. Our goals are twofold. The first is see how results correlate with results, second assess their impact strategies for long-running computations workstations networks...
Lithium-ion batteries are highly complex electrochemical systems whose performance and safety governed by coupled nonlinear electrochemical-electrical-thermal-mechanical processes over a range of spatiotemporal scales. Gaining an understanding the role these as well development predictive capabilities for design better performing requires synergy between theory, modeling, simulation, fundamental experimental work to support models. This paper presents overview performed authors aligned with...
Theory-based integrated modeling validated against DIII-D experiments predicts that fully non-inductive operation with βN > 4.5 is possible certain upgrades. IPS-FASTRAN a new iterative numerical procedure integrates models of core transport, edge pedestal, equilibrium, stability, heating, and current drive self-consistently to find steady-state (d/dt = 0) solutions reproduces most features high discharges stationary profile. Projecting forward scenarios on future upgrades, the qmin 2...
As computing capabilities have increased, the coupling of computational models has become an increasingly viable and therefore important way improving physical fidelity simulations. Applications currently using some form multicode or multi-component include climate modeling, rocket simulations, chemistry. In recent years, plasma physics community also begun to pursue integrated multiphysics simulations for space weather fusion energy applications. Such model generally exposes new issues in...
Abstract Integrated modeling of plasma-surface interactions provides a comprehensive and self-consistent description the system, moving field closer to developing predictive design capabilities for plasma facing components. One such workflow, including descriptions scrape-off-layer plasma, ion-surface sub-surface evolution, was previously used address steady-state scenarios has recently been extended incorporate time-dependence two-way information flow. The new model can dynamic recycling in...
Two neural networks for general mapping problems, backpropagation and counterpropagation, are trained to predict students' grades in Calculus I from placement test responses. The effect of the number hidden units is investigated. benefit including topological structure on cluster a counterpropagation net illustrated. Noisy data sets used train improve ability generalize.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">></ETX>
Parareal is a novel algorithm that allows the solution of time-dependent systems differential or partial equations (PDE) to be parallelized in temporal domain. Parareal-based implementations PDE problems can take advantage this parallelism significantly reduce time for simulation (though at an increased total cost) while making effective use much larger processor counts available on current high-end systems. In paper, we present dynamic, dependency-driven version parareal which breaks final...
In this manuscript we introduce a simulation tool-suite for predicting plasma-surface interactions (PSI), which aims to predict the evolution of plasma-facing surfaces that continually change due exposure fusion plasmas. A comprehensive description PSI involves wide range physical phenomena, include components (a) gas implantation and its dynamic below divertor surface; (b) erosion wall material; (c) transport re-deposition eroded impurities; (d) scrape-off layer plasma including fuel ions...
Many scientific workloads are comprised of many tasks, where each task is an independent simulation or analysis data. The execution millions tasks on heterogeneous HPC platforms requires scalable dynamic resource management and multi-level scheduling. RADICAL-Pilot (RP) -- implementation the Pilot abstraction, addresses these challenges serves as effective runtime system to execute tasks. In this paper, we characterize performance executing using RP when interfaced with JSM PRRTE Summit:...
Computational biology is one of many scientific disciplines ripe for innovation and acceleration with the advent high-performance computing (HPC). In recent years, field machine learning has also seen significant benefits from adopting HPC practices. this work, we present a novel pipeline that incorporates various machine-learning approaches structure-based functional annotation proteins on scale whole genomes. Our makes extensive use deep provides computational insights into best practices...