6 citations · 9 across the 4 of their papers we have counts for
7 papers
High-Performance Resilient Multi-GPU Hybrid Particle-in-Cell Monte Carlo Simulations at Scale
Jeremy J. Williams, Stefan Costea, David Tskhakaya +13
The increasing demand for high-performance computing in plasma physics has driven scalable and resilient simulation methods capable of efficiently exploiting modern multi-GPU archi…
Post-Moore Technologies for Plasma Simulation: A Community Roadmap
Luca Pennati, Erik M. Åsgrim, Jeremy J. Williams +21
Plasma simulations are among the most computationally demanding scientific workloads, combining high-dimensional kinetic evolution, particle-mesh coupling, field solves, and data-i…
Integrating High Performance In-Memory Data Streaming and In-Situ Visualization in Hybrid MPI+OpenMP PIC MC Simulations Towards Exascale
Jeremy J. Williams, Stefan Costea, Daniel Medeiros +11
Efficient simulation of complex plasma dynamics is crucial for advancing fusion energy research. Particle-in-Cell (PIC) Monte Carlo (MC) simulations provide insights into plasma be…
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…
In-Situ Techniques on GPU-Accelerated Data-Intensive Applications
Yi Ju, Mingshuai Li, Adalberto Perez +5
The computational power of High-Performance Computing (HPC) systems is constantly increasing, however, their input/output (IO) performance grows relatively slowly, and their storag…
Understanding Large-Scale Plasma Simulation Challenges for Fusion Energy on Supercomputers
Jeremy J. Williams, Ashish Bhole, Dylan Kierans +11
Understanding plasma instabilities is essential for achieving sustainable fusion energy, with large-scale plasma simulations playing a crucial role in both the design and developme…