7 citations · 19 across the 18 of their papers we have counts for
19 papers
Computational Methods and GPU Acceleration in Plasma Physics: A Empirical Analysis of arXiv Publications and Research Trends
Jeremy J. Williams, Anders Brostrom, Stefano Markidis
Computational plasma physics increasingly relies on high-performance computing (HPC) methods, including particle-in-cell (PIC), gyrokinetic, and magnetohydrodynamic (MHD) simulatio…
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…
Generating wall-bounded turbulent inflows at high Reynolds numbers
Ronith Stanly, Timofey Mukha, Martin Karp +2
One of the main challenges in simulating high Reynolds number () turbulent boundary layers (TBLs) is the long streamwise distance required for large-scale outer-layer structure…
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…
SWAP-Network Routing and Spectral Qubit Ordering for MPS Imaginary-Time Optimization
Erik M. Åsgrim, Stefano Markidis
We propose a quantum-inspired combinatorial solver that performs imaginary-time evolution (ITE) on a matrix product state (MPS), incorporating non-local couplings through structure…
Portable High-Performance Kernel Generation for a Computational Fluid Dynamics Code with DaCe
Måns I. Andersson, Martin Karp, Niclas Jansson +1
With the emergence of new high-performance computing (HPC) accelerators, such as Nvidia and AMD GPUs, efficiently targeting diverse hardware architectures has become a major challe…
Effects of lower floating-point precision on scale-resolving numerical simulations of turbulence
Martin Karp, Ronith Stanly, Timofey Mukha +11
Modern computing clusters offer specialized hardware for reduced-precision arithmetic that can speed up the time to solution significantly. This is possible due to a decrease in da…
Robustness and uncertainty of direct numerical simulation under the influence of rounding and noise
Martin Karp, Niclas Jansson, Saleh Rezaeiravesh +2
Numerical precision in large-scale scientific computations has become an emerging topic due to recent developments in computer hardware. Lower floating point precision offers the p…
Optimizing FDTD Solvers for Electromagnetics: A Compiler-Guided Approach with High-Level Tensor Abstractions
Yifei He, Måns I. Andersson, Stefano Markidis
The Finite Difference Time Domain (FDTD) method is a widely used numerical technique for solving Maxwell's equations, particularly in computational electromagnetics and photonics.…
PySEMTools: A library for post-processing hexahedral spectral element data
Adalberto Perez, Siavash Toosi, Tim Felle Olsen +2
PySEMTools is a Python-based library for post-processing simulation data produced with high-order hexahedral elements in the context of the spectral element method in computational…
A Parallel and Highly-Portable HPC Poisson Solver: Preconditioned Bi-CGSTAB with alpaka
Luca Pennati, Måns I. Andersson, Klaus Steiniger +4
This paper presents the design, implementation, and performance analysis of a parallel and GPU-accelerated Poisson solver based on the Preconditioned Bi-Conjugate Gradient Stabiliz…
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…
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…
Understanding the Impact of openPMD on BIT1, a Particle-in-Cell Monte Carlo Code, through Instrumentation, Monitoring, and In-Situ Analysis
Jeremy J. Williams, Stefan Costea, Allen D. Malony +7
Particle-in-Cell Monte Carlo simulations on large-scale systems play a fundamental role in understanding the complexities of plasma dynamics in fusion devices. Efficient handling a…
Experience and Analysis of Scalable High-Fidelity Computational Fluid Dynamics on Modular Supercomputing Architectures
Martin Karp, Estela Suarez, Jan H. Meinke +4
The never-ending computational demand from simulations of turbulence makes computational fluid dynamics (CFD) a prime application use case for current and future exascale systems.…
Supercomputers as a Continous Medium
Martin Karp, Niclas Jansson, Philipp Schlatter +1
As supercomputers' complexity has grown, the traditional boundaries between processor, memory, network, and accelerators have blurred, making a homogeneous computer model, in which…
A GPU-Accelerated Interior Point Method for Radiation Therapy Optimization
Felix Liu, Albin Fredriksson, Stefano Markidis
Optimization plays a central role in modern radiation therapy, where it is used to determine optimal treatment machine parameters in order to deliver precise doses adapted to each…
Accelerating Particle-in-Cell Monte Carlo Simulations with MPI, OpenMP/OpenACC and Asynchronous Multi-GPU Programming
Jeremy J. Williams, Felix Liu, Jordy Trilaksono +11
As fusion energy devices advance, plasma simulations are crucial for reactor design. Our work extends BIT1 hybrid parallelization by integrating MPI with OpenMP and OpenACC, focusi…
ParaLog: Consistent Host-side Logging for Parallel Checkpoints
Steven W. D. Chien, Kento Sato, Artur Podobas +3
Output-intensive scientific applications are highly sensitive to low storage throughput. While existing scientific application stacks are optimized for traditional High-Performance…