most citedMulti-GPU Hybrid Particle-in-Cell Monte Carlo Simulations for Exascale Computing Systems

1 citations · 1 across the 1 of their papers we have counts for

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5 papers

physics.plasm-ph20261 cited

Multi-GPU Hybrid Particle-in-Cell Monte Carlo Simulations for Exascale Computing Systems

Jeremy J. Williams, Jordy Trilaksono, Stefan Costea +13

Particle-in-Cell (PIC) Monte Carlo (MC) simulations are central to plasma physics but face increasing challenges on heterogeneous HPC systems due to excessive data movement, synchr…

cs.AR2026

Evaluating Four FPGA-accelerated Space Use Cases based on Neural Network Algorithms for On-board Inference

Pedro Antunes, Muhammad Ihsan Al Hafiz, Jonah Ekelund +4

Space missions increasingly deploy high-fidelity sensors that produce data volumes exceeding onboard buffering and downlink capacity. This work evaluates FPGA acceleration of neura…

cs.LG2025

Adaptive PCA-Based Outlier Detection for Multi-Feature Time Series in Space Missions

Jonah Ekelund, Savvas Raptis, Vicki Toy-Edens +4

Analyzing multi-featured time series data is critical for space missions making efficient event detection, potentially onboard, essential for automatic analysis. However, limited o…

cs.CE2025

Discovering Governing Equations of Geomagnetic Storm Dynamics with Symbolic Regression

Stefano Markidis, Jonah Ekelund, Luca Pennati +2

Geomagnetic storms are large-scale disturbances of the Earth's magnetosphere driven by solar wind interactions, posing significant risks to space-based and ground-based infrastruct…

cs.DC2025

Boosting Performance of Iterative Applications on GPUs: Kernel Batching with CUDA Graphs

Jonah Ekelund, Stefano Markidis, Ivy Peng

Graphics Processing Units (GPUs) have become the standard in accelerating scientific applications on heterogeneous systems. However, as GPUs are getting faster, one potential perfo…