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Article Dans Une Revue IEEE Access Année : 2023

VESTEC: Visual Exploration and Sampling Toolkit for Extreme Computing

Nick Brown
Rupert Nash
  • Fonction : Auteur
Gordon Gibb
  • Fonction : Auteur
Evgenij Belikov
  • Fonction : Auteur
Charles Gueunet
Johannes Günther
Miroslaw Pawlowski
Piero Poletti
Mattia Manica
Agnese Zardini
Jean-Pierre Chaboureau
Miguel Mendes
  • Fonction : Auteur
Adrián Cardil
Joaquin Ramirez

Résumé

Natural disasters and epidemics are unfortunate recurring events that lead to huge societal and economic loss. Recent advances in supercomputing can facilitate simulations of such scenarios in (or even ahead of) real-time, therefore supporting the design of adequate responses by public authorities. By incorporating high-velocity data from sensors and modern high-performance computing systems, ensembles of simulations and advanced analysis enable urgent decision-makers to better monitor the disaster and to employ necessary actions (e.g., to evacuate populated areas) for mitigating these events. Unfortunately, frameworks to support such versatile and complex workflows for urgent decision-making are only rarely available and often lack in functionalities. This paper gives an overview of the VESTEC project and framework, which unifies orchestration, simulation, in-situ data analysis, and visualization of natural disasters that can be driven by external sensor data or interactive intervention by the user. We show how different components interact and work together in VESTEC and describe implementation details. To disseminate our experience three different types of disasters are evaluated: a Wildfire in La Jonquera (Spain), a Mosquito-Borne disease in two regions of Italy, and the magnetic reconnection in the Earth magnetosphere.
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Dates et versions

hal-04253251 , version 1 (22-10-2023)

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Paternité - Pas d'utilisation commerciale - Pas de modification

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Markus Flatken, Artur Podobas, Riccardo Fellegara, Achim Basermann, Johannes Holke, et al.. VESTEC: Visual Exploration and Sampling Toolkit for Extreme Computing: Urgent Decision Making Meets HPC: Experiences and Future Challenges. IEEE Access, 2023, 11, pp.87805-87834. ⟨10.1109/ACCESS.2023.3301177⟩. ⟨hal-04253251⟩
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