STRIELAD -- A Scalable Toolkit for Real-time Interactive Exploration of Large Atmospheric Datasets
January 24, 2025 Β· Declared Dead Β· π arXiv.org
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Authors
Simon Schneegans, Lori Neary, Markus Flatken, Andreas Gerndt
arXiv ID
2502.00033
Category
cs.HC: Human-Computer Interaction
Cross-listed
cs.DC,
cs.GR
Citations
2
Venue
arXiv.org
Last Checked
4 months ago
Abstract
Technological advances in high performance computing and maturing physical models allow scientists to simulate weather and climate evolutions with an increasing accuracy. While this improved accuracy allows us to explore complex dynamical interactions within such physical systems, inconceivable a few years ago, it also results in grand challenges regarding the data visualization and analytics process. We present STRIELAD, a scalable weather analytics toolkit, which allows for interactive exploration and real-time visualization of such large scale datasets. It combines parallel and distributed feature extraction using high-performance computing resources with smart level-of-detail rendering methods to assure interactivity during the complete analysis process.
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