Imagine trying to predict exactly how a wildfire spreads or how air pollution moves through a city; it's like trying to track a billion tiny invisible particles at once. This work uses the world's most powerful supercomputers to run massive simulations that are far more accurate than standard cloud computing. It's like upgrading from a basic calculator to a super-brain to better predict weather and energy needs.
Standard cloud computing lacks the power to accurately simulate complex fluid flows, making it difficult to predict wildfires, floods, and urban air quality with high precision.
A set of highly-scalable software tools and benchmarks for Computational Fluid Dynamics (CFD) optimized for pre-exascale HPC and AI systems.
If you are a municipal agency dealing with urban smog and health risks — this project developed high-scale simulation tools that improve air quality monitoring in urban agglomerations. This allows for more precise city planning to reduce pollution.
If you are a developer dealing with unpredictable wind or solar yields — this project developed optimized fluid flow simulations that improve the planning of renewable energy sources. This leads to better site selection and higher energy output.
If you are an insurer dealing with unpredictable wildfire and flood losses — this project developed advanced meteo-hydrological and wildfire forecasting tools. This enables more accurate risk pricing through ensemble run uncertainty analysis.
Based on available project data, no specific commercial pricing or licensing costs are mentioned as the project is currently in the research and development phase.
Yes, the project specifically focuses on scalability for pre-exascale systems and high-performance computing (HPC) infrastructures to handle complex global challenges.
Based on available project data, the specific IP and licensing terms are not disclosed, though the project emphasizes sharing knowledge through specialized workflows and trainings.
The project aims to provide accuracy that is not achievable using standard Cloud solutions by utilizing top-notch HPC systems and co-designing software for specific hardware.
The project period runs from 2023-01-01 to 2026-12-31, indicating that full results and final tools will be available toward the end of 2026.
The consortium is well-balanced for technology transfer, consisting of 11 partners across 8 countries. With a 27% industry ratio (3 industrial partners, including 2 SMEs), there is a clear bridge between the 5 universities and 3 research institutes and the commercial market, ensuring the software is developed with practical application in mind.
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