HiDALGO2 aims to explore synergies between modelling, data acquisition, simulation, data analysis and visualisation along with achieving better scalability on current and future HPC and AI infrastructures to deliver highly scalable solutions that can effectively utilise pre-exascale systems. The project focuses on five use cases from the environmental area: improving air quality in urban agglomerations, energy efficiency of buildings, renewable energy sources, wildfires and meteo-hydrological forecasting.
Eviden participation in the project is focused on the implementation of workflow orchestration to manage hybrid workflows as a way to implement HIDALGO2 simulations and use cases. The orchestration solution will abstract the complexity of the infrastructure to users and, therefore, this task will guarantee the solution will be compatible with all the schedulers required (Slurm, PBS Pro and any other used tools). We also contribute to tasks related to data harvesting, artificial intelligence and coupling technologies.
The scope of the work proposed in this project is to some extent a continuation of tasks carried out in the HiDALGO project. Thus, Eviden will improve its positioning with respect to the usage of data analytics and AI capabilities for Global Challenges.
Moreover, one of the ambitions of HIDALGO2 is to advance in the transition towards Exascale capabilities, a key aspect for the company as the main HPC European provider.
