The CASTIEL “Training Sprint” initiative is a dynamic program designed to rapidly enhance skills and competencies among NCCs and CoEs. Through intensive workshops, hands-on exercises, and tailored learning experiences, participants accelerate their professional development, equipping them with the tools and knowledge needed to excel in their roles.
Machine learning prototype for SPACE applications
The objective of this webinar is to present the prototype of a machine learning tool to enable the exploration, analysis, and interpretation of the outputs of large-volume cosmological simulations using Representation Learning techniques. The tool efficiently learns a low-dimensional representation of the structure of simulated galaxies in arbitrary physical components, uncovering their intrinsic structural distribution. It also provides an interactive hierarchical visualization of the entire simulation and its compact representation, and scales to arbitrarily large simulations beyond the Exascale era.
ChEESE: Tsunami and Meteo-Tsunami Modelling
ChEESE Tsunami and Meteo-Tsunami Modelling Training Course aims to provide the participants with the knowledge and numerical tools required to perform the mathematical modelling and numerical simulation of tsunamis and meteo-tsunamis. A brief theoretical overview on the processes and mechanisms producing this kind of natural events will be first provided. Then, the European flagship code, Tsunami-HySEA, will be used to simulate various tsunami and meteo-tsunami events. Tsunami-HySEA solves the 2D shallow water equations on hydrostatic and dispersive versions. Based on a high-order Finite Volume (FV) discretisation (hydrostatic) with Finite Differences (FD) for the dispersive version on two-way structured nested meshes in spherical coordinates. Meteo-HySEA is a version of Tsunami-HySEA code able to include meteorological forcing (atmospheric pressure and wind stress) as input, more precisely as boundary conditions.
The training course will include an introduction to tsunami and meteo-tsunami modelling, the basics of the numerical code used and the required data. The course will also tackle pre-process and post-process strategies based on Python scripts.
Requirements:
Attendees can only download, make and retain a copy of the materials for their use for non‐commercial and research purposes. The User may not commercially use the material unless has been granted prior written consent by the Licensor.
Further information:
This webinar, crafted by the ChEESE Equality Committee, welcomes participation from all EuroHPC Centers of Excellence and other interested parties.
MaX: Materials and Molecular Modelling with QUANTUM ESPRESSO
A School organized by MaX, in collaboration with: NCC Czechia, NCC Austria, NCC Slovakia, NCC Slovenia, NCC Poland and NCC Hungary