The EuroCC & CASTIEL2 "Training Sprint" initiative is designed to quickly disseminate the expertise and abilities of CoEs. These training events target individuals from academia and industry who stand to gain from high-performance computing.
November 11 - 15
MaX: SIESTA School 2024
This course organized by MaX CoE, in collaboration with: NCC Spain
The school is aimed at students and researchers from different disciplines who already use, or plan to use, first-principles techniques to simulate properties of matter at the atomic scale. In particular, the school will focus on the SIESTA method . Participants will learn its essential theoretical foundations, and how to use the SIESTA code effectively. Pre- and post-processing tools will also be presented.
October 28 - 29
EXCELLERAT P2: Scientific Visualization
This course organized by EXCELLERAT P2, in collaboration with: NCC Germany
This course is targeted at researchers with basic knowledge in numerical simulation, who would like to learn how to visualize their simulation results on the desktop but also in Augmented Reality and Virtual Environments. The two-day workshop gives a short overview over scientific visualization in general, followed by a hands-on introduction to 3D desktop visualization with VISTLE (webpage on the EXCELLERAT P2 service portal) and COVISE. Participants will further learn how to build interactive 3D Models for Virtual Environments and how to set up an Augmented Reality visualization.
October 15
SPACE: The RAMSES code for structure formation in the Universe
This series organized by SPACE, in collaboration with: NCC Czechia, NCC Austria, UNITO, CNRS-CRAL, INAF, LMU, and UiO.
The training is addressed to researchers working in the field of fluid dynamics as well as astrophysicists interested in structure formation in general. We will first present the main features of the RAMSE code, as well as its current scalability. We will then highlight the science than can be done with RAMSES using Tier0 resources. Last, we will discuss our work-plan to improve the performance of the code.
October 4
EESSI: Introduction to EESSI – European Environment for Scientific Software Installations
This event organized by EESSI CoE, in collaboration with: NCC Slovenia, NCC Austria together with MultiXscale CoE.
Have you ever wished that all the scientific software you use was available on all the resources you had access to, without having to go through the pain of getting them installed the way you want/need?
The European Environment for Scientific Software Installations (EESSI – pronounced “easy”) is a common stack of scientific software for HPC systems and beyond, including laptops, personal workstations, and cloud infrastructure. In many ways it works like a streaming service for scientific software, instantly giving you the software you need, when you need it, and compiled to work efficiently for the architecture you have access to.
In this online workshop, we’ll explain what EESSI is, how it is being designed, how to get access to it, and how to use it. We’ll give a number of demonstrations and you can try EESSI out yourself on the Vienna Scientific Cluster (VSC).
September 23 - 25
SPACE: PLUTO Symposium 2024
This Symposium organized by SPACE CoE, in collaboration with: UNITO and INAF, Osservatorio Astronomico di Torino.
The PLUTO symposium 2024 aims at bringing together developers, scientists and users with the purpose of sharing recent numerical algorithms, new code features as well as challenging astrophysical applications. A special focus will give to the GPU porting of the code and its forthcoming release. A hands-on session will also take place in order to help the new users to get used to the code structure. While we strongly encourage in-person participation, we will also ensure remote participation through the Webex application.
September 12 - 13
ESiWACE3: GPU optimization with Kernel Tuner
The National Competence Center for HPC in Austria is organizing this 2 half-day training together with ESiWACE3, the Centre of Excellence in simulation of weather and climate in Europe. With expertise in earth system modelling, software design, and high-performance computing, ESiWACE3 is supporting scientists on the path to exascale computing.
This training is about Kernel Tuner, a tool for automatic optimization of GPU code, developed by a team from ESiWACE3. As a new development, Kernel Tuner adds support for mixed precision and tuning accuracy, which comes in addition to the existing functionality of tuning parameters and code optimizations for compute performance and/or energy efficiency. The first day of the training will focus on getting to know the tool, where as the second day is all about (energy) efficient computing on GPUs.
September 4 - 6
POP3: Profiling and Optimisation Tools
The POP3 CoE, NCC Austria, NCC Czechia, NCC Hungary, NCC Poland, NCC Slovakia and NCC Slovenia are inviting you to the POP3 Profiling and Optimisation Tools Workshop.
This workshop focuses on tools and methodologies for performance analysis, debugging, and tuning through collaborative learning, particularly for teams working on similar codes.
The first day of the workshop introduces participants to the POP Centre of Excellence (CoE), detailing its services, methodology, and tools for performance assessments and second-level services. On the second day, the focus shifts to getting started with open-source multi-platform tools for analysing MPI+OpenMP application executions on CPU architectures. The third day delves into more advanced usage, including analysing application executions on combined CPU and GPU architectures. During this hands-on workshop, participants will be introduced to the use of Paraver/Extrae and Scalasca/Score-P/CUBE toolsets for CPUs and GPUs.
May 28 - July 2
SPACE: PLUTO, OpenGadjet and ChanGa. Four Free online Training Events about Astrophysical and Cosmological Simulation Codes
This series organized by SPACE, in collaboration with: NCC Czechia, NCC Austria, UNITO, CNRS-CRAL, INAF, LMU, and UiO
July 2
The ChaNGa code and the Charm++ framework
The training is addressed to researchers interested in HPC and the challenges that astrophysics codes present when scaling towards exa-scale. We will discuss both the benefits and difficulties of the ChaNGa code and the Charm++ framework. We will also discuss recent and future improvements of the code.
June 18
The OpenGadget code for Cosmological Simulations
The training is addressed to HPC experts from all domains interested in evolving their codes to “exa-scale”. The audience will benefit from the training, discovering how a different community is solving computational problems and implementing algorithms. Conversely, the benefits for the speakers will come from the audience observations, discussions, suggestions, and even error spotting.
May 28
Recent Advances on PLUTO GPU Development and Astrophysical Applications
The training is addressed to researchers working in the field of HPC as well as astrophysicists interested in plasma astrophysics and fluid dynamics in general. We aim at sharing our recent achievements on PLUTO GPU to a larger community in order to foster discussions and possible solutions to common problems and implementation bottlenecks.
June 19 - 21
MaX: Materials and Molecular Modelling with QUANTUM ESPRESSO
This School organized by MaX, in collaboration with: NCC Czechia, NCC Austria, NCC Slovakia, NCC Slovenia, NCC Poland and NCC Hungary
The course encompasses a comprehensive curriculum designed to cover the primary features of the Quantum ESPRESSO code. The emphasis is on practical skill development. The course strikes a balance between theory and application, offering a hands-on learning experience. It caters to a beginner to intermediate level, aiming to equip participants with the fundamental knowledge and skills necessary for the effective utilization of QUANTUM ESPRESSO in their research and academic pursuits.
The school is designed for participants with a background in condensed matter physics or chemistry interested in learning to use Quantum ESPRESSO.
The school plans to cover the main features of the code and provide basic user skills such as compilation, simple scripting, choice of parallel options, and similar.
May 13 - 14
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.
May 7
Machine learning prototype for SPACE applications
This course organized by SPACE, in collaboration with: NCC Czechia, NCC Austria, UNITO, CNRS-CRAL, INAF, LMU, and UiO
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.