Fundamentals of Modern HPC Systems (Agueny)

In this lecture, we will cover the fundamentals of high-performance computing systems, from CPU and GPU architectures to high-speed interconnects and parallel file systems, including optimization strategies for GPU-aware data movement for performance and scalability.

Uncertainty quantification in physical systems (Lye)

This lecture series will introduce the motivation for and core concepts behind uncertainty quantification in physical systems. We will cover Monte Carlo methods and their variants, and explore alternative algorithms for computing uncertainty in specific settings. We will also use the uncertainty quantification framework to discuss the efficient construction and best-practice use of surrogate models. The presentation will be accompanied by small, self-contained coding exercises to help participants engage with and better understand the material.

Monte Carlo methods and Polynomial Chaos Expansion for uncertainty propagation (Métivier)

This series of lectures introduces sampling-based methods, focusing on Monte Carlo and Quasi-Monte Carlo techniques for numerical integration and uncertainty propagation. The second part presents Polynomial Chaos Expansion as an alternative approach. Hands-on exercises will reinforce the concepts through computational applications.

Practical Bayesian inference using MCMC methods (Reinarz)

This lecture series will focus on practical Bayesian inference using MCMC methods, including multilevel extensions, supported by hands-on use of UM-Bridge to run complex models efficiently.

European Environment for Scientific Software Installations (EESSI) - from zero to science in minutes (Röblitz)

Thomas will demonstrate how EESSI allows you to go "from zero to science in minutes" on virtually any Linux system in the world. Beyond the introduction, he will be available to guide you through the hands-on sessions, helping you get your code running smoothly on the available HPC systems.

Hicham Agueny

Hicham Agueny is a senior engineer in high-performance computing (HPC) at the University of Bergen. His work focuses on optimizing HPC and AI applications using GPU accelerators. Previously, he worked as a researcher for nearly a decade in theoretical physics, with an emphasis on mathematical modeling and large-scale computing applied to physics and chemistry. He holds a PhD in computational physics and chemistry from both Sorbonne University and Moulay Ismail University, and a master’s degree in theoretical nanophysics.

Kjetil Olsen Lye

Kjetil Olsen Lye is a Research Scientist at SINTEF Digital in Oslo, working at the intersection of uncertainty quantification, machine learning, and high-performance computing, with a strong focus on industrially relevant applications. He holds a PhD in applied mathematics from ETH Zurich and a master’s degree in pure mathematics from the University of Oslo.

David Métivier

David Métivier is a permanent researcher at INRAE Montpellier, working in Applied Mathematics and Physics. His current research interests focus on statistical models (e.g., Hidden Markov Models) and Deep Learning to tackle environmental and climate change problems. This includes developing stochastic weather generators to estimate risks in agronomy and energy, as well as modeling water quality in lakes and the Seine River. He also works on practical robust statistics. He completed a PhD and postdoctoral work in theoretical physics on mean-field dynamics of particle systems, studying bifurcations, synchronization, instabilities, and partial differential equations. He is a Julia enthusiast and contribute to several packages.

Anne Reinarz

Dr Anne Reinarz is an Associate Professor of Computer Science at Durham University working in the Scientific Computing group. Her research focuses on developing scalable algorithms and software for Bayesian inference, with particular emphasis on high-performance computing and multilevel methods. She is a core developer of UM-Bridge (Uncertainty Quantification and Modeling Bridge), a unified model interface designed to make complex scientific simulations accessible to a wide range of uncertainty-quantification tools.

Thomas Röblitz

Thomas Röblitz is a Senior Engineer at the University of Bergen, bringing years of hands-on experience in operating HPC infrastructure and supporting researchers. As a core contributor to the European Environment for Scientific Software Installations (EESSI), he focuses on ensuring that scientific software is fast, reliable, and accessible everywhere.

All lectures will take place at Dr. Holms Hotel in Geilo, Norway. Participants will receive more information by email. Exact times will also appear in the following schedule once the program is completely finalized.

Booking a train/checking the train schedule is done through Vy. The hotel is a walkable distance from the train station in Geilo.

You can subscribe to the above calendar by using this link.

See the About page for general information about the winter school.

Costs and registration

There is no registration fee for the winter school, but participants must cover their own travel costs and hotel costs at Dr. Holms. Hotel rates per person:

• 2 195 NOK/night for single room.
• 1 755 NOK/night in a double room.

You can register for the winter school here.

Room allocation

The winter school has a limited number of rooms at Dr. Holms which will be reserved on a first come first serve basis. We have in previous years exceeded our room allocation, so please register as early as possible!

Posters

We welcome all posters to be presented, and will make space in the program for a poster session in which participants can present their work to colleagues and others. The aim of the session is to make new contacts and share your research, and it is an informal event. You need to indicate in your registration if you want to present a poster during the poster session. Please limit your poster to A0 in portrait orientation.

The organizing committee for the Geilo Winter School consists of

• Øystein Klemetsdal, Research Scientist (Department of Mathematics and Cybernetics, SINTEF).
• Torkel Andreas Haufmann, Research Manager (Department of Mathematics and Cybernetics, SINTEF). 

To get in touch with the committee, send an email .