Complementing the gaps in current HE courses and taking up high performance computing (HPC) knowledge for future science, technology, engineering and mathematics (STEM) professionals.
For business experts
For future HPC HE courses
The course focuses on using HPCs for solving complex PDE-based engineering problems, using the Finite Element and Finite Volume Methods. An introduction to HPC usage will be presented, as well as the employment of different software, such as Ansys, Elmer FEM, and OpenFOAM. Background on problem parallelization and benefits of using GPUs will be explained. The course will take place between June 28 and July 2 2021 and is free of charge.
- Izvajalec: Claudia Blaas-Schenner
- Izvajalec: Matic Brank
- Izvajalec: Borut Černe
- Izvajalec: Miroslav Halilovic
- Izvajalec: Leon Kos
- Izvajalec: Tomas Kozubek
- Izvajalec: Nikolaj Mole
- Izvajalec: Raffaele Ponzini
- Izvajalec: Janez Povh
- Izvajalec: Arul Sivasankar
- Izvajalec: Bojan Starman
- Izvajalec: Pavel Tomšič
- Izvajalec: Janez Urevc
- Izvajalec: Damijan Zorko
The course focuses on raising the level of knowledge and competences on the topic of HPC in Data Science -with a focus on Parallelisation with the Message Passing Interface (MPI). Parallel programming with MPI as well as shared-memory parallelisation with OpenMP will be presented. Participants will embrace basic knowledge of programming (e.g. programming with Python, C/C++, Fortran).
The course focuses on raising the level of knowledge and competences on the topic of HPC in Engineering -with a focus on CFD (Computational Fluid Dynamics). Participants will be acquainted with solving dynamic real-world problems, quite large in size due to many variables involved and the complex physics. They will deal with time dependency problems, with HPC and parallelization. They will embrace both programming skills as well as advanced numerical simulation skills.
The course will focus on raising the level of knowledge and competences on the topic of HPC in Data Science - with a focus on Big Data and IOT. Classical Big Data topics (using commonly used frameworks such as Spark for Big Data management and analysis) and container technologies will be presented. To the participants different research methods to tackle large data problems will be introduced.