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Summer School

High-Performance Computing

23 Jun 2026 - 2 Jul 2026

The CSC Summer School brings together students and researchers in different disciplines of scientific computing from all over the world. The school consist of lectures and hands-on training on parallel programming, code performance, and other necessary skills for the development of scientific software for supercomputers.

Experience ten exciting days of coding and social activities, creating unforgettable memories with new friends under the Nordic summer’s midnight sun, right next to breathtaking wilderness!

Practical information:

23 Jun 2026 - 2 Jul 2026
80 hours
Hotelli Nuuksio, Espoo, Finland
English
Target audience: Graduate students working in various fields of science, industrial R&D professionals, undergraduates and post-docs.

Want to register?

  • Prerequisites: Basic skills to operate in a Linux environment; Basic working knowledge in programming with C or C++ (MPI and OpenMP modules of the school can also be completed optionally with Fortran instead of C or C++).
  • Price: Price upon request
More info & registration ⇗

Georganiseerd door:

The following topics will be covered:

  • Programming at supercomputer scale using message-passing interface (MPI)
  • Using threading (OpenMP) for programming CPU nodes
  • Programming GPUs with HIP/CUDA and OpenMP
  • Hybrid parallel programming combining MPI with OpenMP and HIP/CUDA (multi-GPU programming)
  • Principles of efficient parallel input/output in supercomputers
  • Applying learned concepts in HPC and AI applications

Learning outcomes

The goal is to build HPC expertise up to an intermediate/semi-advanced level during the school.

After the summer school participants will be able to:

  • Identify main parallel programming concepts
  • Create parallel MPI programs with C, C++, or Fortran programming languages
  • Create GPU-accelerated programs
  • Recognize advanced parallel programming constructs
  • Read and modify scientific applications implemented in C, C++, or Fortran and utilizing MPI, OpenMP, and/or HIP/CUDA

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