Effective High-Performance Computing & Data Analytics

This CSCS/USI HPC summer university course will focus on the effective exploitation of state-of-the-art hybrid High-Performance Computing (HPC) systems with a special focus on Data Analytics. Starting from an introductory explanation of the available systems at CSCS, the course will progress to more applied topics such as parallel programming on accelerators, code optimization, scientific libraries, and deep learning software frameworks. The following topics will be covered:

• GPU architectures
• GPU programming (CUDA)
  • Programming model
  • Memory management
  • Performance optimization and scientific libraries
• GPU-Accelerated Computing with Python
  • NumPy-like libraries for both CPUs and GPUS computing
  • Just-in-time compilation from Python code
  • Distributed workloads on HPC clusters

The summer university will be organized on 19.07.2025-25.07.2025. Further information and content is available on the HPC Summer University 2025 page.

The content of the course is tailored for intermediate graduate students (Master’s students, and Ph.D students, in particular EUMaster4HPC students) interested in both learning parallel programming models and having hands-on experience using HPC systems, including GPUs. 

In presence

Extensive lab sessions will help to clarify and consolidate the theoretical material. The in-person training will be composed of lectures and interactive sessions for hands-on exercises, as well as Q&A. We are aiming at limiting the lectures to 50% so as to have enough time for hands-on; however, the mileage may vary depending on the topic. 

On the last day of the course students will have the possibility to take an exam in order to obtain ECT credit points (6 ECTS for MSc students / 4 ECTS for PhD students), provided that they pass the exam. The examination method will be a quiz. The examination will be graded on a binary basis (pass/fail). A pass in the examination results in 6 ECTS credits being awarded for this course.

• CSCS, 25.07.25 - 25.07.25 (Optional)