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Effective High-Performance Computing & Data Analytics

People

Schenk O.

Course director

Description

  • GPU and ARM architectures
  • GPU programming (CUDA ), and ARM programming
  • Performance optimization and scientific libraries (Kokkos)
  • Interactive supercomputing (JupyterLab)
  • Python HPC libraries (Numpy/SciPy/Dask/Numba)
  • Introduction to Machine Learning and GPU optimized frameworks (Rapids)
  • Deep Learning on HPC platforms

Objectives

This CSCS/USI 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. The content of the course is tailored for intermediate graduate students (3rd year Bachelor's students, Master’s students, and Ph.D students) interested in both learning parallel programming models and having hands-on experience using HPC systems. 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 course "Effective High-Performance Computing & Data Analytics" will be offered online as well to also allow double-degree Master's students and EUMaster4HPC Master's students to enroll.

Teaching mode

In presence

Learning methods

Extensive practical and exercise lab sessions.

Examination information

 The examination method will be an online quiz on the last day of the summer university program on Thursday, July 20,  2023, at 13:30 CEST (Central European Summer Time).

Education

Prerequisite