Effective High-Performance Computing & Data Analytics Summer School
This summer school 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 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 following topics will be covered: • GPU programming • Performance optimization and scientific libraries • Interactive supercomputing (JupyterLab) • Python HPC libraries (Numpy/SciPy/Dask/Numba/CuPy) • Introduction to Machine Learning and GPU optimized frameworks (Rapids) • Deep Learning on HPC platforms (TensorFlow)
Extensive practical and exercise lab sessions will help to clarify and consolidate the material
- For all additional information please refer to the summer school website