April 02, 2019 - by CSCS
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 (students with a Master’s degree, Ph.D. students, and early stage postdocs) 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:
First week
- GPU architectures
- GPU programming (CUDA and OpenACC)
- Message passing programming model (MPI)
- Performance optimization and scientific libraries
Second week
- Interactive supercomputing
- Python HPC libraries
- 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 theoretical material.
Lectures will be held by ETH Zurich / CSCS, USI, NVIDIA and Cray experts.
Students will be able to earn six ECT credit points for this course from Università della Svizzera italiana (subject to exam).
More details, including the application procedure, can be found in the CSCS event page >