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Effective High-Performance Computing & Data Analytics

Descrizione

COURSE OBJECTIVES

This 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 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 will be offered online to also allow double-degree Master students to enroll.

 

COURSE DESCRIPTION

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)

 

LEARNING METHODS

Extensive practical and exercise lab sessions.

 

EXAMINATION INFORMATION
Written exam.

 

REFERENCES
For all additional information please refer to the course website from 2021: https://www.cscs.ch/events/upcoming-events/event-detail/cscs-usi-summer-school-2021/

Persone

 

Schenk O.

Docente titolare del corso

Informazioni aggiuntive

Semestre
Primaverile
Anno accademico
2021-2022
ECTS
4
Lingua
Inglese
Offerta formativa
Master of Science in Artificial Intelligence, Corso a scelta, Corso, 1° anno (6 ECTS)
Master of Science in Artificial Intelligence, Corso a scelta, Corso, 2° anno (6 ECTS)
Master of Science in Computational Science, Corso a scelta, Corso, 1° anno (6 ECTS)
Master of Science in Computational Science, Corso a scelta, Corso, 2° anno (6 ECTS)
Dottorato in Scienze informatiche, Scuola estiva, Corso, 1° anno
Dottorato in Scienze informatiche, Scuola estiva, Corso, 2° anno