PHYS-743 / 3 crédits

Enseignant(s): Lanti Emmanuel, Richart Nicolas

Langue: Anglais

Remark: Next time: Fall (Block course)


Frequency

Every year

Summary

Learn the concepts, tools and API's that are needed to debug, test, optimize and parallelize a scientific application on a cluster from an existing code or from scratch. Both OpenMP (shared memory) and MPI (distributed memory) paradigms are presented and experimented.

Content

Keywords

OpenMP, MPI, HPC, Parallel programming

Learning Prerequisites

Required courses

  • Basic knowledge of C, C++, Fortran or Python.
  • Basic knowledge of Linux and bash scripting

Recommended courses

Learning Outcomes

By the end of the course, the student must be able to:

  • Optimize sequential and parallel codes
  • Implement algorithms in parallel with OpenMP and MPI
  • investigate the performances of parallel code

Resources

Notes/Handbook

By the end of the course, the student must be able to:

  • Optimize sequential and parallel codes
  • Implement algorithms in parallel with OpenMP and MPI
  • Investigate the performances of parallel code

Moodle Link

Dans les plans d'études

  • Nombre de places: 15
  • Matière examinée: Parallel programming
  • Cours: 20 Heure(s)
  • Exercices: 20 Heure(s)
  • TP: 16 Heure(s)

Semaine de référence

Cours connexes

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