Course

PHYS-743: Parallel programming

Summary

Learn to debug, benchmark, optimize, and parallelize scientific applications on HPC clusters using OpenMP and MPI. Through profiling and measurement, you'll identify bottlenecks, evaluate optimizations, and understand performance using a finite-difference Poisson solver as a case study.

Lectures

Instructors (2)

Emmanuel Lanti

Teaching & PhD Courses Parallel programming PHYS-743 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.

Nicolas Richart

I graduated as an engineer in computer science in 2005 at the Ecole National Superieur en Electronique Informatique et Radiocomunication de Bordeaux (ENSEIRB). My degree is colored by an option od High Performance Computing (HPC). Then I made my thesis at LaBRI/INRIA Bordeaux in the ScalApplix/HiePACS team, on the in-situ steering of coupled parallel numerical simulations. I graduated as a Ph D. of computer science of the Universite de Bordeaux 1 in 2010. Since then I am working at EPFL in the Laboratoire de Simulations en Mechanique des Solides (LSMS) as a scientific collaborator.

Official source

https://edu.epfl.ch/coursebook/en/parallel-programming-PHYS-743

Moodle Page

http://go.epfl.ch/PHYS-743

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Summary

Lectures

Instructors (2)

Emmanuel Lanti

Nicolas Richart

Official source

https://edu.epfl.ch/coursebook/en/parallel-programming-PHYS-743

Moodle Page

http://go.epfl.ch/PHYS-743

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