Distributed memory parallelization with the Message Passing Interface MPI (Mon, for beginners): On clusters and distributed memory architectures, parallel programming with the Message Passing Interface (MPI) is the dominating programming model. The course gives an introduction into MPI-1. Hands-on sessions (in C, Fortran, and Python) will allow users to immediately test and understand the basic constructs of the Message Passing Interface (MPI).
Shared memory parallelization with OpenMP (Tue, for beginners): The focus is on shared memory parallelization with OpenMP, the key concept on hyper-threading, dual-core, multi-core, shared memory, and ccNUMA platforms. This course teaches shared memory OpenMP parallelization. Hands-on sessions (in C and Fortran) will allow users to immediately test and understand the directives and other interfaces of OpenMP. Race-condition debugging tools are also presented.
Intermediate and advanced topics in parallel programming (Wed-Fri): Topics are advanced usage of communicators and virtual topologies, one-sided communication, derived datatypes, MPI-2 parallel file I/O. MPI-3.0 introduced a new shared memory programming interface, which can be combined with MPI message passing and remote memory access on the cluster interconnect. It can be used for direct neighbor accesses similar to OpenMP or for direct halo copies, and enables new hybrid programming models. Several aspects of hybrid mixed model MPI+OpenMP parallelization are discussed in the MPI and OpenMP advanced topics.
HLRS, University of Stuttgart Nobelstraße 19 70569 Stuttgart, Germany Room 0.439 / Rühle Saal Location and nearby accommodations
Oct 14, 2024 08:30
Oct 18, 2024 17:00
Stuttgart, Germany
English
Basic
Parallel Programming
MPI
OpenMP
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Unix / C or Fortran (or Python for the MPI part)
Learn more about course curricula and content levels.
Dr. Rolf Rabenseifner and Prof. Dr.-Ing. Rainer Keller.
Please refer to the course overview.
This course provides scientific training in Computational Science, and in addition, the scientific exchange of the participants among themselves.
All times are local times in the Central European Summer Time zone (Berlin).
See link to detailed program (preliminary program)
Each participant will get all slides as pdf and all exercises as tar.gz and zip archive.
Most MPI exercises are (in addition to C and Fortran) also available for Python+mpi4py+numpy.
Besides the content of the training itself, an important aspect of this event is the scientific exchange among the participants. We try to facilitate such communication by
Please be informed that recomendations according to the Occupational Safety and Health Measures of the University of Stuttgart at the time of event and additional rules might be applied.
Register via the button at the top of this page (will be available soon).
Link to the EU and EU-associated (Horizon Europe), and PRACE countries.
Our course fees include coffee breaks (in classroom courses only).
Khatuna Kakhiani phone 0711 685 65796, khatuna.kakhiani(at)hlrs.de
Maksym Deliyergiyev phone 0711 685 87261, maksym.deliyergiyev(at)hlrs.de
In conjunction with this course, a Train the Trainer Program is provided. Whereas this regular course teaches parallel programming, the Train the Trainer Program is an education for future trainers in parallel programming. For further details, see here.
HLRS is part of the Gauss Centre for Supercomputing (GCS), together with JSC in Jülich and LRZ in Garching near Munich. EuroCC@GCS is the German National Competence Centre (NCC) for High-Performance Computing. HLRS is also a member of the Baden-Württemberg initiative bwHPC.
This course is provided within the framework of the bwHPC training program.
https://www.hlrs.de/training/2024/PAR and http://www.hlrs.de/training/2024/TtT
See the training overview and the Supercomputing Academy pages.
November 04 - December 06, 2024
Online (flexible)
December 02 - 05, 2024
Online by JSC
January 13 - 31, 2025
Hybrid Event - Stuttgart, Germany
January 21 - 23, 2025
February 17 - 21, 2025
March 17 - 21, 2025
Dresden, Germany
