Most HPC systems are clusters of shared memory nodes. To use such systems efficiently both memory consumption and communication time has to be optimized. Therefore, hybrid programming may combine the distributed memory parallelization on the node interconnect (e.g., with MPI) with the shared memory parallelization inside of each node (e.g., with OpenMP or MPI-3.0 shared memory). This course analyzes the strengths and weaknesses of several parallel programming models on clusters of SMP nodes. Multi-socket-multi-core systems in highly parallel environments are given special consideration. MPI-3.0 has introduced a new shared memory programming interface, which can be combined with inter-node MPI communication. It can be used for direct neighbor accesses similar to OpenMP or for direct halo copies, and enables new hybrid programming models. These models are compared with various hybrid MPI+OpenMP approaches and pure MPI. Numerous case studies and micro-benchmarks demonstrate the performance-related aspects of hybrid programming.
Hands-on sessions are included on all days. Tools for hybrid programming such as thread/process placement support and performance analysis are presented in a "how-to" section. This course provides scientific training in Computational Science and, in addition, the scientific exchange of the participants among themselves.
This course is a PRACE training event. It is organized by the VSC Research Center, TU Wien, in cooperation with HLRS and NHR@FAU.
Online course Organizer: VSC Research Center, TU Wien, Austria
Dec 12, 2022
Dec 14, 2022
Online by VSC Vienna
Programming Languages for Scientific Computing
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Learn more about course curricula and content levels.
Georg Hager (NHR@FAU, Uni. Erlangen), Rolf Rabenseifner (HLRS, Uni. Stuttgart), Claudia Blaas-Schenner (VSC Research Center, TU Wien)
1st day – 13 December 2022
08:45 Join online 09:00 Welcome 09:05 Motivation 09:15 Introduction 09:30 Programming Models 09:35 - MPI + OpenMP 10:00 Practical (how to compile and start) 10:30 Break 10:45 - continue: MPI + OpenMP 11:30 Break 11:45 - continue: MPI + OpenMP 12:30 Practical (how to do pinning) 13:00 Lunch 14:00 Practical (hybrid through OpenMP parallelization) 15:30 Q & A, Discussion 16:00 End of first day
2nd day – 14 December 2022
08:45 Join online 09:00 - Overlapping Communication and Computation 09:30 Practical (taskloops) 10:30 Break 10:45 - MPI + OpenMP Conclusions 11:00 - MPI + Accelerators 11:30 Tools 11:45 Break 12:00 Programming Models (continued) 12:05 - MPI + MPI-3.0 Shared Memory 13:00 Lunch 14:00 Practical (replicated data) 15:30 Q & A, Discussion 16:00 End of second day
3rd day – 15 December 2022
08:45 Join online 09:00 - MPI Memory Models and Synchronization 09:40 - Pure MPI 10:00 Break 10:15 - Recap - MPI Virtual Topologies 10:45 - Topology Optimization 11:15 Break 11:30 Practical/Demo (application aware Cartesian topology) 12:30 - Topology Optimization (Wrap up) 12:45 Conclusions 13:00 Lunch 14:00 Finish the hands-on labs, Discussion, Q & A, Feedback 16:00 End of third day (course)
A link to the course material (slides and exercises) will be available at course start
Register via the button at the top of this page.
Registration period is from 3 Oct to 30 Nov 2022, and follows the "first come – first served" principle. Following your successful registration, you will receive further information approx. 1 week before the course. For the online course we can take a maximum of 40 persons. Additional registrations will be added to a waiting list.
Claudia Blaas-Schenner and Ulrike Faltin: trainingvsc.ac.at
https://www.hlrs.de/training/2022/HY-VSC2 or https://vsc.ac.at/training/2022/HY-VSC-Dec (at VSC)
See the training overview and the Supercomputing Academy pages.
https://vsc.ac.at/training (at the VSC Research Center, TU Wien)
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High-Performance Computing Center Stuttgart
Nobelstraße 19, 70569 Stuttgart, Germany
+49 (0) 711 / 685-87 209
A member of the Gauss Centre for Supercomputing, HLRS is one of three German national centers for high-performance computing.
HLRS is a central unit of the University of Stuttgart.