1st Block: Linux and First Steps on the VSC-3 Cluster
Date and Time: March 14, 2019, 14:00 - 18:00
Location: TU Wien, FH Schulungsraum ZID (TU Wien, Wiedner Hauptstraße 8-10, ground floor, red area)
Lecturers: VSC Team (Claudia Blaas-Schenner, Siegfried Höfinger, Dieter Kvasnicka,
Balazs Lengyel, Irene Reichl, Siegfried Reinwald, Markus Stöhr, Jan Zabloudil)
Details and Registration see: http://vsc.ac.at/training/2019/VSC-Linux-Mar
Abstract:
This Linux command-line course is for users (or soon to be users) of the VSC-3 cluster only. You will learn how to login to VSC-3 and step-by-step we will show you how to work on the Linux command line and a few basic things that will help you to organise your workflows on the cluster. Focusing on hands-on teaching throughout the course, you will immediately try out what you've heard and adapt it to your own needs. After attending this course you are prepared for and might consider to continue with "Introduction to Working on the VSC-3 Cluster" to be able to use the VSC-3 supercomputer and especially its queuing system efficiently.
2nd Block: Introduction to Working on the VSC-3 Cluster
Date and Time: March 19, 2019, 09:00 - 16:00
Location: TU Wien, FH Schulungsraum ZID (TU Wien, Wiedner Hauptstraße 8-10, ground floor, red area)
Lecturers: VSC Team (Claudia Blaas-Schenner, Siegfried Höfinger, Dieter Kvasnicka,
Balazs Lengyel, Irene Reichl, Siegfried Reinwald, Markus Stöhr, Jan Zabloudil)
Details and Registration see: http://vsc.ac.at/training/2019/VSC-Intro-Mar
Abstract:
In this course we will help you getting started on the VSC-3 cluster, Austria's most powerful supercomputer. With running and developing software on a supercomputer there are many similarities and fewer but crucial differences compared to your desktop PC. Focusing on hands-on teaching throughout the course, you will immediately try out what you've heard and adapt it to your own needs. This lecture is equally relevant to those who will merely be running existing software as to those who will develop scientific codes.
3rd Block: Deep Learning and GPU programming using OpenACC
Date and Time: March 27 - 29, 2019, 09:00 - 17:00
Location: TU Wien, FH Internet-Raum FH1 (TU Wien, Wiedner Hauptstraße 8-10, ground floor, red area)
Lecturers: Yu Wang (LRZ), Volker Weinberg (LRZ), Georg Zitzlsberger (IT4Innovations)
Details and Registration see: http://vsc.ac.at/training/2019/DL/
Abstract:
Learn how to train and deploy a neural network to solve real-world problems, how to generate effective descriptions of content within images and video clips and how to accelerate your applications with OpenACC. The workshop combines lectures about fundamentals of Deep Learning for Computer Vision and Multiple Data Types with a lecture about Accelerated Computing with OpenACC. The lectures are interleaved with many hands-on sessions using Jupyter Notebooks. The exercises will be done on a fully configured GPU-accelerated workstation in the cloud.
4th Block: Parallelization with MPI
Date and Time: May 13 - 15, 2019, 09:00 - 16:30 (15.05. until 16:00)
Location: TU Wien, FH Internet-Raum FH1 (TU Wien, Wiedner Hauptstraße 8-10, ground floor, red area)
Lecturers: Claudia Blaas-Schenner and Irene Reichl (VSC Team, TU Wien)
Details and Registration see: http://vsc.ac.at/training/2019/MPI
Abstract:
On clusters and distributed memory architectures, parallel programming with the Message Passing Interface (MPI) is the dominating programming model. This 3 days course teaches parallel programming with MPI starting from a beginners level. Hands-on sessions (in C and Fortran) will allow users to immediately test and understand the basic constructs of the Message Passing Interface (MPI).
5th Block: Shared memory parallelization with OpenMP
Date and Time: May 16 - 17, 2019, 09:00 - 16:40
Location: TU Wien, FH Internet-Raum FH1 (TU Wien, Wiedner Hauptstraße 8-10, ground floor, red area)
Lecturers: Lukas Einkemmer (lectures+practicals; Department of Mathematics, University of Innsbruck),
Claudia Blaas-Schenner and Irene Reichl (practicals only; VSC Team, TU Wien)
Details and Registration see: http://vsc.ac.at/training/2019/OpenMP
Abstract:
The focus of this 2 days course is on shared memory parallelization with OpenMP for dual-core, multi-core, shared memory, and ccNUMA platforms. This course teaches OpenMP starting from a beginners level. Hands-on sessions (in C and Fortran) will allow users to immediately test and understand the OpenMP directives, environment variables, and library routines. Race-condition debugging tools are also presented.
6th Block: Introduction to Working on the VSC-3 Cluster
Date and Time: June 4, 2019, 09:00 - 16:00
Location: TU Wien, FH Schulungsraum ZID (TU Wien, Wiedner Hauptstraße 8-10, ground floor, red area)
Lecturers: VSC Team (Claudia Blaas-Schenner, Siegfried Höfinger, Dieter Kvasnicka,
Balazs Lengyel, Irene Reichl, Siegfried Reinwald, Markus Stöhr, Jan Zabloudil)
Details and Registration see: http://vsc.ac.at/training/2019/VSC-Intro-Jun
Abstract:
In this course we will help you getting started on the VSC-3 cluster, Austria's most powerful supercomputer. With running and developing software on a supercomputer there are many similarities and fewer but crucial differences compared to your desktop PC. Focusing on hands-on teaching throughout the course, you will immediately try out what you've heard and adapt it to your own needs. This lecture is equally relevant to those who will merely be running existing software as to those who will develop scientific codes.
7th Block: Introduction to Hybrid Programming in HPC
Date and Time: June 12 - 13, 2019, 08:45 - 17:00 (June 13: 09:00 - 16:30)
Location: TU Wien, FH Internet-Raum FH1 (TU Wien, Wiedner Hauptstraße 8-10, ground floor, red area)
Lecturers: Georg Hager (RRZE / HPC, Uni. Erlangen), Rolf Rabenseifner (HLRS, Uni. Stuttgart),
Claudia Blaas-Schenner and Irene Reichl (VSC Team, TU Wien)
Details and Registration see: http://vsc.ac.at/training/2019/HY-VSC
Abstract:
Most HPC systems are clusters of shared memory nodes. Such SMP nodes can be small multi-core CPUs up to large many-core CPUs. Parallel programming may combine the distributed memory parallelization on the node interconnect (e.g., with the Message Passing Interface - MPI) with the shared memory parallelization inside of each node (e.g., with OpenMP or MPI-3.0 shared memory). This course analyses the strengths and weaknesses of several parallel programming models on clusters of SMP nodes. 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.
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