Section outline

  • Dear Fellows,
    we look forward to welcoming you to the Summer School 2024 of the NHR Graduate School. The NHR Summer School, organized by the NHR Alliance and the following NHR centres, aims to convey HPC knowledge and software development skills to all fellows of the NHR Graduate School. In addition, special emphasis is given to networking and communication training as well as career planning.

    The following NHR centres and the NHR Office organizes the NHR Summer School 2024:
    This Moodle page provides all necessary information, including links to lecture slides and miscellaneous material.

    If you have any further questions on the NHR Summer School 2024, please contact us.

    The NHR Team will be available by phone during the NHR-Summer School 2024

    Monique Drees, NHR-Office: 0171-2100 151 (Mo – Tue; Thu-Fri)
    Diana Häsener, ZIH-Office: 0351-463 40783 (Mo – Fri).




    Date:
    June 10-14, 2024

    Location:
    Zentrum für Informationsdienste und Hochleistungsrechnen (ZIH), TU Dresden
    Zellescher Weg 12
    01069 Dresden
    Germany
    Willers-Bau, A-Wing
    PC-Pool WIL-A119
    1. Floor.


    Accomodation:
    Hotel ibis Dresden Zentrum
    Prager Straße 5
    01069 Dresden
    Phone: +49(0)351 48564856
    E-Mail: ww.ibis-dresden.de

    Travel Advice:
    Bus route 66 from Dresden main station "Unter den Brücken" to "Dresden Techn. Universität" (two stations; bus direction: Freital Deuben).
    350 m walk from station "Dresden Techn. Universität" to "Zentrum für Informationsdienste und Hochleistungsrechnen (ZIH), TU Dresden".

    Wifi access
    We recommend logging in via eduroam to the university Wifi. If you already using eduroam at your NHR home centre, it should work automatically on the host campus.
    If you haven't used eduroam before, please follow the set-up instructions of your NHR home centre, ideally before your start at the NHR Summer School.
  • To tailor the program to the knowledge and experience of all participants in the best possible way, we kindly ask you to carry out the survey on your HPC knowledge level.
    Participation will take approx. 2 minutes. All answers are anonymous.
    https://event.zih.tu-dresden.de/nhr/summerschool/survey.

    Participation is required. Please complete the questionnaire by April 24, 2024. 

    • Welcome Event and Get-Together
      *We kindly ask you to check in at the hotel at least 2 hours before the start of the event.

      Agenda
      14:00 -14:30  Welcome
      14:30 - 16:00 Getting to know each other via presentations (research topics and self-presentations, 3 min for each fellow)
      16:00 - 17:30 Guided tour in the ScaDS.AI Living Lab, Location: APB-1020
      17:30 - Informal Get-Together and joint dinner at Willers-Bau
    • Opened: Monday, 8 April 2024, 12:00 AM
      Due: Sunday, 9 June 2024, 12:00 AM

      Fellows should give a short presentation on themselves and their research work to a maximum of 3 minutes.

    • Machine Learning Course, organized by NHR@TUD & ScaDS.AI
         
      Agenda:
      09:00 – 10:30     ML on HPC, Part I
      10:30 – 11:00     Break
      11:00 – 11:30     ML on HPC, Part II + Q&A session
      11:30 – 12:30     Hackathon (Intro
      +team building)
      12:30 – 13:30     Lunch Break
      13:30 – 14:00     Guided Hands-On: ML on HPC
      14:00 – 17:00     Hackathon
      17:00 – 18:00     Evaluation & Lessons Learned 
      19:00                 Joint dinner at Augustusgarten Dresden
      Directions to Dinner: see below


      Lecturers: Christoph Lehmann, Elias Werner, Lalith Manjunath, Lena Jurkschat, Apurv Deepak Kulkarni, Norman Koch
      On Tuesday we will learn how to bring Machine Learning workflows to HPC. Due to the heterogeneity of Machine Learning applications, the motivation to move to an HPC system can be manifold, e.g. due to large memory requirements, GPU usage or increase in computational speed. Participants will learn how a typical machine learning workflow can be realised in the HPC environment. It is possible to switch to the HPC system at different points in the workflow, depending on the requirements. The development of machine learning applications is often done in groups, which is also taken into account in the implementation of the machine learning workflow.
      The guided hands-on and hackathon format provides a perfect opportunity to get in touch with the ZIH HPC system, to practice the learned HPC principles and to set up a machine learning pipeline for image classification in a competitive way.
      A computer or laptop with SSH access to the cluster is required to take part in the hands-on section of this course. No further pre-knowledge is required.
    • Course on Parallel I/O, organized by NHR@Göttingen
      Topic: Holistic HPC I/O Evaluation (H2IO)
      Agenda:

      Evening program for own design

      Lecturers 
      Kevin Lüdemann (GWDG, IO)
      Mohammad Hossein Biniaz (GWDG, ML)
      This day will provide an introduction to storage types with an emphasis on parallelism. Participants will get to know distributed filesystems and experiment with storage API on them. Again, strong emphasis will be on how to optimize an application to utilize the underlying system to its maximum. Example applications will include standard MPI applications, but special attention will be given to machine learning-type applications.

      After the lunch break, benchmarking and performance engineering will be introduced and directly used to analyse the popular benchmarking suit IO500. The knowledge gained will be applied to a theoretical roofline model and compared with data collected before the course from several NHR systems.
      The course is rounded off by exploring alternative storage APIs like MPI-IO, HDF5, and are compared with the standard API called POSIX.

      Pre-Requisites
      A computer or laptop with SSH access to the cluster is required to take part in the hands-on section of this course.
      Time series and benchmark results of the full system will be provided, and a scaled down version of the IO500 will be set up for running the highly IO-intensive benchmark.


      Update 20.05.2024

      The content for this day is uploaded except for the part we are developing new. These slides will change in appearance, but the content stays.

      Update 05.06.2024

      We updated the timetable since we dropped the analysis tool section and increased the API part to include a longer hands on section. Additionally, we drop all the breaks, since there is no time to waste ... Just kidding (maybe). Further updates of the content will be done in the following days.

      Update 08.06.2024

      We updated the API slides. For the exercise, you need to know python. It is also enough if you know someone, who is there and know python. We will work in groups.

  • Applied Quantum Computing, organized by NHR@SW

    09:00 – 09:30                 Introduction / General Information
    09:30 – 10:30                 Introduction to Quantum Computing (QC)
    10:30 – 11:00                 Coffee Break
    11:00 – 12:30                 Gate-Based QC & Variational Methods
    12:30 – 13:30                 Lunch Break
    13:30 – 15:00                 Quantum Annealing
    15:00 – 15:30                 Coffee Break
    15:30 – 18:00                 Hands-On Sessions (Annealing & Gate-Based)

    18:30 onwards                organized evening program with joint dinner
                                            (more information see PDF below)

    Thursday is all about quantum computing. In the morning, an introduction to quantum computing (QC), its formalisms, and mathematical descriptions from the start of this workshop. Once the foundations have been laid, we will dive deeper into the world of gate-based QC and Variational Quantum Algorithms (VQA). In the afternoon, participants will be introduced to quantum annealing before deepening what has been learned with hands-on sessions featuring topics of gate-based QC as well as quantum annealing.

    Lecturers
    Dr. Manpreet Singh Jattana (Postdoc Goethe University - MSQC)
    Philip Döbler (Ph.D. Student Goethe University - MSQC)
    Cedric Gaberle (Ph.D. Student Goethe University - MSQC)
    Further information: https://msqc.uni-frankfurt.de/

    Pre-Requisites
    Working knowledge of Python to execute the code on Jupyter notebooks. Please bring your laptop. No previous knowledge of quantum mechanics is necessary to participate. Some knowledge of classical optimization algorithms and Qiskit is helpful but optional. 
    We ask you to create a virtual environment for the hands-on session. The file "requirements.txt" below lists all the packages you will need among other requirements.
    If you have any further questions or problems with the installation, please contact Mr. Manpreet Singh Jattana via: jattana@em.uni-frankfurt.de.




  • Soft-Skills Training, organized by the NHR Office

    Agenda
    09:00-14:30 - 1st cohort: Career planning and networking
    09:00-14:30 - 2nd cohort: Self-presentation and effective communication
    09:00-14:30 - 3rd cohort: Intercultural communication, anti-bias training

    10:15 - 10:30 Coffee break
    11:30 - 12:00 Lunch break
    13:30 - 13:45 Coffee break

    15:00 Farewell and departure

    Lecturers: 
    1st cohort - Dr. Cornelia Rahn, Career planning and networking for academics, https://www.corneliarahn.de/
    2nd cohort - Konstanze Bittmann, Successful communication and presentation for scientists, https://www.konstanzebittmann.de/zur-person/
    3rd cohort - Nora Benariba + Dennis Sadiq Kirschbaum, intercultural communication, Antibias, glokal e.V., https://www.glokal.org/en/about-us/