Introduction to Supercomputing at JSC - Theory & Practice

Course/Event Essentials

Event/Course Start
Event/Course End
Event/Course Format
Online
Live (synchronous)

Venue Information

Country: Germany
Venue Details: Click here

Training Content and Scope

Scientific Domain
Level of Instruction
Beginner
Sector of the Target Audience
Research and Academia
HPC Profile of Target Audience
Application Users
Application Developers
Data Scientists
Language of Instruction

Other Information

Organiser
Event/Course Description

Disclaimer: This course offers the opportunity to attend lectures selectively, based on individual needs and knowledge levels. Participants are not required to attend all sessions as some may cover advanced or basic material. While flexibility is offered, it is important to assess personal needs and choose sessions accordingly, as attending lectures out of order may result in knowledge gaps.

Research Centre Jülich provides cutting-edge high-performance computing resources to scientific groups and industry partners across Germany and Europe via the John von Neumann Institute for Computing. To help new users of JSC's supercomputers efficiently leverage their allocated resources, we offer an introductory course that covers system basics and best practices.

The course includes theoretical lectures held every afternoon from Monday to Thursday, and practical tutorials offered in the mornings from Tuesday to Thursday. The tutorials are based on the previous afternoon's lectures and allow articipants to put theory into practice. We cover a wide range of topics, starting from basic log-in procedures to intermediate-level techniques. Participants are free to choose the lectures that best match their needs and interests.

Topics covered include:

  • User account management with the JuDoor portal
  • System access via SSH, Jupyter, and UNICORE
  • System configuration for JURECA and JUWELS
  • File systems, I/O, and data management
  • Software modules (compilers, MPI, math libraries, applications, debuggers, tools)
  • Building software from source
  • Submitting jobs via the resource manager
  • Using GPUs
  • Performance tuning
  • Deep Learning
  • Visualization