guest ::
| Home > Publications database > Deep Learning on Supercomputers |
| Home > Publications database > Deep Learning on Supercomputers |
| Lecture (Other) | FZJ-2025-01619 |
; ;
2024
Abstract: 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 portalSystem access via SSH, Jupyter, and UNICORESystem configuration for JURECA and JUWELSFile systems, I/O, and data managementSoftware modules (compilers, MPI, math libraries, applications, debuggers, tools)Building software from sourceSubmitting jobs via the resource managerUsing GPUsPerformance tuningDeep LearningVisualization
|
The record appears in these collections: |
