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Introduction and training "Intel KNL Many-Core - usage and profiling"

(Course no. 12720182 in the training programme 2018 of Forschungszentrum Jülich)

begin
03 Sep 2018 11:00
end
06 Sep 2018 12:00
venue
Jülich Supercomputing Centre, Rotunda, building 16.4, room 301

 IMPORTANT:

  • This course is exclusively for users of JSC's supercomputers JUWELS and JURECA
  • Participants need to bring their own laptop and need to be able to access JURECA from it
Target audience:
Users of the supercomputers in Jülich
Contents:

The Research Centre Juelich has extended its general purpose supercomputing system JURECA with a Booster module based on Intel’s KNL architecture. The aim of this course is to give users of the supercomputing resources an introductory overview of the KNL architecture and its usage, and to help them in making efficient use of their allocated resources.
Topics covered include

  • Overview of the KNL architecture
  • Building code for KNL
  • Analysing code correctness and performance
  • Vectorisation
  • Roof-line analysis
  • Performance tuning
  • "Bring-your-own-code" hands-on sessions
  • Special topics depending on users' interest

This course is exclusively for users of JSC’s supercomputers JUWELS and JURECA. Participants need to bring their own laptop and need to be able to access JURECA from it.

Prerequisites:
User account on and basic knowledge of JURECA or JUWELS
Agenda:
 Agenda of Introduction and training "Intel KNL Many-Core - usage and profiling" (PDF, 44 kB)
Language:
This course is given in English.
Duration:
3,5 days
Date:
3-6 September 2018,
starting on 3 September at 11:00, ending on 6 September at 12:00
Venue:
Jülich Supercomputing Centre, Rotunda, building 16.4, room 301
Number of participants:
maximum 25
Instructors:
Representatives of Intel, JSC staff members
Contact:
sc@fz-juelich.de
Registration:
Please register until 27 August via the registration form.
Announcement as pdf file:
 Announcement of the training course "Introduction and training ’Intel KNL Many-Core - usage and profiling’" (PDF, 47 kB)

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