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GPU Programming with OpenACC
Date: 04.12.2017 9:00 - 05.12.2017 16:00
Location details: The event is organised at the CSC Training Facilities located in the premises of CSC at Keilaranta 14, Espoo, Finland. The best way to reach us is by public transportation; more detailed travel tips are available.
Language: english-language
lecturers: Sami Ilvonen (CSC)
Fredrik Robertsén (CSC)
  • free-price-finnish-academics.
  • free-price-others.
The course materials, lunches as well as morning and afternoon coffees are free of charge.
The seats are filled in the registration order. If you have registered to this course and you are not able to attend, please cancel your registration in advance.
Additional Information
This course is part of the PRACE Advanced Training Centres (PATCs) activity. Please visit the PRACE Training portal for further information about the course. For content please contact, for practicalities


This course gives a thorough introduction to programming GPUs using the directive based OpenACC paradigm. The course consists of lectures and hands-on exercises. Topics of this course include the basic usage of OpenACC, as well as some more advanced issues related to profiling, performance and interoperability with CUDA.

Learning outcome

After the course the participants should have the basic skills needed for utilizing OpenACC in new, or existing programs.


The participants are assumed to have working knowledge of Fortran and/or C programming languages. In addition, fluent operation in a Linux/Unix environment will be assumed.

Day 1, Monday 4.12

09:00 - 12:00 SESSION 1 & Coffee break

  • Introduction to accelerators​
  • Introduction to OpenACC
  • Exercises

12:00 - 13:00 Lunch

13:00 - 16:00 SESSION 2 & Coffee break

  • Data movement
  • Exercises

Day 2, Tuesday 5.12

09:00 - 12:00 SESSION 3 & Coffee break

  • Profilling
  • Performance considerations
  • Exercises

12:00 - 13:00 Lunch

13:00 - 16:00 SESSION 4 & Coffee break

  • Asynchronous operations and pipelining
  • Interoperability with CUDA and GPU-Accelerated libraries
  • Exercises