OpenACC Tutorial: Difference between revisions

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* [[OpenACC Tutorial - Data movement|Expressing data movement]]
* [[OpenACC Tutorial - Data movement|Expressing data movement]]
* [[OpenACC Tutorial - Optimizing loops|Optimizing loops]]
* [[OpenACC Tutorial - Optimizing loops|Optimizing loops]]
* [[OpenACC Tutorial - Conclusion|Conclusion]]


== External references ==
== External references ==

Revision as of 17:37, 18 May 2016

Introduction

This tutorial is strongly inspired from the OpenACC Bootcamp session presented at GPU Technology Conference 2016.

OpenACC is an application programming interface (API) for porting code onto accelerators such as GPU and coprocessors. It has been developed by Cray, CAPS, NVidia and PGI. Like in OpenMP, the programmer annotates C, C++ or Fortran code to identify portions that should be parallelized by the compiler.


Prerequisites for this tutorial

This tutorial uses OpenACC to accelerate C, C++ or Fortran code. A working knowledge of one of these languages is therefore required to gain the most benefit out of it.



Getting ready

This tutorial is based on examples. You can download all of the examples in this Github repository.


Lesson plan

External references

Here are some useful external references: