OpenACC Tutorial: Difference between revisions
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== Lesson plan == | == Lesson plan == | ||
* [[OpenACC Tutorial - Introduction|Introduction]] | * [[OpenACC Tutorial - Introduction|Introduction]] | ||
* [[OpenACC Tutorial - Profiling|Gathering a profile]] | * [[OpenACC Tutorial - Profiling|Gathering a profile and getting compiler information]] | ||
* [[OpenACC Tutorial - Adding directives|Expressing parallelism with OpenACC directives]] | |||
* [[OpenACC Tutorial - Data movement|Expressing data movement]] | |||
* [[OpenACC Tutorial - Optimizing loops|Optimizing loops]] | |||
== External references == | == External references == | ||
Revision as of 18:39, 3 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 annotated 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
- Introduction
- Gathering a profile and getting compiler information
- Expressing parallelism with OpenACC directives
- Expressing data movement
- Optimizing loops
External references
Here are some useful external references: