OpenACC Tutorial: Difference between revisions
Jump to navigation
Jump to search
(Marked this version for translation) |
No edit summary |
||
Line 1: | Line 1: | ||
<languages /> | <languages /> | ||
<translate> | <translate> | ||
This tutorial is strongly inspired from the OpenACC Bootcamp session presented at [http://www.gputechconf.com/ GPU Technology Conference 2016]. | This tutorial is strongly inspired from the OpenACC Bootcamp session presented at [http://www.gputechconf.com/ GPU Technology Conference 2016]. | ||
Revision as of 23:40, 27 February 2017
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
- 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: