OpenCL / GEGL-OpenCL

Gimp-GEGL is the first official OpenCL Porting Project of
http://opencl.org
GNU Lesser General Public License v3.0
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GEGL-OpenCL

First official OPP (OpenCL Porting Project) of OpenCL.org

GEGL (Generic Graphics Library) is a graph based image processing framework.

With GEGL you chain together image processing operations represented by nodes into a graph. GEGL provides such operations for loading and storing images, adjusting colors, filtering in different ways, transforming and compositing images.

GEGL also depends on BABL to translate pixel formats. BABL allows converting between different methods of storing pixels known as pixel formats that have with different bitdepths and other data representations, color models and component permutations. A vocabulary to formulate new pixel formats from existing primitives is provided as well as the framework to add new color models and data types.

For a brief explanation on how GEGL works, read this document

Index

  1. Installing
  2. Development
  3. Contributing
  4. How to Port an Operation
  5. How to Test Output
  6. How to Benchmark Performance

Installing

Read the document above for more information, or refer to the links below for the respective platforms

On Windows

On Linux Platforms

Ensure that BABL is installed first before GEGL.

Development

The code for GEGL-OpenCL can be found at GEGL-OpenCL Github.

There already exists OpenCL integration into GEGL and some operations have already been ported to run on OpenCL. However, there is still a lot of operations that need porting as listed in the Google Sheet below.

Task List for GEGL-OpenCL (Excel)

Task List for GEGL-OpenCL (Github)

Likewise, we have a slack channel for discussions pertaining to development and issues here, GEGL-OpenCL Slack

Contributing

It is recommended that you fork this repository and create your branches there. After every discussion, if your kernel has the fastest speed for the vendor, you can create a pull request to have your changes merged. Please include the test results (correctness and timing), and name the pull request according to the operation you're working on and the vendor you're optimizing for, eg. box-blur_kernel_nv

Please ensure that make clean is executed before requesting a pull request

How to Port an Operation
How to Test Output
How to Benchmark Performance