GPU: Difference between revisions

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* [http://lists.osgeo.org/pipermail/grass-user/2009-December/053476.html Comment]
* [http://lists.osgeo.org/pipermail/grass-user/2009-December/053476.html Comment]


* As I understand it, CODA is 100% dependent on the closed-source binary driver from nVidia and works on their video cards alone. Which is fine for today for people with nVidia hardware using their binary video card driver. If nVidia decides in a couple of years to stop supporting CODA, your old card, your specific OS or distro, your OS or distro version+cpu type, or if they go out of business or are bought/sold to another company who is not interested, any code based on it becomes useless. For this reason code written for an open platform such as OpenCL, even if less advanced, seems to have a brighter long-term future. -- ''HB''
* As I understand it, CUDA is 100% dependent on the closed-source binary driver from nVidia and works on their video cards alone. Which is fine for today for people with nVidia hardware using their binary video card driver. If nVidia decides in a couple of years to stop supporting CUDA, your old card, your specific OS or distro, your OS or distro version+cpu type, or if they go out of business or are bought/sold to another company who is not interested, any code based on it becomes useless. For this reason code written for an open platform such as OpenCL, even if less advanced, seems to have a brighter long-term future. -- ''HB''




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* {{cmd|v.surf.rst}}
* {{cmd|v.surf.rst}}
* {{cmd|v.vol.rst}}
* {{cmd|v.vol.rst}}
* {{AddonCmd|r.viewshed}}
* {{cmd|r.sun}}
* raster library
* raster library
* vector library
* vector library

Revision as of 07:42, 1 April 2010

Comments from the mailing list concerning GRASS and GPU parallelization:

  • As I understand it, CUDA is 100% dependent on the closed-source binary driver from nVidia and works on their video cards alone. Which is fine for today for people with nVidia hardware using their binary video card driver. If nVidia decides in a couple of years to stop supporting CUDA, your old card, your specific OS or distro, your OS or distro version+cpu type, or if they go out of business or are bought/sold to another company who is not interested, any code based on it becomes useless. For this reason code written for an open platform such as OpenCL, even if less advanced, seems to have a brighter long-term future. -- HB


Modules of interest to be parallelized

The target version will be GRASS 7 (alias SVN trunk).