[Digikam-devel] GPU Implementation of image processing algorithms

[Gilles Caulier]

For my viewpoint, it's always a bad idea to force implementation to
use specific API relevant of hardware specification. Your code must be
compiled as well without an indeed dependency. Optionally of course
providing a way to speedup computation is always welcome.

For ex, in libraw, we use OpenMp to parallelize computation during RAW
demosaicing. OpenMP is GNU compatible and available with GCC and other
compiler as M$ VisualC

Other consideration is platform compatible. Always use a libs which is
available under all platforms, as Linux, Mac and windows.

My 10cts€

Gilles Caulier

2010/4/17 kunal ghosh <kunal.t2 at gmail.com>:
> Hi,
> I am implementing the face recognition algorithm for digikam, and wanted to
> use GPGPU frameworks for the same. But
> was not able to decide which framework to use OpenCL or CUDA (C for CUDA
> specifically).
>
> PS: I am willingly not including any more information about either of the
> above frameworks to attract unbiased opinions.
>
> Also, i could code part that would execute on the GPU in python , shortening
> the development cycle. Good python bindings exist for either GPU programming
> frameworks. Py[CUDA,OpenCL] are the bindings.
>
> Python functions are easily callable from within C/C++ code as demonstrated
> by Link 1 Link2 and Link3
> so, is it fine if the algorithms are implemented in python and then called
> from within digikam.
>
> all suggestions , comments welcome.
>
> --
> regards
> -------
> Kunal Ghosh
> Dept of Computer Sc. & Engineering.
> Sir MVIT
> Bangalore,India
>
> Quote:
> "Ignorance is not a sin, the persistence of ignorance is"
> --
> "If you find a task difficult today, you'll find it difficult 10yrs later
> too !"
> -----
> "Failing to Plan is Planning to Fail"
>
> Blog:kunalghosh.wordpress.com
> Website:www.kunalghosh.net46.net
> V-card:http://tinyurl.com/86qjyk
>
>
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