Thanks for the advice!
Regards,
Luis
> Luis -
>
> ...
> Not surprisingly, nVidia has a ton of developer resources for getting
> started with CUDA. Probably the best place is their own page dedicated
> to this task, which includes videos and slides introducing the topic:
> http://developer.nvidia.com/cuda/get-started-cuda-cc
>
> Wen-mei co-authored a book with David Kirk entitled "Programming
> Massively Parallel Processors." I bought the book but have made little
> use of it, mostly because the classes I took taught me nearly
> everything that the book covered. As a beginner, it may prove more
> useful to you.
>
> If you want to play around with mixing CUDA and Perl, you will likely
> want to use ExtUtils::nvcc, which handles the build chain intricacies
> and includes a complete working example for Inline::C. I also wrote
> CUDA::Minimal, which is only available on github
> (https://github.com/run4flat/perl-CUDA-Minimal), and provides
> Perl-level functions for shuttling data back and forth between the GPU
> and the CPU. You'll still have to write GPU kernels and the C code to
> invoke those kernels (again, Inline::C is useful for this), but the
> intricacies of extracting data from PDL or packed Perl scalars are
> covered for you.
>
> I am more than happy to answer any questions you may have about CUDA
> and perl+CUDA. :-)
>
> David
>
> --
> "Debugging is twice as hard as writing the code in the first place.
> Therefore, if you write the code as cleverly as possible, you are,
> by definition, not smart enough to debug it." -- Brian Kernighan
--
o
W. Luis Mochán, | tel:(52)(777)329-1734 /<(*)
Instituto de Ciencias Físicas, UNAM | fax:(52)(777)317-5388 `>/ /\
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