[Insight-developers] [Insight-users] Cuda ITK

[kent williams]

I'm not familiar with the Cuda programming model.  Though the president of
Nvidia was on Charlie Rose last weekend and they were chattering about as
though they knew what they were talking about.

How applicable it would be to ITK would depend on what writing code for CUDA
entails. I presume it isn't a 'transparent' process -- you must have to
download your code into the CUDA system, then use interprocessor message
passing to send data and call functions on the CUDA as well.

The best thing for the ITK community at large would be if existing filters
were modified so that you could conditionally compile CUDA support.  This
would require hoisting out the guts of a particular algorithm or filter for
CUDA implementation, and then encapsulate the CUDA usage inside the current
ITK classes.

This might be sub-optimal in some cases -- i.e. If you have 3 Cuda-fied
filters, and then stick them in a pipeline, instead of running the whole
pipeline on the Cuda, you'd run one filter, retrieve the results, and then
pass the results into the next pipeline stage.  Every Cuda-fied filter in a
pipeline would add an additional copy-data-in/copy-data-out pair. If you did
the whole pipeline natively in the Cuda, you'd copy your inputs in once and
copy your outputs once.

As far as I can tell from the Cuda website, they don't yet support C++, so
there's no chance of building ITK itself on the Cuda platform.

On 2/12/09 11:06 AM, "Marcel Weiss" <mweiss at cbs.mpg.de> wrote:
> As we ordered a new number crunching machine including a NVIDIA Tesla TM C1060
> and we are planning to use it for the fast processing of our high-resolition
> 3D images, I´d be interested in some more statements and experiences on CUDA
> (pure and/or with ITK).

Would you suggest planning and programming new code
> or adjusting existing code?
I´m sure there is a tradeoff between man power
> needed and speed-up gained ...



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