[Rtk-users] Multi GPU capabilities

[Simon Rit]

Hi,
No. This is quite a challenge to implement this and we have no resources on
this topic. My first attempt to do this would be to use ASTRA
<http://www.astra-toolbox.com/> from RTK. RTK only automagically select the
"best" GPU, see here
<https://github.com/SimonRit/RTK/blob/master/utilities/ITKCudaCommon/src/itkCudaContextManager.cxx#L67>
.
For FDK, I think it would be easy to split the volume and ask each GPU to
reconstruct a specific part of the volume (but I never did it and RTK would
need to allow parameterization of the device which it currently doesn't).
Note that we don't use the unified memory framework.
Simon

On Tue, Oct 15, 2019 at 5:43 PM vincent <vl at xris.eu> wrote:

> Hello everyone,
>
> I was wondering if RTK automagically spread the workload over several
> GPU's when available on a machine ?  I tried to find the answer by
> myself, but up to now, the only information I could get were that:
>
> - cuda provides with a unified memory framework supposed to simplify
> memory management,
>
> - class itkCudaUtil has members that identify all the GPU's present on
> the computer.
>
> I had a look on the other itkCuda*** classes but found nothing that
> could help me understand if multiple GPU's are managed by RTK.
>
> Would someone would be so kind as to help me find an answer ?
>
> I thank you very much in advance,
>
> best regards,
>
> Vincent
>
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