[Rtk-users] Use existing Images when copying from/to GPU

[C S]

Hi Simon,

thank you for your swift reply and suggestions!

In fact I'm already using your snippet
<https://github.com/SimonRit/RTK/blob/master/examples/FirstReconstruction/FirstCudaReconstruction.py#L64-L70>
for
cpu->gpu transfer. My main issue is using the existing cpu image when
transfering back to cpu, which I have not been able to do. I can use
the itk.ImageDuplicator for getting the data into RAM but I haven't found a
way to point the itk.ImageDuplicator's *output* to an exisiting Image. It
always creates a new Image and allocates new memory AFAIK.

Once I can do that the next optimization step would be to also use an
exisiting CudaImage (with according buffer) when transfering cpu->gpu,
*contrary
to your snippet.* For that I have found no way at all so far.

To clarify, I do not want to perform my own CUDA computations. Using RTK's
CUDA forward/backprojectors is the main feature I want to use from RTK.
With *explicit* I mean doing the transfer myself instead of relying on
RTK's implicit methods implied in the source code
<https://github.com/SimonRit/RTK/blob/master/utilities/ITKCudaCommon/include/itkCudaImage.h#L32>
.


Best
Clemens

Am Mo., 8. Juli 2019 um 16:20 Uhr schrieb Simon Rit <
simon.rit at creatis.insa-lyon.fr>:

> Hi,
> Conversion from Image to CudaImage is not optimal. The way I'm doing it
> now is shown in an example in these few lines
> <https://github.com/SimonRit/RTK/blob/master/examples/FirstReconstruction/FirstCudaReconstruction.py#L64-L70>.
> I am aware of the problem and discussed it on the ITK forum
> <https://discourse.itk.org/t/shadowed-functions-in-gpuimage-or-cudaimage/1614>
> but I don't have a better solution yet.
> I'm not sure what you mean by explicitely transferring data from/to GPU
> but I guess you can always work with itk::Image and do your own CUDA
> computations in the GenerateData of the ImageFilter if you don't like the
> CudaImage mechanism.
> I hope this helps,
> Simon
>
> On Mon, Jul 8, 2019 at 10:06 PM C S <clem.schmid at gmail.com> wrote:
>
>> Dear RTK users,
>>
>> I'm looking for a way to use exisiting ITK Images (either on GPU or in
>> RAM) when transfering data from/to GPU. That is, not only re-using the
>> Image object, but writing into the memory where its buffer is.
>>
>> Why: As I'm using the Python bindings, I guess this ties in with ITK
>> wrapping the CudaImage type. In
>> https://github.com/SimonRit/RTK/blob/master/utilities/ITKCudaCommon/include/itkCudaImage.h#L32 I
>> read that the memory management is done implicitly and the CudaImage can be
>> used with CPU filters. However when using the bindings,
>> only rtk.BackProjectionImageFilter can be used with CudaImages. The other
>> filters complain about not being wrapped for that type.
>>
>> That is why I want to explicitely transfer the data from/to GPU, but
>> preferably using the exisiting Images and buffers. I can't rely on RTK
>> managing GPU memory implicitly.
>>
>>
>> Thank you very much for your help!
>> Clemens
>>
>>
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>
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