Hi Kate,
It shouldn't be too hard for you to expose the vtkImageGaussianSmooth in
PV. I have one caveat for you re: using vtkImageGaussianSmooth in
parallel: when it runs it will trigger a complete re-execution of your
entire pipeline including the reader.This happens because
vtkImageGaussianSmooth increases the update extents which, unless
something has changed in the recent version of PV, would be satisfied by
the reader re-executing. this could cause you some performance related
issues especially for large data where I/O becomes a significant
bottleneck. On the other hand, this re-execution would happen only when
running in parallel and if you have small data it might not be too bad.
I encountered this issue a while back. with our data size the additional
I/O was unacceptable. i wrote a parallel ghost cell generator for image
data to prevent the pipeline re-execution for operations like kernel
convolution that require ghost cells. The plugin includes a kernel
convolution filter as well. To use it you'd have to build and load our
plugin and add the "image ghosts" filter right before the "kernel
convolution" filter. Our kernel convolution filter also has a CUDA
implementation that's about 20x faster than the cpu version (note: CUDA
stuff is still being developed, still some issue when update extent is
too large to fit on the gpu). I'm attaching a link to the latest release
of the plugin in case you could use it. It requires a parallel build of
PV. http://www.hpcvis.com/SciVisToolKit/SciVisToolKit-12.02.tar.gz
Burlen
On 03/14/2012 10:16 AM, fiss...@pitt.edu wrote:
Hi,
I didn't see a paraview plugin for the vtkImageGaussianSmooth.cxx filter
in the paraview Filters menus or the filters.xml file.
Is there some equivalent ?
If not: am I right that I will need to write a little paraview plugin
wrapper in
order to be able to use vtkImageGaussianSmooth in a pvpython script ?
Any reason other than somewhat ugly parameter specification or lack
of interest/time that there isn't a plugin ?
thanks
kate
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