Hey,
I discovered pycuda today (after deciding it is time to finally put my
cuda card to some use) and was very thrilled to find a library so much
in my style: write code in a nice language, make sure the inner loop
is fast! I was also quite pleased how fast I got my toy example (1d
cubic spline interpolation) to run on the gpu. I then turned to my
real problem.
I need cubic interpolation of numpy arrays, so I can sample my pixels
at pixel positions (x=2.345,y=pi). I used scipy.interpolate before,
but now I'm looking for a cuda implementation. I found http://www.dannyruijters.nl/cubicinterpolation/
which seems like exactly what i want, but i was unable to get it to
work with pycuda: The kernels rely on texture<> to write their results
to and I have not understood how I can feed the memory of my numpy
array as a texture to the kernels. I have some vague understanding of
textures in cuda in general, so I think some preprocessing is needed
(feeding alignement informations, how the data should be adressed and
it must be transferred to the cuda device). Does somebody have sample
code using pycuda? Something simple like a rotation kernel would be a
perfect example!
Hope somebody can help!
Greetings and thanks for the great work with pycuda. I will follow it
closely.
Holger
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Dipl.-Phys. Holger Rapp
Institut für Mess- und Regelungstechnik
Universität Karlsruhe (TH)
Engler-Bunte-Ring 21
76131 Karlsruhe, Germany
Geb. 40.32, Zi. 232, zweite Etage
Tel: +49 (0)721 / 608-2341
Fax: +49 (0)721 / 661874
Mail: [email protected]
Web: www.mrt.uni-karlsruhe.de
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