Comments (3)
Hi James,
You're right, there is a maximum-grid-size-imposed limitation on the size of
the convolution that can be performed in filterActs. I'm not really sure what
to do about it yet, though. One hacky solution if you really need to perform
such a big convolution is to split your filters into several sets, each set in
its own matrix. Then call filterActs for each set. The target matrix can be the
same for all calls (just a different offset into the same array). The gradient
computation routines would have to be called twice too.
I'll probably come up with something better in the future but for now it's an
unfixed bug.
Alex
Original comment by [email protected]
on 10 Mar 2012 at 9:57
from cuda-convnet.
CUDA compute compatibility 2.x or lower has a limitation that x, y and z
dimension of a grid must be smaller than 65536. However when it comes to 3.x,
x dimension of a grid can be as large as 2^31-1, which will be enough for
larger pictures. The original function can be enhanced just by swapping x and y
dimension.
Original comment by [email protected]
on 26 Dec 2013 at 12:37
from cuda-convnet.
The suggested fix sounds very promising, Any plans to swap x and y in the
future?
Original comment by [email protected]
on 7 Jan 2014 at 7:59
from cuda-convnet.
Related Issues (15)
- Local units HOT 1
- Is the svn link not available? HOT 1
- Visualising feature output from layers
- Any solution to the number of filters limitation ? HOT 1
- image 256x256
- cuda convnet compilation error GTS 450
- saving multiview predictions (--test-out) not work HOT 1
- Backprop won't work if you use fprop(NVMatrixV&) HOT 1
- Confirmation for strange-looking assert in filter_acts.cu HOT 1
- CUDA 5 compatibility HOT 2
- Destructors.
- compile error HOT 3
- Getting nan values while using response normalization layer HOT 1
- a small bug in NVMatrix::rightMult()
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from cuda-convnet.