Limit on input Tensor size using cunn

[torch]

Limit on input Tensor size using cunn

[etrulls]

I'm also running into this.
(I'm trying to hunt down the magic number but I'm new to CUDA and it's not very friendly.)

[dominikgrewe]

The grid used to launch the kernel uses the batch size as the first dimension: https://github.com/torch/cunn/blob/master/LogSoftMax.cu#L238

There's a limit on the size of these grids, which depends on the version of CUDA you're using. It's 65536 for compute capability <= 2.x and 2^31-1 for newer versions (see https://en.wikipedia.org/wiki/CUDA#Version_features_and_specifications)

[etrulls]

Aha, I got that far, and I couldn't see why it wasn't working out of the box on a K40.
Turns out cunn is compiling for a compute capability of 2.0, so changing that seems to solve the problem. Thanks!

[hogwild]

I use a Geforce 750Ti. The problem is solved by changing the CUDA_NVCC_FLAGS from "-arch=sm_20" to "-arch=sm_50" in the CmakeLists.txt.

[mrharicot]

I have the same issue with SpatialSoftmax on the GPU, I am using a Titan X and cunn was compiled with CUDA 7.5 and compute capability 5.2
Any idea if this is fixable?

EDIT: I think I have fixed this by explicitly using cudnn.SpatialSoftMax