Thanks for the investigation.
Can you also try running the Python script from inside cuda-memcheck?
For instance:
CUDA_LAUNCH_BLOCKING=1 THEANO_FLAGS=... cuda-memcheck python 
/home/luca/data/DeepLearningTutorials/Theano-3D-Convnet-master/convnet3d/core/run_multi_conv.py

Thanks,
On Wed, Nov 02, 2016, [email protected] wrote:
> Hi, I did this test as Fred suggested:
> 
> 
> - floatX=float16, device=cuda;
> 
> - CUDA_LAUNCH_BLOCKING=1 
> 
> - used theano.tensor.nnet.conv3d
> 
>  out = theano.tensor.nnet.conv3d(
>                         input=input,  
>                         filters=self.W, 
>                         input_shape = None,
>                         filter_shape= None,
>                         border_mode = 'valid',
>                         subsample=(1,1,1),
>                         filter_flip = True,
>                         filter_dilation=(1,1,1)
>                         ) 
> 
> 
> this is the output (same error: pygpu.gpuarray.
> GpuArrayException: an illegal memory access was encounteredt): 
> 
> Python 2.7.12 |Continuum Analytics, Inc.| (default, Jul  2 2016, 17:42:40) 
> [GCC 4.4.7 20120313 (Red Hat 4.4.7-1)] on linux2
> Type "help", "copyright", "credits" or "license" for more information.
> Anaconda is brought to you by Continuum Analytics.
> Please check out: http://continuum.io/thanks and https://anaconda.org
> >>> 
> runfile('/home/luca/data/DeepLearningTutorials/Theano-3D-Convnet-master/convnet3d/core/run_multi_conv.py',
>  
> wdir='/home/luca/data/DeepLearningTutorials/Theano-3D-Convnet-master/convnet3d/core')
> 
> Mapped name None to device cuda: Tesla K40c
> Using cuDNN version 5103 on context None
> Disabling C code for Elemwise{mul,no_inplace} due to unsupported float16
> Disabling C code for Elemwise{Cast{float32}} due to unsupported float16
> Disabling C code for MaxAndArgmax due to unsupported float16
> 
> 
> start time:
> 02/11/2016
> 10:39:10
> 
> 
> 
> ... training neural network 63
> 
> 
> 
> training @ iter =  0
> Traceback (most recent call last):
>   File "<stdin>", line 1, in <module>
>   File 
> "/home/luca/anaconda2/lib/python2.7/site-packages/spyder/utils/site/sitecustomize.py",
>  
> line 866, in runfile
>     execfile(filename, namespace)
>   File 
> "/home/luca/anaconda2/lib/python2.7/site-packages/spyder/utils/site/sitecustomize.py",
>  
> line 94, in execfile
>     builtins.execfile(filename, *where)
>   File 
> "/home/luca/data/DeepLearningTutorials/Theano-3D-Convnet-master/convnet3d/core/run_multi_conv.py",
>  
> line 43, in <module>
>     run_experiments()
>   File 
> "/home/luca/data/DeepLearningTutorials/Theano-3D-Convnet-master/convnet3d/core/run_multi_conv.py",
>  
> line 34, in run_experiments
>     Synthetic_data = False,
>   File "mpr_convnet_class.py", line 424, in __init__
>     training_cost_ij=train_model(a, b) 
>   File "/home/luca/data/Theano-master/theano/compile/function_module.py", 
> line 879, in __call__
>     storage_map=getattr(self.fn, 'storage_map', None))
>   File "/home/luca/data/Theano-master/theano/gof/link.py", line 172, in 
> raise_with_op
> 
>     "\nInputs values: %s" % scalar_values)
>   File "pygpu/gpuarray.pyx", line 1941, in pygpu.gpuarray.GpuArray.__repr__ 
> (pygpu/gpuarray.c:24742)
>   File 
> "/home/luca/anaconda2/lib/python2.7/site-packages/numpy/core/numeric.py", 
> line 482, in asarray
>     return array(a, dtype, copy=False, order=order)
>   File "pygpu/gpuarray.pyx", line 1572, in 
> pygpu.gpuarray.GpuArray.__array__ (pygpu/gpuarray.c:20224)
>   File "pygpu/gpuarray.pyx", line 1320, in pygpu.gpuarray.pygpu_as_ndarray 
> (pygpu/gpuarray.c:17346)
>   File "pygpu/gpuarray.pyx", line 347, in pygpu.gpuarray.array_read 
> (pygpu/gpuarray.c:6114)
> pygpu.gpuarray.GpuArrayException: an illegal memory access was encountered
> 
> 
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-- 
Pascal

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