The order of GPU between nvidia-smi and the cuda driver that Theano use is
not always the same. Try with gpu1 as this could the be GPU with memory
available.

Le 12 oct. 2016 11:34, <jos...@josephpcohen.com> a écrit :

> On this machine I have another process using theano with memory on the
> GPU. Normally I can launch many processes and import theano but now I get
> this error.
>
> $ python
>
> Python 2.7.12 |Anaconda 2.3.0 (64-bit)| (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
>
> >>> import theano
>
> ERROR (theano.sandbox.cuda): ERROR: Not using GPU. Initialisation of
> device 0 failed:
> cublasCreate() returned this error 'the CUDA Runtime initialization
> failed'
> ERROR (theano.sandbox.cuda): ERROR: Not using GPU. Initialisation of
> device gpu failed:
> Not able to select available GPU from 2 cards (out of memory).
>
> ERR!\nTraceback (most recent call last):
>
>   File "<stdin>", line 1, in <module>
>
>   File "/u/cohenjos/.local/lib/python2.7/site-packages/theano/__init__.py",
> line 111, in <module>
>     theano.sandbox.cuda.tests.test_driver.test_nvidia_driver1()
>
>   File "/u/cohenjos/.local/lib/python2.7/site-packages/
> theano/sandbox/cuda/tests/test_driver.py", line 29, i
> n test_nvidia_driver1
>
>     A = cuda.shared_constructor(a)
>
>   File 
> "/u/cohenjos/.local/lib/python2.7/site-packages/theano/sandbox/cuda/var.py",
> line 218, in float32_sha
> red_constructor
>
>     enable_cuda=False)
>
>   File "/u/cohenjos/.local/lib/python2.7/site-packages/
> theano/sandbox/cuda/__init__.py", line 554, in use
>     cuda_ndarray.cuda_ndarray.select_a_gpu()
>
> RuntimeError: ('Not able to select available GPU from 2 cards (out of
> memory).', 'You asked to force this de
> vice and it failed. No fallback to the cpu or other gpu device.')
> >>>
>
>
> ~/.theanorc
> [global]
>
> device=gpu0
>
> floatX=float32
>
>
> Nvidia-smi shows there is plenty of memory:
>
> +-----------------------------------------------------------
> ------------------+
> | NVIDIA-SMI 367.44                 Driver Version: 367.44
>                   |
> |-------------------------------+----------------------+----
> ------------------+
> | GPU  Name        Persistence-M| Bus-Id
> Disp.A | Volatile Uncorr. ECC |
> | Fan  Temp  Perf  Pwr:Usage/Cap|         Memory-Usage |
> GPU-Util  Compute M. |
> |===============================+======================+====
> ==================|
> |   0  GeForce GTX TIT...  Off  | 0000:04:00.0      On |
>                  N/A |
> | 82%   86C    P2   195W / 250W |   2358MiB /  6081MiB |
>    100%      Default |
> +-------------------------------+----------------------+----
> ------------------+
> |   1  GeForce GTX TIT...  Off  | 0000:05:00.0     Off |
>                  N/A |
> | 40%   68C    P2   224W / 250W |   5851MiB /  6082MiB |
>     92%      Default |
> +-------------------------------+----------------------+----
> ------------------+
>
>
> +-----------------------------------------------------------
> ------------------+
> | Processes:
>        GPU Memory |
> |  GPU       PID  Type  Process name
>              Usage      |
> |===========================================================
> ==================|
> |    0      6566    G   /usr/bin/X
>              22MiB |
> |    0     15578    C   python
>                 2331MiB |
> |    1     13043    C   python
>                 5846MiB |
> +-----------------------------------------------------------------------------+
>
>
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>
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