If you use the flag

device=gpu*

you use the old back-end.

If you use the flag:

device=cuda*

you use the new back-end(libgpuarray).

If the new back-end work for you, use it. If not, tell us! But we are
pretty confident that it should work. We passed practically all operation
to it now. The one missing are very not frequently used, so you probably
won't miss them.

Here is a link to help you convert to the new back-end. It have some
information that should help you:

https://github.com/Theano/Theano/wiki/Converting-to-the-new-gpu-back-end%28gpuarray%29

On Wed, Nov 9, 2016 at 2:51 PM, Michael Klachko <[email protected]>
wrote:

> I'm a little confused regarding the two backends. Is there any
> recommendation to when we should be using one or the other? I installed
> both on my Ubuntu machine, and I don't even know which one I'm using for my
> convnets. How can I tell? Or how can I configure it to use one or another?
>
> On Wed, Nov 9, 2016 at 8:48 AM, Frédéric Bastien <
> [email protected]> wrote:
>
>> It could be that the new back-end (libgpuarray) is faster and more
>> efficient in that cases. So just use that back-end :)
>>
>> The speed difference between both back-end isn't constant, but should be
>> a little bit faster with the new back-end in average.
>>
>> We have found a few speed regression in the new back-end, but they where
>> fixed. If you found one, just tell us and we'll fix it. But the probably is
>> still low of having slowdown in the new back-end.
>>
>> We just merged one such fix with indexing. Make sure to update
>> libgpuarray and recompile it if you want to be sure to have the fastest
>> version.
>>
>> Fred
>>
>> On Tue, Nov 8, 2016 at 1:56 PM, Ragav Venkatesan <
>> [email protected]> wrote:
>>
>>> Ok, here is a problem I'm getting and I am not sure how to solve this.
>>> If I use the libgpuarray backend on the cnn_tutorial I am getting a 98% gpu
>>> tutilization with cudnn 5105. If I use cuda backend, I am only getting
>>> about 35% utilization.
>>> Anyidea why this might be so ?
>>>
>>> On Monday, October 24, 2016 at 9:38:17 AM UTC-7, nouiz wrote:
>>>>
>>>> What errors do you have? Delete your Theano cache, just in case and be
>>>> sure to use Theano dev version. The last release don't support it I think.
>>>>
>>>> Fred
>>>>
>>>> On Mon, Oct 24, 2016 at 12:33 PM, Michael Klachko <[email protected]
>>>> > wrote:
>>>>
>>>>> Yes, it's supported, I'm using it right now (CUDA 8.0 on Ubuntu 14.04):
>>>>>
>>>>> >>> import theano
>>>>> Using gpu device 0: TITAN X (Pascal) (CNMeM is enabled with initial
>>>>> size: 30.0% of memory, cuDNN 5105)
>>>>> >>> print theano.__version__
>>>>> 0.9.0dev3.dev-20fd30a38d34687e9d944140042762ca9fca6276
>>>>>
>>>>>
>>>>>
>>>>>
>>>>>
>>>>> On Saturday, October 22, 2016 at 2:54:00 PM UTC-7, Ragav Venkatesan
>>>>> wrote:
>>>>>>
>>>>>> I updated and I'm getting some weird errors. With Cuda backend,
>>>>>> convolutions only run on CPU and with libgpuarray backend GPUs only run 
>>>>>> at
>>>>>> about 35% util.
>>>>>>
>>>>>>
>>>>>> --
>>>>>
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