Hello Sir,

When I used command "device=gpuN python file.py" then code is successfullt
running on gpu.As you said theano FLAGS will override .rc file settings so
I think there is no need of making .theanorc file. Kindly tell me how to
make cuda memory faster if I dont use cnmem...I want to gain speedup in gpu
as compare to cpu....



On Fri, Mar 3, 2017 at 7:08 PM, Ramana Subramanyam <[email protected]>
wrote:

> Hi,
> You don't set the device parameter. Set your device to gpuN and try
> running again. cnmem is from the old backend, which will be depreciated
> soon. You should start using device=cudaN and config.gpuarray.preallocate 
> instead
> of lib.cnmem. Also, you seem to override the config file with THEANO_FLAGS.
> Use either of them (remember FLAGS can override .rc file settings).
>
> Ramana
>
> On Friday, March 3, 2017 at 7:06:24 PM UTC+5:30, Ani wrote:
>>
>> No sir I have put
>> [lib]
>> cnmem=1
>> but it shows error of lib command not found..what to do sir now.
>> On 3 Mar 2017 5:07 p.m., "Kiuhnm Mnhuik" <[email protected]> wrote:
>>
>> You probably forgot [lib]:
>>
>>     [lib]
>>     cnmem = 1
>>
>> Hello Sir...
>>>
>>> I have successfully installed CuDNN and it is also available...but
>>> problem is with cnmem..When I wrote cnmem=1 in my .theanorc file which is
>>> at home directory..it gives error on running any code with cpu or
>>> gpu..please have a look at error(screenshot is attached).
>>>
>>> Thanks in advance....
>>> Regards
>>> Anishi Gupta
>>>
>>> On Saturday, 28 May 2016 11:05:29 UTC+5:30, Poornachandra Sandur wrote:
>>>>
>>>> Hi,
>>>>                    CNMem is  fast CUDA memory allocator ... if you want
>>>> to set it you can do it by writing the below lines in your .theanorc file
>>>>  ...
>>>>
>>>> [lib]
>>>> cnmem=1
>>>>
>>>>
>>>> -------------------------------
>>>>
>>>> For CUDNN you can do it with the following steps :
>>>>
>>>> *First download the file : cudnn-7.0-linux-x64-v3.0-prod.tgz*
>>>>
>>>> *Extract it to home directory*
>>>>
>>>> *and set the LD_LIBRARY_PATH to the above extracted directory*
>>>>
>>>> *and then follow the below steps :*
>>>>
>>>>
>>>>
>>>> *sudo cp /home/poornachandra/cuda/include/cudnn.h
>>>> /usr/local/cuda-7.5/include/*
>>>>
>>>> *sudo cp /home/poornachandra/cuda/lib64/libcudnn*
>>>> /usr/local/cuda-7.5/lib64/*
>>>>
>>>>
>>>> On Fri, May 27, 2016 at 1:22 PM, Ramana Subramanyam <[email protected]>
>>>> wrote:
>>>>
>>>>> Hello there,
>>>>> If anyone is running theano on OSX, you need to make  a few changes to
>>>>> Poornachandra's answer. Instead of setting the path of *LD_LIBRARY_PATH,
>>>>> *set *DYLD_LIBRARY_PATH *to the extracted directory of CUDNN. I have
>>>>> extracted them into `/home/packages/` and I am using CUDA 7.5. Copy those
>>>>> files to the following destination,
>>>>>
>>>>>
>>>>> 1) sudo cp ~/packages/cuda/lib/libcudnn* /Developer/NVIDIA/CUDA-7.5/
>>>>> lib/
>>>>>
>>>>>
>>>>>
>>>>> 2) sudo cp ~/packages/cuda/include/cudnn.h /Developer/NVIDIA/CUDA-7.5/
>>>>> include/
>>>>>
>>>>>
>>>>>
>>>>> Hope this helps!
>>>>>
>>>>> On Tuesday, March 15, 2016 at 7:52:50 AM UTC+5:30, Ashutosh Modi wrote:
>>>>>>
>>>>>> Hi,
>>>>>>
>>>>>> I am running the latest version of Theano 0.8 on linux server using
>>>>>> the GPUs. When I run my code I get the following message :
>>>>>>
>>>>>> Using gpu device 0: GeForce GTX TITAN X (CNMeM is disabled, CuDNN not
>>>>>> available)
>>>>>>
>>>>>>
>>>>>> Is it normal or something is lacking or is it some bug? I ran my code
>>>>>> after clearing the .thano directory.
>>>>>>
>>>>>>
>>>>>> Please help me in resolving this.
>>>>>>
>>>>>>
>>>>>> Thanks,
>>>>>>
>>>>>> Ashutosh
>>>>>>
>>>>> --
>>>>>
>>>>> ---
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>>>>>
>>>>
>>>>
>>>>
>>>> --
>>>> warm regards,
>>>> Poornachandra Sandur,
>>>> Mob.No.+91-9901913049
>>>>
>>> --
>>
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With Best Wishes and Regards
Anishi Gupta

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