Issue with running CP2K on multi-GPU node

Vedran Miletić riv... at gmail.com
Wed Nov 12 16:13:48 CET 2014


I believe Hyper-Q only works for Kepler cards (using CUDA 5 as you said).

Regards,
Vedran

Dana srijeda, 12. studenoga 2014. 11:49:41 UTC+1, korisnik Ole Schütt 
napisao je:
>
> Hi Abhishek,
>
> another thing you could try is to update your CUDA version. About a year 
> ago Nvidia added a feature called HyperQ, which allows multiple processes 
> to access the same GPU concurrently.
>
> -Ole
>
> On Wednesday, November 12, 2014 9:46:26 AM UTC+1, Vedran Miletić wrote:
>>
>> Hello Abhishek,
>>
>> can you try changing line 199 in cp2k/src/start/cp2k_runs.F from:
>>
>>   CALL acc_set_active_device(MOD(para_env%mepos, acc_get_ndevices()))
>>
>> to
>>
>>   CALL acc_set_active_device(1)
>>
>> and see if this works? You can use 2 or 3 if you prefer.
>>
>> Regards,
>> Vedran
>>
>> Dana utorak, 11. studenoga 2014. 20:06:42 UTC+1, korisnik Abhishek 
>> Bagusetty napisao je:
>>>
>>> Hi Developers,
>>>
>>> The cluster we use have a 4 on-node GPUs. It is apparent that the 
>>> GPU-IDs are tagged as 0,1,2,3 and when GPU_ID 0 is being used by some-other 
>>> application, CP2K reports in the output that *CUDA Error: all 
>>> CUDA-capable devices are busy or unavailable*. It looks like the 
>>> deviceIndex is defaulted to 0 for the CUDA APIs.
>>>
>>> Is there a way to specify a specific GPU-ID, so that memory management 
>>> and/or kernel computations are performed with respect to that particular 
>>> device ID ?
>>>
>>> Thanks,
>>> Abhishek 
>>>
>>>
>>> -----------------------------------------------------------------------------------------------------------
>>> Abhishek Bagusetty
>>> PhD Student, Computational Modeling & Simulation
>>> Center for Simulation and Modeling
>>> Department of Chemical & Petroleum Engineering
>>> University of Pittsburgh
>>> Pittsburgh, PA - 15261
>>> Office : 920 Benedum Hall
>>>
>>> -----------------------------------------------------------------------------------------------------------
>>>
>>>
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