[CP2K:8395] Running CP2K on CPU v/s GPU

Iain Bethune ibet... at epcc.ed.ac.uk
Mon Nov 14 10:58:08 CET 2016

Dear Aman,

The CP2K GPU implementation only benefits the DBCSR (sparse matrix) part of the code, and the planewave grids/FFT (if PW_CUDA is defined).  For your system, most likely much of the time is in dense linear algebra (OT or DIAGONALISATION), so it will not benefit from the GPU.

There is no single ‘cp2k manual’ but you will find a lot of information on cp2k.org, especially the HowTo section, and information from previous CP2K tutorials/events.


- Iain


Iain Bethune
Project Manager, EPCC

Email: ibet... at epcc.ed.ac.uk
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> On 13 Nov 2016, at 11:05, Aman Jindal <amanjin... at gmail.com> wrote:
> Dear all,
> I submitted the exactly same job on cp2k-3.0 version, compiled for CRAY-XC40-gfortran on CPU as well as on Cuda. My system contains 1000 atoms and I submitted 500 MD steps for it. I am surprised to see that the job is taking much less time to finish on CPU as compared to the GPU one. On CPU, each step is taking only half a minute whereas on GPU it's taking around 3 minutes. I don't know why it is so. Do I need to change my input file too to make it faster on GPU ?
> I just started to use cp2k for my research, can you please tell me if there is any proper manual available for it ?
> Thanks,
> Aman Jindal
> Research Scholar
> Indian Institute of Science
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