Dear Sergey,

some (trivial) advice:

* version 6.7 detects accelerators but does not use them, the actual release of the accelerated version is here: https://gitlab.com/QEF/q-e-gpu. The two codes have been merged therefore the next release will include GPU support as well.

* You may get a little speedup by linking fftw3, but most of the ffts are done on the GPU with cufft.

* OpenMP should definitively be enabled and provides the way to fully exploit the CPUs. Indeed, the number of *MPI processes* should be (as a rule) equal to the number of GPUs (6 x node in your case).

* CUDA-aware MPI is an experimental feature. I have used it extensively without problems though.

Hope this helps,
Pietro


On 3/9/21 3:04 PM, Sergey Lisenkov wrote:
Hello,
I have an access to IBM Power9 cluster with 6 V100 GPUs cores/node, and 40 CPU cores/node. I have a CPU version of QE-6.7 running, but I would like to explore GPU version. We have Nvidia compilers installed (PGI 21.2, cuda 11.1, ESSL 6.2).  When I ran congifure script, in the way described on Wiki page for QE-GPU, it creates 'make.inc' file with internal FFTW and USE_CUSOLVER. Also, configure give blas/lapack libraries from PGI. Is it the way it should be? I see that there are cublas, cufft and other cuda libraries, but can they be used in QE? ESSL also has "libesslsmcuda" library, but I don't know if it is relevant. All examples on QE-GPU Wiki page seems to be outdated, or I may be wrong. Also, since every computing node has 6 GPUs, I could use CUDA-aware MPI (enabled with __GPU_MPI flag). Should I provide OMP_NUM_THREADS variable (=40), to utilize CPU cores? BTW, configure script for some reason does not activate OpenMP (even if --enable-openmp) is used.
Thanks,
  Sergey

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