On 13/05/2025 08:47, Wang Xing wrote:
#SBATCH --ntasks-per-node=4
#SBATCH --cpus-per-task=72
72 OpenMP threads are too many, and in any case: is your compute node a
4*72=288 CPU one?
srun pw.x -pd .true. -npool 1 -in aiida.in > aiida.out
-pd has no effect for GPUs, I think
GPU acceleration is ACTIVE. 1 visible GPUs per MPI rank
this doesn't look right to me: it should say 4 (but I don't know how
reliable this message is)
GPU-aware MPI enabled
Message from routine print_cuda_info:
High GPU oversubscription detected. Are you sure this is what you want?
this also doesn't look right: it seems to indicate that all four MPI
processes access a single GPU (but I don't know how reliable this
message is)
Does anyone have experience optimizing Gamma-point-only calculations on
multiple GPUs? Is there a known bottleneck or best practice for using
multiple GPUs efficiently in such a case?
there are two distinct aspects here:
1. how to convince your machine to run the code the way it should (and
not the way it shouldn't) and
2. how to optimized the parallelization over GPUs.
I can't say anything about the former point: it is a task for system
administrators. Once you are sure that the code runs the way it should,
have a look at the time reports for 1, 2, 4 GPUs, with no OpenMP
threads. You should easily spot anomalies or bottlenecks. Note that at
Gamma point you have no "easy" parallelization levels to exploit.
Paolo
Any insights would be greatly appreciated.
Best,
Xing
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Paolo Giannozzi, Dip. Scienze Matematiche Informatiche e Fisiche,
Univ. Udine, via delle Scienze 206, 33100 Udine Italy, +39-0432-558216
_______________________________________________________________________________
The Quantum ESPRESSO Foundation stands in solidarity with all civilians
worldwide who are victims of terrorism, military aggression, and indiscriminate
warfare.
--------------------------------------------------------------------------------
Quantum ESPRESSO is supported by MaX (www.max-centre.eu)
users mailing list users@lists.quantum-espresso.org
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