Hi Solal,

It looks like you are using the incompressible solver.

Was your colleague also using this solver (just so we can be sure that we are 
comparing apples with apples).

Peter

Dr Peter Vincent MSci ARCS DIC PhD FRAeS
Reader in Aeronautics and EPSRC Fellow
Department of Aeronautics
Imperial College London
South Kensington
London
SW7 2AZ
UK



On 4 Feb 2020, at 13:52, Solal Amouyal 
<[email protected]<mailto:[email protected]>> wrote:

Hi All,

I'm a new user of PyFR. I started by running the 2D benchmark cases provided 
with the source files and then moved up to the supplementary materials of 
journal publications.

I'm currently running the 3D sd7003 case, files are attached. At first, I am 
using p1 to initialize my domain. Then starting at t=25s, I switch the p3 with 
the multi-p method until t=32s. Lastly, statistics are gathered until t=45s. A 
colleague ran the same case using 2 V100 GPUs and it took him about 4 days for 
the full simulation.

I am using 9 nodes of 2x Intel Xeon 6540 (18 cores per CPU, 2 CPU per node, 324 
cores total) and therefore running with the OpenMP backend. From previous 
posts, I've read that PyFR runs best with one MPI rank per CPU and I'm 
therefore using with OMP_NUM_THREADS=18.
The p1 case (sd7003_1.ini) took about 24 hours to run. However, after 36 hours 
of running the first p3 case (sd7003_2.ini), the estimated time is about 10 
days. Extrapolating, this would mean the entire run would take about 28 days.

I don't have experience running with GPUs but I was expecting each GPU to match 
the performance of 3-4 CPUs. The above indicates a ratio of about 60 and does 
not seem right.

  *   I know PyFR runs very well on GPUs but are these results to be expected?
  *   I've been running a case that was meant to run on GPUs. Perhaps other 
numerical methods are more adapted to CPUs / OpenMP backend?

Thanks,

Solal


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<sd7003_1.ini><sd7003_2.ini><sd7003_3.ini>

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