Hi
According to the user guide, I ran the couette_flow_2d example and saw
an output like below

mahmood@orca:~$ cp -r /opt/PyFR-1.7.5/examples/couette_flow_2d/ .
mahmood@orca:~$ cd couette_flow_2d/
mahmood@orca:couette_flow_2d$ pyfr import couette_flow_2d.msh
couette_flow_2d.pyfrm
/home/mahmood/.local/lib/python3.6/site-packages/h5py/__init__.py:36:
FutureWarning: Conversion of the second argument of issubdtype from
`float` to `np.floating` is deprecated. In future, it will be treated
as `np.float64 == np.dtype(float).type`.
  from ._conv import register_converters as _register_converters
mahmood@orca:couette_flow_2d$
mahmood@orca:couette_flow_2d$ ls
couette_flow_2d.ini  couette_flow_2d.msh  couette_flow_2d.pyfrm
mahmood@orca:couette_flow_2d$ which pyfr
/usr/local/bin/pyfr
mahmood@orca:couette_flow_2d$ pyfr run -b cuda -p
couette_flow_2d.pyfrm couette_flow_2d.ini
/home/mahmood/.local/lib/python3.6/site-packages/h5py/__init__.py:36:
FutureWarning: Conversion of the second argument of issubdtype from
`float` to `np.floating` is deprecated. In future, it will be treated
as `np.float64 == np.dtype(float).type`.
  from ._conv import register_converters as _register_converters
 100.0% [=================================================>] 4.00/4.00
ela: 00:03:35 rem: 00:00:00



Couple of things:

1- Only one cpu core was 100%.
2- GPU utilization according to nvidia-smi was about 30%.

Is that normal?


Regards,
Mahmood

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