Setting up PyFR flow solver on clusters

Description These instructions were executed on the FASTER and Grace cluster computing facilities at Texas A&M University. However, the process can be applied to other clusters with similar environments. For local installation, please refer to the PyFR documentation.

Please note that these instructions were valid at the time of writing. Depending on the time you're executing these, the versions of the modules may need to be updated.

1. Loading Modules
The first step involves loading pre-installed software libraries required for PyFR. Execute the following commands in your terminal to load these modules:

module load foss/2022b
module load libffi/3.4.4
module load OpenSSL/1.1.1k
module load METIS/5.1.0
module load HDF5/1.13.1

2. Python Installation from Source
Choose a location for Python 3.11.1 installation, preferably in a .local directory. Navigate to the directory containing the Python 3.11.1 source code. Then configure and install Python:

cd $INSTALL/Python-3.11.1/
./configure --prefix=$LOCAL --enable-shared --with-system-ffi --with-openssl=/sw/eb/sw/OpenSSL/1.1.1k-GCCcore-11.2.0/ PKG_CONFIG_PATH=$LOCAL/pkgconfig LDFLAGS=/usr/lib64/libffi.so.6.0.2
make clean; make -j20; make install;


3. Virtual Environment Setup
A virtual environment allows you to isolate Python packages for this project from others on your system. Create and activate a virtual environment using:

pip3.11 install virtualenv
python3.11 -m venv pyfr-venv
. pyfr-venv/bin/activate

4. Install PyFR Dependencies
Several Python packages are required for PyFR. Install these packages using the following commands:

pip3 install --upgrade pip
pip3 install --no-cache-dir wheel
pip3 install --no-cache-dir botorch pandas matplotlib pyfr
pip3 uninstall -y pyfr

5. Install PyFR from Source
Finally, navigate to the directory containing the PyFR source code, and then install PyFR:

cd /scratch/user/sambit98/github/PyFR/
python3 setup.py develop

Congratulations! You've successfully set up PyFR on the FASTER and Grace cluster computing facilities. You should now be able to use PyFR for your computational fluid dynamics simulations.