Setting up a Rayleigh Development Environment ============================================== When running Rayleigh on HPC resources, always compile the software with the recommended compiler and link against libraries optimized for the architecture you are running on. When developing Rayleigh or editing its documentation, however, such optimizations are rarely necessary. Instead, it is sufficient for the code and documentation to compile. For this purpose, we recommend setting up a `conda environment`_ or using our `Docker container`_. Instructions for setting up an environment on Linux and Mac OS are provided below. Conda Environment ----------------- First, if you don't have Conda, you should download and install the version appropriate for your architecture `here. `_ Once you have Conda installed, create a Conda environment using the environment files we provide in Rayleigh's main directory. There are two different environments for MacOSX and Linux to account for different compiler packages, for MacOSX replace `environment.yml` by `environment_mac.yml`. .. code-block:: bash conda env create -f environment.yml conda activate radev This command will likely take a while (a few minutes) and will install all necessary packages to compile Rayleigh. MKL Setup: Linux and Mac ^^^^^^^^^^^^^^^^^^^^^^^^ Once your packages are installed, you will most likely want to have the ``MKLROOT`` environment variable set whenever you activate your Conda environment. To do this we set ``MKLROOT`` to the location of the currently activated conda environment from the enviroment variable ``CONDA_PREFIX``. .. code-block:: bash export MKLROOT="$CONDA_PREFIX" Note that this is Bash syntax (use setenv if running c-shell). Note that there should be no spaces on either side of the "=" sign. If you stop here, you will have to do this every time you activate your development environment. To have this happen automatically, you only need to add two small scripts to radev/etc/conda/activate.d and radev/etc/conda/deactivate.d directories. Scripts in these directories are automatically executed when your conda environment is activated and deactivated, respectively. Change to your activate.d directory (for me, this was /custom/software/miniconda3/envs/radev/etc/conda/activate.d) and create a file named activate_mkl.sh with the following three lines: .. code-block:: bash #!/bin/bash export MKLSAVE="$MKLROOT" export MKLROOT="$CONDA_PREFIX" In the deactivate.d directory, create a file named deactivate_mkl.sh with the following two lines: .. code-block:: bash #!/bin/bash export MKLROOT="$MKLSAVE" Now, try it out. .. code-block:: bash conda deactivate echo $MKLROOT conda activate radev echo $MKLROOT The MKLSAVE variable is used so that a separate MKL installation on your machine, if one exists, is properly reset in your environment following deactivation. Configuration and Compilation ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ Building the documentation is the same on Linux and Mac. .. code-block:: bash conda activate radev cd /path/to/Rayleigh make doc Once the documetation builds, you can access it by opening Rayleigh/doc/build/html/index.html in your web browser. Building the code different slightly on Linux and Mac. For Linux, execute the following: .. code-block:: bash conda activate radev cd /path/to/Rayleigh ./configure -conda-mkl --FC=mpifort make For Mac, run: .. code-block:: bash conda activate radev cd /path/to/Rayleigh ./configure -mac-mkl -conda-mkl --FC=mpifort make At this point, you can run "make install," and run the code using mpirun as you normally would (keep the radev environment active when doing this). Docker Container ---------------- Docker provides a standardized way to build, distribute and run containerized environments on Linux, macOS, and Windows. To get started you should install Docker on your system following the instructions from `here `_. On Linux you can likely also install it from a distribution package (e.g., ``docker-io`` on Debian/Ubuntu). Launching the container ^^^^^^^^^^^^^^^^^^^^^^^ You can download our pre-built container from Docker Hub and launch it using the command .. code-block:: bash docker run -it --rm -v $HOME:/root geodynamics/rayleigh-buildenv-bionic This will give you a shell inside the container and mount your home directory at ``/root``. You can clone, configure, build, and run the code and analyze the outputs using Python inside the container. Any changes below ``/root`` will be reflected in your home directory. Any other changes to the container will be deleted once you exit the shell. .. note:: This looks like you are running everything as the root user, but viewed from outside the container you are still running everything as the user who launched docker. Running as root inside the container has the advantage that you can easily get additional package using the ``apt`` command. Configuration and Compilation ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ .. note:: All these commands are run inside the Docker container and assume you have a copy of Rayleigh at ``$HOME/path/to/Rayleigh`` (which corresponds to ``/root/path/to/Rayleigh`` inside the container). Building the documentation .. code-block:: bash cd /root/path/to/Rayleigh make doc Building the code .. code-block:: bash cd /root/path/to/Rayleigh ./configure --with-fftw=/usr make Building the container ^^^^^^^^^^^^^^^^^^^^^^ .. note:: This step purely optional. You only need to do this if you cannot pull the container from Docker Hub or you want to modify the Dockerfile. To build the container you have to run this command from your host system (i.e., not from inside the container). .. code-block:: bash cd docker docker build -t geodynamics/rayleigh-buildenv-bionic:latest rayleigh-buildenv-bionic You can check the newly built container is there using this command. .. code-block:: bash docker images