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.
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.
export MKLROOT="$CONDA_PREFIX"
Note that this is Bash syntax (use setenv if running c-shell). Note that there should be no spaces on either side of the “=” sign. If you stop here, you will have to do this every time you activate your development environment. To have this happen automatically, you only need to add two small scripts to radev/etc/conda/activate.d and radev/etc/conda/deactivate.d directories. Scripts in these directories are automatically executed when your conda environment is activated and deactivated, respectively.
Change to your activate.d directory (for me, this was /custom/software/miniconda3/envs/radev/etc/conda/activate.d) and create a file named activate_mkl.sh with the following three lines:
#!/bin/bash
export MKLSAVE="$MKLROOT"
export MKLROOT="$CONDA_PREFIX"
In the deactivate.d directory, create a file named deactivate_mkl.sh with the following two lines:
#!/bin/bash
export MKLROOT="$MKLSAVE"
Now, try it out.
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.
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 is again the same on Linux and Mac. Execute the following:
conda activate radev
cd /path/to/Rayleigh
./configure -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 from the main Rayleigh directory. The following command is for GNU/Linux and macOS users.
./docker-devel
# This runs the following command:
# docker run -it --rm -v $HOME:/work -e HOSTUID=$UID -e HOSTGID=$GROUPS -e HOSTUSER=$USER geodynamics/rayleigh-devel-bionic:latest
This will give you a shell inside the container and mount your home directory at /work. You can clone, configure, build, and run the code and analyze the outputs using Python inside the container. Any changes below /work will be reflected in your home directory. Any other changes to the container will be deleted once you exit the shell.
Note
Your user has sudo rights within the container. This allows to install packages using the apt command or modify the system in any other way.
Windows users should run the script docker-devel.bat instead.
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
cd /work/path/to/Rayleigh
make doc
Building the code
cd /work/path/to/Rayleigh
./configure --with-fftw=/usr
make
Updating the container¶
On the first launch of the container, your local Docker engine will automatically download our pre-built container from Docker Hub. Subsequent launches will just use this container and will not check for updates. You can download a newer version of the container using the following command.
docker pull geodynamics/rayleigh-devel-bionic:latest
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).
cd docker
docker build -t geodynamics/rayleigh-devel-bionic:latest rayleigh-devel-bionic
You can check the newly built container is there using this command.
docker images
Spack Environment¶
Spack can be used to create a development environment to build the code in a local directory. First set up Spack using the instructions in Alternative: Installation using Spack
Afterwards create a new environment, activate it and set the status of the Rayleigh package to development. We select $PWD as the path, so run this command from the base directory of your git clone.
spack env create rayleigh
spack env activate rayleigh
spack add rayleigh@master
spack develop -p "$PWD" rayleigh@master
A subsequent spack install will install necessary dependencies and build Rayleigh in the selected directory.
