@@ -248,8 +248,7 @@ Using `module load tensorflow-gpu/py36/1.14` and `conda activate tensorflow-gpu-
### Creating Custom MPI Anaconda Environment
Some conda packages available on `conda-forge` and `bioconda` support MPI (via `openmpi` or `mpich`).
**Currently only packages that were built using `openmpi 4.1` and `mpich 4.0` are supported on HCC clusters.**
Some conda packages available on `conda-forge` and `bioconda` support MPI (via `openmpi` or `mpich`). However, just using the `openmpi` and `mpich` packages from `conda-forge` often does not work on HPC systems. More information about this can be found [here](https://conda-forge.org/docs/user/tipsandtricks.html#using-external-message-passing-interface-mpi-libraries).
In order to be able to correctly use these MPI packages with the MPI libraries installed on our clusters, two steps need to be performed.
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@@ -257,6 +256,7 @@ First, at install time, besides the package, the "dummy" package `openmpi=4.1.*=
These "dummy" packages are empty, but allow the solver to create correct environments and use the system-wide modules when the environment is activated.
Secondly, when activating the conda environment and using the package, the system-wide `openmpi/4.1` or `mpich/4.0` module needs to be loaded depending on the MPI library used.
**Currently only packages that were built using `openmpi 4.1` and `mpich 4.0` are supported on HCC clusters.**
For example, the steps for creating conda environment with `mpi4py` that supports `openmpi` are:
{{% panel theme="info" header="Creating Anaconda environment with openmpi" %}}
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@@ -275,7 +275,6 @@ conda activate mpi4py-openmpi
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The steps for creating conda environment with `mpi4py` that supports `mpich` are:
{{% panel theme="info" header="Creating Anaconda environment with mpich" %}}
