-[Using an Anaconda Environment in a Jupyter Notebook](#using-an-anaconda-environment-in-a-jupyter-notebook)
### Using Anaconda
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@@ -245,6 +246,52 @@ If you have custom GPU Anaconda environment please only use the two lines from a
Using `module load tensorflow-gpu/py36/1.14` and `conda activate tensorflow-gpu-1.14-custom` in the same script is **wrong** and may give you various errors and incorrect results.
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### 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.**
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.
First, at install time, besides the package, the package `openmpi=4.1.*=external_*` or `mpich=4.0.*=external_*` needs to be installed for `openmpi` or `mpich` respectively.
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.
For example, the steps for creating conda environment with `mpi4py` that supports `openmpi` are:
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