Connecting to a Cluster¶

We recommend interacting with clusters primarily through Jupyter Notebooks and Jobs. However, it may be necessary to connect directly to a cluster in some cases. In that case, you can connect through a notebook terminal.

Connecting with a Notebook Terminal¶

Notebook-Terminal

If your cluster has more than one node , you can connect to any of the cluster nodes by running the following command in the terminal:

ssh <NODE-IP>

Connect-Cluster

Through this terminal, you can access the /bodofs folder, which is shared by all the instances in the cluster and the Notebook instance. Verify your connection to interact directly with your cluster.

Verify your Connection¶

Once you have connected to a node in your cluster, you should verify that you can run operations across all the instances in the cluster.

Verify the path to the hostfile for your cluster. You can find it by running:
```
ls -la /home/bodo/hostfile
```
Check that you can run a command across you cluster. To do this, run:
```
mpiexec -n <TOTAL_CORE_COUNT> -f /home/bodo/hostfile hostname
```
This will print one line per each core in the cluster, with one unique hostname per cluster node.

Your cluster's TOTAL_CORE_COUNT is usually half the number of vCPUs on each instance times the number of instances in your cluster. For example, if you have a 4 instance cluster of c5.4xlarge, then your TOTAL_CORE_COUNT is 32.
Verify that you can run a python command across your cluster. For example, run:
```
mpiexec -n <TOTAL_CORE_COUNT> -f /home/bodo/hostfile python --version
```

If all commands succeed, you should be able to execute workloads across your cluster. You can place scripts and data that are shared across cluster nodes in /bodofs.