Check and correct uses of `partition` in changed places

doc.zih.tu-dresden.de/docs/jobs_and_resources/slurm_examples.md

@@ -196,7 +196,7 @@ When `srun` is used within a submission script, it inherits parameters from `sba
 `--ntasks=1`, `--cpus-per-task=4`, etc. So we actually implicitly run the following
 
 ```bash
-srun --ntasks=1 --cpus-per-task=4 [...] --partition=power9 some-gpu-application
+srun --ntasks=1 --cpus-per-task=4 [...] some-gpu-application
 ```
 
 Now, our goal is to run four instances of this program concurrently in a single batch script. Of

doc.zih.tu-dresden.de/docs/software/distributed_training.md

@@ -208,8 +208,8 @@ parameter `--ntasks-per-node=<N>` equals the number of GPUs you use per node.
 Also, it can be useful to increase `memory/cpu` parameters if you run larger models.
 Memory can be set up to:
 
-- `--mem=250G` and `--cpus-per-task=7` for the partition `power9`.
-- `--mem=900G` and `--cpus-per-task=6` for the partition `alpha`.
+- `--mem=250G` and `--cpus-per-task=7` for the `Power9` cluster.
+- `--mem=900G` and `--cpus-per-task=6` for the `Alpha` cluster.
 
 Keep in mind that only one memory parameter (`--mem-per-cpu=<MB>` or `--mem=<MB>`) can be specified.
 

doc.zih.tu-dresden.de/docs/software/modules.md

@@ -338,10 +338,11 @@ So the concept if this hierarchical toolchains is already built into this module
 ## Per-Architecture Builds
 
 Since we have a heterogeneous cluster, we do individual builds of the software for each
-architecture present. This ensures that, no matter what partition the software runs on, a build
+architecture present.
+This ensures that, no matter what partition/cluster the software runs on, a build
 optimized for the host architecture is used automatically.
 
-However, not every module will be available for each node type or partition.
+However, not every module will be available on all clusters.
 Use `ml av` or `ml spider` to search for modules available on the sub-cluster you are on.
 
 ## Advanced Usage

doc.zih.tu-dresden.de/docs/software/power_ai.md

@@ -5,7 +5,7 @@ the PowerAI Framework for Machine Learning. In the following the links
 are valid for PowerAI version 1.5.4.
 
 !!! warning
-    The information provided here is available from IBM and can be used on partition `power9` only!
+    The information provided here is available from IBM and can be used on the `Power9` cluster only!
 
 ## General Overview
 
@@ -47,7 +47,7 @@ are valid for PowerAI version 1.5.4.
   (Open Neural Network Exchange) provides support for moving models
   between those frameworks.
 - [Distributed Deep Learning](https://www.ibm.com/support/knowledgecenter/SS5SF7_1.5.4/navigation/pai_getstarted_ddl.html?view=kc)
-  Distributed Deep Learning (DDL). Works on up to 4 nodes on partition `power9`.
+  Distributed Deep Learning (DDL). Works on up to 4 nodes on cluster `Power9`.
 
 ## PowerAI Container
 

doc.zih.tu-dresden.de/docs/software/virtual_machines.md

@@ -47,7 +47,7 @@ times till it succeeds.
 bash-4.2$ cat /tmp/marie_2759627/activate
 #!/bin/bash
 
-if ! grep -q -- "Key for the VM on the partition power9" "/home/marie/.ssh/authorized_keys" > /dev/null; then
+if ! grep -q -- "Key for the VM on the cluster power" "/home/marie/.ssh/authorized_keys" > /dev/null; then
   cat "/tmp/marie_2759627/kvm.pub" >> "/home/marie/.ssh/authorized_keys"
 else
   sed -i "s|.*Key for the VM on the cluster power.*|ssh-rsa AAAAB3NzaC1yc2EAAAADAQABAAABAQC3siZfQ6vQ6PtXPG0RPZwtJXYYFY73TwGYgM6mhKoWHvg+ZzclbBWVU0OoU42B3Ddofld7TFE8sqkHM6M+9jh8u+pYH4rPZte0irw5/27yM73M93q1FyQLQ8Rbi2hurYl5gihCEqomda7NQVQUjdUNVc6fDAvF72giaoOxNYfvqAkw8lFyStpqTHSpcOIL7pm6f76Jx+DJg98sXAXkuf9QK8MurezYVj1qFMho570tY+83ukA04qQSMEY5QeZ+MJDhF0gh8NXjX/6+YQrdh8TklPgOCmcIOI8lwnPTUUieK109ndLsUFB5H0vKL27dA2LZ3ZK+XRCENdUbpdoG2Czz Key for the VM on the cluster power|" "/home/marie/.ssh/authorized_keys"