Update conda page and fix broken link

content/applications/user_software/using_anaconda_package_manager.md

@@ -122,6 +122,13 @@ Our new environment is now active, and we can use it.  The shell prompt will cha
 
 ### Adding and Removing Packages from an Existing Environment
 
+{{% notice note %}}
+**NOTE:** By default, conda packages are installed in the user's `home` directory.
+Since Crane's `home` directories are not writeable from the worker nodes, 
+the commands for installing, adding and removing conda packages shown here
+should be performed on the **login node**, and not as part of an interactive or SLURM job.
+{{% /notice %}}
+
 To install additional packages in an environment, use the `install`
 subcommand.  Suppose we want to install iPython in our 'mynumpy'
 environment.  While the environment is active, use `install `with no
@@ -230,7 +237,7 @@ Jupyter Notebook. To do so, follow the steps below, replacing
         server.
     3.  Click the logout button in the top right corner.  
           
-2.  Using the command-line environment, load the target conda
+2.  Using the command-line environment of the **login node**, load the target conda
     environment:
     {{< highlight bash >}}conda activate myenv{{< /highlight >}}
 

content/applications/user_software/using_singularity.md

@@ -153,7 +153,7 @@ srun --pty --mem=4gb --qos=short --gres=gpu --partition=gpu $SHELL
 {{% notice info %}}
 The `--gres=gpu --partition=gpu` options are used here as the `tensorflow-gpu` image is
 GPU enabled.  If you are using a non-GPU image, you may omit those options.  See the page
-on [submitting GPU jobs]({{< relref "/guides/submitting_jobs/submitting_cuda_or_openacc_jobs/_index.md" >}})
+on [submitting GPU jobs]({{< relref "../../submitting_jobs/submitting_gpu_jobs/" >}})
 for more information.
 {{% /notice %}}