Merge pull request #239 from NYU-RTS/main

Updating DTN info

Author: mdweisner

docs/hpc/07_containers/03_singularity_with_conda.md

@@ -83,10 +83,14 @@ For the most recent supported versions of PyTorch, please check the [PyTorch web
 
 Launch the appropriate Singularity container in read/write mode (with the :rw flag):
 ```sh
-singularity exec --overlay overlay-15GB-500K.ext3:rw /share/apps/images/cuda12.1.1-cudnn8.9.0-devel-ubuntu22.04.2.sif /bin/bash
+singularity exec --fakeroot --overlay overlay-15GB-500K.ext3:rw /share/apps/images/cuda12.1.1-cudnn8.9.0-devel-ubuntu22.04.2.sif /bin/bash
 ```
 
-The above starts a bash shell inside the referenced Singularity Container overlaid with the 15GB 500K you set up earlier. This creates the functional illusion of having a writable filesystem inside the typically read-only Singularity container.
+The above starts a bash shell inside the referenced Singularity Container overlaid with the 15GB 500K you set up earlier. This creates the functional illusion of having a writable filesystem inside the typically read-only Singularity container. 
+
+:::note
+Please note that the default Singularity on Torch is now Apptainer, which requires the --fakeroot option to load overlay files in read/write mode.
+:::
 
 Now, inside the container, download and install miniforge to `/ext3/miniforge3`:
 ```bash
@@ -164,7 +168,7 @@ The login nodes restrict memory to 2GB per user, which may cause some large pack
 After it is running, you’ll be redirected to a compute node. From there, run singularity to setup on conda environment, same as you were doing on login node:
 
 ```sh
-[NetID@cm001 pytorch-example]$ singularity exec --overlay overlay-15GB-500K.ext3:rw /share/apps/images/cuda12.1.1-cudnn8.9.0-devel-ubuntu22.04.2.sif /bin/bash
+[NetID@cm001 pytorch-example]$ singularity exec --fakeroot --overlay overlay-15GB-500K.ext3:rw /share/apps/images/cuda12.1.1-cudnn8.9.0-devel-ubuntu22.04.2.sif /bin/bash
 
 Singularity> source /ext3/env.sh
 # activate the environment

docs/hpc/09_ood/07_jupyter_with_conda_singularity.mdx

@@ -65,7 +65,7 @@ Above we used the overlay file `overlay-15GB-500K.ext3.gz` which will contain al
 
 ### Launch Singularity Environment for Installation
 ```bash
-[NetID@log-1 ~]$ singularity exec --overlay /scratch/$USER/my_env/overlay-15GB-500K.ext3:rw /share/apps/images/cuda12.3.2-cudnn9.0.0-ubuntu-22.04.4.sif /bin/bash
+[NetID@log-1 ~]$ singularity exec --fakeroot --overlay /scratch/$USER/my_env/overlay-15GB-500K.ext3:rw /share/apps/images/cuda12.3.2-cudnn9.0.0-ubuntu-22.04.4.sif /bin/bash
 ```
 Above we used the Singularity OS image `cuda12.3.2-cudnn9.0.0-ubuntu-22.04.4.sif` which provides the base operating system environment for the conda environment. There are other Singularity OS images available at `/share/apps/images`
 
@@ -137,6 +137,8 @@ Singularity> which pip
 
 Now use either conda or pip to install your required python packages to the Miniforge environment.
 
+:::note If using Apptainer (the default Singularity installation on Torch) be sure to use the --fakeroot flag when launching overlay files in read-write mode (:rw).
+
 To install larger packages, like Tensorflow, you must first start an interactive job with adequate compute and memory resources to install packages. The login nodes restrict memory to 2GB per user, which may cause some large packages to crash.
 ```bash
 Singularity> exit
@@ -145,7 +147,7 @@ Singularity> exit
 
 # wait to be assigned a node
 
-[NetID@cm001 my_env]$ singularity exec --overlay /scratch/$USER/my_env/overlay-15GB-500K.ext3:rw /share/apps/images/cuda12.3.2-cudnn9.0.0-ubuntu-22.04.4.sif /bin/bash
+[NetID@cm001 my_env]$ singularity exec --fakeroot --overlay /scratch/$USER/my_env/overlay-15GB-500K.ext3:rw /share/apps/images/cuda12.3.2-cudnn9.0.0-ubuntu-22.04.4.sif /bin/bash
 
 Singularity> source /ext3/env.sh
 # activate the environment