Convert ROCm snippet to macro and fix Apptainer references

Make rocmcontainers a reusable macro-based snippet with {CLUSTER}/{cluster}
placeholders, replace remaining Singularity wording with Apptainer, correct
the biocontainers detailed-guide link to apptainer.org, and update the FAQ
cache path to .apptainer.

Author: Guangzhen-Jin

docs/snippets/examples/apps/biocontainers.md

@@ -9,7 +9,7 @@ The BioContainers project came from the idea of using the containers-based techn
 
 Users can download bioinformatic containers from the [BioContainers.pro](https://biocontainers.pro) and run them directly using Apptainer instructions from the corresponding container’s catalog page.
 
-Brief Apptainer guide and examples are available at the [{CLUSTER} Apptainer user guide](apptainer.md) page. Detailed Apptainer user guide is available at: [sylabs.io/guides/3.8/user-guide](https://sylabs.io/guides/3.8/user-guide/)
+Brief Apptainer guide and examples are available at the [{CLUSTER} Apptainer user guide](apptainer.md) page. Detailed Apptainer user guide is available at: [apptainer.org/docs/user/main](https://apptainer.org/docs/user/main/)
 
 In addition, a subset of pre-downloaded biocontainers wrapped into convenient software modules are provided. These modules wrap underlying complexity and provide the same commands that are expected from non-containerized versions of each application.
 

docs/snippets/examples/apps/rocmcontainers.md

@@ -1,16 +1,17 @@
+<!-- Template snippet: {CLUSTER} = title-case cluster name (e.g. "{CLUSTER}"), {cluster} = lowercase (e.g. "{cluster}"). Replaced at build time by `rocmcontainers_snippet` in main.py. -->
 # ROCm Containers Collection
 
 ## What is ROCm Containers?
 
-The AMD Infinity Hub contains a collection of advanced AMD GPU software containers and deployment guides for HPC, AI & Machine Learning applications, enabling researchers to speed up their time to science. Containerized applications run quickly and reliably in the high performance computing environment with full support of AMD GPUs. A collection of Infinity Hub tools were deployed to extend cluster capabilities and to enable powerful software and deliver the fastest results. By utilizing Singularity and Infinity Hub ROCm-enabled containers, users can focus on building lean models, producing optimal solutions and gathering faster insights. For more information, please visit [AMD Infinity Hub](https://web.archive.org/web/20230902021513/https://www.amd.com/en/technologies/infinity-hub/).
+The AMD Infinity Hub contains a collection of advanced AMD GPU software containers and deployment guides for HPC, AI & Machine Learning applications, enabling researchers to speed up their time to science. Containerized applications run quickly and reliably in the high performance computing environment with full support of AMD GPUs. A collection of Infinity Hub tools were deployed to extend cluster capabilities and to enable powerful software and deliver the fastest results. By utilizing Apptainer and Infinity Hub ROCm-enabled containers, users can focus on building lean models, producing optimal solutions and gathering faster insights. For more information, please visit [AMD Infinity Hub](https://web.archive.org/web/20230902021513/https://www.amd.com/en/technologies/infinity-hub/).
 
 ## Getting Started
 
-Users can download ROCm containers from the [AMD Infinity Hub](https://web.archive.org/web/20230902021513/https://www.amd.com/en/technologies/infinity-hub/) and run them directly using Singularity instructions from the corresponding container’s catalog page.
+Users can download ROCm containers from the [AMD Infinity Hub](https://web.archive.org/web/20230902021513/https://www.amd.com/en/technologies/infinity-hub/) and run them directly using Apptainer instructions from the corresponding container’s catalog page.
 
 In addition, a subset of pre-downloaded ROCm containers wrapped into convenient software modules are provided. These modules wrap underlying complexity and provide the same commands that are expected from non-containerized versions of each application.
 
-On Bell, type the command below to see the lists of ROCm containers we deployed.
+On {CLUSTER}, type the command below to see the lists of ROCm containers we deployed.
 
 ```
 

docs/userguides/bell/faqs.md

@@ -77,7 +77,7 @@ There are several common locations that tend to grow large over time and are mer
 /home/myusername/.local/share/Trash
 /home/myusername/.cache/pip
 /home/myusername/.conda/pkgs
-/home/myusername/.singularity/cache
+/home/myusername/.apptainer/cache
 ```
 
 ### My SSH connection hangs

docs/userguides/bell/run/examples/apps/rocmcontainers.md

@@ -8,6 +8,6 @@ search:
   boost: 2
 ---
 
---8<-- "docs/snippets/examples/apps/rocmcontainers.md"
+{{ rocmcontainers_snippet(resource) }}
 
 [**Back to the Specific Applications section**](../apps.md)

main.py

@@ -709,6 +709,12 @@ def biocontainers_snippet(resource):
             content = f.read()
         return content.replace("{CLUSTER}", resource.title()).replace("{cluster}", resource.lower())
 
+    @env.macro
+    def rocmcontainers_snippet(resource):
+        with open("docs/snippets/examples/apps/rocmcontainers.md", "r") as f:
+            content = f.read()
+        return content.replace("{CLUSTER}", resource.title()).replace("{cluster}", resource.lower())
+
     @env.macro
     def resource_use(resource):
         with open("docs/snippets/resourceuse.md", "r") as f: