docs/static/json/swan_partitions.json

+{
+    "table_generated": "1970-01-01T00:00:00UTC",
+    "table_header": [
+      "Partition",
+      "Owner",
+      "Node total(NODExCPU/MEM/FEATURE)",
+      "Description",
+      "SLURM Specification",
+      "Max Job Run Time",
+      "Max CPUs Per User",
+      "Max Jobs PerUser"
+    ],
+    "table_data": [
+      [
+        "batch",
+        "shared",
+        "91 total (4x40/1510.0GB/opa; 85x56/250.0GB/cx6; 2x112/503.085GB/cx6)",
+        "(default, no specification)",
+        "#SBATCH --partition=batch",
+        "7-00:00:00",
+        "opa:160 cx6:4760",
+        "1000"
+      ]
+    ]
+}
\ No newline at end of file

docs/static/markdown/anvil-images.md

+|       Image Name                |  Username to Connect  |        Access instructions           |                                 Description                                       |
+| ------------------------------- | --------------------- | ------------------------------------ | --------------------------------------------------------------------------------- |
+| Alma Linux 8.10                 |  `almalinux`          | `ssh -l almalinux <ip address>`      | AlmaLinux is a free and open source Linux distribution that is binary-compatible with Red Hat Enterprise Linux (RHEL).|
+| Alma Linux 8.10 Xfce            |  `almalinux`          | [X2Go instructions](/anvil/connecting_to_linux_instances_using_x2go/)   | AlmaLinux 8.10 with the Xfce Desktop Environment pre-installed.|
+| Cloudera 5.12 GNOME             |  `cloudera`           | [X2Go instructions](/anvil/connecting_to_linux_instances_using_x2go/) | Cloudera 5.12 QuickStart VM. *Note*: Follow the X2Go instructions, but choose GNOME for the Session type instead of Xfce.|
+| Fedora 39 Cloud                 |  `fedora`             | `ssh -l fedora <ip address>`          | Fedora is a Linux distribution developed by the community-supported Fedora Project and sponsored by the Red Hat company.|
+| Fedora 40 Cloud                 |  `fedora`             | `ssh -l fedora <ip address>`          | Fedora is a Linux distribution developed by the community-supported Fedora Project and sponsored by the Red Hat company.|
+| Fedora 40 Xfce                  |  `fedora`             | [X2Go instructions](/anvil/connecting_to_linux_instances_using_x2go/) | Fedora 40 with the Xfce Desktop Environment pre-installed.|
+| Windows 10                      |  `.\cloud-user`       | [Windows instructions](/anvil/connecting_to_windows_instances)       | Windows 10 LTSC edition with remote desktop access.|
+| Windows 10 Matlab               |  `.\cloud-user`       | [Windows instructions](/anvil/connecting_to_windows_instances)       | Windows 10 LTSB with Matlab r2013b, r2014b, r2015b, r2016b, r2017a pre-installed. |
+| Windows 10 Matlab r2018b/r2019b |  `.\cloud-user`       | [Windows instructions](/anvil/connecting_to_windows_instances)       | Windows 10 LTSC with Matlab r2018b and r2019b pre-installed. |
+| Windows 10 SAS                  |  `.\cloud-user`       | [Windows instructions](/anvil/connecting_to_windows_instances)       | Windows 10 LTSC with SAS 9.4 pre-installed. |
+| Windows 10 Mathematica          |  `.\cloud-user`       | [Windows instructions](/anvil/connecting_to_windows_instances)       | Windows 10 LTSB with Mathematica 10.4 and 11.0 pre-installed.|
+| Windows 10 Mathematica 12.0     |  `.\cloud-user`       | [Windows instructions](/anvil/connecting_to_windows_instances)  | Windows 10 LTSC with Mathematica 12.0 pre-installed.|
+| Ubuntu Cloud 20.04 LTS          |   `ubuntu`            | `ssh -l ubuntu <ip address>`         | Ubuntu Cloud Image from the 20.04 Long Term Support release.|
+| Ubuntu Cloud 22.04 LTS          |   `ubuntu`            | `ssh -l ubuntu <ip address>`         | Ubuntu Cloud Image from the 22.04 Long Term Support release.|
+| Ubuntu 22.04 LTS Xfce           |   `ubuntu`            | [X2Go instructions](/anvil/connecting_to_linux_instances_using_x2go/) | Ubuntu 22.04 with the Xfce Desktop Environment pre-installed.|
+| MariaDB Server 10.5             |   `centos`/`root`     | `ssh -l centos <ip address>`/[MySQL instructions](/anvil/using_mysql)  | CentOS 7 based image with a pre-configured MariaDB server. |

docs/static/markdown/class-guidelines.md

+The following guidelines apply to any accounts and groups created for the purposes of courses and coursework: 
+
+1) User accounts added to a class group will be removed from the class group one (1) calendar week after the end of the semester. 
+User accounts solely used in class groups will be locked at this time as well. All files/data in user account directories
+($HOME, $WORK, and $COMMON) contained within the class group will be removed at that time. It will be the students’ responsibility 
+to copy any files they would like to keep to a more permanent location before that time. Each student who applies to join 
+the class group must read and agree to these guidelines in advance. The class group owner’s account will be unaffected. 
+Additionally, HCC should be notified in advance of any other accounts, such as teaching assistants, that should not be removed. 
+If a student account is also a member of another, non-coursework, HCC group (e.g., a research group of a faculty member), 
+the user account and the associated files/data under the research group will not be affected. Students will be notified 
+throughout the semester (up to (3) three emails) that they will need to backup their data elsewhere, and it is encouraged 
+that instructors provide reminders in-class.
+
+
+2) All Anvil instances created for the class, excluding the group owner’s instances, will be removed one (1) calendar week after the semester ends. 
+All files/data/software associated with the instances will be removed at that time.
+
+
+3) The class group will be disabled one (1) calendar week after the end of the semester. To re-use a class group for a 
+future semester, the group owner will need to request that the class group be “renewed” using the Class Group Renewal 
+form at least one (1) calendar week before the group will be used. If the group owner plans to teach a new class 
+using HCC resources, they should apply for a new group specific for the class using the course catalog code as 
+the preferred group name, such as “csce123”. As part of the renewal form, HCC encourages optionally uploading a 
+class roster to help expedite the account approval process to avoid the need to manually approve each account.

docs/static/markdown/common-power-off.md

+!!! failure "$COMMON Retirement - **{{ hcc.common.retirement_date }}**"
+    The Common filesystem will be retired from service on **{{ hcc.common.retirement_date }}**!!! 
+    
+    Any jobs on Swan trying to start with the `{{ hcc.common.variable }}` filesystem or `--licenses=common` will not be able to be submitted. 
+
+    **Any data under **`{{ hcc.common.path }}`** or **`{{ hcc.common.variable }}`** will be lost if it is not moved to another location before the retirement  date of {{ hcc.common.retirement_date }}.**
+    
+    It is strongly recommended to begin moving data and updating workflows immediately to avoid lossing data.
+    
+    More information on the retirement is available on the [Common Retirement FAQ Page](/FAQ/common_retirement). If you have any questions about the retirement, please email <a href="mailto:hcc-support@unl.edu" class="external-link">{{ hcc.support_email }}</a>.

docs/static/markdown/events/hybrid_expectations_05-2025.md

+### Workshop Recommendations
+
+To make the most of this workshop, we strongly encourage active participation throughout the entire session, including participating in the hands-on exercises and asking questions throughout the workshop. 
+
+If you are stuck or not sure on something at any point of the workshop, please let us know and we would be happy to help. 
+
+Participation can be accomplished by using the sticky notes, raising hands, or if you are remote, using the Zoom Reactions or use the Zoom chat box.
+

docs/static/markdown/events/hybrid_reactions_05-2025.md

+### Sticky Notes and Reactions
+
+Throughout the workshop, we will use sticky notes and Zoom reactions to indicate status. These help instructors and helpers in the workshop assist with various issues and provide formative feedback during the workshops.
+
+!!! tip "Please make sure the sticky note is visibly on both the front and back of your laptop"
+
+- **Yellow Sticky Note / Green Check Reaction**: All good to go
+- **Red Sticky Note / Red "X" Reaction**: I need help or I am not ready to continue
+
+{% include "./zoom_reactions_05-2025.md" %}

docs/static/markdown/events/in-person_expectations_05-2025.md

+### Workshop Recommendations
+
+To make the most of this workshop, we strongly encourage active participation throughout the entire session, including participating in the hands-on exercises and asking questions throughout the workshop. 
+
+If you are stuck or not sure on something at any point of the workshop, please let us know and we would be happy to help. 
+
+Participation can be accomplished by using the sticky notes or raising hands.
+

docs/static/markdown/events/in-person_reactions_05-2025.md

+### Sticky Notes and Reactions
+
+Throughout the workshop, we will use sticky notes to indicate status. These help instructors and helpers in the workshop assist with various issues and provide formative feedback during the workshops.
+
+!!! tip "Please make sure the sticky note is visibly on both the front and back of your laptop"
+
+- **Yellow Sticky Note**: All good to go
+- **Red Sticky Note**: I need help or I am not ready to continue
+

docs/static/markdown/events/ood_setup_hybrid_05-2025.md

+!!! warning "Please make sure to complete the setup steps below each week."
+
+    1. Ensure your HCC Account is active.
+
+    2. Sign into Swan's Open OnDemand Portal: {{ hcc.swan.ood.url }}
+
+    3. When you have signed into the Swan Open OnDemand Portal, please put up your Yellow Sticky Note or Green Checkmark.
+
+    **If you have any issues logging in or accesing Swan, please visit our [event troubleshooting guide here](/Events/general_materials/#troubleshooting-logging-into-swan)**

docs/static/markdown/events/zoom_expectations_05-2025.md

+### Workshop Recommendations
+
+To make the most of this workshop, we strongly encourage active participation throughout the entire session, including participating in the hands-on exercises and asking questions throughout the workshop. 
+
+If you are stuck or not sure on something at any point of the workshop, please let us know and we would be happy to help. 
+
+Participation can be accomplished by using the Zoom Reactions or use the Zoom chat box.

docs/static/markdown/events/zoom_reactions_05-2025.md

+??? note "How to use Zoom Reactions"
+    1. In the menu bar at the bottom of the Zoom window, click on `React`.
+    
+        ![](/images/events/guides/zoom_menu_bar_05-2025.png)
+    
+    2. In the pop up panel, select the appropriate reaction. 
+
+        ![](/images/events/guides/zoom_react_panel_05-2025.png)
+    
+    Full Details: https://support.zoom.com/hc/en/article?id=zm_kb&sysparm_article=KB0063323

docs/stylesheets/extra.css

+:root  > * {
+  --md-primary-fg-color:        #D00000;
+  --md-primary-fg-color--light: #FEFDFA;
+  --md-primary-fg-color--dark:  #14151a;
+}
+
+/* Add padding to bottom of content to prevent overlap */
+.md-main {
+  padding-bottom: 80px; /* adjust based on footer height */
+}

docs/submitting_jobs/.nav.yml

+title: Submitting Jobs

docs/submitting_jobs/app_specific/index.md

+---
+title: "Application Specific Guides"
+weight: 100
+---
+
+!!! note
+    All of the examples below are available in a single repository at https://github.com/unlhcc/job-examples.
+
+## In-depth guides for running applications on HCC resources
+
+This repository contains scripts, data, and submit files for running many popular applications on the Holland Computing Center clusters.
+
+#### Applications included:
+- **BLAST** – includes advanced examples
+- **MATLAB**
+- **Python**
+- **R** – includes advanced examples
+- **Mathematica**
+- **Gaussian**
+- **Jupyter Notebook** – including Python and R scripts
+- **GAMESS**
+- **And More...**
+<br>
+<br>
+- [Application Examples](https://github.com/unlhcc/job-examples)
+- [Submitting ANSYS Jobs](./submitting_ansys_jobs/)
+- [Submitting MATLAB Jobs](./submitting_matlab_jobs/)
+- [Submitting R Jobs](./submitting_r_jobs/)
+
+
+For assistance or support regarding these examples or any HCC resources, please contact us at **[hcc-support@unl.edu](mailto:hcc-support@unl.edu)**.
+

content/guides/submitting_jobs/submitting_ansys_jobs.md → docs/submitting_jobs/app_specific/submitting_ansys_jobs.md

-+++
-title = "Submitting ANSYS Jobs"
-description =  "How to submit ANSYS jobs on HCC resources."
-+++
+---
+title: Submitting ANSYS Jobs
+summary: "How to submit ANSYS jobs on HCC resources."
+---
+
+!!! note
+    The ANSYS software licenses are managed by College of Engineering. To arrange access to ANSYS on HCC resources, contact Paul Pokorny ([paul.pokorny@unl.edu](mailto:paul.pokorny@unl.edu)).
 
-ANSYS license is purchased by College of Engineering. Only users from CoE can access ANSYS on HCC resources. To be added to the 'ansys' group, send an email to hcc-support@unl.edu.
 
 The number of ANSYS tasks is restricted by its license. 
 For research computations, users need to add the line below to their job submission file.
-{{< highlight batch >}}
+```code
 #SBATCH --licenses=ansys_research
-{{< /highlight >}}
+```
 For teaching purposes, users need to add
-{{< highlight batch >}}
+```bat
 #SBATCH --licenses=ansys_teaching
-{{< /highlight >}}
+```
 
 ### Running ANSYS scripts in batch
 
-{{% panel theme="info" header="ANSYS.submit" %}}
-{{< highlight batch >}}
-#!/bin/sh
+!!! note "ANSYS.submit"
+    ```bat
+    #!/bin/bash
     #SBATCH --ntasks=1
     #SBATCH --time=00:30:00
     #SBATCH --mem-per-cpu=1024
@@ -30,12 +32,12 @@ For teaching purposes, users need to add
     
     module load ansys/19.2
     YOUR_ANSYS_COMMAND
-{{< /highlight >}}
-{{% /panel %}}
-Details of SLURM job submission can be found at [SUBMITTING JOBS]({{< relref "submitting_jobs" >}}).
+    ```
+
+Details of SLURM job submission can be found at [SUBMITTING JOBS](/submitting_jobs/).
 
 ### Running ANSYS interactively
 
-1. To use graphical user interface, users need to first setup X11 forwarding. [HOW TO SETUP X11 FORWARDING]({{< relref "how_to_setup_x11_forwarding" >}})
-1. Start an interactie job using srun. NOTE: users need to add \--licenses=ansys_research or \--licenses=ansys_teaching to the srun command. [SUBMITTING AN INTERACTIVE JOB]({{< relref "submitting_an_interactive_job" >}})
+1. To use graphical user interface, users need to first setup X11 forwarding. [HOW TO SETUP X11 FORWARDING](/connecting/how_to_setup_x11_forwarding/)
+1. Start an interactie job using srun. NOTE: users need to add \--licenses=ansys_research or \--licenses=ansys_teaching to the srun command. [SUBMITTING AN INTERACTIVE JOB](../../creating_an_interactive_job/)
 1. After the interactive job starts, execute "module load ansys/19.2", then run the ANSYS command, e.g. fluent, from command line. The GUI will show up if steps 1-2 are configured correctly. 

content/guides/submitting_jobs/submitting_matlab_jobs.md → docs/submitting_jobs/app_specific/submitting_matlab_jobs.md

-+++
-title = "Submitting MATLAB Jobs"
-description =  "How to submit MATLAB jobs on HCC resources."
-+++
+---
+title: Submitting MATLAB Jobs
+summary: "How to submit MATLAB jobs on HCC resources."
+---
 
 Submitting Matlab jobs is very similar to
-[submitting MPI jobs]({{< relref "submitting_an_mpi_job" >}}) or
-[serial jobs]({{< relref "/guides/submitting_jobs/_index.md" >}})
+[submitting MPI jobs](../../submitting_an_mpi_job/) or
+[serial jobs](/submitting_jobs/)
 (depending if you are using parallela matlab).
 
 ### Submit File
@@ -13,9 +13,9 @@ Submitting Matlab jobs is very similar to
 The submit file will need to be modified to allow Matlab to work.
 Specifically, these two lines should be added before calling matlab:
 
-{{% panel theme="info" header="serial_matlab.submit" %}}
-{{< highlight batch >}}
-#!/bin/sh
+!!! note "serial_matlab.submit"
+    ```bat
+    #!/bin/bash
     #SBATCH --time=03:15:00
     #SBATCH --mem-per-cpu=1024
     #SBATCH --job-name=[job_name]
@@ -24,16 +24,16 @@ Specifically, these two lines should be added before calling matlab:
     
     module load matlab/r2014b
     matlab -nodisplay -r "[matlab script name], quit"
-{{< /highlight >}}
-{{% /panel %}}
+    ```
+
 
 ### Parallel Matlab .m file
 
 The submit file:
 
-{{% panel theme="info" header="parallel_matlab.submit" %}}
-{{< highlight batch >}}
-#!/bin/sh
+!!! note "parallel_matlab.submit"
+    ```bat
+    #!/bin/bash
     #SBATCH --nodes=1
     #SBATCH --ntasks-per-node=5
     #SBATCH --time=03:15:00
@@ -44,8 +44,8 @@ The submit file:
     
     module load matlab/r2014b
     matlab -nodisplay -r "[matlab script name], quit"
-{{< /highlight >}}
-{{% /panel %}}
+    ```
+
 
 #### Matlab File Additions
 
@@ -53,9 +53,9 @@ In addition to the changes in the submit file, if you are running
 parallel Matlab, you will also need to add to the .m file the additional
 lines:
 
-{{< highlight batch >}}
+```matlab
 ...
 i=str2num(getenv('SLURM_TASKS_PER_NODE'));
 parpool(i);
 ...
-{{< /highlight >}}
+```

content/guides/submitting_jobs/submitting_r_jobs.md → docs/submitting_jobs/app_specific/submitting_r_jobs.md

-+++
-title = "Submitting R Jobs"
-description =  "How to submit R jobs on HCC resources."
-+++
+---
+title: Submitting R Jobs
+summary: "How to submit R jobs on HCC resources."
+---
 
 Submitting an R job is very similar to submitting a serial job shown
-on [Submitting Jobs]({{< relref "/guides/submitting_jobs/_index.md" >}}).
+on [Submitting Jobs](/submitting_jobs/).
 
 - [Running R scripts in batch](#running-r-scripts-in-batch)
   - [Running R scripts using `R CMD BATCH`](#running-r-scripts-using-r-cmd-batch)
   - [Running R scripts using `Rscript`](#running-r-scripts-using-rscript)
 - [Multicore (parallel) R submission](#multicore-parallel-r-submission)
 - [Multinode R submission with Rmpi](#multinode-r-submission-with-rmpi)
-- [Adding packages](#adding-packages)
-  - [Installing packages interactively](#installing-packages-interactively)
-  - [Installing packages using R CMD INSTALL](#installing-packages-using-r-cmd-install)
 
   
 ### Running R scripts in batch
@@ -28,17 +25,17 @@ When utilizing `R CMD BATCH` all output will be directed to an `.Rout`
 file named after your script unless otherwise specified. For
 example:
 
-{{% panel theme="info" header="serial_R.submit" %}}
-{{< highlight batch >}}
-#!/bin/sh
+!!! note "serial_R.submit"
+    ```bat
+    #!/bin/bash
     #SBATCH --time=00:30:00
     #SBATCH --mem-per-cpu=1024
     #SBATCH --job-name=TestJob
     
     module load R/3.5
     R CMD BATCH Rcode.R
-{{< /highlight >}}
-{{% /panel %}}
+    ```
+
 
 In the above example, output for the job will be found in the file
 `Rcode.Rout`. Notice that we did not specify output and error files in
@@ -48,17 +45,17 @@ the `.Rout` file. To direct output to a specific location, follow your
 directed to, as follows:
 
 
-{{% panel theme="info" header="serial_R.submit" %}}
-{{< highlight batch >}}
-#!/bin/sh
+!!! note "serial_R.submit"
+    ```bat
+    #!/bin/bash
     #SBATCH --time=00:30:00
     #SBATCH --mem-per-cpu=1024
     #SBATCH --job-name=TestJob
     
     module load R/3.5
     R CMD BATCH Rcode.R Rcodeoutput.txt
-{{< /highlight >}}
-{{% /panel %}}
+    ```
+
 
 In this example, output from running the script `Rcode.R` will be placed
 in the file `Rcodeoutput.txt`.
@@ -67,17 +64,17 @@ To pass arguments to the script, they need to be specified after `R CMD
 BATCH` but before the script to be executed, and preferably preceded
 with `--args` as follows:
 
-{{% panel theme="info" header="serial_R.submit" %}}
-{{< highlight batch >}}
-#!/bin/sh
+!!! note "serial_R.submit"
+    ```bat
+    #!/bin/bash
     #SBATCH --time=00:30:00
     #SBATCH --mem-per-cpu=1024
     #SBATCH --job-name=TestJob
     
     module load R/3.5
     R CMD BATCH "--args argument1 argument2 argument3" Rcode.R Rcodeoutput.txt
-{{< /highlight >}}
-{{% /panel %}}
+    ```
+
 
 
 #### Running R scripts using `Rscript`
@@ -88,9 +85,9 @@ in a manner similar to other programs. This gives the user larger
 control over where to direct the output. For example, to run our script
 using `Rscript` the submit script could look like the following:
 
-{{% panel theme="info" header="serial_R.submit" %}}
-{{< highlight batch >}}
-#!/bin/sh
+!!! note "serial_R.submit"
+    ```bat
+    #!/bin/bash
     #SBATCH --time=00:30:00
     #SBATCH --mem-per-cpu=1024
     #SBATCH --job-name=TestJob
@@ -99,22 +96,22 @@ using `Rscript` the submit script could look like the following:
     
     module load R/3.5
     Rscript Rcode.R
-{{< /highlight >}}
-{{% /panel %}}
+    ```
+
 
 In the above example, STDOUT will be directed to the output file
 `TestJob.%J.stdout` and STDERR directed to `TestJob.%J.stderr`. You
 will notice that the example is very similar to to the
-[serial example]({{< relref "/guides/submitting_jobs/_index.md" >}}).
+[serial example](/submitting_jobs/).
 The important line is the `module load` command.
 That tells the cluster to load the R framework into the environment so jobs may use it.
 
 To pass arguments to the script when using `Rscript`, the arguments
 will follow the script name as in the example below:
 
-{{% panel theme="info" header="serial_R.submit" %}}
-{{< highlight batch >}}
-#!/bin/sh
+!!! note "serial_R.submit"
+    ```bat
+    #!/bin/bash
     #SBATCH --time=00:30:00
     #SBATCH --mem-per-cpu=1024
     #SBATCH --job-name=TestJob
@@ -123,20 +120,20 @@ will follow the script name as in the example below:
     
     module load R/3.5
     Rscript Rcode.R argument1 argument2 argument3
-{{< /highlight >}}
-{{% /panel %}}
+    ```
+
 
 ---
 
 ### Multicore (parallel) R submission
 
 Submitting a multicore R job to SLURM is very similar to
-[Submitting an OpenMP Job]({{< relref "submitting_an_openmp_job" >}}),
+[Submitting an OpenMP Job](../../submitting_an_openmp_job/),
 since both are running multicore jobs on a single node. Below is an example:
 
-{{% panel theme="info" header="parallel_R.submit" %}}
-{{< highlight batch >}}
-#!/bin/sh
+!!! note "parallel_R.submit"
+    ```bash
+    #!/bin/bash
     #SBATCH --ntasks-per-node=16
     #SBATCH --nodes=1
     #SBATCH --time=00:30:00
@@ -147,8 +144,8 @@ since both are running multicore jobs on a single node. Below is an example:
     
     module load R/3.5
     R CMD BATCH Rcode.R
-{{< /highlight >}}
-{{% /panel %}}
+    ```
+
 
 The above example will submit a single job which can use up to 16 cores.
 
@@ -157,26 +154,26 @@ performance will suffer.  For example, when using the
 [parallel](http://stat.ethz.ch/R-manual/R-devel/library/parallel/doc/parallel.pdf)
 package function mclapply:
 
-{{% panel theme="info" header="parallel.R" %}}
-{{< highlight R >}}
+!!! note "parallel.R"
+    ``` R
     library("parallel")
     ...
     mclapply(rep(4, 5), rnorm, mc.cores=16)
-{{< /highlight >}}
-{{% /panel %}}
+    ```
+
 
 ---
 
 ### Multinode R submission with Rmpi
 
 Submitting a multinode MPI R job to SLURM is very similar to 
-[Submitting an MPI Job]({{< relref "submitting_an_mpi_job" >}}),
+[Submitting an MPI Job](../../submitting_an_mpi_job/),
 since both are running multicore jobs on a multiple nodes.
-Below is an example of running Rmpi on Crane on 2 nodes and 32 cores:
+Below is an example of running Rmpi on Swan on 2 nodes and 32 cores:
 
-{{% panel theme="info" header="Rmpi.submit" %}}
-{{< highlight batch >}}
-#!/bin/sh
+!!! note "Rmpi.submit"
+    ```bat
+    #!/bin/bash
     #SBATCH --nodes=2
     #SBATCH --ntasks-per-node=16
     #SBATCH --time=00:30:00
@@ -188,10 +185,10 @@ Below is an example of running Rmpi on Crane on 2 nodes and 32 cores:
     module load compiler/gcc/4.9 openmpi/1.10 R/3.5
     export OMPI_MCA_mtl=^psm
     mpirun -n 1 R CMD BATCH Rmpi.R
-{{< /highlight >}}
-{{% /panel %}}
+    ```
 
-When you run Rmpi job on Crane, please use the line `export
+
+When you run Rmpi job on Swan, please use the line `export
 OMPI_MCA_mtl=^psm` in your submit script. Regardless of how may cores your job uses, the Rmpi package should
 always be run with `mpirun -n 1` because it spawns additional
 processes dynamically.
@@ -199,8 +196,8 @@ processes dynamically.
 Please find below an example of Rmpi R script provided by
 [The University of Chicago Research Computing Center](https://rcc.uchicago.edu/docs/software/environments/R/index.html#rmpi):
 
-{{% panel theme="info" header="Rmpi.R" %}}
-{{< highlight R >}}
+!!! note "Rmpi.R"
+    ``` R
     library(Rmpi)
     
     # initialize an Rmpi environment
@@ -218,57 +215,8 @@ mpi.remote.exec(paste("I am", id, "of", ns, "running on", host))
     # close down the Rmpi environment
     mpi.close.Rslaves(dellog = FALSE)
     mpi.exit()
-{{< /highlight >}}
-{{% /panel %}}
+    ```
+
 
 ---
 
-### Adding packages
-
-There are two options to install packages. The first is to run R on the
-login node and run R interactively to install packages. The second is to
-use the `R CMD INSTALL` command.
-
-{{% notice info %}}
-All R packages must be installed from the login node. R libraries are
-stored in user's home directories which are not writable from the worker
-nodes.
-{{% /notice %}}
-
-#### Installing packages interactively
-
-1.  Load the R module with the command `module load R`
-    -  Note that each version of R uses its own user libraries. To
-       install packages under a specific version of R, specify which
-       version by using the module load command followed by the version
-       number. For example, to load R version 3.5, you would use the
-       command `module load R/3.5`
-2.  Run R interactively using the command `R`
-3.  From within R, use the `install.packages()` command to install
-    desired packages. For example, to install the package `ggplot2`
-    use the command `install.packages("ggplot2")`
-
-Some R packages, require external compilers or additional libraries. If
-you see an error when installing your package you might need to load
-additional modules to make these compilers or libraries available. For
-more information about this, refer to the package documentation.
-
-#### Installing packages using R CMD INSTALL
-
-To install packages using `R CMD INSTALL` the zipped package must
-already be downloaded to the cluster. You can download package source
-using `wget`. Then the `R CMD INSTALL` command can be used when
-pointed to the full path of the source tar file. For example, to install
-ggplot2 the following commands are used:
-
-{{< highlight bash >}}
-# Download the package source:
-wget https://cran.r-project.org/src/contrib/ggplot2_2.2.1.tar.gz
-
-# Install the package:
-R CMD INSTALL ./ggplot2_2.2.1.tar.gz
-{{< /highlight >}}
-
-Additional information on using the `R CMD INSTALL` command can be
-found in the R documentation which can be seen by typing `?INSTALL`
-within the R console.

docs/submitting_jobs/creating_an_interactive_job.md

+---
+title: Creating an Interactive Job
+summary: "How to run an interactive job on HCC resources."
+weight: 20
+---
+
+!!! note
+    The `/home` directories are not intended for active job I/O.
+    
+    Output from run your processing should be directed to either `/work` or `/common`.
+
+
+Submitting an interactive job is done with the command `srun`.
+```bash
+$ srun --pty $SHELL
+```
+
+This command will allocate the **default resources of 1GB of RAM, 1 hour of running time, and a single CPU core**. Oftentimes, these resources are not enough. If the job is terminated, there is a high chance that the reason is exceeded resources, so please make sure you set the memory and time requirements appropriately.
+
+Submitting an interactive job to allocate 4 CPU cores per node for 3 hours with RAM memory of 1GB per core on the general `batch` partition:
+```bash
+$ srun --nodes=1 --ntasks-per-node=4 --mem-per-cpu=1024 --time=3:00:00 --pty $SHELL
+```
+
+Submitting an interactive job is useful if you require extra resources
+to run some processing by hand.  It is also very useful to debug your
+processing.  
+
+An interactive job is scheduled onto a worker node just like a regular
+job.  You can provide options to the interactive job just as you would a
+regular SLURM job. The default job runtime is 1 hour, and can be
+increased by including the `--time` argument.
+
+### Interactive job for Apptainer
+
+Running Apptainer via an interactive job requires at least 4GBs of RAM:
+```bash
+$ srun --mem=4gb --nodes=1 --ntasks-per-node=4 --pty $SHELL
+```
+If you get any memory-related errors, continue to increase the requested memory amount.
+
+### Priority for short jobs
+
+To run short jobs for testing and development work, a job can specify a
+different quality of service (QoS). The *short* QoS increases a jobs
+priority so it will run as soon as possible.
+
+| SLURM Specification |
+|---------------------|
+| `--qos=short`       |
+
+
+!!! warning "Limits per user for 'short' QoS"
+    - 6 hour job run time
+    - 2 jobs of 16 CPUs or fewer
+    - No more than 256 CPUs in use for *short* jobs from all users
+
+
+!!! note "Using the short QoS"
+    ```bash
+    srun --qos=short --nodes=1 --ntasks-per-node=1 --mem-per-cpu=1024 --pty $SHELL
+    ```
+

content/guides/submitting_jobs/hcc_acknowledgment_credit.md → docs/submitting_jobs/hcc_acknowledgment_credit.md

-+++
-title = "HCC Acknowledgment Credit"
-description =  "Details on the Acknowledgment Credit system."
-+++
+---
+title: HCC Acknowledgment Credit
+summary: "Details on the Acknowledgment Credit system."
+weight: 90
+---
+
+!!! note
+    To submit an acknowledgement and receive the credit, please use the form here: https://hcc.unl.edu/acknowledgement-submission.
+
+
+!!! note
+    The following text provides a detailed description of how the Acknowledgment Credit works.
+
+As a quickstart, add the line
+
+`#SBATCH --qos=ac_<group>`
+
+to your submit script, replacing `<group>` with your group name. Run the `hcc-ac` program to check the remaining balance.
 
-{{% notice note %}}
-To submit an acknowledgement and receive the credit, please use the form
-here: https://hcc.unl.edu/acknowledgement-submission.
-{{% /notice %}}
 
 ### What is HCC Acknowledgment Credit?
 
@@ -45,7 +55,7 @@ exhausted.
 
 **Why this ratio?**
 
-All nodes in the Crane batch partition can meet this CPU to memory
+All nodes in the Swan batch partition can meet this CPU to memory
 ratio.
 
 **Why have this ratio?**
@@ -72,47 +82,46 @@ Column description of the hcc-ac utility
 | per-CPU AvgMEM | The per-CPU average memory size available for the CPU time remaining in the qos.  If CPU time is consumed faster than memory time, this value will increase.  If memory time is consumed faster than CPU time, this value will decrease. |
 
 
-##### Example of how to use the awarded time for the 'demo' group.
-
+### Example of how to use the awarded time for the 'demo' group.
 The awarded time is reduced down to 10 minutes to show consumption
 changes with differing job resource requirements:
 
 All times are in days-hours:minutes:seconds as used in Slurm's '--time='
 argument.
 
-{{% panel theme="info" header="Default output" %}}
-{{< highlight batch >}}
+!!! note "Default output"
+    ```bat
     [demo01@login.hcc_cluster ~]$ hcc-ac
     +-----------+--------------+--------------+----------------+
     | Slurm qos | CPUx1 time   | MEMx4GB time | per-CPU AvgMEM |
     +-----------+--------------+--------------+----------------+
     | ac_demo   | 0-00:10:00   | 0-00:10:00   | 4.0GB          |
     +-----------+--------------+--------------+----------------+
-{{< /highlight >}}
-{{% /panel %}}
+    ```
+
 
 Use the Slurm quality of service argument '--qos' to gain access to the
 awarded time with increased priority:
 
-{{% panel theme="info" header="**--qos=ac_demo**" %}}
-{{< highlight batch >}}
+!!! note "**--qos=ac_demo**"
+    ```bat
     [demo01@login.hcc_cluster ~]$ srun --qos=ac_demo --ntasks=1 --mem=8g --time=1:00 /bin/sleep 60
-{{< /highlight >}}
-{{% /panel %}}
+    ```
+
 
 \*\***job runs for 60 seconds**\*\*
 
 
-{{% panel theme="info" header="**After 60 second job**" %}}
-{{< highlight batch >}}
+!!! note "**After 60 second job**"
+    ```bat
     [demo01@login.hcc_cluster ~]$ hcc-ac
     +-----------+--------------+--------------+----------------+
     | Slurm qos | CPUx1 time   | MEMx4GB time | per-CPU AvgMEM |
     +-----------+--------------+--------------+----------------+
     | ac_demo   | 0-00:09:00   | 0-00:08:00   | 3.556GB        |
     +-----------+--------------+--------------+----------------+
-{{< /highlight >}}
-{{% /panel %}}
+    ```
+
 
 1 CPU minute and 2 4GB memory minutes were consumed by the prior srun
 job.
@@ -135,24 +144,24 @@ against 4GB:
 
 ie, 9 \* 3.556 \~= 8 \* 4
 
-{{% panel theme="info" header="**--ntasks=4**" %}}
-{{< highlight batch >}}
+!!! note "**--ntasks=4**"
+    ```bat
     [demo01@login.hcc_cluster ~]$ srun --qos=ac_demo --ntasks=4 --mem-per-cpu=2G --time=1:00 /bin/sleep 60
-{{< /highlight >}}
-{{% /panel %}}
+    ```
+
 
 \*\***job runs for 60 seconds**\*\*
 
-{{% panel theme="info" header="**After 60 second job**" %}}
-{{< highlight batch >}}
+!!! note "**After 60 second job**"
+    ```bat
     [demo01@login.hcc_cluster ~]$ hcc-ac
     +-----------+--------------+--------------+----------------+
     | Slurm qos | CPUx1 time   | MEMx4GB time | per-CPU AvgMEM |
     +-----------+--------------+--------------+----------------+
     | ac_demo   | 0-00:05:00   | 0-00:06:00   | 4.8GB          |
     +-----------+--------------+--------------+----------------+
-{{< /highlight >}}
-{{% /panel %}}
+    ```
+
 
 4 CPU minutes and 2 4GB minutes were consumed by the prior srun job.
 
@@ -163,34 +172,34 @@ ie, 9 \* 3.556 \~= 8 \* 4
 
 6 / 5 \* 4 == 4.8
 
-{{% panel theme="info" header="**Insufficient Time**" %}}
-{{< highlight batch >}}
+!!! note "**Insufficient Time**"
+    ```bat
     [demo01@login.hcc_cluster ~]$ srun --qos=ac_demo --ntasks=5 --mem-per-cpu=5000M --time=1:00 /bin/sleep 60
     srun: error: Unable to allocate resources: Job violates accounting/QOS policy (job submit limit, user's size and/or time limits)
-{{< /highlight >}}
-{{% /panel %}}
+    ```
+
 
 An example of a job requesting more resources than what remains
 available in the qos.
 
-{{% panel theme="info" header="**Corrected Memory Requirement**" %}}
-{{< highlight batch >}}
+!!! note "**Corrected Memory Requirement**"
+    ```bat
     [demo01@login.hcc_cluster ~]$ srun --qos=ac_demo --ntasks=5 --mem-per-cpu=4800M --time=1:00 /bin/sleep 60
-{{< /highlight >}}
-{{% /panel %}}
+    ```
+
 
 \*\***job runs for 60 seconds**\*\*
 
-{{% panel theme="info" header="**Exhausted QoS**" %}}
-{{< highlight batch >}}
+!!! note "**Exhausted QoS**"
+    ```bat
     [demo01@login.hcc_cluster ~]$ hcc-ac
     +-----------+--------------+--------------+----------------+
     | Slurm qos | CPUx1 time   | MEMx4GB time | per-CPU AvgMEM |
     +-----------+--------------+--------------+----------------+
     | ac_demo   | exhausted    | exhausted    | 0.0GB          |
     +-----------+--------------+--------------+----------------+
-{{< /highlight >}}
-{{% /panel %}}
+    ```
+
 
 All remaining time was used.  Any further submissions to the qos will be
 **denied at submission time**.
@@ -199,10 +208,10 @@ All of the above **srun** arguments work the same with **sbatch** within
 the submit file header.
 
 
-{{% panel theme="info" header="**Submit File Example**" %}}
-{{< highlight batch >}}
+!!! note "**Submit File Example**"
+    ```bat
     [demo01@login.hcc_cluster ~]$ cat submit_test.slurm
-#!/bin/batch
+    #!/bin/bash
     #SBATCH --ntasks=4
     #SBATCH --qos=ac_demo
     #SBATCH --ntasks=5
@@ -211,8 +220,8 @@ the submit file header.
     
     /bin/sleep 60
     [demo01@login.hcc_cluster ~]$ sbatch ./submit_test.slurm
-{{< /highlight >}}
-{{% /panel %}}
+    ```
+
 
 CPU and memory time in the qos are only consumed when jobs run against
 the qos.  Therefore it is possible for more jobs to be submitted
@@ -234,8 +243,8 @@ argument to size the job against what time remains in the qos.
 For example, with the same 10 minute limit:
 
 
-{{% panel theme="info" header="**--test-only job to see if it fits within qos time limits**" %}}
-{{< highlight batch >}}
+!!! note "**--test-only job to see if it fits within qos time limits**"
+    ```bat
     
     [demo01@login.hcc_cluster ~]$ hcc-ac
     +-----------+--------------+--------------+----------------+
@@ -266,5 +275,5 @@ allocation failure: Job violates accounting/QOS policy (job submit limit, user's
     
     [demo01@login.hcc_cluster ~]$ srun --test-only --qos=ac_demo --ntasks=1 --time=3:00 --mem-per-cpu=12G
     srun: Job <number> to start at YYYY-MM-DDTHH:MM:SS using 1 processors on compute_node
-{{< /highlight >}}
-{{% /panel %}}
+    ```
+