ResearchComputing · SchneiderCode · Apr 30, 2026 · Apr 30, 2026 · May 4, 2026
diff --git a/docs/additional-resources/contrib_curc_docs.md b/docs/additional-resources/contrib_curc_docs.md
@@ -140,6 +140,9 @@ To ensure that our documentation is uniform and is easily digestible for users,
     ```
     ::::
 - [ ] Define any acronyms when they are first introduced.
+- [ ] Ensure the following common terms utilize the approved spelling and style: 
+    - High-Performance Computing : First letter is capitalized in each word and includes a hyphen
+    - HPC : Acronym for High-Performance Computing. Each letter must be capitalized.
 - [ ] If there is a related topic in our documentation, link to it.
 - [ ] Avoid links such as `[here]()` instead of using `here`, provide a title. 
 - [ ] For each new topic, provide at least a small introduction to the topic. The focus is on informing the user in a complete and clear way, not just stating information. 

diff --git a/docs/ai-ml/llms.md b/docs/ai-ml/llms.md
@@ -273,7 +273,7 @@ python llama_query.py
 At the time of running this model, we obtain the following output:
 ```text
 CU Research Computing is an exceptionally cool and powerful resource that provides researchers 
-with access to high-performance computing clusters, advanced data storage systems, and expert 
+with access to High-Performance Computing clusters, advanced data storage systems, and expert 
 support to facilitate cutting-edge research and innovation.
 ```
 This of course is just a simple example showing how one can query Ollama models from within a Python script. This functionality opens the door for more complex queries and scripts. This example also touches on just one aspect of the Python API. For more tutorials and documentation of the API, see the `examples` directory and `README.md` file in the official [ollama-python](https://github.com/ollama/ollama-python) GitHub repository. 

diff --git a/docs/clusters/alpine/index.md b/docs/clusters/alpine/index.md
@@ -1,11 +1,11 @@
 # Alpine
 
-On May 18, 2022, CU Research Computing released phase 1 of Alpine, the third generation CURC High Performance 
+On May 18, 2022, CU Research Computing released phase 1 of Alpine, the third generation CURC High-Performance 
 Computing Cluster. Phase 2 was released in September 2022. Phase 3 was released in July 2023. 
 
 ## Overview
 
-Alpine is the University of Colorado Boulder Research Computing’s third-generation high performance computing (HPC) cluster. 
+Alpine is the University of Colorado Boulder Research Computing’s third-generation High-Performance Computing (HPC) cluster. 
 Alpine is a heterogeneous compute cluster currently composed of hardware provided from University of Colorado Boulder, Colorado 
 State University, and Anschutz Medical Campus. Alpine currently offers {{ alpine_total_compute_nodes }} compute nodes and a total of {{ alpine_total_cores }} cores. Alpine can 
 be securely accessed anywhere, anytime using Open OnDemand or ssh connectivity to the CURC system. All nodes are available to all 

diff --git a/docs/clusters/alpine/quick-start.md b/docs/clusters/alpine/quick-start.md
@@ -1,6 +1,6 @@
 # Alpine Quick Start
 
-Alpine is the University of Colorado Boulder Research Computing's third-generation high performance computing (HPC) 
+Alpine is the University of Colorado Boulder Research Computing's third-generation High-Performance Computing (HPC) 
 cluster. Alpine is a heterogeneous compute cluster currently composed of hardware provided from University of Colorado 
 Boulder, Colorado State University, and Anschutz Medical Campus. Alpine currently offers {{ alpine_total_compute_nodes }} compute nodes and a total 
 of {{ alpine_total_cores }} cores. Alpine can be securely accessed anywhere, anytime using Open OnDemand or ssh connectivity to the CURC system.

diff --git a/docs/clusters/summit/summit.md b/docs/clusters/summit/summit.md
@@ -1,6 +1,6 @@
 # Summit
 
-**CU Research Computing's Summit cluster was officially retired on March 1, 2023 in favor of Alpine, the third generation CURC High Performance Computing Cluster.** Users looking to transition to Alpine can reference the [Alpine Quick-Start Guide](https://curc.readthedocs.io/en/latest/clusters/alpine/quick-start.html) for additional information.
+**CU Research Computing's Summit cluster was officially retired on March 1, 2023 in favor of Alpine, the third generation CURC High-Performance Computing Cluster.** Users looking to transition to Alpine can reference the [Alpine Quick-Start Guide](https://curc.readthedocs.io/en/latest/clusters/alpine/quick-start.html) for additional information.
 
 Summit was the second-generation HPC cluster at University of Colorado Research Computing, following Janus. Summit was an NSF-Funded cluster shared between the University of Colorado, Colorado State University, and institutions in the Rocky Mountain Advanced Computing Consortuium (RMACC).
 

diff --git a/docs/compute/monitoring-resources.md b/docs/compute/monitoring-resources.md
@@ -466,7 +466,7 @@ Refer to ["Why am I getting unexpected results for my GPU memory or utilization
 
 XDMoD is a web portal for viewing metrics at the system-, partition- and user-levels.
 
-Would you like to know average queue wait times?  Do you need to better understand your historical resource utilization or utilization of your project account by user? The XDMoD ([XD Metrics on Demand](https://open.xdmod.org/9.0/index.html)) web-based tool provides users with the ability to easily obtain detailed metrics for high performance computing resources. This open-source tool was developed by the University at Buffalo [Center for Computational Research (CCR)](http://www.buffalo.edu/ccr.html). CU Boulder Research Computing runs its own instance, [CURC XDMoD](https://xdmod.rc.colorado.edu) that enables users to query metrics for the _RMACC_, _Alpine_ and _Blanca_ computing resources. 
+Would you like to know average queue wait times?  Do you need to better understand your historical resource utilization or utilization of your project account by user? The XDMoD ([XD Metrics on Demand](https://open.xdmod.org/9.0/index.html)) web-based tool provides users with the ability to easily obtain detailed metrics for High-Performance Computing resources. This open-source tool was developed by the University at Buffalo [Center for Computational Research (CCR)](http://www.buffalo.edu/ccr.html). CU Boulder Research Computing runs its own instance, [CURC XDMoD](https://xdmod.rc.colorado.edu) that enables users to query metrics for the _RMACC_, _Alpine_ and _Blanca_ computing resources. 
 
 __Getting started with XDMoD__
 

diff --git a/docs/getting_started/acknowledge_curc_resources.md b/docs/getting_started/acknowledge_curc_resources.md
@@ -4,7 +4,7 @@ Use of University of Colorado Research Computing resources, including (but not l
 
 ## Acknowledging Alpine
 
-“This work utilized the Alpine high performance computing resource at the University of Colorado Boulder. Alpine is jointly funded by the University of Colorado Boulder, the University of Colorado Anschutz, Colorado State University, and the National Science Foundation (award 2201538).”
+“This work utilized the Alpine High-Performance Computing resource at the University of Colorado Boulder. Alpine is jointly funded by the University of Colorado Boulder, the University of Colorado Anschutz, Colorado State University, and the National Science Foundation (award 2201538).”
 
 - DOI: https://doi.org/10.25811/k3w6-pk81 
 - Citation: University of Colorado Boulder Research Computing. (2023). Alpine. University of Colorado Boulder. https://doi.org/10.25811/k3w6-pk81

diff --git a/docs/getting_started/faq.md b/docs/getting_started/faq.md
@@ -142,7 +142,7 @@ re-enroll by visiting <https://duo.colorado.edu>. If that did not resolve your i
 303-735-4357.
 ::::
 
-## General High Performance Computing
+## General High-Performance Computing
 
 ### What is Arbiter2? 
 ::::{dropdown} Show 

diff --git a/docs/getting_started/navigating_docs.md b/docs/getting_started/navigating_docs.md
@@ -1,8 +1,8 @@
 # Navigating CURC Documentation
 
-CU Research Computing (CURC) offers a variety of services encompassing High Performance Computing (HPC), cloud computing assistance, and storage solutions. Many of these services are available to users associated with CU Boulder, Anschutz Medical Campus (AMC), Colorado State University (CSU), and institutions that are members of the Rocky Mountain Advanced Computing Consortium (RMACC). Our team understands that navigating the various services we provide can be overwhelming for both new and experienced users. To aid users, we have constructed flowcharts that outline the core areas of our documentation that every user on our system should become familiar with. Please refer to the section [High Performance Computing Flowchart](#high-performance-computing-flowchart) for a diagram of how to navigate our HPC systems (clusters) and storage solutions. For a diagram of the various cloud computing resources we can assist you with, please refer to the [Cloud Computing Flowchart](#cloud-computing-flowchart) section. 
+CU Research Computing (CURC) offers a variety of services encompassing High-Performance Computing (HPC), cloud computing assistance, and storage solutions. Many of these services are available to users associated with CU Boulder, Anschutz Medical Campus (AMC), Colorado State University (CSU), and institutions that are members of the Rocky Mountain Advanced Computing Consortium (RMACC). Our team understands that navigating the various services we provide can be overwhelming for both new and experienced users. To aid users, we have constructed flowcharts that outline the core areas of our documentation that every user on our system should become familiar with. Please refer to the section [High-Performance Computing Flowchart](#high-performance-computing-flowchart) for a diagram of how to navigate our HPC systems (clusters) and storage solutions. For a diagram of the various cloud computing resources we can assist you with, please refer to the [Cloud Computing Flowchart](#cloud-computing-flowchart) section. 
 
-## High Performance Computing Flowchart
+## High-Performance Computing Flowchart
 
 At CURC, we host two HPC clusters, Alpine and Blanca, along with various storage solutions. Before you utilize these resources, there are several items that you should take into consideration. To guide users, we've included a flowchart below that highlights the key areas users should focus on.
 

diff --git a/docs/getting_started/trainings_and_consults/index.md b/docs/getting_started/trainings_and_consults/index.md
@@ -13,7 +13,7 @@ online-trainings
 
 ## Weekly Office Hours
 
-Join the CURC Weekly Office Hours during the academic year and get one-on-one support with a member of the User Support Team. Whether you're trying to optimize your workflows on Alpine and Blanca or just getting started with your first high-performance computing project, we’re here to help you bridge the gap between "it’s broken" and "it’s running."
+Join the CURC Weekly Office Hours during the academic year and get one-on-one support with a member of the User Support Team. Whether you're trying to optimize your workflows on Alpine and Blanca or just getting started with your first High-Performance Computing project, we’re here to help you bridge the gap between "it’s broken" and "it’s running."
 
 Don't let technical bottlenecks stall your progress. Come with your questions, leave with a plan, and get your research back on track.
 

diff --git a/docs/getting_started/trainings_and_consults/online-trainings.md b/docs/getting_started/trainings_and_consults/online-trainings.md
@@ -8,7 +8,7 @@
 :img-top: ./training_images/RC_Quiz.png
 :img-alt: A student is taking an online quiz to test their knowledge of HPC systems
 
-This course covers the ins and outs of CU Research Computing's (CURC) High Performance Computing (HPC) systems. 
+This course covers the ins and outs of CU Research Computing's (CURC) High-Performance Computing (HPC) systems. 
 
 Topics include: 
   * Alpine & Blanca Clusters 

diff --git a/docs/index.md b/docs/index.md
@@ -1,6 +1,6 @@
 # CU Research Computing User Guide
 
-Welcome to CU Research Computing's (CURC's) user guide! CURC offers a variety of services encompassing High Performance Computing (HPC), cloud computing assistance, and storage solutions. Many of these services are available to users associated with CU Boulder, Anschutz Medical Campus (AMC), Colorado State University (CSU), and institutions that are members of the Rocky Mountain Advanced Computing Consortium (RMACC). 
+Welcome to CU Research Computing's (CURC's) user guide! CURC offers a variety of services encompassing High-Performance Computing (HPC), cloud computing assistance, and storage solutions. Many of these services are available to users associated with CU Boulder, Anschutz Medical Campus (AMC), Colorado State University (CSU), and institutions that are members of the Rocky Mountain Advanced Computing Consortium (RMACC). 
 
 ```{tip}
 - Documentation can be overwhelming. If you would like guidance on navigating CURC documentation, please see our [Navigating CURC Documentation](./getting_started/navigating_docs.md) page.

diff --git a/docs/open_ondemand/index.md b/docs/open_ondemand/index.md
@@ -1,6 +1,6 @@
 # Open OnDemand _(Browser Based HPC Portal)_
 
-Open OnDemand is a browser based, integrated, single access point for all of your high performance computing (HPC) resources at CU Research Computing. Open OnDemand provides a graphical interface to manage files; create and view job Slurm jobs on CURC's clusters; and access interactive applications (such as Jupyter and RStudio). All of these actions are completed via a web browser and require only minimal knowledge of Linux and scheduler commands.
+Open OnDemand is a browser based, integrated, single access point for all of your High-Performance Computing (HPC) resources at CU Research Computing. Open OnDemand provides a graphical interface to manage files; create and view job Slurm jobs on CURC's clusters; and access interactive applications (such as Jupyter and RStudio). All of these actions are completed via a web browser and require only minimal knowledge of Linux and scheduler commands.
 
 ## Getting started with Open OnDemand
 

diff --git a/docs/software/containerization.md b/docs/software/containerization.md
@@ -15,7 +15,7 @@ Containers distinguish themselves through their low computational overhead and t
 
 ## Container engines
 
-[Docker](https://www.docker.com/) is the most widely used container engine, and  can be used on any system where you have administrative privileges. _Docker cannot be run directly on high-performance computing (HPC) platforms like Alpine because users do not have administrative privileges._ CURC documentation on Docker can be found below. 
+[Docker](https://www.docker.com/) is the most widely used container engine, and  can be used on any system where you have administrative privileges. _Docker cannot be run directly on High-Performance Computing (HPC) platforms like Alpine because users do not have administrative privileges._ CURC documentation on Docker can be found below. 
 
 [Apptainer](https://apptainer.org/) (formerly Singularity) is a container engine that does not require administrative privileges to execute. Therefore, it is safe to run on HPC platforms like Alpine or Blanca.