When most people think about applications of high-performance computing (HPC), STEM-based research readily comes to mind. While HPC absolutely excels at that, it is also useful in pedagogical contexts, including:

• Facilitating analysis of datasets that are too large to work with easily on personal devices, or that cannot easily be shared or disseminated. As real-world data analysis relies on increasingly large amounts of data, enabling students to interact with such data can provide important skills-based learning opportunities.
• Providing collaborative spaces for teams or entire courses. The multi-user environment of HPC systems can make it easier to facilitate collaborative work among teams of learners.
• Similarly, enabling analytical techniques that require too much time on personal devices. Students can access HPC resources from anywhere and are no longer limited to computer labs, and many tasks can be submitted to run unattended, opening up, e.g., large parameter sweeps, parallel workflows, or time-consuming operations that might be otherwise challenging or impossible.
• Providing a stepping stone towards using national supercomputing resources. Our HPC environment is extremely similar to those found on most large-scale systems, such as those available through ACCESS. Experience with similar workflows can be a benefit for those seeking graduate education, internships, and technical jobs.

In sum, the goal of our HPC system is to enable the asking and exploration of questions that are otherwise impossible, whether due to scale, resource, or temporal limitations. To be able to offer that as part of deep teaching and learning is exciting and valuable, and is unfortunately rare at smaller institutions. Please explore our HPC ecosystem, and feel free to request an account, or reach out to jsimms1@swarthmore.edu to discuss ways in which you can use these resources in your teaching and learning.