Wrap-up

Overview

Teaching: 15 min
Exercises: 0 min

Questions

• Looking back at what was covered and how different pieces fit together

• Where are some advanced topics and further reading available?

Objectives

• Put the course in context with future learning.

With this, we conclude our workshop. We have only scratched the surface of how HPC can be applied to astronomical software development, as HPC is an entire discipline in its own right, spanning algorithm design, optimization, engineering, and software architecture. But the tools you’ve worked with over the past two days are enough to get started. From here, it is a good idea to read the documentation for the HPC facility you plan to use, experiment with running your own code, and analyze which parts of your workflow can be parallelized and which may become bottlenecks.

Do not hesitate to reach out to us for help with the exercises or with any questions regarding the materials, and keep an eye on the advertisements in the LSST Slack, as we plan to organize a more in-depth workshop on HPC software development in the next few months.

Further Resources

Below are some additional resources to help you continue learning:

• A comprehensive HPC manual
• Carpentries HPC workshop Using Python in an HPC environment course
• Foundations of Astronomical Data Science Carpentries Workshop
• A previous InterPython workshop materials, covering collaborative usage of GitHub, Programming Paradigms, Software Architecture and many more
• CodeRefinery courses on FAIR (Findable, Accessible, Interoperable, and Reusable) software practices
• Python documentation
• GitHub Actions documentation

Key Points

• This course teaches the basics of HPC, however, the topic itself is vast and may take a long time to master.