Better Scientific Software

a tutorial presented at

ISC High Performance

on 2:00 pm - 6:00 pm CEST Sunday 12 May 2024

Presenter: Anshu Dubey (Argonne National Laboratory)

This page provides detailed information specific to the tutorial event above. Expect updates to this page up to, and perhaps shortly after, the date of the tutorial. Pages for other tutorial events can be accessed from the main page of this site.

Quick Links

Presentation Slides (FigShare)

Description

The computational science and engineering (CSE) community is in the midst of an extremely challenging period created by the confluence of disruptive changes in computing architectures, demand for greater scientific reproducibility, and new opportunities for greatly improved simulation capabilities, especially through coupling physics and scales. Computer architecture changes require new software design and implementation strategies, including significant refactoring of existing code. Reproducibility demands require more rigor across the entire software endeavor and for running computational experiments. These challenges demand large investments in scientific software development and improved practices. Focusing on improved developer productivity and software sustainability is both urgent and essential.

This tutorial will provide information and illustrative use cases of software practices, processes, and tools explicitly tailored for CSE. Goals are improving the productivity of those who develop CSE software and increasing the quality and sustainability of software artifacts. We discuss practices that are relevant for projects of all sizes, with emphasis on complex workflows and reproducible science. Topics include software design, refactoring, software testing (including automated testing, legacy code testing, and continuous integration), and methodologies for running reproducible computational experiments.

Target Audience: This tutorial is designed to benefit any scientific software development project, irrespective of its size and scope. The tutorial can benefit people at any stage of their career, whether they are students, post-docs, or established practitioners with a skew towards intermediate levels. Intermediate level: 75%, advanced level: 25%, prerequisites: none.

Agenda

Time (CEST)	Title	Presenter
2:00 PM	Introduction	Anshu Dubey (ANL)
2:05 PM	Motivation and Overview of Best Practices in HPC Software Development	Anshu Dubey (ANL)
2:20 PM	Scientific Software Design	Anshu Dubey (ANL)
2:50 PM	Software Testing and Verification	Anshu Dubey (ANL)
3:30 PM	Refactoring Scientific Software	Anshu Dubey (ANL)
4:00 PM	Break
4:30 PM	Lab Notebooks for Computational Mathematics, Sciences, & Engineering	Anshu Dubey (ANL)
5:15 PM	Documentation	Anshu Dubey (ANL)
6:00 PM	Adjourn

Presentation Slides

The latest version of the slides will always be available at https://doi.org/10.6084/m9.figshare.25686426.

Note that these files may include additional slides that will not be discussed during the tutorial, but questions are welcome.

How to Participate

We want to interact with you! We find these tutorials most interesting and informative (for everyone) if you ask questions and share experiences! We learn too!
Please raise your hand at any time to ask a question

Stay in Touch

After the tutorial please feel free to email questions or feedback to the BSSw tutorial team at bssw-tutorial@lists.mcs.anl.gov.
To find out about future events organized by the IDEAS Productivity Project, you can subscribe to our mailing list (usually ~2 messages/month).
For monthly updates on the Better Scientific Software site, subscribe to our monthly digest.

If you’re interested in this tutorial, you might be interested in this list of other software-related events taking place in the ISC24 conference.

Resources from Presentations

Links from the tutorial presentations are listed here for convenience

Module 1: Introduction
- Better Scientific Software site
- BSSw Digest
- BSSw RSS Feed
- Inclusive Naming Initiative
- Bssw.io resource on Inclusive Naming
- Email the tutorial authors
Module 2: Motivation and Overview of Best Practices in HPC Software Development
Module 3: Scientific Software Design
- Technical Debt in Plain English
- Resources for independent exploration
  - Code repository in python: https://github.com/abiswas-odu/heateq-design-intersect-2023
- Complete example in C++: https://xsdk-project.github.io/MathPackagesTraining2020/lessons/hand_coded_heat/
Module 4: Software Testing and Verification
Module 5: Refactoring Scientific Software
- Refactoring example code repository: https://github.com/bssw-tutorial/hello-numerical-world
Module 6: Lab Notebooks for Computational Mathematics, Sciences, & Engineering
- Writing the Laboratory Notebook
- HPC and the Lab Manager
- What All Codes Should Do (ATPESC 2019)
- DIKW pyramid
- How to pick an electronic notebook
- Resources – Execution Environments
  - ATPESC 2022 Laboratory Environment BSSw Tutorial
    - Example Repo
  - Lab Notebooks for Computational Mathematics, Sciences & Engineering (previously linked to ~~ideas-productivity.org/events/hpc-best-practices-webinars/#webinar070~~)
  - Popper
  - FlashKit
  - Code Ocean
  - Weight & Biases
Module 7: Documentation
- API documentation tools
  - Doxygen
  - NDoc
  - Visual Expert
  - Javadoc
  - EiffelStudio
  - Sandcastle
  - ROBODoc
  - POD
  - TwinText
- Flash-X documentation examples
- Diataxis Framework
- Fortran tools
- Markup languages
  - Markdown
  - ReStructured Text
- Formatting/generation tools
  - Sphinx
  - Jekyll
- Publishing/hosting sites
  - ReadtheDocs
  - GitHub Pages
- MeerCat contact Stephen Fickas

Requested Citation

The requested citation the overall tutorial is:

Anshu Dubey, Better Scientific Software tutorial, in ISC High Performance, Hamburg, Germany, 2024. DOI: 10.6084/m9.figshare.25686426.

Individual modules may be cited as Speaker, Module Title, in Better Scientific Software tutorial…

Acknowledgements

This tutorial is produced by the IDEAS Productivity project.

This work was supported by the U.S. Department of Energy Office of Science, Office of Advanced Scientific Computing Research (ASCR), and by the Exascale Computing Project (17-SC-20-SC), a collaborative effort of the U.S. Department of Energy Office of Science and the National Nuclear Security Administration.

This work was supported by the U.S. Department of Energy, Office of Science, Office of Advanced Scientific Computing Research, Next-Generation Scientific Software Technologies (NGSST) program.