Software Productivity and Sustainability

a track presented at

Argonne Training Program on Extreme-Scale Computing

on 8:30 am - 6:30 pm CDT Friday 2 August 2024

Presenters: Anshu Dubey (Argonne National Laboratory), David E. Bernholdt (Oak Ridge National Laboratory), Todd Gamblin (Lawrence Livermore National Laboratory), and Jared O'Neal (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 BSSw tutorial focuses on issues of developer productivity, software sustainability, and reproducibility in scientific research software, particularly targeting high-performance computers.

Agenda

Time (CDT)	Title	Presenter
8:30 AM	Introduction	David E. Bernholdt (ORNL)
8:35 AM	Motivation and Overview of Best Practices in HPC Software Development	David E. Bernholdt (ORNL)
9:15 AM	Scientific Software Design	Anshu Dubey (ANL)
10:00 AM	Break
10:30 AM	Spack: Package Management for HPC	Todd Gamblin (LLNL)
11:30 AM	Spack Hands-On	Todd Gamblin (LLNL)
12:30 PM	Lunch
1:30 PM	Software Testing and Verification	Anshu Dubey (ANL)
2:30 PM	Refactoring Scientific Software	Anshu Dubey (ANL)
3:00 PM	Break
3:30 PM	Software Licensing	David E. Bernholdt (ORNL)
4:30 PM	Improving Reproducibility Through Better Software Practices	David E. Bernholdt (ORNL)
5:30 PM	Lab Notebooks for Computational Mathematics, Sciences, & Engineering	Jared O'Neal (ANL)
6:30 PM	Adjourn

Presentation Slides

The latest version of the slides will always be available at https://doi.org/10.6084/m9.figshare.26384188.

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).
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Resources from Presentations

Links from the tutorial presentations are listed here for convenience

Module 1: Introduction
- Consortium for the Advancement of Scientific Software (CASS)
- IDEAS Productivity
- Spack
- 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
- https://enterprisersproject.com/article/2020/6/technical-debt-explained-plain-english
- Resources for independent exploration
  - https://github.com/abiswas-odu/heateq-design-intersect-2023
  - https://xsdk-project.github.io/MathPackagesTraining2020/lessons/hand_coded_heat/
- https://github.com/Flash-X/Flash-X/blob/ylee/try_pushTile_spark/source/physics/Hydro/HydroMain/Spark/Hydro_interface.ini
  - This link will work only if you have access to the Flash-X code repository. Please email flash-x@lists.cels.anl.gov with your github username to get access
Module 4: Spack: Package Management for HPC
- Spack Website
- Spack Slack
- Spack Tutorial
- Spack Documentation
- Spack on GitHub
- Spack Release Notes
- Spack Twitter
- Extreme Scale Scientific Software Stack (E4S)
- Find available packages at https://packages.spack.io
- See available builds at https://cache.spack.io
- Other package management tools (HPC and otherwise)
  - Easybuild
  - Functional Package Managers
    - Nix
    - Guix
  - Other build-from-source systems
    - Homebrew, LinuxBrew
    - Macports
    - Gentoo
  - Conda ecosystem
    - Conda
    - Conda-forge
    - Mamba
    - Pixi
Module 5: Software Testing and Verification
Module 6: Refactoring Scientific Software
- Refactoring example code repository: https://github.com/bssw-tutorial/hello-numerical-world
Module 7: Software Licensing
- See Additional Resources in lesson
Module 8: Improving Reproducibility Through Better Software Practices
- Toward a Compatible Reproducibility Taxonomy for Computational and Computing Sciences
- Reproducibility and Replicability in Science
- Many Psychology Findings Not As Strong As Claimed
- The War Over Supercooled Water
- Researchers find bug in Python Script may have affected hundreds of studies
- National Science Foundation Data Management Plan Requirements
- Findable, Accessible, Interoperable, Re-usable
- FAIR Data Principles US
- SC Conference Reproducibility Initiative
  - HOWTO for AEC Submitters
  - Artifact Evaluation: Tips for Authors
  - SIGOPS articles on award winning artifacts
    - https://www.sigops.org/2021/how-are-award-winning-systems-research-artifacts-prepared-part-1/
    - https://www.sigops.org/2021/how-are-award-winning-systems-research-artifacts-prepared-part-2/
  - Github CSArtifacts Resources
- ACM Reproducible Computational Results
- ACM Artifact Review and Badging
- http://fursin.net/reproducibility.html
- National Information Standards Organization (NISO) on Reproducibility and Badging
- Helpful Tools
  - Floating Point Analysis Tools
  - Code Ocean (Cloud platforms - publish and reproduce research code and data)
  - DOIs and hosting of data, code, documents:
    - Zenodo
    - FigShare
- Other Resources:
  - The FAIR Guiding Principles for Scientific Data Management and Stewardship. Mark D. Wilkinson, et al. 2016
  - FAIR4RS (previously linked to ~~www.rd-alliance.org/groups/fair-research-software-fair4rs-wg~~)
  - Editorial: ACM TOMS Replicated Computational Results Initiative. Michael A. Heroux. 2015
  - Enhancing Reproducibility for Computational Methods
  - Simple experiments in reproducibility and technical trust by Mike Heroux and students (work in progress)
  - What every scientist should know about floating-point arithmetic. David Goldberg.
Module 9: Lab Notebooks for Computational Mathematics, Sciences, & Engineering
- European Southern Observatory
- HPC and the Lab Manager
- What All Codes Should Do (ATPESC 2019)
- Writing the Laboratory Notebook
- DIKW pyramid
- How to pick an electronic notebook
- BSSw article by Nicole Brewer
- Resources – Execution Environments
- BSSw article by Jean Shuler
- Popper by Ivo Jimenez
- Code Ocean
- Weight & Biases
- Multiphase Simulations
- FlashKit
- Computational Lab Environment Example

Requested Citation

The requested citation the overall tutorial is:

Anshu Dubey, David E. Bernholdt, Todd Gamblin, and Jared O’Neal, Software Productivity and Sustainability track, in Argonne Training Program on Extreme-Scale Computing, St. Charles, Illinois, 2024. DOI: 10.6084/m9.figshare.26384188.

Individual modules may be cited as Speaker, Module Title, in Software Productivity and Sustainability track…

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.