Difference between revisions of "2019 Workshop:Software Engineering for Heliophysics"

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===Location, Date/Time and Duration===
Monday, 13:30-15:30, Zia/Eldorado
Monday, 13:30-15:30, Zia/Eldorado

Revision as of 08:06, 6 June 2019

Software Engineering for Heliophysics


Monday, 13:30-15:30, Zia/Eldorado


Michael Hirsch
Matthew Zettergren
Guy Grubbs


This session targets those doing this work every day (students and early-mid career) as well as more senior scientists interested in the best trends and techniques from industry as applied to heliophysics. The intended audience is as broad as possible: students to senior career--we will discuss intermediate to advanced geospace software engineering at a level accessible and useful to all.

Scope includes coding languages commonly used in heliophysics, including: C++, Fortran, Matlab, Python

Use cases we address include:

  • scripting languages to analyze large data sets quickly
  • model developers reduce the time spent tutoring new users in building / modifying / using the model
  • reduce debugging effort by adding automated self-tests
  • ensure code will be usable on most current computing platforms and easily adaptable to future systems

We intend that most participants will be able to apply industry best-practices to their own work tonight, if not in the workshop itself.

Tutorial topic areas

Please let the organizers know if you have any additions or interest in these areas. We intend to give a tutorial in each of these areas, but probably can't cover each little bullet point. We will distribute a simple Google user survey in May to gauge topics of highest community interest.

  • Modern / efficient coding practices (for any language)
    • What should be object-oriented vs. functionalized
    • use of linters / type checkers (Python: flake8, mypy; C++: clang-tidy)
    • deciding what language(s) are best for a project and the development team
  • Language transitions / interfaces
    • proprietary software ↔ open world (e.g. IDL → GDL → Python)
    • using open software in a closed / proprietary environment
    • Python for Matlab / IDL users
  • Distributing code more easily via:
    • code sharing sites (GitHub)
    • Build systems (Meson)
    • Package managers (Julia, Python)
    • proprietary (IDL) or less common languages
  • Version control (Git):
    • sharing and developing code effectively across diverse teams
    • sharing versioned big data files as part of a program/library
  • Build systems (CMake, Meson, Pip)
    • make it easy for users to get prereqs and build your code on any computer
    • Deploying a complex application anywhere, from Raspberry Pi to Windows/Mac laptop to CentOS HPC
  • Continuous test / integration (Travis-CI)
    • automatically run tests "in the cloud" on Linux, Mac, Windows for each code change
    • examples with Meson and CMake + compiled languages (C++, Fortran)
    • Seamless integration and testing of scripted languages (Matlab, Python) with compiled (C++, Fortran)
    • how to create tests in your preferred language
  • Asynchronous architectures: parallel and concurrent processing
    • Examples in Python and Fortran:


Please let the organizers know if you have something to present.

Preliminary timeline:

  • Intro: How to do X with Y--discuss geospace software survey results (5 minutes)
  • software modernization talks (25 minutes)
  • code / data sharing (15 minutes)
  • build and test across languages (20 minutes)
  • asynchronous / parallel / concurrent programming (15 minutes)
  • specific geospace examples (30 minutes)
  • closing survey -- what should we do until next CEDAR (online collaboration, more sessions next year?) (10 minutes)

Other sessions of interest

Special technology requests

tables so attendees can use laptops. WiFi.


ST #5: Fuse the Knowledge Base across Disciplines

  1. Good software engineering practices expedite reliable, repeatable science results and encourage diverse outside collaborator participation. Repeatable, traceable science analyses are better trusted and solidify community and stakeholder confidence in published results.
  2. Software sharing / collaboration sites like GitHub have matured and are widely used by the heliophysics community. We address minor changes in practice that reduce time to science closure.
  3. Progress is readily measured by semi-automated metrics such as:
    • quantity and diversity (institutional, geographical, participant) of code contributions and issues opened
    • an increase in the use of continuous integration facilities such as Travis-CI
    • increased use of public data sharing such as Zenodo

ST #6: Manage, Mine, Manipulate Geoscience Data and Models

  1. Increased scientific computing efficiencies are essential for computer-aided discovery of the growing petabytes of data collected. Extracting value from the decades of diverse existing data sources can be greatly aided by more efficient software engineering practices
  2. Effective use of software toolchains can be a significant force multiplier in avoiding mistakes and repeated or manual work.
  3. Progress might be measured by mining papers for citations / keywords used such as links to software repos used, which can themselves be mined for use of continuous integration tools, build system type and specific software libraries

Workshop Categories

  • Altitudes: all
  • Latitudes: global

Format of the Workshop

Tutorials (2 hours)

Estimated attendance


Workshop Summary

This is where the final summary workshop report will be.

Presentation Resources

Upload presentation and link to it here. We will also try to archive talks in Zenodo.

Upload Files Here

  • Add links to your presentations here, including agendas, that are uploaded above. Please add bullets to separate talks. See further information on how to upload a file and link to it.