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Pangeo for Plasma Thomas Nicholas (Columbia University / Lamont-Doherty Earth Observatory) thomas.nicholas@columbia.edu Lessons for plasma software from the climate data analytics community

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Who am I?

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Who am I? PhD with Ben Dudson, Fulvio Militello, BOUT++

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Who am I? PhD with Ben Dudson, Fulvio Militello, BOUT++ RSE with Ryan Abernathey, various projects

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What do I do now?

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What I hope to convince you of ● Our computational infrastructure needs to change a lot ● Can use solutions from climate science community ● Modular approach makes everyone's work easier ● Opportunities exist for plasma coders...

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A multi-agency initiative across the federal government to spark change and inspire open science engagement through events and activities that will advance adoption of open science. Website: https://open.science.gov/ WH: https://www.whitehouse.gov/ostp/news-updates/ Nature: https://doi.org/10.1038/d41586-023-00019-y The White House announces The Federal Year of Open Science NASA ✦ NSF ✦ NOAA ✦ DOA ✦ DOC ✦ DOE ✦ GSA ✦ NEH ✦ NIH ✦ NIST ✦ USDA ✦ USGS Along with other organizations, including CENDI group, voluntary collaboration among Federal managers, and HELIOS, a coalition of 80+ universities

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Climate Science == Plasma Physics ● Multidimensional (often fluid turbulent) ● Large (bigger than local RAM) ● On regular but warped grids ● Often pulled from central servers ● From multiple sources but with common structure (e.g. experimental and simulation data for same device).

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Climate Science == Plasma Physics ● Multidimensional (often fluid turbulent) ● Large (bigger than local RAM) ● On regular but warped grids ● Often pulled from central servers ● From multiple sources but with common structure (e.g. experimental and simulation data for same device). =

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Typical scientific workflow

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Typical scientific workflow step 3: debug Because you likely rolled-your-own code…

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Problem 1: Code not reused

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Problem 1: Code not reused Modern data science libraries 🚀 Me as PhD student, circa 2017 MATLAB

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Problem 2: Data accessibility

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Problem 2: Data accessibility

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Problem 2: Data accessibility

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Problem 2: Data accessibility

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Problem 3: Scale “Brb, let me just go download the data to my laptop…”

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Problem 3: Scale “Brb, let me just go download the data to my laptop…”

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Problem 3: Scale “Brb, let me just go download the data to my laptop…”

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Problem 3: Scale “Brb, let me just go download the data to my laptop…”

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Problem 3: Scale “Brb, let me just go download the data to my laptop…”

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Problem 3: Scale

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Geoscientists’ solution:

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Geoscientists’ solution: ✨ ✨

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Solution 1: Modular, open ecosystem

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Solution 1: Modular, open ecosystem Domain-agnostic libraries General-purpose tools Domain-specific packages Science projects

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Solution 1: Modular, open ecosystem

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Solution 2: Cloud Computing

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Solution 2: Cloud Computing

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Solution 2: Cloud Computing

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Solution 2: Cloud Computing

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Solution 2: Cloud Computing

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Solution 3: Parallel computing frameworks

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Solution 3: Parallel computing frameworks

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How might this work for plasma?

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How might this work for plasma? Domain-agnostic libraries General-purpose tools Fusion plasma projects

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How might this work for plasma? Domain-agnostic libraries General-purpose tools tokamak-specific packages Fusion plasma projects

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How might this work for plasma? -PLASMA

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How might this work for plasma? Shared plasma metadata conventions Tokamak plotting package Common analysis tools (e.g. field-line tracing) Code-specific compatibility wrappers Standard data model Blog post: https://hackmd.io/@TomNicholas/rkyERwcoO#

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Other bonuses of joining this ecosystem - Parallel and out-of-core analysis - Labelled dimensions - Unit-aware arithmetic - Easier reproducibility - Plotting flexibility - Machine Learning integration SIX

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Summary ● Geoscience has same problems as plasma physics 🌍🤝🌞 ● Being solved using: ○ Modular community software ecosystem 🔧 ○ Cloud computing ⛅ ○ Parallel execution frameworks 🚀 ● It's working for them - it could work for us! 🔬

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