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DOE OSTI · 3484786

Report of the 2026 Workshop on Next-Generation Ecosystems for Scientific Computing: Harnessing Community, Software, and AI for Cross-Disciplinary Team Science

McInnes, Lois Curfman·Arnold, Dorian·Balaprakash, Prasanna·Bernhardt, Mike·Cappello, Franck·Cerny, Beth A.·DiazGranados, Deborah·Dubey, Anshu·Etienne, Nichole·Giles, Roscoe·Gomez-Zara, Diego·Hood, Denice Ward·Leung, Mary Ann·Lopez-Marrero, Vanessa·Newton, Olivia B.·Qualters, Irene·Teranishi, Keita·Wild, Stefan·Allen, Gabrielle·Arthur, Richard·Ballow, Alexandra·Baylis, Tony·Bernholdt, David E.·Bielich, Daniel·Cohoon, Johannah·Crampton, Jeremy·Ferenbaugh, Charles·Fiore, Stephen M.·Herault, Thomas·Islam, Tanzima·Jacobsohn, Stephen·Lin, Meifeng·Lively, Charles·Matsuoka, Satoshi·Milojevic, Stasa·Nichols, Daniel·Oehmen, Chris·Tabares, Santiago Ospina·Papka, Michael (ORCID:0000000264185767)·Riley, K. M.·Rouson, Damian·Seal, Sudip K.·Segundo, Brittany·Shalf, J·Siegel, Andrew R.·Taylor, Valerie E.·Willenbring, Jim·Woodley, Lou
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Abstract

Scientific computing is undergoing rapid transformation as advances in artificial intelligence, heterogeneous computing, automation, and data-intensive research reshape not only computational tools but also the institutions, workforce models, and collaborative practices that support scientific discovery. This report synthesizes insights from the 2026 Workshop on Next-Generation Ecosystems for Scientific Computing, the second in a three-year series focused on strengthening scientific computing ecosystems through socio-technical co-design. Workshop discussions identified four interdependent strategic themes: software ecosystems for AI-enabled scientific discovery; trust, validation, and traceability; human-AI teaming and paradigm shifts; and workforce, pedagogy, and governance. The report translates these themes into eight priorities for community action spanning shared research infrastructure, trust and traceability, user experience, human-AI teaming, workforce development, cross-sector coordination, stewardship and sustainability, and evaluation of scientific value. Together, these priorities outline directions for building scientific computing ecosystems that remain trustworthy, sustainable, innovative, and resilient as AI assumes a growing role in scientific work.

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McInnes, Lois Curfman, Arnold, Dorian, Balaprakash, Prasanna, Bernhardt, Mike, Cappello, Franck, Cerny, Beth A., DiazGranados, Deborah, Dubey, Anshu, Etienne, Nichole, Giles, Roscoe, Gomez-Zara, Diego, Hood, Denice Ward, Leung, Mary Ann, Lopez-Marrero, Vanessa, Newton, Olivia B., Qualters, Irene, Teranishi, Keita, Wild, Stefan, Allen, Gabrielle, Arthur, Richard, Ballow, Alexandra, Baylis, Tony, Bernholdt, David E., Bielich, Daniel, Cohoon, Johannah, Crampton, Jeremy, Ferenbaugh, Charles, Fiore, Stephen M., Herault, Thomas, Islam, Tanzima, Jacobsohn, Stephen, Lin, Meifeng, Lively, Charles, Matsuoka, Satoshi, Milojevic, Stasa, Nichols, Daniel, Oehmen, Chris, Tabares, Santiago Ospina, Papka, Michael (ORCID:0000000264185767), Riley, K. M., Rouson, Damian, Seal, Sudip K., Segundo, Brittany, Shalf, J, Siegel, Andrew R., Taylor, Valerie E., Willenbring, Jim, Woodley, Lou. 2026-08-01. Report of the 2026 Workshop on Next-Generation Ecosystems for Scientific Computing: Harnessing Community, Software, and AI for Cross-Disciplinary Team Science. https://doi.org/10.2172/3484786

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