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SUMMARY:Toward Next-Generation Ecosystems for Scientific Computing
DTSTART:20260414T133000Z
DTEND:20260416T220000Z
DTSTAMP:20260604T112100Z
UID:indico-event-741@events.cels.anl.gov
CONTACT:rlynch@anl.gov\;630-252-3426
DESCRIPTION:Speakers: Lois Curfman McInnes (Argonne National Laboratory)\n
 \n \nWorkshop Organizing Committee: \n\nLois Curfman McInnes\, Argonne Na
 tional Laboratory (ANL)\, chair\nDorian Arnold\, Emory University\nPrasann
 a Balaprakash\, PrimaLabs\nMike Bernhardt\, Team Libra\nFranck Cappello\, 
 ANL\nBeth Cerny\, ANL\nAnshu Dubey\, ANL\nDenice Ward Hood\, University of
  Illinois Urbana-Champaign\nMary Ann Leung\, Sustainable Horizons Institut
 e\nOlivia Newton\, University of Montana\nKeita Teranishi\, Oak Ridge Nati
 onal Laboratory\nStefan Wild\, Lawrence Berkeley National Laboratory \n\n
  \nWorkshop Charge: \nThe high-performance computing (HPC) community has
  long driven scientific discovery at the limits of scale\, complexity\, an
 d performance. Today\, this leadership role is evolving rapidly as AI-enab
 led methods\, heterogeneous architectures\, and data-intensive workflows r
 eshape how scientific computing is conducted. At the center of this transf
 ormation lies high-quality scientific software—the durable embodiment of
  domain expertise\, computational methods\, and collaborative practice tha
 t enables discovery to scale beyond individuals and institutions.\nMotivat
 ed by urgent findings from recent community reports on scientific software
  development and AI for science\, energy\, and security\, this workshop wi
 ll convene cross-disciplinary experts spanning HPC\, AI\, computational sc
 ience\, applied mathematics\, computer science\, research software enginee
 ring\, cognitive and social sciences\, and community development. Particip
 ants will share\, develop\, and evaluate emerging strategies that address 
 the challenges and opportunities shaping next-generation ecosystems for sc
 ientific computing.\nThe workshop will employ a co-design methodology\, in
 tentionally weaving together:\n\nTeam-based scientific software developmen
 t\nAI-enabled scientific workflows and software infrastructure\nCommunity\
 , workforce\, and ecosystem development\n\nThis integrated approach ensure
 s that technical innovation and community evolution advance together\, ena
 bling broad\, sustainable\, and impactful scientific computing ecosystems.
 \nThis workshop represents Year 2 of a three-year series focused on streng
 thening team-based scientific software in an AI-driven future:\n\nYear 1 (
 2025): Identifying and understanding challenges\, gaps\, and opportunities
 \nYear 2 (2026): Sharing\, developing\, and evaluating strategies and prog
 ress\nYear 3 (2027): Coordinating ecosystem-wide advances that meld techni
 cal solutions and community-building\n\nThe 2026 workshop builds directly 
 on insights from the 2025 workshop\, as summarized in the reporthttps://do
 i.org/10.48550/arXiv.2510.03413\, with an emphasis on leveraging synergies
  across AI\, scientific software\, and community initiatives to accelerate
  ecosystem-level impact.\nAreas of emphasis: Our goal is to assess\, stren
 gthen\, and transform scientific software ecosystems\, informed by state-o
 f-the-art team science\, to meet the needs of next-generation research in 
 scientific computing\, while responsibly advancing emerging AI technologie
 s. Technical and community perspectives will be integrated throughout disc
 ussions on the following themes:\n\nSoftware and next-generation science\n
 \nExamining how new scientific frontiers\, AI-augmented workflows\, and he
 terogeneous computing platforms demand new approaches to software and work
 force development.\nEmbedding community-driven practices to ensure that te
 chnical solutions reflect broad expertise\, use cases\, and stakeholder ne
 eds.\n\n\n\n\nAI-driven software ecosystems for scientific computing\n\nMa
 pping pathways toward robust\, interoperable\, and scalable software ecosy
 stems that enable AI-driven discovery in HPC and data-intensive environmen
 ts.\nAdvancing AI tools\, frameworks\, and infrastructure for scientific c
 omputing that address current gaps while supporting openness\, reproducibi
 lity\, and broad participation.\n\n\nTeam-based software and cross-discipl
 inary research\n\nIdentifying evolving roles\, career paths\, and best pra
 ctices for collaborative scientific software teams operating at the inters
 ection of AI and computational science.\nEmphasizing community co-design\,
  where software evolves through continuous dialogue among scientists\, dev
 elopers\, users\, and maintainers.\n\n\nAI for scientific software product
 ivity and sustainability\n\nExploring how AI-assisted development\, testin
 g\, performance tuning\, documentation\, and maintenance can enhance produ
 ctivity and long-term software sustainability.\nEmbedding feedback loops t
 hat align AI-enabled tools with real-world scientific computing workflows 
 and community needs.\n\n\nCommunity and workforce development \n\nAcceler
 ating strategies to cultivate next-generation R&D teams equipped to operat
 e in AI-rich scientific computing environments.\nFostering collaborative c
 ultures that bridge technical excellence with broad\, community-centered e
 cosystem growth.\n\n\n\nWorkshop Objectives:  \nThe workshop aims to shap
 e a forward-looking\, actionable vision for the future of team-based softw
 are in scientific computing\, grounded in both emerging AI capabilities an
 d the realities of cross-disciplinary collaboration. Key objectives includ
 e:\n\nAdvancing scientific software practices: Building shared understandi
 ng of emerging methodologies\, tools\, and norms for team-based scientific
  software development\, integrating technical rigor with community sustain
 ability.\nToward strategies for excellence: Curating and refining resourc
 es\, frameworks\, and exemplars that support excellence\, effectiveness\, 
 and resilience in scientific software collaborations.\nOvercoming challeng
 es and creating opportunities: Identifying strategies to address barriers 
 faced by scientific software teams while enabling innovation aligned with 
 emerging research and AI-driven needs.\nEnvisioning the future: Articulati
 ng a shared\, forward-looking vision for next-generation scientific softwa
 re ecosystems that harmonizes technical innovation with community dynamics
 .\nFostering community development: Defining concrete actions to strengthe
 n and broaden the workforce\, while fostering durable communities prepared
  to meet urgent challenges in HPC and AI-enabled scientific computing.\n\n
 By intentionally integrating technical innovation with community-centered 
 design\, this workshop seeks to shape a future in which thriving\, cross-d
 isciplinary ecosystems drive the next wave of scientific discovery through
  advanced computing. In this future\, high-quality scientific software—c
 o-designed\, AI-enabled\, and sustainably maintained—serves as the keyst
 one of enduring collaboration and scientific progress. \nWorkshop Outcomes
 : \nParticipants will share and examine perspectives\, experiences\, and 
 emerging practices related to team-based scientific software in an AI-enab
 led future\, with the goal of assessing progress\, identifying remaining g
 aps\, and prioritizing areas for continued attention. Through discussion a
 nd co-design activities\, the workshop will surface high-impact focus area
 s\, spanning technical\, organizational\, and community dimensions.\nInsig
 hts emerging from the workshop will be synthesized in a post-workshop repo
 rt\, extending the findings of the 2025 workshop. This report will contrib
 ute to a growing body of community knowledge intended to inform ongoing an
 d future efforts in scientific software development\, workforce advancemen
 t\, and ecosystem coordination\, and may help to shape evolving perspectiv
 es\, policies\, and practices across the scientific computing community.\n
 By intentionally interweaving community considerations with technical disc
 ussions throughout the workshop series\, this three-year effort aims to ex
 pand and strengthen the scientific software community\, foster cross-disci
 plinary collaboration\, and help accelerate next-generation scientific dis
 covery in an increasingly AI-driven world.\nNOTE: Registration is by invit
 ation only\n\nhttps://events.cels.anl.gov/event/741/
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LOCATION:11th Floor Conference Room (Harper Court)
URL:https://events.cels.anl.gov/event/741/
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