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2025年下一代科学计算生态系统研讨会报告：利用社区、软件和AI促进跨学科团队科学

Report of the 2025 Workshop on Next-Generation Ecosystems for Scientific Computing: Harnessing Community, Software, and AI for Cross-Disciplinary Team Science

Argonne National Laboratory（阿贡国家实验室）；Emory University（埃默里大学）；Oak Ridge National Laboratory（橡树岭国家实验室）；Team Libra（团队Libra）；Boston University（波士顿大学）；University of Illinois Urbana-Champaign（伊利诺伊大学厄巴纳-香槟分校）；Sustainable Horizons Institute（可持续远景研究所）；Stony Brook University（石溪大学）；University of Montana（蒙大拿大学）；Pacific Northwest National Laboratory（太平洋西北国家实验室）；Lawrence Berkeley National Laboratory（伯克利国家实验室）；Sandia National Laboratories（桑塔那国家实验室）；Center for Scientific Collaboration and Community Engagement（科学协作与社区参与中心）；Lawrence Livermore National Laboratory（劳伦斯利弗莫尔国家实验室）；Californi（加利福尼亚）
Lois Curfman McInnes, Dorian Arnold, Prasanna Balaprakash, Mike Bernhardt, Beth Cerny, Anshu Dubey, Roscoe Giles, Denice Ward Hood, Mary Ann Leung, Vanessa Lope… 展开作者

Lois Curfman McInnes, Dorian Arnold, Prasanna Balaprakash, Mike Bernhardt, Beth Cerny, Anshu Dubey, Roscoe Giles, Denice Ward Hood, Mary Ann Leung, Vanessa Lopez-Marrero, Paul Messina, Olivia B. Newton, Chris Oehmen, Stefan M. Wild, Jim Willenbring, Lou Woodley, Tony Baylis, David E. Bernholdt, Chris Camano, Johannah Cohoon, Charles Ferenbaugh, Stephen M. Fiore, Sandra Gesing, Diego Gomez-Zara, James Howison, Tanzima Islam, David Kepczynski, Charles Lively, Harshitha Menon, Bronson Messer, Marieme Ngom, Umesh Paliath, Michael E. Papka, Irene Qualters, Elaine M. Raybourn, Katherine Riley, Paulina Rodriguez, Damian Rouson, Michelle Schwalbe, Sudip K. Seal, Ozge Surer, Valerie Taylor, Lingfei Wu

备注：
38 pages, 6 figures
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AI总结：

本报告总结2025年研讨会成果，提出通过社会-技术协同设计构建融合AI、HPC与软件的下一代科学计算生态系统，强调模块化可信AI系统、跨学科协作及创新培训，并以试点项目推动发展。

摘要：

本报告总结了2025年下一代科学计算生态系统研讨会（主题：利用社区、软件和AI促进跨学科团队科学）的见解。该研讨会汇集了来自国家实验室、学术界、工业界和社区组织的40多位专家，共同规划通往更强大、可持续和协作的科学软件生态系统的路径。为应对高性能计算（HPC）、AI和科学软件交叉领域的紧迫挑战，与会者设想通过社会-技术协同设计——即将社会和技术组件作为统一战略中相互依存的部分进行有意整合——来构建敏捷、健壮的生态系统。该方法将AI、HPC和软件方面的进展与跨学科协作、培训和劳动力开发的新模式相结合。主要建议包括：构建模块化、可信赖的AI赋能科学软件系统；使科学团队能够将AI系统集成到其工作流程中，同时保持人类创造力、信任和科学严谨性；以及创建能跟上快速技术变革的创新培训管道。试点项目被确定为近期催化剂，初始优先事项集中在混合AI/HPC基础设施、跨学科协作与教学法、负责任AI指南以及公私合作伙伴关系的原型设计上。本报告提出了下一代科学计算生态系统的愿景，其中AI、软件、硬件和人类专业知识相互交织，以推动发现、扩大访问、加强劳动力并加速科学进步。

英文摘要：

This report summarizes insights from the 2025 Workshop on Next-Generation Ecosystems for Scientific Computing: Harnessing Community, Software, and AI for Cross-Disciplinary Team Science, which convened more than 40 experts from national laboratories, academia, industry, and community organizations to chart a path toward more powerful, sustainable, and collaborative scientific software ecosystems. To address urgent challenges at the intersection of high-performance computing (HPC), AI, and scientific software, participants envisioned agile, robust ecosystems built through socio-technical co-design--the intentional integration of social and technical components as interdependent parts of a unified strategy. This approach combines advances in AI, HPC, and software with new models for cross-disciplinary collaboration, training, and workforce development. Key recommendations include building modular, trustworthy AI-enabled scientific software systems; enabling scientific teams to integrate AI systems into their workflows while preserving human creativity, trust, and scientific rigor; and creating innovative training pipelines that keep pace with rapid technological change. Pilot projects were identified as near-term catalysts, with initial priorities focused on hybrid AI/HPC infrastructure, cross-disciplinary collaboration and pedagogy, responsible AI guidelines, and prototyping of public-private partnerships. This report presents a vision of next-generation ecosystems for scientific computing where AI, software, hardware, and human expertise are interwoven to drive discovery, expand access, strengthen the workforce, and accelerate scientific progress.

机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。

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