Collaborative Research: PPoSS: Planning: Performance Scalability, Trust, and Reproducibility: A Community Roadmap to Robust Science in High-throughput Applications

协作研究：PPoSS：规划：性能可扩展性、信任和可重复性：高通量应用中稳健科学的社区路线图

• 批准号: 2028930
• 负责人: Ewa Deelman
• 金额: $ 7万
• 依托单位: University of Southern California
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2020
• 资助国家: 美国
• 起止时间: 2020-10-01 至 2022-09-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2028930&HistoricalAwards=false
• 关键词: Collaborative; Research; PPoSS; Planning; Performance

This project is focused on a critical issue in computational science. As scientists in all fields increasingly rely on high-throughput applications (which combine multiple components into increasingly complex multi-modal workflows on heterogeneous systems), the increasing complexities of those applications hinder the scientists’ ability to generate robust results. The project recruits a cross-disciplinary community working together to define, design, implement, and use a set of solutions for robust science. In so doing, the community defines a roadmap that enables high-throughput applications to withstand and overcome adverse conditions such as heterogeneous, unreliable architectures at all scales including extreme scale, rigorous testing under uncertainties, unexplainable algorithms (e.g., in machine learning), and black-box methods. The project’s novelties are its comprehensive, cross-disciplinary study of high-throughput applications for robust scientific discovery from hardware and systems all the way to policies and practices.Through three virtual mini-workshops called virtual world cafes, this project engages a community of scientists at campuses (through the Computing Alliance of Hispanic-Serving Institutions [CAHSI], the Coalition for Academic Scientific Computing [CASC], and the Southern California Earthquake Center [SCEC]), at national laboratories, and in industry. The scientists participate in defining scalability, trust, and reproductivity in an initial set of high-throughput applications; identifying a set of experimental practices that support the in-concert successful progress of these applications’ workflows; advancing towards a vision of general hardware and software solutions for robust science by evaluating the generality and transferability of experimental practices and by identifying any missing parts; and defining a research agenda for the next-generation workflows.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

该项目的重点是计算科学中的关键问题。随着所有领域的科学家越来越依赖于高通量应用（将多个组件结合到异质系统上日益复杂的多模式工作流程中），这些应用的复杂性的增加阻碍了科学家产生强大结果的能力。该项目招募了一个跨学科的社区，共同努力定义，设计，实施和使用一套用于强大科学的解决方案。这样一来，社区定义了一个路线图，该路线图可以实现高通量应用，以承受和克服不利条件，例如在所有尺度上的异质，不可靠的体系结构，包括极端尺度，不确定性下的严格测试，无法确定的算法（例如，机器学习中）以及黑包装方法。 The project’s novelties are its comprehensive, cross-disciplinary study of high-throughput applications for robust scientific discovery from hardware and systems all the way to policies and practices.Through three virtual mini-workshops called virtual world cafes, this project engages a community of scientists at campuses (through the Computing Alliance of Hispanic-Serving Institutions [CAHSI], the Coalition for Academic Sc​​ientific Computing [CASC], and国家实验室和工业的南加州地震中心[SCEC]）。科学家参与在初始高通量应用程序集中定义可扩展性，信任和生殖力；确定一组实验实践，以支持这些应用程序工作流程的CONCERT成功进展；通过评估实验实践的一般性和可传递性并确定任何缺失的零件，可以朝着对鲁棒科学的一般硬件和软件解决方案的愿景前进；并定义了下一代工作流程的研究议程。该奖项反映了NSF的法定任务，并通过使用基金会的知识分子优点和更广泛的影响评估标准来评估，被认为是珍贵的支持。

项目成果

A Roadmap to Robust Science for High-throughput Applications: The Scientists’ Perspective

高通量应用的稳健科学路线图：科学家的观点

• DOI: 10.1109/escience51609.2021.00044
• 发表时间: 2021
• 期刊: eScience 2021
• 作者: Taufer, M.;Deelman, E.;da Silva, R. Ferreira;Estrada, T.;Hall, M.
• 通讯作者: Hall, M.

A Roadmap to Robust Science for High-throughput Applications: The Developers’ Perspective

高通量应用的稳健科学路线图：开发人员的视角

• DOI: 10.1109/cluster48925.2021.00068
• 发表时间: 2021
• 期刊: CLUSTER 2021
• 作者: Taufer, M.;Deelman, E.;Silva, R. Ferreira;Estrada, T.;Hall, M.;Livny, M.
• 通讯作者: Livny, M.