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: 2028923
• 负责人: Michela Taufer
• 金额: $ 9万
• 依托单位: University of Tennessee Knoxville
• 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=2028923&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.

该项目专注于计算科学中的一个关键问题，随着各个领域的科学家越来越依赖高通量应用程序（将多个组件组合成异构系统上日益复杂的多模式工作流程），这些应用程序日益复杂的情况阻碍了科学家们的发展。该项目招募了一个跨学科的社区，共同定义、设计、实施和使用一套可靠的科学解决方案，从而定义了一个路线图，使高通量应用能够实现。承受并克服不利条件，例如各种规模的异构、不可靠的架构，包括极端规模、不确定性下的严格测试、无法解释的算法（例如机器学习）和黑盒方法，该项目的新颖之处在于其对高通量应用程序的全面、跨学科研究，以实现稳健。从硬件和系统一直到政策和实践的科学发现。通过三个称为虚拟世界咖啡馆的虚拟迷你研讨会，该项目吸引了校园里的科学家社区（通过计算联盟）西班牙裔服务机构 [CAHSI]、学术科学计算联盟 [CASC] 和南加州地震中心 [SCEC]）、国家实验室和工业界的科学家们参与定义可扩展性、信任和再现性。初始的高通量应用程序集；通过评估通用性和可转移性，确定一组支持这些应用程序工作流程协调一致成功进展的实验实践；该奖项反映了 NSF 的法定使命，并通过使用基金会的智力价值和更广泛的影响审查标准进行评估，被认为值得支持。

项目成果

A Research-Based Course Module to Study Non-determinism in High Performance Applications

用于研究高性能应用中的非确定性的研究型课程模块

• DOI: 10.1109/ipdpsw55747.2022.00067
• 发表时间: 2022
• 期刊: 2022 IEEE International Parallel and Distributed Processing Symposium Workshops (IPDPSW
• 作者: Bell, Patrick;Suarez, Kae;Fossum, Barbara;Chapp, Dylan;Bhowmick, Sanjukta;Taufer, Michela
• 通讯作者: Taufer, Michela

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.