EAGER: Cyberinfrastructure Reproducibility Project: Computational Science and Engineering

EAGER：网络基础设施再现性项目：计算科学与工程

基本信息

批准号：
1747669
负责人：
Lorena Barba
金额：
$ 29.98万
依托单位：
George Washington University
依托单位国家：
美国
项目类别：
Standard Grant
财政年份：
2017
资助国家：
美国
起止时间：
2017-09-01 至 2021-08-31
项目状态：
已结题

来源：
https://www.nsf.gov/awardsearch/showAward?AWD_ID=1747669&HistoricalAwards=false
关键词：
EAGER Cyberinfrastructure Reproducibility Project Computational

项目摘要

The progress of science today relies heavily on the use of computers, from lab workstations to national supercomputers. This project confronts the issue of ensuring that scientific knowledge stemming from computational research complies to high standards of reproducibility and rigor. The NSF CISE Directorate "Dear Colleague Letter: Encouraging Reproducibility in Computing and Communications Research" (NSF 17-022, 2016) encourages researchers to embrace completeness and transparency in developing rigorous protocols. Reproducibility concerns often focus on transparency via open data, code, and other research objects. But providing the data and code to run all analyses again is, however, a minimum standard. In the context of high-performance computing where research uses multi-million-dollar facilities the understanding of where lie the sources of non-reproducibility is still lacking. This project uses methodical replication of previous studies in computational fluid dynamics as the model for reaching that understanding and for developing the guiding principles of study design that can guarantee, as much as possible, reproducible findings. The results of this project will serve NSF's mission to promote the progress of science; to advance the national health, prosperity and welfare; to secure the national defense by bringing new and necessary understanding about how to achieve rigorous, reproducible computational research. This project conducts methodical replication of published studies in computational fluid dynamics, as a model for the broad field of computational science and engineering. Its aims are to 1) identify and characterize sources of non-reproducibility, and 2) develop guidelines on Design for Reproducibility, i.e., study design guaranteeing reproducible findings. The project addresses the role of scientific software libraries (like linear algebra solvers), the influence of hardware architectures , the role of new technologies for reproducible research (e.g., containers, cloud services). The project also provides guidelines for making assessments about the success of replication studies in the context of high-performance computing, including when it is reasonable or not to expect bit-by-bit numerical reproducibility. The research tackles three phases of computational research: Research methods; Research communication; Research assessment. The project also develops openly licensed training materials on reproducible computational research, including a graduate seminar course and a Responsible Conduct of Research (RCR) module.

今天的科学进步在很大程度上取决于计算机的使用，从实验室工作站到国家超级计算机。该项目面临着确保计算研究所源自的科学知识的问题，符合可重复性和严格性的高标准。 NSF CISE局“亲爱的同事信：鼓励计算和通信研究中的可重复性”（NSF 17-022，2016）鼓励研究人员在制定严格的协议方面具有完整性和透明度。可重复性问题通常通过开放数据，代码和其他研究对象集中在透明度上。但是，提供数据和代码以再次进行所有分析是最低标准。在高性能计算的背景下，研究使用数百万美元的设施的理解仍然缺乏对不可复制性的来源的理解。该项目利用对计算流体动力学先前研究的有条理复制，作为达到理解和发展研究设计的指导原理的模型，可以保证尽可能多地可再现的发现。该项目的结果将有助于NSF促进科学进步的使命；促进民族健康，繁荣和福利；通过对如何实现严格，可再现的计算研究的新知识来确保国防。该项目对计算流体动力学中发表的研究进行了有条理的复制，作为计算科学和工程广泛领域的模型。它的目的是1）识别和表征不可复制性的来源，以及2）制定有关可重复性设计的指南，即，研究设计保证可重复可重复的发现。该项目介绍了科学软件库（例如线性代数求解器），硬件体系结构的影响，新技术在可复制研究中的作用（例如，容器，云服务）。该项目还提供了在高性能计算的背景下对复制研究成功进行评估的准则，包括在合理或不期望逐个数值可重复性的情况下进行评估。该研究解决了计算研究的三个阶段：研究方法；研究沟通；研究评估。该项目还开发了有关可再现计算研究的公开许可的培训材料，包括研究生研讨会课程和负责任的研究（RCR）模块。