SWQU: Composable Next Generation Software Framework for Space Weather Data Assimilation and Uncertainty Quantification

SWQU：用于空间天气数据同化和不确定性量化的可组合下一代软件框架

基本信息

批准号：
2028125
负责人：
RICHARD LINARES
金额：
$ 310万
依托单位：
Massachusetts Institute of Technology
依托单位国家：
美国
项目类别：
Continuing Grant
财政年份：
2020
资助国家：
美国
起止时间：
2020-09-01 至 2024-08-31
项目状态：
已结题

来源：
https://www.nsf.gov/awardsearch/showAward?AWD_ID=2028125&HistoricalAwards=false
关键词：
SWQU Composable Next Generation Software

项目摘要

This project seeks to develop the next generation of software for space weather modeling and prediction by bringing together experts in geospace sciences, uncertainty quantification, and software development, management, and sustainability. The electronic technologies that govern modern life are deeply dependent on satellite technologies such as the Global Positioning System (GPS), which helps us navigate cities and manages air-traffic all over the world. These satellites are also the de facto timing standard of technology and commerce, used to synchronize banking transactions worldwide, our smart-phones, and the internet. Yet, the accuracy and robustness of their signals are highly vulnerable to geospace disturbances. Satellite orbits have to be controlled precisely and to do so, geospace disturbances have to be predicted in advance. Space weather models with quantifiable predictive capability are the tools that are needed, and are presently largely absent, to continue to advance the satellite technologies and everything that depends on them. The composable software framework to be developed under this project will serve as a foundation that can be expanded on and improved over time, growing both the space weather prediction capabilities and the space weather modeling community.Composable software is the crucible of computational science, allowing scientists to add their contribution to the numerical realm without having to repeat the work of others. The goal of this project is to build a next-generation framework for space weather uncertainty quantification and data assimilation, as the foundation of the growing body of computational tools for the field. The "must-haves" for this framework will be modern dispatch-based composability, reproducibility, ease-of-use, performance, portability, and extendability to today's and tomorrow's heterogeneous and novel architectures. This project will produce computationally scalable algorithms and open-source Julia-based software framework for data-driven models of space weather with the following properties: i) Composability: Software is composable when features and behaviors work together. For example, if uncertainty quantification can be applied to a program without a rewrite, the program and the uncertainty quantification compose; ii) Sustainability: Software is sustainable when the author of the program can leave the project, and new members of the project can maintain the software; iii) Portability: Software is portable when it can perform on heterogeneous hardware with a variety of underlying architectures; iv) Reproducibility: Software is reproducible today and into the future when a convenient and backward compatible pathway exists for users to readily examine, run, share, and modify code.This award is made as a part of the joint NSF-NASA pilot program on Next Generation Software for Data-driven Models of Space Weather with Quantified Uncertainties (SWQU). It is supported by NSF Division of Atmospheric and Geospace Sciences, Division of Mathematical Sciences, Office of Advanced Cyberinfrastructure, and Office of Multidisciplinary Activities. All software developed as a result of this award will be made available by the awardee free of charge for non-commercial use; the software license will permit modification and redistribution of the software free of charge for non-commercial use.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.

该项目旨在通过将地理水平科学，不确定性量化以及软件开发，管理和可持续性的专家汇集在一起来开发用于太空天气建模和预测的下一代软件。统治现代生活的电子技术深处取决于卫星技术，例如全球定位系统（GPS），该技术可帮助我们在全球范围内驾驶城市和管理空中流量。这些卫星也是技术和商业的实际时机标准，用于使全球银行交易，我们的智能手机和互联网同步。然而，信号的准确性和鲁棒性极易受到地形干扰的影响。必须精确控制卫星轨道，并要这样做，必须提前预测地理空间干扰。具有可量化预测能力的太空天气模型是所需的工具，目前在很大程度上没有，以继续推进卫星技术及其所有依赖它们的工具。该项目下要开发的可组合软件框架将作为一个基础，可以随着时间的推移而扩展和改进，增强了太空天气预测能力和太空天气建模社区。可实现的软件是计算科学的坩埚，使科学家可以将其贡献添加到数值领域，而无需重复其他人的工作。该项目的目的是为空间不确定性量化和数据同化建立下一代框架，这是该领域计算工具不断增长的基础。该框架的“必备品”将是基于现代调度的合成性，可重复性，易用性，性能，可移植性以及对当今和明天的异质性和新颖体系结构的可扩展性。该项目将生成可扩展的算法和开源朱莉娅的软件框架，用于具有以下属性的数据驱动模型的数据驱动模型：i）合并性：当功能和行为共同使用时，软件是可以组合的。例如，如果不确定性量化可以在没有重写的情况下应用于程序，则构成程序和不确定性量化； ii）可持续性：当计划的作者能够离开项目时，软件是可持续的，项目的新成员可以维护软件； iii）可移植性：软件可以在具有各种基础体系结构的异质硬件上执行时可移植； iv）可重复性：当存在方便且后退的兼容途径时，软件是可重现的，当存在一个方便，向后兼容的途径，以便用户可以轻松地检查，运行，共享和修改代码。该奖项是作为NSF NSF-NASA PILOT计划的一部分，用于NEXT Generation Next Generation Space of Next Generation Space Weathers in Next Generation Space Weather具有量化的不介绍（SWERCECERIES）。它得到了NSF大气和地理水平科学部，数学科学部，高级网络基础设施办公室和多学科活动办公室的支持。由于该奖项而开发的所有软件都将由获奖者免费提供，以供非商业使用；该软件许可将允许免费修改和重新分配该软件以供非商业使用。该奖项反映了NSF的法定任务，并被认为是值得通过基金会的知识分子优点和更广泛的影响评估标准通过评估来支持的。