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Collaborative Research: Frameworks: Seismic COmputational Platform for Empowering Discovery (SCOPED)

合作研究：框架：增强发现能力的地震计算平台（SCOPED）

基本信息

批准号：
2103701
负责人：
Marine Denolle
金额：
$ 66.06万
依托单位：
University of Washington
依托单位国家：
美国
项目类别：
Standard Grant
财政年份：
2021
资助国家：
美国
起止时间：
2021-09-01 至 2025-08-31
项目状态：
未结题

来源：
https://www.nsf.gov/awardsearch/showAward?AWD_ID=2103701&HistoricalAwards=false
关键词：
Collaborative Research Frameworks Seismic COmputational

项目摘要

Seismology is the most powerful tool for investigating the interior structure of Earth—from its surface down to the inner core—and its wide range of processes, including earthquakes, volcanic activity, glacial processes, oceanic and environmental processes, and human-caused processes such as nuclear explosions or hydraulic fracturing in oil and gas exploration. Seismology cannot achieve its greatest potential without harnessing state-of-the-art computing capabilities for the dual purpose of scientific modeling and analysis of rapidly increasing data sets. The SCOPED (Seismic COmputational Platform for Empowering Discovery) project establishes a computing platform that delivers data, computation, and service to the seismological community in a way that promotes education, innovation, and discovery, and enables efficient solutions to outstanding scientific problems in geophysics. By focusing on openly available data, openly available software, and virtual training, SCOPED opens seismological research to a broad range of users. Four research components emphasize openly available software for the purpose of characterizing Earth's subsurface structure and the wide range of natural and man-made events that are recorded by seismometers every day. Training of seismologists is a central focus of the project. SCOPED training workshops (seismoHackweeks) are open to the community. Emphasis on virtual research and training diversifies strategies to engage minority groups entering computational geosciences. The project trains a new generation of seismologists to harness the latest capabilities for processing and modeling large data sets. The SCOPED project establishes cyberinfrastructure that provides fast access to large seismic archives from a suite of containerized open-source computational tools for big data analysis, machine learning, and high-performance simulations. The implementation focuses on four interconnected, compute- and data-intensive research components: seismic imaging of Earth’s interior, waveform modeling of earthquakes and Earth structure, monitoring of Earth structure using ambient noise, and precision monitoring of earthquakes and faults. Each research component is enabled by open-source codes that meet, or aspire to meet, best practices for software development. The project contains several transformative components. First, it offers compute performance for both model- and data-driven seismological problems. Hundreds of terabytes of waveform data are directly accessible both to modelers—for data assimilation problems—and to data scientists for processing, analysis, and exploration. Second, it establishes a direct collaborative link among four teams of seismologists at four institutions and a team of computational scientists at Texas Advanced Computing Center. This unity reflects the necessity of both groups to achieve research-ready codes that can exploit high-performance computing (HPC) and Cloud systems. Third, it establishes a gateway with ready-to-run (or adapt) container images and data as a service for the seismological community. Fourth, it develops computational tools that promote the democratization of HPC/Cloud with cutting-edge data processing and modeling software through their scalability from laptops to HPC or Cloud systems and through their portability with containerization. Finally, although the development of cyberinfrastructure is the main priority, ancillary scientific results from advanced techniques are expected to offer insights into fundamental seismological problems. The project has the potential for discoveries across fields (seismology, Earth science, computer science, data science, material science), as well as societal relevance in the realms of seismic hazard assessment, environmental science, cryosphere, earthquake early warning, energy systems, and geophysical detection of nuclear proliferation.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.

地震学是研究地球内部结构--从地表到内核--及其广泛过程的最强大工具，包括地震、火山活动、冰川过程、海洋和环境过程以及石油和天然气勘探中的核爆炸或水力压裂等人为过程。如果不利用最先进的计算能力来实现科学建模和分析快速增长的数据集的双重目的，地震学就无法实现其最大潜力。Scope(增强发现能力的地震计算平台)项目建立了一个计算平台，该平台以一种促进教育、创新和发现的方式向地震界提供数据、计算和服务，并能够有效地解决地球物理中突出的科学问题。通过专注于公开可用的数据、公开可用的软件和虚拟培训，Scope向广泛的用户开放了地震学研究。有四个研究部分强调公开可用的软件，目的是描述地球的地下结构以及地震仪每天记录的各种自然和人为事件。地震学家的培训是该项目的中心重点。范围内的培训讲习班(SeismoHackWeek)对社区开放。对虚拟研究和培训的重视使使少数群体参与计算地球科学的战略多样化。该项目培训了新一代地震学家，以利用处理和模拟大型数据集的最新能力。这个有范围的项目建立了网络基础设施，通过一套用于大数据分析、机器学习和高性能模拟的集装箱化开源计算工具，提供对大型地震档案的快速访问。实施的重点是四个相互关联的、计算机和数据密集型研究组成部分：地球内部的地震成像、地震和地球结构的波形建模、利用环境噪声监测地球结构以及地震和断层的精确监测。每个研究组成部分都由符合或渴望符合软件开发最佳实践的开放源码支持。该项目包含几个变革性的组成部分。首先，它为模型驱动和数据驱动的地震学问题提供了计算性能。对于数据同化问题，建模师和数据科学家都可以直接访问数百TB的波形数据，以进行处理、分析和探索。其次，它在四个机构的四个地震学家团队和德克萨斯高级计算中心的一个计算科学家团队之间建立了直接的合作联系。这种统一反映了两个团队实现可利用高性能计算(HPC)和云系统的研究就绪代码的必要性。第三，它建立了一个门户，将准备好运行(或调整)的容器图像和数据作为服务提供给地震界。第四，通过从笔记本电脑到HPC或云系统的可扩展性以及通过集装箱化的便携性，它开发了利用尖端数据处理和建模软件促进HPC/云的民主化的计算工具。最后，尽管网络基础设施的发展是主要的优先事项，但来自先进技术的辅助科学成果预计将为基本的地震学问题提供见解。该项目具有跨领域(地震学、地球科学、计算机科学、数据科学、材料科学)的发现潜力，以及在地震危险评估、环境科学、冰冻圈、地震预警、能源系统和核扩散的地球物理探测等领域的社会相关性。该奖项反映了NSF的法定使命，并通过使用基金会的智力优势和更广泛的影响审查标准进行评估，被认为值得支持。