Collaborative Research: Frameworks: The Einstein Toolkit ecosystem: Enabling fundamental research in the era of multi-messenger astrophysics

合作研究：框架：爱因斯坦工具包生态系统：在多信使天体物理学时代实现基础研究

基本信息

批准号：
2004311
负责人：
Zachariah Etienne
金额：
$ 33.59万
依托单位：
West Virginia University Research Corporation
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：
2020-07-01 至 2022-05-31
项目状态：
已结题

来源：
https://www.nsf.gov/awardsearch/showAward?AWD_ID=2004311&HistoricalAwards=false
关键词：
Collaborative Research Frameworks Einstein Toolkit

项目摘要

A team of experts from five institutions (University of Illinois Urbana-Champaign, Georgia Institute of Technology, Rochester Institute of Technology, Louisiana State University, and West Virginia University) are collaborating on further development of the Einstein Toolkit, a community-driven, open-source cyberinfrastructure ecosystem providing computational tools supporting research in computational astrophysics, gravitational physics, and fundamental science. The new tools address current and future challenges in gravitational wave source modeling, improve the scalability of the code base, and support an expanded science and user community around the Einstein Toolkit.The Einstein Toolkit is a community-driven suite of research-grade Python codes for performing astrophysics and gravitational wave calculations. The code is open-source, accessible via Conda (an open source package management system) and represents a long-term investment by NSF in providing such computational infrastructure. The software is designed to simulate compact binary stars as sources of gravitational waves. This project focuses on the sustainability of the Einstein Toolkit; specific research efforts center around the development of three new software capabilities for the toolkit: • CarpetX -- a new mesh refinement driver and interface between AMReX, a software framework containing the functionality to write massively parallel block-structured adaptive mesh refinement (AMR) code, and Cactus, a framework for building a variety of computing applications in science and engineering;• NRPy+ -- a user-friendly code generator based on Python; and • Canuda -- a new physics library to probe fundamental physics. Integration of graphics processing units (GPUs) will incorporate modern heterogeneous computing devices into the system and will enhance the capability of the toolkit. The end product is sustainable through integration into the Einstein Toolkit, yet also includes an active community maintaining and enhancing the foundational components. Broader impacts are enhanced through training, documentation and a support infrastructure that reduces the barrier to adoption by the community. The team is also creating a science portal with additional educational and showcase resources. This award by the Office of Advanced Cyberinfrastructure is jointly supported by the National Science Foundation's Big Idea activities in Windows on the Universe (WoU).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.

A team of experts from five institutions (University of Illinois Urbana-Champaign, Georgia Institute of Technology, Rochester Institute of Technology, Louisiana State University, and West Virginia University) are collaborating on further development of the Einstein Toolkit, a community-driven, open-source cyberinfrastructure ecosystem providing computational tools supporting research in computational astrophysics, gravitational physics, and fundamental 科学。新工具解决了引力波源建模中的当前和未来挑战，提高代码库的可扩展性，并支持Einstein Toolkit周围扩展的科学和用户社区。EinsteinToolkit是一套由社区驱动的研究级Python代码，用于执行天体物理学和重力波浪计算。该代码是开源的，可以通过CONDA（开源软件包管理系统）访问，并代表NSF在提供此类计算基础架构时的长期投资。该软件旨在模拟紧凑型二进制恒星作为引力波的来源。该项目着重于爱因斯坦工具包的可持续性； specific research efforts center around the development of three new software capabilities for the toolkit: • CarpetX -- a new mesh refinement driver and interface between AMReX, a software framework containing the functionality to write massively parallel block-structured adaptive mesh refinement (AMR) code, and Cactus, a framework for building a variety of computing applications in science and engineering;• NRPy+ -- a user-friendly code generator based on Python; •Canuda-一个新的物理库来探测基本物理学。图形处理单元（GPU）的集成将将现代异质计算设备纳入系统，并将增强工具包的能力。最终产品通过将其集成到爱因斯坦工具包中是可持续的，但还包括一个积极的社区来维护和增强基础组件。通过培训，文档和支持基础设施减少社区采用障碍，从而增强了更大的影响。该团队还创建了一个具有额外教育和展示资源的科学门户网站。美国高级网络基础设施办公室的奖项得到了国家科学基金会在宇宙Windows（WOU）中的重大思想活动（WOU）共同支持。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标准通过评估来诚实地支持支持。