Collaborative Research:Framework:Software:NSCI:Enzo for the Exascale Era (Enzo-E)

合作研究：框架：软件：NSCI：Exascale时代的Enzo（Enzo-E）

• 批准号: 1835509
• 负责人: Greg Bryan
• 金额: $ 43.94万
• 依托单位: Columbia University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2018
• 资助国家: 美国
• 起止时间: 2018-09-01 至 2023-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1835509&HistoricalAwards=false
• 关键词: Collaborative; Research; Framework; Software; NSCI

The earliest stages of the formation of galaxies and quasars in the universe are soon to be explored with a powerful new generation of ground and space-based observatories. Broad and deep astronomical surveys of the early universe beginning in the next decade using the Large Synoptic Survey Telescope and the James Webb Space Telescope will revolutionize our understanding of the origin of galaxies and quasars, and help constrain the nature of the dark matter which is the dominant matter constituent in the universe. Detailed physical simulations that model the formation of these objects are an indispensible aid to understanding the coming glut of observational data, and to maximize the scientific return of these instruments. In this project, investigators at the Univ. California San Diego, Columbia Univ., Georgia Tech, and Michigan State Univ. are collaborating with the goal of developing a next generation community simulation software framework for the coming generation of supercomputers for cosmological simulations of the young universe. Undergraduate and graduate students will be directly involved in the software development as well as its application to several frontier cosmological research topics. The software framework that will be produced will be disseminated as open source software to enable a much broader range of scientific explorations of astrophysical topics. The project brings together the key developers of the open source Enzo adaptive mesh refinement (AMR) hydrodynamic cosmology code, who will port its software components to a newly developed AMR software framework called Cello. Cello implements the highly scalable array-of-octrees AMR algorithm on top of the powerful Charm++ parallel object system. Designed to be extensible and scalable to millions of processors, the new framework, called Enzo-E, will target exascale high performance computing (HPC) systems of the future. Through this project, the entire Enzo community will have a viable path to exascale simulations of unprecedented size and scope. The investigators have chosen three frontier problems in cosmology to drive the development of the Enzo-E framework: (1) the assembly of the first generation of stars and black holes into the first galaxies; (2) the role of cosmic rays in driving galactic outflows; and (3) the evolution of the intergalactic medium from cosmic dawn to the present day. Annual developer workshops and software releases will keep the broader research community informed and involved in the developments.This project is supported by the Office of Advanced Cyberinfrastructure in the Directorate for Computer & Information Science & Engineering and the Division of Astronomical Sciences in the Directorate of Mathematical and Physical Sciences.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.

不久将利用强大的新一代地面和空间观测站探索宇宙中星系和类星体形成的最早阶段。在未来十年开始，利用大型综合巡天望远镜和詹姆斯·韦伯太空望远镜对早期宇宙进行广泛而深入的天文观测，将彻底改变我们对星系和类星体起源的理解，并有助于限制暗物质的性质，暗物质是宇宙中的主要物质成分。模拟这些物体形成的详细物理模拟是理解即将到来的观测数据过剩和最大限度地提高这些仪器的科学回报的不可或缺的帮助。在这个项目中，加州圣地亚哥大学，哥伦比亚大学，格鲁吉亚理工学院和密歇根州立大学正在合作，目标是为下一代超级计算机开发下一代社区模拟软件框架，用于年轻宇宙的宇宙学模拟。本科生和研究生将直接参与软件开发以及其应用到几个前沿宇宙学研究课题。 将制作的软件框架将作为开放源码软件传播，以便能够对天体物理专题进行范围更广的科学探索。该项目汇集了开源Enzo自适应网格细化（AMR）流体动力学宇宙学代码的主要开发人员，他们将其软件组件移植到新开发的AMR软件框架Cello中。Cello在强大的Charm++并行对象系统之上实现了高度可扩展的八叉树阵列AMR算法。被设计为可扩展和可扩展到数百万个处理器，新的框架，称为恩佐-E，将目标是未来的exascale高性能计算（HPC）系统。通过这个项目，整个恩佐社区将有一个可行的途径，以前所未有的规模和范围的艾级模拟。研究人员选择了宇宙学中的三个前沿问题来推动Enzo-E框架的发展：（1）第一代恒星和黑洞组装成第一个星系;（2）宇宙射线在驱动星系外流中的作用;（3）从宇宙黎明到现在的星系际介质的演化。年度开发人员研讨会和软件发布将使更广泛的研究社区了解并参与开发。该项目由计算机信息科学工程局高级网络基础设施办公室&&和数学与物理科学局天文科学部支持。该奖项反映了NSF的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准。

项目成果

Efficient Long-range Active Galactic Nuclei (AGNs) Feedback Affects the Low-redshift Lyα Forest

高效的远程活跃星系核 (AGN) 反馈影响低红移 Lyα 森林

• DOI: 10.3847/2041-8213/acb7f1
• 发表时间: 2023
• 期刊: The Astrophysical Journal Letters
• 作者: Tillman, Megan Taylor;Burkhart, Blakesley;Tonnesen, Stephanie;Bird, Simeon;Bryan, Greg L.;Anglés-Alcázar, Daniel;Davé, Romeel;Genel, Shy
• 通讯作者: Genel, Shy

The Structure of Multiphase Galactic Winds

多相星系风的结构

• DOI: 10.3847/1538-4357/ac2f41
• 发表时间: 2022
• 期刊: The Astrophysical Journal
• 作者: Fielding, Drummond B.;Bryan, Greg L.
• 通讯作者: Bryan, Greg L.

Which AGN jets quench star formation in massive galaxies?

• DOI: 10.1093/mnras/stab2021
• 发表时间: 2021-02
• 期刊: Monthly Notices of the Royal Astronomical Society
• 影响因子: 4.8
• 作者: Kung-Yi Su;P. Hopkins;G. Bryan;R. Somerville;C. Hayward;D. Angl'es-Alc'azar;C. Faucher-Giguère;S. Wellons;J. Stern;Bryan A. Terrazas;T. K. Chan;Matthew E. Orr;C. Hummels;R. Feldmann;D. Kerevs

The CAMELS Project: Cosmology and Astrophysics with Machine-learning Simulations

• DOI: 10.3847/1538-4357/abf7ba
• 发表时间: 2020-10
• 期刊: The Astrophysical Journal
• 作者: F. Villaescusa-Navarro;D. Anglés-Alcázar;S. Genel;D. Spergel;Rachel S. Somerville;R. Davé;A. Pillepich;L. Hernquist;D. Nelson;P. Torrey;D. Narayanan;Yin Li;O. Philcox;Valentina La Torre;Ana Maria Delgado;S. Ho;Sultan Hassan;B. Burkhart;D. Wadekar;N. Battaglia;Gabriella Contardo;G. Bryan

First Results from SMAUG: The Need for Preventative Stellar Feedback and Improved Baryon Cycling in Semianalytic Models of Galaxy Formation

• DOI: 10.3847/1538-4357/abc3c1
• 发表时间: 2020-06
• 期刊: The Astrophysical Journal
• 作者: V. Pandya;R. Somerville;D. Angl'es-Alc'azar;C. Hayward;G. Bryan;D. Fielding;John C. Forbes;B. Burkhart;S. Genel;L. Hernquist;Chang-Goo Kim;S. Tonnesen;T. Starkenburg