Collaborative Research: Data Infrastructure for Open Science in Support of LIGO and IceCube

合作研究：支持 LIGO 和 IceCube 的开放科学数据基础设施

• 批准号: 1841479
• 负责人: David Schultz
• 金额: $ 19.72万
• 依托单位: University of Wisconsin-Madison
• 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: 2018-10-01 至 2020-11-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1841479&HistoricalAwards=false
• 关键词: Collaborative; Research; Data; Infrastructure; Open

In 2015, the NSF-funded LIGO Observatory made the first-ever detection of gravitational waves, from the collision of two black holes, a discovery that was recognized by the 2017 Nobel Prize in Physics. In 2017, LIGO and its sister observatory Virgo in Italy made the first detection of gravitational waves from another extreme event in the Universe - the collision of two neutron stars. Gamma rays from the same neutron star collision were also simultaneously detected by NASA's Fermi space telescope. Meanwhile, the NSF-funded IceCube facility, located at the U.S. South Pole Station, has made the first detection of high-energy neutrinos from beyond our galaxy, giving us unobstructed views of other extreme objects in Universe such as supermassive black holes and supernova remnants. The revolutionary ability to observe gravitational waves, neutrinos, and optical and radio waves from the same celestial events has launched the era of "Multi-Messenger Astrophysics," an exciting new field supported by one of NSF's ten Big Ideas, "Windows on the Universe".The success of Multi-Messenger Astrophysics depends on building new data infrastructure to seamlessly share, integrate, and analyze data from many large observing instruments. The investigators propose a cohesive, federated, national-scale research data infrastructure for large instruments, focused initially on LIGO and IceCube, to address the need to access, share, and combine science data, and make the entire data processing life cycle more robust. The novel working model of the project is a multi-institutional collaboration comprising the LIGO and IceCube observatories, Internet2, and platform integration experts. The investigators will conduct a fast-track two-year effort that draws heavily on prior and concurrent NSF investments in software, computing and data infrastructure, and international software developments including at CERN. Internet2 will establish data caches inside the national network backbone to optimize the LIGO data analysis. The goal is to achieve a data infrastructure platform that addresses the production needs of LIGO and IceCube while serving as an exemplar for the entire scope of Multi-messenger Astrophysics and beyond. In the process, the investigators are prototyping a redefinition of the role the academic internet plays in supporting science.This project is supported by the Office of Advanced Cyberinfrastructure in the Directorate for Computer and Information Science and Engineering.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.

2015年，NSF资助的LIGO天文台首次探测到两个黑洞碰撞产生的引力波，这一发现获得了2017年诺贝尔物理学奖的认可。2017年，LIGO和它在意大利的姐妹天文台Virgo首次探测到了宇宙中另一个极端事件的引力波-两颗中子星的碰撞。来自同一颗中子星星碰撞的伽马射线也同时被美国宇航局的费米太空望远镜探测到。与此同时，位于美国南极站的NSF资助的IceCube设施首次探测到了来自银河系以外的高能中微子，使我们能够毫无阻碍地观察宇宙中的其他极端物体，如超大质量黑洞和超新星遗迹。观测来自同一天体事件的引力波、中微子以及光波和无线电波的革命性能力开启了“多信使天体物理学”时代，这是一个令人兴奋的新领域，由美国国家科学基金会十大理念之一的“宇宙视窗”支持。多信使天体物理学的成功取决于建立新的数据基础设施，以无缝共享、集成、并分析来自许多大型观测仪器的数据。研究人员提出了一个有凝聚力的，联合的，全国规模的大型仪器研究数据基础设施，最初集中在LIGO和IceCube，以满足访问，共享和联合收割机科学数据的需求，并使整个数据处理生命周期更加强大。该项目的新工作模式是多机构合作，包括LIGO和IceCube天文台，Internet 2和平台集成专家。调查人员将进行为期两年的快速通道工作，该工作将大量利用NSF在软件，计算和数据基础设施以及包括CERN在内的国际软件开发方面的先前和并行投资。 Internet 2将在国家网络骨干内建立数据缓存，以优化LIGO数据分析。目标是实现一个数据基础设施平台，满足LIGO和IceCube的生产需求，同时成为整个多信使天体物理学及其他领域的典范。在此过程中，研究人员正在重新定义学术互联网在支持科学方面的作用。该项目得到了计算机和信息科学与工程局高级网络基础设施办公室的支持。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进行评估，被认为值得支持。

项目成果

IceCube's Long Term Archive Software

IceCube 的长期存档软件

• DOI: 10.1145/3332186.3332196
• 发表时间: 2019
• 期刊: Proceedings of the Practice and Experience in Advanced Research Computing on Rise of the Machines (learning
• 作者: Meade, P;Riedel, B;Schultz, D
• 通讯作者: Schultz, D

Pushing the Cloud Limits in Support of IceCube Science

突破云极限以支持 IceCube Science

• DOI: 10.1109/mic.2020.3045209
• 发表时间: 2021
• 期刊: IEEE Internet Computing
• 影响因子: 3.2
• 作者: Sfiligoi, Igor;Schultz, David;Wurthwein, Frank;Riedel, Benedikt;Deelman, Ewa
• 通讯作者: Deelman, Ewa

Running a Pre-exascale, Geographically Distributed, Multi-cloud Scientific Simulation

• DOI: 10.1007/978-3-030-50743-5_2
• 发表时间: 2020-05-22
• 期刊: High Performance Computing
• 作者: Sfiligoi I;Würthwein F;Riedel B;Schultz D
• 通讯作者: Schultz D

Demonstrating a Pre-Exascale, Cost-Effective Multi-Cloud Environment for Scientific Computing: Producing a fp32 ExaFLOP hour worth of IceCube simulation data in a single workday

演示用于科学计算的前百亿亿次规模、经济高效的多云环境：在单个工作日内生成 fp32 ExaFLOP 小时的 IceCube 模拟数据

• DOI: 10.1145/3311790.3396625
• 发表时间: 2020
• 期刊: PEARC '20: Practice and Experience in Advanced Research Computing
• 作者: Sfiligoi, Igor;Schultz, David;Riedel, Benedikt;Wuerthwein, Frank;Barnet, Steve;Brik, Vladimir
• 通讯作者: Brik, Vladimir

Creating a content delivery network for general science on the internet backbone using XCaches

使用 XCache 在互联网骨干网上创建普通科学内容交付网络

• DOI: 10.1051/epjconf/202024504041
• 发表时间: 2020
• 期刊: EPJ Web of Conferences
• 作者: Fajardo, Edgar;Weitzel, Derek;Rynge, Mats;Zvada, Marian;Hicks, John;Selmeci, Mat;Lin, Brian;Paschos, Pascal;Bockelman, Brian;Hanushevsky, Andrew
• 通讯作者: Hanushevsky, Andrew