MRI: Development of a Cloud-Computing Platform for Interferometric Processing

MRI：开发用于干涉处理的云计算平台

基本信息

批准号：
1828513
负责人：
Sheperd Doeleman
金额：
$ 84.71万
依托单位：
Smithsonian Institution Astrophysical Observatory
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 2022-09-30
项目状态：
已结题

来源：
https://www.nsf.gov/awardsearch/showAward?AWD_ID=1828513&HistoricalAwards=false
关键词：
MRI Development Cloud Computing Platform

项目摘要

The technique of Very Long Baseline Interferometry (VLBI) links together radio dishes around the globe to form Earth-sized telescopes. Each telescope in the array, synchronized by a network of atomic clocks, observes the same cosmic target at the same moment, recording data onto banks of hard-disk drives. Currently, these disks are sent to a purpose-built computer cluster for processing and imaging. But the sensitivity required for the most cutting edge work in this field has led to recording rates and data volumes that now exceed the capacity of in-house computing clusters. This project will include a partnership with Google to develop infrastructure and software that will shift VLBI processing to the cloud, where enormous virtual machines can be nimbly configured to process scientific data at speeds that easily keep pace with advancing recording rates. This project will revolutionize the practice of VLBI, and provide an extensible means of increasing array bandwidths and spectral resolution for a broad range of science. At the absolute limits of the VLBI technique, a millimeter wavelength global array will image nearby supermassive black holes as part of the Event Horizon Telescope (EHT). This project will also include educational participation and early career development opportunities in instrumentation and astronomy research.This project will develop a scalable, cloud-based computational system for VLBI. This project is motivated by the computational needs of extending EHT observations to short wavelengths; however, it will develop a methodology that is broadly applicable to the current and future needs of VLBI observations. The project will develop a hardware/software approach in conjunction with commercial partner, Google. This approach will include a new recording system for VLBI using customized commercial appliances for the transfer of data from the telescope to the cloud, and modifications to existing correlator code to make it suitable for execution on a parallelized, cloud-based platform. This project will contribute to broadening participation in science through student research opportunities made in conjunction with the Urban Massachusetts Louis Stokes Alliance for Minority Participation Program and the Akamai Workforce Initiative.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.

很长的基线干涉法（VLBI）的技术将全球的无线电菜肴连接在一起，形成了地球大小的望远镜。数组中的每个望远镜都通过原子钟网络同步，同时观察到相同的宇宙目标，将数据记录到硬盘驱动器的库中。当前，这些磁盘被发送到专门的计算机群集进行处理和成像。但是，该领域最尖端工作所需的灵敏度导致记录速率和数据量超过了内部计算簇的能力。该项目将包括与Google建立合作伙伴关系，以开发基础架构和软件，将VLBI处理转移到云中，可以将巨大的虚拟机构成巨大的虚拟机，以便以速度处理科学数据，从而可以轻松地保持速度与前进的记录率。该项目将彻底改变VLBI的实践，并提供一种可扩展的方法，以增加阵列带宽和光谱分辨率的广泛科学。在VLBI技术的绝对范围内，作为事件地平线望远镜（EHT）的一部分，毫米波长全球阵列将在附近的超级质量黑洞图像。该项目还将包括仪器和天文学研究中的教育参与和早期职业发展机会。该项目将为VLBI开发可扩展的，基于云的计算系统。该项目是由将EHT观测值扩展到短波长的计算需求的动机。但是，它将开发一种广泛适用于VLBI观察的当前和未来需求的方法。该项目将与商业合作伙伴Google共同开发一种硬件/软件方法。这种方法将使用定制的商业设备为VLBI提供一个新的录制系统，以将数据从望远镜传输到云，并对现有的相关代码进行修改，以使其适合在基于云的平行平台上执行。该项目将通过与马萨诸塞州城市少数民族参与计划和Akamai Workforce Initiative结合结合的学生研究机会为扩大科学的参与做出贡献。该奖项反映了NSF的法定使命，并通过基金会的知识优点和广泛的影响来评估NSF的法定任务，并被认为是值得的。