Efficient Astronomical Data Processing Among Distributed Astronomical Radio Observatories
分布式天文射电观测站的高效天文数据处理
基本信息
- 批准号:2206522
- 负责人:
- 金额:$ 58.69万
- 依托单位:
- 依托单位国家:美国
- 项目类别:Standard Grant
- 财政年份:2022
- 资助国家:美国
- 起止时间:2022-09-01 至 2025-08-31
- 项目状态:未结题
- 来源:
- 关键词:
项目摘要
Astronomy has become a data rich science and one of the biggest consumers of computing resources. NSF’s National Radio Astronomy Observatory (NRAO) collects and processes radio telescope data from a broad selection of facilities, but this centralized approach cannot provide timely analysis, driving an increasing need for an efficient astronomical data processing system among distributed observatories. As future telescope projects come online, the data size will grow dramatically and astronomical experiments will require more accurate data analysis and processing, and more detailed results. A critical challenge is job scheduling to maximize application performance and minimize system cost. This project will design and develop system software for geo-distributed observatories, focusing on astronomical data processing performance measurement and performance analysis, and efficient processing system design. Research results will be disseminated through open-source software releases. The project will be showcased in relevant courses and will provide thorough training and collaborative research opportunities to participating undergraduate, graduate, and K-12 students and faculty, and under-represented and female students.This software for scalable and efficient astronomical (SEA) data processing includes novel coordination between job scheduling, job directed acyclic graph (DAG) configuration, and the distribution of data around the globe. The team will analyze the performance of NRAO’s Common Astronomy Software Applications (CASA), and of machine learning (ML) and deep learning (DL) algorithms for astronomical research, on realistic datasets. Using those results, they will design ML/DL-assisted heuristic methods that adaptively determine the job DAG configuration and schedule, allowing an application to process geo-distributed datasets with maximum performance and minimum system cost.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.
天文学已经成为一门数据丰富的科学,也是计算资源的最大消费者之一。美国国家科学基金会(NSF)的国家射电天文台(NRAO)从广泛选择的设施中收集和处理射电望远镜数据,但这种集中的方法不能提供及时的分析,这推动了对分布式天文台之间高效天文数据处理系统的日益增长的需求。随着未来的望远镜项目上线,数据量将急剧增长,天文实验将需要更准确的数据分析和处理,以及更详细的结果。一个关键的挑战是作业调度,以最大化应用程序性能和最小化系统成本。本项目将设计和开发地理分布式天文台系统软件,重点研究天文数据处理性能测量和性能分析,以及高效处理系统设计。研究成果将通过开源软件发布进行传播。该项目将在相关课程中展示,并将为参与的本科生,研究生,K-12学生和教师,以及代表性不足的学生和女性学生提供全面的培训和合作研究机会。该软件用于可扩展和高效的天文(SEA)数据处理,包括作业调度、作业有向无环图(DAG)配置和全球数据分布之间的新颖协调。该团队将分析NRAO的通用天文学软件应用程序(CASA)以及用于天文学研究的机器学习(ML)和深度学习(DL)算法在实际数据集上的性能。利用这些结果,他们将设计ML/ dl辅助的启发式方法,自适应地确定作业DAG配置和时间表,允许应用程序以最大的性能和最小的系统成本处理地理分布式数据集。该奖项反映了美国国家科学基金会的法定使命,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
期刊论文数量(0)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
数据更新时间:{{ journalArticles.updateTime }}
{{
item.title }}
{{ item.translation_title }}
- DOI:
{{ item.doi }} - 发表时间:
{{ item.publish_year }} - 期刊:
- 影响因子:{{ item.factor }}
- 作者:
{{ item.authors }} - 通讯作者:
{{ item.author }}
数据更新时间:{{ journalArticles.updateTime }}
{{ item.title }}
- 作者:
{{ item.author }}
数据更新时间:{{ monograph.updateTime }}
{{ item.title }}
- 作者:
{{ item.author }}
数据更新时间:{{ sciAawards.updateTime }}
{{ item.title }}
- 作者:
{{ item.author }}
数据更新时间:{{ conferencePapers.updateTime }}
{{ item.title }}
- 作者:
{{ item.author }}
数据更新时间:{{ patent.updateTime }}
Haiying Shen其他文献
SPread: Exploiting fractal social community For efficient multi-coPy routing in VDTNs
SPread:利用分形社交社区在 VDTN 中实现高效的多副本路由
- DOI:
10.1109/iccnc.2017.7876149 - 发表时间:
2017 - 期刊:
- 影响因子:0
- 作者:
Bo Wu;Kang;Haiying Shen - 通讯作者:
Haiying Shen
Action Potential, Bioenergy Resource, and the Principle of Perpetual Natural Electromagnetic Dynamics: the Living Essence and Eternal Elegant-Beauty— from Biology to the Universe (I)
动作电位、生物能源与永恒的自然电磁动力原理:生命的本质和永恒的优雅之美——从生物到宇宙(一)
- DOI:
- 发表时间:
2017 - 期刊:
- 影响因子:0
- 作者:
Haiying Shen - 通讯作者:
Haiying Shen
Analysis the cooperation strategies in mobile ad hoc networks
移动自组网协作策略分析
- DOI:
10.1109/mahss.2008.4660129 - 发表时间:
2008 - 期刊:
- 影响因子:0
- 作者:
Ze Li;Haiying Shen - 通讯作者:
Haiying Shen
Surface-modified mesoporous nanofibers for microfluidic immunosensor with an ultra-sensitivity and high signal-to-noise ratio
用于具有超灵敏和高信噪比的微流控免疫传感器的表面修饰介孔纳米纤维
- DOI:
10.1016/j.bios.2020.112444 - 发表时间:
2020 - 期刊:
- 影响因子:12.6
- 作者:
Zulan Li;Ye Liu;Xing-Ming Chen;Hongyan Cao;Haiying Shen;Lei Mou;Xinli Deng;Xingyu Jiang;Yulong Cong - 通讯作者:
Yulong Cong
Electric Vehicle Trip Information Inference Based on Time-Series Residential Electricity Consumption
- DOI:
10.1109/jiot.2023.3265185 - 发表时间:
2023 - 期刊:
- 影响因子:10.6
- 作者:
Liuwang Kang;Haiying Shen;Shiwei Xu;Yezhuo Li - 通讯作者:
Yezhuo Li
Haiying Shen的其他文献
{{
item.title }}
{{ item.translation_title }}
- DOI:
{{ item.doi }} - 发表时间:
{{ item.publish_year }} - 期刊:
- 影响因子:{{ item.factor }}
- 作者:
{{ item.authors }} - 通讯作者:
{{ item.author }}
{{ truncateString('Haiying Shen', 18)}}的其他基金
CICI:TCR: Enhancing Security and Privacy of Community Cyberinfrastructures for Collaborative Research
CICI:TCR:增强社区网络基础设施的安全性和隐私性以进行协作研究
- 批准号:
2319988 - 财政年份:2023
- 资助金额:
$ 58.69万 - 项目类别:
Standard Grant
Organizing CSSI PI Meeting - Towards a National Cyberinfrastructure Ecosystem
举办CSSI PI会议——迈向国家网络基础设施生态系统
- 批准号:
2006409 - 财政年份:2020
- 资助金额:
$ 58.69万 - 项目类别:
Standard Grant
PFI-RP: A Smart Building for Enhancing Human Performance, Comfort and Health
PFI-RP:提高人类表现、舒适度和健康的智能建筑
- 批准号:
1827674 - 财政年份:2018
- 资助金额:
$ 58.69万 - 项目类别:
Standard Grant
CAREER: A New Efficient and Cooperative Large-Scale Distributed Data Sharing System
CAREER:新型高效协作的大规模分布式数据共享系统
- 批准号:
1733596 - 财政年份:2017
- 资助金额:
$ 58.69万 - 项目类别:
Continuing Grant
CIF21 DIBBs: PD: Building High-Availability Data Capabilities in Data-Centric Cyberinfrastructure
CIF21 DIBB:PD:在以数据为中心的网络基础设施中构建高可用性数据功能
- 批准号:
1724845 - 财政年份:2017
- 资助金额:
$ 58.69万 - 项目类别:
Standard Grant
Application Characterization for Adaptive Computing Platform Determination for Computational and Data-Enabled Science and Engineering
计算和数据支持的科学与工程的自适应计算平台确定的应用表征
- 批准号:
1661378 - 财政年份:2016
- 资助金额:
$ 58.69万 - 项目类别:
Standard Grant
Application Characterization for Adaptive Computing Platform Determination for Computational and Data-Enabled Science and Engineering
计算和数据支持的科学与工程的自适应计算平台确定的应用表征
- 批准号:
1404981 - 财政年份:2014
- 资助金额:
$ 58.69万 - 项目类别:
Standard Grant
EAGER: An Efficient and Effective Distributed Information System
EAGER:高效、有效的分布式信息系统
- 批准号:
1354123 - 财政年份:2013
- 资助金额:
$ 58.69万 - 项目类别:
Standard Grant
CAREER: A New Efficient and Cooperative Large-Scale Distributed Data Sharing System
CAREER:新型高效协作的大规模分布式数据共享系统
- 批准号:
1254006 - 财政年份:2013
- 资助金额:
$ 58.69万 - 项目类别:
Continuing Grant
CSR: EAGER: A Scalable and Efficient Resource Discovery System for Large-Scale Distributed Systems
CSR:EAGER:适用于大型分布式系统的可扩展且高效的资源发现系统
- 批准号:
1249603 - 财政年份:2012
- 资助金额:
$ 58.69万 - 项目类别:
Standard Grant
相似海外基金
An Ear to the Sky: Intuitive Exploration & Discovery in Astronomical Data using Sonification
倾听天空:直觉探索
- 批准号:
ST/X004651/1 - 财政年份:2023
- 资助金额:
$ 58.69万 - 项目类别:
Research Grant
DMS-EPSRC Collaborative Research: Advancing Statistical Foundations and Frontiers from and for Emerging Astronomical Data Challenges
DMS-EPSRC 合作研究:推进统计基础和前沿,应对新出现的天文数据挑战
- 批准号:
EP/W015080/1 - 财政年份:2022
- 资助金额:
$ 58.69万 - 项目类别:
Research Grant
DMS-EPSRC Collaborative Research: Advancing Statistical Foundations and Frontiers for and from Emerging Astronomical Data Challenges
DMS-EPSRC 合作研究:为新出现的天文数据挑战推进统计基础和前沿
- 批准号:
2113605 - 财政年份:2021
- 资助金额:
$ 58.69万 - 项目类别:
Standard Grant
DMS-EPSRC Collaborative Research: Advancing Statistical Foundations and Frontiers for and from Emerging Astronomical Data Challenges
DMS-EPSRC 合作研究:为新出现的天文数据挑战推进统计基础和前沿
- 批准号:
2113397 - 财政年份:2021
- 资助金额:
$ 58.69万 - 项目类别:
Standard Grant
DMS-EPSRC Collaborative Research: Advancing Statistical Foundations and Frontiers for and from Emerging Astronomical Data Challenges
DMS-EPSRC 合作研究:为新出现的天文数据挑战推进统计基础和前沿
- 批准号:
2113615 - 财政年份:2021
- 资助金额:
$ 58.69万 - 项目类别:
Standard Grant
Cambridge Astronomical Survey Unit (CASU): Filling the Astronomical Data Lake (2020-2024)
剑桥天文测量单位 (CASU):填充天文数据湖(2020-2024 年)
- 批准号:
ST/T003081/1 - 财政年份:2020
- 资助金额:
$ 58.69万 - 项目类别:
Research Grant
Managing "Big Data" for Astronomical Data Analysis.
管理天文数据分析的“大数据”。
- 批准号:
2296668 - 财政年份:2019
- 资助金额:
$ 58.69万 - 项目类别:
Studentship
OAC Core: Small: Collaborative Research: Scalable distributed algorithms for tree structured astronomical data
OAC 核心:小型:协作研究:树结构天文数据的可扩展分布式算法
- 批准号:
1910428 - 财政年份:2019
- 资助金额:
$ 58.69万 - 项目类别:
Standard Grant
Development of a Homogeneous Data Management and Visualization System for Astronomical Multi-Wavelength Open Images Enabled by a Reverse Projection Method onto the Celestial Sphere
开发天文多波长开放图像的均匀数据管理和可视化系统,通过逆向投影方法实现天球
- 批准号:
19K12244 - 财政年份:2019
- 资助金额:
$ 58.69万 - 项目类别:
Grant-in-Aid for Scientific Research (C)
From Stars to Baht: Broadening the economic impact of astronomical data handling techniques in Thailand - Phase II
从星星到泰铢:扩大泰国天文数据处理技术的经济影响 - 第二阶段
- 批准号:
ST/S002820/1 - 财政年份:2019
- 资助金额:
$ 58.69万 - 项目类别:
Research Grant