EarthCube Building Blocks: Collaborative Proposal: Deploying Multi-Facility Cyberinfrastructure in Commercial and Private Cloud-based Systems. (GeoSciCloud)
EarthCube 构建模块:协作提案:在商业和基于私有云的系统中部署多设施网络基础设施。
基本信息
- 批准号:1639709
- 负责人:
- 金额:$ 60.52万
- 依托单位:
- 依托单位国家:美国
- 项目类别:Standard Grant
- 财政年份:2016
- 资助国家:美国
- 起止时间:2016-09-01 至 2021-08-31
- 项目状态:已结题
- 来源:
- 关键词:
项目摘要
It is common to hear that it is optimal to perform computations necessary for the operation of corporations in the ?cloud? and it is true that many commercial companies are moving their information technology into that environment. Scientific data centers funded by the NSF have unique constraints that they must accommodate. Funding is limited and costs of managing data centers using cloud technology can be quite costly. Additionally, government funded research organizations typically have much smaller IT staffs than do corporations. The impact of managing IT operations in the cloud is not identical between large corporations and NSF funded data centers. In the GeoSciCloud project, two medium-size NSF funded data centers plan to deploy data collections along with cloud-based services in different environments in order to assess the feasibility and impact. These environments include:- Commercial cloud environments such as those offered by Amazon, Google, and Microsoft and- NSF supported large computing facilities that are just beginning to offer services that have characteristics of cloud computingThe operation of these infrastructures in these two cloud environments will be compared to current in-house environments and assessed.This project will thereby help NSF/EarthCube identify the most suitable IT environment in which the EarthCube should deploy and support shared infrastructure. The potential reliability and cost-savings are excellent motivating factors.IRIS and UNAVCO operate data centers with several hundred terabytes of data and services that match our community's needs and requirements. Each organization currently operates its own infrastructure. GeoSciCloud tasks will include moving subsets of our archives, as a test, into commercial cloud and XSEDE cloud environments where we will compare and contrast several aspects of working in different infrastructures. GeoSciCloud partners will also deploy key services developed under the GeoWS building block to enable access to data sets by domain scientists. GeoSciCloud will help EarthCube compare and contrast the three environments (XSEDE, Commercial Cloud, and current infrastructure) in the following areas:- Gain an understanding of issues related to the ingestion of large data sets into the cloud and curating the data in a cloud environment.- Compare processing times for real world requests for data by practicing domain scientists- Test elasticity of the cloud for doing large amounts of digital signal processing of seismic data and reprocessing GPS solutions for long periods of time.- Compare the speed of data egress from multiple environments including tests of using higher access systems such as Grid-FTP.- Compare overall costs of operating in the three environments- Document what the best practices are that emerge from the GeoSciCloud test that should be promoted within EarthCube.- Perform conversion of data held in domain formats to more widely used formats such as HDF5 for improved interoperability.- Test the reliability of streaming real time data into the cloud.GeoSciCloud will also explore providing some infrastructure in support of other EarthCube partners so that multiple data centers can cohabitate within the GeoSciCloud. IRIS and UNAVCO will commit to ultimately demonstrate the utility of shared infrastructure and how it can improve the efficiency and economics within EarthCube and specifically shared infrastructure in a cloud environment.
我们经常听到这样的说法:在“云”中执行公司运营所需的计算是最优的。的确,许多商业公司正在将他们的信息技术转移到这种环境中。由NSF资助的科学数据中心有独特的限制,它们必须适应这些限制。资金有限,使用云技术管理数据中心的成本可能相当昂贵。此外,政府资助的研究机构通常比公司拥有更少的IT人员。管理云中的IT操作的影响在大公司和NSF资助的数据中心之间是不相同的。在GeoSciCloud项目中,两个由美国国家科学基金会资助的中型数据中心计划在不同的环境中部署数据收集和基于云的服务,以评估可行性和影响。这些环境包括:-商业云环境,如亚马逊、b谷歌和微软提供的环境;- NSF支持的大型计算设施,刚刚开始提供具有云计算特征的服务。这些基础设施在这两个云环境中的运行将与当前的内部环境进行比较并进行评估。因此,该项目将帮助NSF/EarthCube确定最合适的IT环境,EarthCube应该在其中部署和支持共享基础设施。潜在的可靠性和成本节约是极好的激励因素。IRIS和UNAVCO运营的数据中心拥有数百tb的数据和服务,符合我们社区的需求和要求。每个组织目前都有自己的基础设施。GeoSciCloud任务将包括将我们的档案子集作为测试移动到商业云和XSEDE云环境中,在那里我们将比较和对比在不同基础设施中工作的几个方面。GeoSciCloud合作伙伴还将部署在GeoWS构建块下开发的关键服务,使领域科学家能够访问数据集。GeoSciCloud将帮助EarthCube在以下方面对三种环境(XSEDE、商业云和当前基础设施)进行比较和对比:-了解与将大型数据集吸收到云中以及在云环境中管理数据相关的问题。-通过实践领域科学家比较真实世界数据请求的处理时间-测试云对地震数据进行大量数字信号处理和长时间重新处理GPS解决方案的弹性。-比较来自多个环境的数据输出速度,包括使用更高访问系统(如Grid-FTP)的测试。-比较三种环境下的总体运营成本-记录应在EarthCube中推广的GeoSciCloud测试中出现的最佳实践。-将域格式的数据转换为更广泛使用的格式,如HDF5,以提高互操作性。-测试实时数据流到云端的可靠性。GeoSciCloud还将探索提供一些基础设施来支持其他EarthCube合作伙伴,以便多个数据中心可以在GeoSciCloud中共存。IRIS和UNAVCO将承诺最终展示共享基础设施的效用,以及它如何提高EarthCube内部的效率和经济性,特别是云环境中的共享基础设施。
项目成果
期刊论文数量(0)
专著数量(0)
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会议论文数量(0)
专利数量(0)
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David Mencin其他文献
Denoising GNSS Velocities for Earthquake Ground Motions with Deep Learning
利用深度学习对地震地面运动的 GNSS 速度进行去噪
- DOI:
- 发表时间:
2024 - 期刊:
- 影响因子:0
- 作者:
Tim Dittmann;Jade Morton;David Mencin - 通讯作者:
David Mencin
David Mencin的其他文献
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{{ truncateString('David Mencin', 18)}}的其他基金
Collaborative Research: Framework: Data: NSCI: HDR: GeoSCIFramework: Scalable Real-Time Streaming Analytics and Machine Learning for Geoscience and Hazards Research
协作研究:框架:数据:NSCI:HDR:GeoSCIFramework:用于地球科学和灾害研究的可扩展实时流分析和机器学习
- 批准号:
1835791 - 财政年份:2019
- 资助金额:
$ 60.52万 - 项目类别:
Standard Grant
Community Workshop: Real-Time GPS Position Data Products and Formats; Boulder, Colorado
社区研讨会:实时 GPS 位置数据产品和格式;
- 批准号:
1207692 - 财政年份:2012
- 资助金额:
$ 60.52万 - 项目类别:
Standard Grant
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