暗能量调查数据管理系统作为数据密集型科学的门户

Kailash Kotwani, J. Myers, Bill Baker, J. Mohr, G. Daues, T. Darnell, Y. D. Cai, M. Gower, S. Desai, B. Armstrong, T. McLaren, D. Petravick, Ankit Chandra, J. Plutchak
{"title":"暗能量调查数据管理系统作为数据密集型科学的门户","authors":"Kailash Kotwani, J. Myers, Bill Baker, J. Mohr, G. Daues, T. Darnell, Y. D. Cai, M. Gower, S. Desai, B. Armstrong, T. McLaren, D. Petravick, Ankit Chandra, J. Plutchak","doi":"10.1145/1890799.1890808","DOIUrl":null,"url":null,"abstract":"The Dark Energy Survey (DES) collaboration is a multi-national science effort to understand cosmic acceleration and the nature of 'dark energy' responsible for this phenomenon. Dark Energy Survey Data Management (DESDM) system is a new observational astronomy processing pipeline and data management system that will be used to: process raw images obtained from a survey with the new DES field camera (DECam) covering 5000 sq degree of southern sky; archive intermediate and final co-added images; extract catalogs of celestial objects from every image and deliver data products to the astronomy community through portals and services. DESDM has been designed as a data intensive Science Gateway coupling use of shared computational resources (e.g. Teragrid) with project-owned databases and file systems for storage distributed across three continents. DESDM system over the next six years time will perform over 10 million CPU-hours (SUs) of image processing and serve over 4 Petabytes of images and 14 billion cataloged objects to the international DES collaboration. When delivered for operations in 2011, it will be one of, if not the, most scalable and powerful systems for processing telescope images, creating co-added deep images, and generating detailed star and galaxy catalogs in existence. The project's software components consist of a processing framework, an ensemble of astronomy codes, an integrated archive, a data-access framework and a portal infrastructure. This paper provides an overview of the DESDM scope and highlights, the architectural features developed and planned to be able to support Gateway-style management peta-scale intensive continuous processing and on-demand user queries for analysis.","PeriodicalId":313448,"journal":{"name":"Middleware for Grid Computing","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2010-11-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"The dark energy survey data management system as a data intensive science gateway\",\"authors\":\"Kailash Kotwani, J. Myers, Bill Baker, J. Mohr, G. Daues, T. Darnell, Y. D. Cai, M. Gower, S. Desai, B. Armstrong, T. McLaren, D. Petravick, Ankit Chandra, J. Plutchak\",\"doi\":\"10.1145/1890799.1890808\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The Dark Energy Survey (DES) collaboration is a multi-national science effort to understand cosmic acceleration and the nature of 'dark energy' responsible for this phenomenon. Dark Energy Survey Data Management (DESDM) system is a new observational astronomy processing pipeline and data management system that will be used to: process raw images obtained from a survey with the new DES field camera (DECam) covering 5000 sq degree of southern sky; archive intermediate and final co-added images; extract catalogs of celestial objects from every image and deliver data products to the astronomy community through portals and services. DESDM has been designed as a data intensive Science Gateway coupling use of shared computational resources (e.g. Teragrid) with project-owned databases and file systems for storage distributed across three continents. DESDM system over the next six years time will perform over 10 million CPU-hours (SUs) of image processing and serve over 4 Petabytes of images and 14 billion cataloged objects to the international DES collaboration. When delivered for operations in 2011, it will be one of, if not the, most scalable and powerful systems for processing telescope images, creating co-added deep images, and generating detailed star and galaxy catalogs in existence. The project's software components consist of a processing framework, an ensemble of astronomy codes, an integrated archive, a data-access framework and a portal infrastructure. This paper provides an overview of the DESDM scope and highlights, the architectural features developed and planned to be able to support Gateway-style management peta-scale intensive continuous processing and on-demand user queries for analysis.\",\"PeriodicalId\":313448,\"journal\":{\"name\":\"Middleware for Grid Computing\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2010-11-29\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Middleware for Grid Computing\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/1890799.1890808\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Middleware for Grid Computing","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/1890799.1890808","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

摘要

暗能量调查(DES)合作是一项多国科学努力,旨在了解宇宙加速和造成这种现象的“暗能量”的本质。暗能量巡天数据管理(DESDM)系统是一个新的观测天文处理管道和数据管理系统,将用于:处理由覆盖5000平方度南部天空的新型DES野外相机(DECam)巡天获得的原始图像;存档中间和最终共同添加的图像;从每张图像中提取天体目录,并通过门户网站和服务向天文学界提供数据产品。DESDM被设计为数据密集型科学网关,将共享计算资源(例如Teragrid)与项目拥有的数据库和文件系统耦合使用,用于分布在三大洲的存储。DESDM系统在未来六年内将执行超过1000万cpu小时(su)的图像处理,并为国际DES协作提供超过4pb的图像和140亿个编目对象。当2011年交付使用时,它将成为处理望远镜图像、创建共同添加的深度图像以及生成现有详细的恒星和星系目录的最具扩展性和最强大的系统之一。该项目的软件组件包括处理框架、天文代码集合、集成归档、数据访问框架和门户基础设施。本文提供了DESDM范围的概述和重点,开发和计划的架构特性能够支持网关式管理、千兆级密集连续处理和按需用户查询分析。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
The dark energy survey data management system as a data intensive science gateway
The Dark Energy Survey (DES) collaboration is a multi-national science effort to understand cosmic acceleration and the nature of 'dark energy' responsible for this phenomenon. Dark Energy Survey Data Management (DESDM) system is a new observational astronomy processing pipeline and data management system that will be used to: process raw images obtained from a survey with the new DES field camera (DECam) covering 5000 sq degree of southern sky; archive intermediate and final co-added images; extract catalogs of celestial objects from every image and deliver data products to the astronomy community through portals and services. DESDM has been designed as a data intensive Science Gateway coupling use of shared computational resources (e.g. Teragrid) with project-owned databases and file systems for storage distributed across three continents. DESDM system over the next six years time will perform over 10 million CPU-hours (SUs) of image processing and serve over 4 Petabytes of images and 14 billion cataloged objects to the international DES collaboration. When delivered for operations in 2011, it will be one of, if not the, most scalable and powerful systems for processing telescope images, creating co-added deep images, and generating detailed star and galaxy catalogs in existence. The project's software components consist of a processing framework, an ensemble of astronomy codes, an integrated archive, a data-access framework and a portal infrastructure. This paper provides an overview of the DESDM scope and highlights, the architectural features developed and planned to be able to support Gateway-style management peta-scale intensive continuous processing and on-demand user queries for analysis.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
Replication for dependability on virtualized cloud environments VMR: volunteer MapReduce over the large scale internet An analytical approach for predicting QoS of web services choreographies Towards an SPL-based monitoring middleware strategy for cloud computing applications Estimating resource costs of data-intensive workloads in public clouds
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1