Data-Oriented Distributed Computing for Science: Reality and Possibilities
Identifieur interne : 001080 ( Main/Exploration ); précédent : 001079; suivant : 001081Data-Oriented Distributed Computing for Science: Reality and Possibilities
Auteurs : S. Katz ; C. Jacob ; P. Li ; Yi Chao ; Gabrielle AllenSource :
- Lecture Notes in Computer Science [ 0302-9743 ] ; 2006.
Abstract
Abstract: As is becoming commonly known, there is an explosion happening in the amount of scientific data that is publicly available. One challenge is how to make productive use of this data. This talk will discuss some parallel and distributed computing projects, centered around virtual astronomy, but also including other scientific data-oriented realms. It will look at some specific projects from the past, including Montage, Grist, OurOcean, and SCOOP, and will discuss the distributed computing, Grid, and Web-service technologies that have successfully been used in these projects.
Url:
DOI: 10.1007/11914952_2
Affiliations:
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<front><div type="abstract" xml:lang="en">Abstract: As is becoming commonly known, there is an explosion happening in the amount of scientific data that is publicly available. One challenge is how to make productive use of this data. This talk will discuss some parallel and distributed computing projects, centered around virtual astronomy, but also including other scientific data-oriented realms. It will look at some specific projects from the past, including Montage, Grist, OurOcean, and SCOOP, and will discuss the distributed computing, Grid, and Web-service technologies that have successfully been used in these projects.</div>
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