Computational Data Grids for Data Intensive Sciences

Statistics – Computation

Scientific paper

Rate now

  [ 0.00 ] – not rated yet Voters 0   Comments 0

Details

Scientific paper

New physics and astronomy experiments bring unprecedented challenges in information technology:(1) providing rapid access to massive data stores of 100 PB or more and (2) providing transparent access to heterogeneous computing resources throughout the world. We discuss here how these challenges can be met by hierarchical computational Grids of data analysis centers linked by fast networks. The integrated Grid architecture will allow physicists at laboratories and home institutions to play key roles in all stages of the data analysis, from development of the software infrastructure to the extraction of first physics results from petabyte-scale data stores. Several Grid projects have been funded in the US and Europe, including PPDG, GriPhyN, and EU DataGrid. These projects, which represent several areas of physics, astronomy and other sciences, are developing a common Grid infrastructure that will be deployed on a worldwide scale and will help drive the design and implementation of future distributed systems in many fields of science, engineering and industry.

No associations

LandOfFree

Say what you really think

Search LandOfFree.com for scientists and scientific papers. Rate them and share your experience with other people.

Rating

Computational Data Grids for Data Intensive Sciences does not yet have a rating. At this time, there are no reviews or comments for this scientific paper.

If you have personal experience with Computational Data Grids for Data Intensive Sciences, we encourage you to share that experience with our LandOfFree.com community. Your opinion is very important and Computational Data Grids for Data Intensive Sciences will most certainly appreciate the feedback.

Rate now

     

Profile ID: LFWR-SCP-O-1184138

  Search
All data on this website is collected from public sources. Our data reflects the most accurate information available at the time of publication.