A Grid Portal for Interactive High Energy Physics Data Analysis

Award Information
Agency:
Department of Energy
Branch
n/a
Amount:
$0.00
Award Year:
2003
Program:
SBIR
Phase:
Phase I
Contract:
DE-FG02-03ER83856
Award Id:
61739
Agency Tracking Number:
70407S02-II
Solicitation Year:
n/a
Solicitation Topic Code:
n/a
Solicitation Number:
n/a
Small Business Information
5541 Central Avenue, Suite 135, Boulder, CO, 80301
Hubzone Owned:
N
Minority Owned:
N
Woman Owned:
N
Duns:
n/a
Principal Investigator:
David Alexander
(303) 448-7751
alexanda@txcorp.com
Business Contact:
John Cary
(303) 448-0727
cary@txcorp.com
Research Institution:
n/a
Abstract
70407S02-II Emerging grid technologies present a clear opportunity to provide the high energy physics (HEP) community with tools to address issues of securely sharing data and processing resources on the scale needed for present and (especially) future experiments. Such experiments produce terabytes of data and involve many remote institutions. This project will develop the next generation, interactive, HEP data analysis environment by integrating grid capabilities into the Java Analysis Studio, an interactive, web-evocable, high energy physics data-analysis and visualization application. This tool will also be enhanced to access all data formats appropriate for next generation experiments. Phase I produced a prototype distributed Java Data Analysis Portal (JDAP) that deploys the framework software and analysis code to nodes of a Grid cluster and then returns the combined results to the client. Phase II will develop a well-documented release version of the fully implemented portal using the latest Grid Service middleware and the latest version of the Java Analysis Studio. A standard set of interactive analysis service interfaces will be developed and implemented in the Grid portal. Commercial Applications and Other Benefits as described by awardee: Enterprise level commercial tools for remote data analysis and visualization should be applicable to any endeavor that requires distributed computing with large datasets. Examples include fusion research, securities exchange, actuarial calculations for insurance, and designing protein blueprinted drugs.

* information listed above is at the time of submission.

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