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A Parallel Microwave/PIC Code for Breakdown Studies

Award Information
Agency: Department of Energy
Branch: N/A
Contract: DE-FG02-03ER83841
Agency Tracking Number: 70629S02-II
Amount: $0.00
Phase: Phase I
Program: SBIR
Solicitation Topic Code: N/A
Solicitation Number: N/A
Timeline
Solicitation Year: N/A
Award Year: 2003
Award Start Date (Proposal Award Date): N/A
Award End Date (Contract End Date): N/A
Small Business Information
5541 Central Avenue Suite 135
Boulder, CO 80301
United States
DUNS: N/A
HUBZone Owned: No
Woman Owned: No
Socially and Economically Disadvantaged: No
Principal Investigator
 Peter Stoltz
 (720) 563-0336
 pstoltz@txcorp.com
Business Contact
 John Cary
Phone: (303) 448-0728
Email: cary@txcorp.com
Research Institution
N/A
Abstract

70629S02-II Simulations and experiments in the fusion community generate large data sets at remote sites. The visualization and analysis of these data sets is difficult because the data comes in different formats; downloading the data to local computers, over even the fastest network connections, can take hours. In this project, grid technologies will be applied and extended to the transfer and access of heterogeneous data sets produced by fusion simulations and experiments. Phase I performed an extensive set of performance tests to evaluate two data transfer mechanisms and formats: MDSplus and GridFTP (with HDF5 files). Although GridFTP was shown to be superior for the transfer of large data sets, MDSplus was extremely well suited to the fusion experimental data. Phase II will implement a Fusion Grid Service for data transfer and access. The service will connect heterogeneous data collections, provide transparent Interactive Data Language and AVS/Express client interfaces with the MDSplus and GridFTP, and allow for pluggable network protocols. Also, performance tests will be continued to formulate optimal system configurations for various types and sizes of data. Commercial Applications and Other Benefits as described by awardee: A tool for remote visualization of large data sets should be applicable to any industry where high-performance computing at remote sites is critical. This includes both the aerospace industry, where new designs depend on critical full-scale simulations, and the oil and gas industry, where the discovery of new sources relies heavily on large-scale modeling.

* Information listed above is at the time of submission. *

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