Interoperability between Ultra High-Speed Networks and traditional IP Networks (SmartNIC)

Award Information
Agency: Department of Energy
Branch: N/A
Contract: DE-FG02-05ER84163
Agency Tracking Number: 79373S05-I
Amount: $749,974.00
Phase: Phase II
Program: SBIR
Awards Year: 2006
Solicitation Year: 2006
Solicitation Topic Code: 40
Solicitation Number: DE-FG02-06ER06-09
Small Business Information
555 Bryant Street, #578, Palo Alto, CA, 94301
DUNS: N/A
HUBZone Owned: N
Woman Owned: Y
Socially and Economically Disadvantaged: Y
Principal Investigator
 Gerald Sabin
 Mr.
 (937) 433-2886
 gsabin@Rnet-Tech.com
Business Contact
 Ram Balasubramanian
Title: Mr.
Phone: (650) 248-3371
Email: rbalasubramanian@Rnet-Tech.com
Research Institution
N/A
Abstract
Emerging, large-scale distributed-science applications increasingly depend on ultra-high-speed lambda-based networks to securely deliver end-to-end throughputs of 10-100 gigabits per second. However, in order to achieve high levels of end-to-end performance, it will be necessary to match the performance of these ultra-high-speed networks to traditional ¿slow¿ Internet Protocol networks. This project will develop a solution to overcome this mismatch problem. Phase I proved feasibility by conducting a simulation that used a previously-developed middleware and networking software stack. It was determined that, in order to be effective in the real world, the middleware and the networking software stack must be off-loaded to a network interface card. Therefore, in Phase II, the required software infrastructure will be developed to off-load the networking software stack to a network interface card, which would serve as a bridge between the ultra-high speed lambda networks and traditional internet protocol networks. Commercial Applications and other Benefits as described by the awardee: The bridging technology should benefit scientists in both national laboratories and universities who are working on large-scale simulation problems and have a need for on-time delivery of large amount of data. The simulations include computational climate modeling, nano-scale science (both experimental and computational), and high energy physics

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

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