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

Award Information
Agency:
Department of Energy
Branch
n/a
Amount:
$749,974.00
Award Year:
2006
Program:
SBIR
Phase:
Phase II
Contract:
DE-FG02-05ER84163
Award Id:
72456
Agency Tracking Number:
79373S05-I
Solicitation Year:
n/a
Solicitation Topic Code:
n/a
Solicitation Number:
n/a
Small Business Information
555 Bryant Street, #578, Palo Alto, CA, 94301
Hubzone Owned:
N
Minority Owned:
N
Woman Owned:
N
Duns:
n/a
Principal Investigator:
Gerald Sabin
Mr.
(937) 433-2886
gsabin@Rnet-Tech.com
Business Contact:
Ram Balasubramanian
Mr.
(650) 248-3371
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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