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EECS500 Spring 2013 Department Seminar

Presenter: 
Adam Covington
Title: 
NetFPGA: The Flexible Open-Source Networking Platform
Affiliation: 
Stanford University
Location: 
White Building, Room 411
Time: 
11:30am-12:30pm
Date: 
April 11, 2013

The NetFPGA is an open platform enabling researchers and instructors to build high-speed, hardware-accelerated networking systems. The NetFPGA is the de-facto experimental platform for line-rate implementations of network research and it continues with a new generation platform capable of 4x10Gbps.

The target audience is not restricted to hardware researchers: the NetFPGA provides the ideal platform for research across a wide range of networking topics from architecture to algorithms and from energy-efficient design to routing and forwarding. The most prominent NetFPGA success is OpenFlow, which in turn has reignited the Software Defined Networking movement. NetFPGA enabled OpenFlow by providing a widely available open-source development platform capable of line-rate and was, until its commercial uptake, the reference platform for OpenFlow. NetFPGA enables high-impact network research.

This seminar will combine presentation and demonstration; no knowledge of hardware programming languages (eg Verilog/VHDL) is required.

A NetFPGA 10G card will be awarded as a door-prize amongst the seminar attendees.

Biography: 

Adam Covington is a Research Associate in Nick McKeown's group at Stanford University. Adam has been working on the NetFPGA project since 2007. He has been helping run the NetFPGA project, both 1G and 10G, since 2009. His current research interests include reconfigurable systems, open-source hardware and software, artificial intelligence (clustering and classification), and dynamic visualizations of large scale data. Previously, he was a Research Associate with the Reconfigurable Network Group (RNG) at Washington University in St. Louis. While at Washington University he designed, and implemented clustering algorithms on FPGAs and supported a hardware accelerated classification system on the FPX platform. Adam completed a Bachelor of Science degree in Computer Engineering from Western Michigan University in April 2003 and accepted a Distinguished Masters of Science Fellowship from Washington University. He completed his Masters of Science degree in Computer Science and Engineering from Washington University in December 2006.