NetFPGA: The Flexible Open-Source Networking Platform

When:
June 4, 2014 @ 2:29 pm – 3:29 pm
2014-06-04T14:29:22-04:00
2014-06-04T15:29:22-04:00

Presenter: 

Adam Covington, Research Associate, Computer Systems Laboratory, Department of Electrical Engineering, Stanford University

When: Tuesday, April 9, 2013

RENCI, 100 Europa Drive, Chapel Hill

Biltmore Conference Room, Suite 590

3 – 5 pm

Abstract:

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. NetFPGA targets audiences broader than hardware researchers: it 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 to one of the seminar attendees.

About the speaker:

Adam Covington is a research associate of the High Performance Networking Group (HPNG) at Stanford University. Adam works on the NetFPGA project, which enables researchers and instructors to build hardware accelerated networking systems. He provides support to users worldwide and arranges and presents NetFPGA tutorials. Previously, he was a research associate with the Reconfigurable Network Group 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’s current research interests include reconfigurable systems, artificial intelligence (clustering and classification), and applications of artificial intelligence algorithms. Adam holds a bachelor’s degree in computer engineering from Western Michigan University and master’s degree in computer science and engineering from Washington University.