Title of the Talk 

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Reconfigurable Computing: Opportunities and Challenges

Speaker 

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Viktor K. Prasanna

University of Southern California

Viktor K. Prasanna is Charles Lee Powell Chair in Engineering in the Ming Hsieh Department of Electrical Engineering and Professor of Computer Science at the University of Southern California. He is the executive director of the USC-Infosys Center for Advanced Software Technologies (CAST). He is also a member of the USC-Chevron Center of Excellence for Research and Academic Training on Interactive Smart Oilfield Technologies. His research interests include parallel and distributed systems including networked sensor systems, embedded systems, configurable architectures and high performance computing. He has served on the editorial boards of the Journal of Parallel and Distributed Computing, Proceedings of the IEEE, IEEE Transactions on VLSI Systems, and IEEE Transactions on Parallel and Distributed Systems. He served as the Editor-in-Chief of the IEEE Transactions on Computers during 2003-06. Prasanna was the founding Chair of the IEEE Computer Society Technical Committee on Parallel Processing. He is the steering chair of the IEEE International Conference on High Performance Computing (www.hipc.org). He is a Fellow of the IEEE and the ACM. He is a recipient of 2009 Outstanding Engineering Alumnus Award from the Pennsylvania State University.

Abstract

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Reconfigurable devices and systems have evolved dramatically over the past decade. Recently, several state-of-the-art high end platforms have incorporated FPGAs (Field Programmable Gate Arrays) for application acceleration. This talk explores algorithmic optimizations for accelerating a wide variety of applications including Gigabit rate deep packet inspection, high speed packet classification in Internet routers, embedded computing and scientific computing. We illustrate the performance improvements for such systems and demonstrate the suitability of FPGAs for these computations. The performance of FPGAs is also compared against those of state-of-the-art embedded processors, general purpose processors, and DSPs (Digital Signal Processors) for floating point intensive applications. We conclude by highlighting the challenges in further exploiting this technology for application acceleration.

http://ceng.usc.edu/~prasanna/