Coding and Message-Passing for Large-Scale Distributed Storage and Inference

SPEAKER: Alexandros G. Dimakis, EECS Dept, UC BerkeleyABSTRACT: Multiple recent advances in technology have catalyzed a paradigm shift away from centralized schemes and in the direction of distributed and cooperative architectures for large-scale systems. In applications like data centers, sensor networks, and peer-to-peer networks, coding is used to introduce redundancy for robustness. I will show that network coding can surprisingly reduce the communication requirements compared to standard Reed-Solomon codes used in current architectures. Further, I will present novel information theoretic performance bounds and explicit network codes that achieve optimal performance.For the case of large-scale distributed inference, I will present some novel message-passing algorithms and show explicit results on convergence rate. In particular, I will present the first gossip algorithm that scales linearly in the number of nodes for a large class of geometric graphs, resolving an open problem in this active new research area.BIO: Alex Dimakis is a Ph.D. candidate in the department of Electrical Engineering and Computer Sciences at UC Berkeley working with Prof. Martin Wainwright and Prof. Kannan Ramchandran. He received the Diploma degree in Electrical and Computer Engineering from the National Technical University of Athens in 2003 and the M.S. degree in Electrical Engineering from UC Berkeley in 2005. His research interests include Communications, Signal Processing, and Networking with applications in distributed systems and sensor networks. Mr. Dimakis has received two outstanding paper awards, the UC Berkeley Departmental Fellowship in 2003, and the Microsoft Research Fellowship in 2007.HOST: Prof. Keith Chugg, chugg@usc.edu

Location: Hughes Aircraft Electrical Engineering Center (EEB) - 248

Audiences: Everyone Is Invited

Contact: Mayumi Thrasher