Molecular-Scale Nanophotonics for Network-on-Chip and Probabilistic Computing Functional Units

Colloq: Speaker: 
Alvin R. Lebeck
Colloq: Speaker Institution: 
Duke University
Colloq: Date and Time: 
Fri, 2015-10-23 10:00
Colloq: Location: 
Building 5200, Room 214 (Emory)
Colloq: Host: 
Jeff Vetter
Colloq: Host Email: 
vetter@ornl.gov
Colloq: Abstract: 
This talk describes ongoing work exploring the use of emerging molecular scale devices for communication and computation. The first part of the talk presents Molecular-scale Network-on-Chip (mNoC). We leverage quantum dot LEDs, which provide electrical to optical signal modulation, and chromophores, which provide optical signal filtering for receivers. These devices replace the ring resonators and the external laser source used in contemporary nanophotonic NoCs enabling crossbar scaling up to radix 256. We'll also present mNoC power topologies, enabled by unique capabilities of mNoC technology, to reduce overall interconnect power consumption. A power topology corresponds to the logical connectivity provided by a given power mode. Broadcast is one power mode and it consumes the maximum power. Additional power modes consume less power but allow a source to communicate with a statically defined (potentially non-contiguous physically) subset of nodes. Overall power is reduced if the frequently communicating nodes use low power modes, while less frequently communicating nodes use higher power modes. The second part of this talk describes our recent work on developing novel computational units to accelerate probabilistic algorithms. Recent advances in statistics and machine learning demonstrate the potential of probabilistic algorithms in achieving high quality solutions; however, there remains a mismatch between current deterministic hardware and these algorithms. To bridge this gap we are exploring devices that exploit Resonance Energy Transfer (RET) between chromophores to create efficient samplers for arbitrary probability distributions. We provide a brief overview of the device behavior, fabrication with DNA Self-assembly, proposed functional units and status of a macro-scale prototype.
Colloq: Speaker Bio: 
Alvin R. Lebeck is a Professor of Computer Science and of Electrical and Computer Engineering at Duke University. Lebeck's research interests include architectures for emerging nanotechnologies, high performance microarchitectures, hardware and software techniques for improved memory hierarchy performance, multiprocessor systems, and energy efficient computing. In the field of emerging nanotechnologies he has done extensive work exploring the architectural implications of DNA self-assembly as a fabrication method for future systems. In the area of memory systems, Lebeck led efforts in improving cache hierarchy performance, tolerating memory latency, and improving main memory power management. Prof. Lebeck received the B.S. in Electrical and Computer Engineering (1989), and the M.S. (1991) and Ph.D. (1995) in Computer Science at the University of Wisconsin---Madison. Lebeck is co-author on over 75 refereed publications, received the best paper award at the 31st IEEE/ACM International Symposium on Microarchitecture, and has papers selected as IEEE MICRO Top Picks in Computer Architecture in 2009 and 2010. He is the recipient of a 1997 NSF CAREER Award and is a member of ACM and senior member of IEEE.