Photonic Neuromorphic Spike Processing for Ultrafast Cognitive Computing

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There has been a recent explosion of interest in spiking neural networks, which code information as spikes or events in time. Spike encoding is widely accepted as the information medium underlying the brain, but it has also inspired a new generation of neuromorphic hardware. Although electronics can match biological time scales and exceed them, they eventually reach a bandwidth fan-in trade-off. An alternative platform is photonics, which could process highly interactive information at speeds that electronics could never reach. Correspondingly, processing techniques inspired by biology could compensate for many of the shortcomings that bar digital photonic computing from feasibility, including high defect rates and signal control problems. We summarize properties of photonic spike processing and initial experiments with discrete components. A technique for mapping this paradigm to scalable, integrated laser devices is explored and simulated in small networks. This approach promises to wed the advantageous aspects of both photonic physics and unconventional computing systems. Further development could allow for fully scalable photonic networks that would open up a new domain of ultrafast, robust and adaptive processing. Applications of this technology ranging from nanosecond response control systems to fast cognitive radio could potentially revitalize specialized photonic computing.

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Bhavin J. Shastri received the Ph.D. degree in electrical engineering from McGill University, Montreal, QC, Canada, in 2011. He is currently a Postdoctoral Research Fellow at Princeton University, Princeton, NJ, USA, working on ultrafast cognitive computing---neuromorphic engineering with photonic neurons. Dr. Shastri has garnered many research awards such as the 2012 D. W. Ambridge Prize for the top graduating Ph.D. student, IEEE Photonics Society 2011 Graduate Student Fellowship, 2011 Postdoctoral Fellowship from National Sciences and Engineering Research Council of Canada (NSERC), and a 2008 Alexander Graham Bell Canada Graduate Scholarship from NSERC. He was the recipient of the Best Student Paper Awards at the 2010 IEEE Midwest Symposium on Circuits and Systems (MWSCAS), the co-recipient of the Silver Leaf Certificate at the 2008 IEEE Microsystems and Nanoelectronics Conference (MNRC), the 2004 IEEE Computer Society Lance Stafford Larson Outstanding Student Award, and the 2003 IEEE Canada Life Member Award

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