Neuromorphic computing with integrated photonics and superconductors - Jeffrey Shainline: 2016 International Conference on Rebooting Computing

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We present a hardware platform combining integrated photonics with superconducting electronics for large-scale neuromorphic computing. Semiconducting few-photon light-emitting diodes work in conjunction with superconducting-nanowire single-photon detectors to behave as spiking neurons. These neurons are connected through a network of waveguides, and variable weights of connection can be implemented using several approaches. These processing units can operate at $20$ MHz with fully asynchronous activity, light-speed-limited latency, and power densities on the order of 1 mW/cm$^2$. The processing units achieve an energy efficiency of 20 aJ/synapse event, an improvement of roughly a million over recent CMOS demonstrations cite{mear2014}. We present calculations showing this approach could scale to massive interconnectivity near that of the human brain, and could surpass the brain in speed and efficiency.

Jeffrey Shainline discusses neuromorphic computing, at ICRC 2016.

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